1 Sivasampu S Wahab YF Ong SM Ismail SA Goh PP Jeyaindran S

Sivasampu S Wahab YF Ong SM Ismail SA Goh PP Jeyaindran S 1

National Medical Care Statistics 2014 January 2016 ©Ministry of Health Malaysia

Published by The National Healthcare Statistics Initiative (NHSI) National Clinical Research Centre National Institutes of Health 3rd Floor, MMA House 124, Jalan Pahang 53000 Kuala Lumpur Malaysia

Tel : (603) 4043 9300/9400 Fax : (603) 4043 9500 Email : [email protected] Website : http://www.crc.gov.my/nhsi

This report is copyrighted. Reproduction and dissemination of this report in part or in whole for research, educational or non-commercial purposes is authorised without any prior written permission from the copyright holders, provided that the source is fully acknowledged.

Suggested citation: Sivasampu S, Wahab YF, Ong SM, Ismail SA, Goh PP, Jeyaindran S. National Medical Care Statistics (NMCS) 2014. Kuala Lumpur: National Clinical Research Centre, National Healthcare Statistics Initiative; 2016. Report No.: NCRC/HSU/2016.1. NMRR Approval No. NMRR-09-842- 4718. Supported by the Ministry of Health Malaysia.

This report is also available electronically on the website of the National Healthcare Statistics Initiative at http://www.crc.gov.my/nhsi

Funding: The National Healthcare Statistics Initiative was funded by a grant from Ministry of Health Malaysia.

NMRR Approval No. NMRR-09-842-4718

ISSN 2289-1811

7722 89 1810 08

Please note that there is potential for minor corrections of data in this report. Do check the online version at http://www.crc.gov.my/nhsi/ for any amendments. Thank you.

National Medical Care Statistics 2014 January 2016 ©Ministry of Health Malaysia

Published by The National Healthcare Statistics Initiative (NHSI) National Clinical Research Centre National Institutes of Health 3rd Floor, MMA House 124, Jalan Pahang 53000 Kuala Lumpur Malaysia

Tel : (603) 4043 9300/9400 Fax : (603) 4043 9500 Email : [email protected] Website : http://www.crc.gov.my/nhsi

This report is also available electronically on the website of the National Healthcare Statistics Initiative at http://www.crc.gov.my/nhsi

Funding: The National Healthcare Statistics Initiative was funded by a grant from Ministry of Health Malaysia.

NMRR Approval No. NMRR-09-842-4718

ISSN 2289-1811

7722 89 1810 08

Please note that there is potential for minor corrections of data in this report. Do check the online version at http://www.crc.gov.my/nhsi/ for any amendments. Thank you.

TABLE OF CONTENTS CHAPTER 5 THE DOCTORS ...... 41

5.1 Characteristics of the Doctors ...... 42 TABLE OF CONTENTS ...... ii 5.2 Gender ...... 44 LIST OF TABLES ...... v 5.3 Age Distribution ...... 45 LIST OF FIGURES ...... vii 5.4 Experience ...... 45 ACKNOWLEDGEMENTS ...... ix 5.5 Place of Graduation ...... 46 NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM ...... x 5.6 Postgraduate Qualification ...... 47 ABBREVIATIONS ...... xi 5.7 Working Hours ...... 48 SYMBOLS ...... xii

CHAPTER 6 THE PATIENTS ...... 49 EXECUTIVE SUMMARY ...... 1 6.1 Characteristics of the Patients ...... 50

6.2 Age-Gender Distribution ...... 53 CHAPTER 1 INTRODUCTION ...... 7 6.3 Nationality and Ethnicity ...... 54 1.1 Background ...... 8 6.4 Mode of Payment ...... 56 1.2 Objectives ...... 8 6.5 Individual Income ...... 56 1.3 Definitions ...... 9 6.6 Education Level ...... 58 1.4 Research Questions ...... 10 6.7 Medical Certificate and Duration of Sick Leave ...... 58

CHAPTER 2 METHODOLOGY ...... 11 CHAPTER 7 REASONS FOR ENCOUNTER ...... 61 2.1 Sample Size Calculation and Sampling Methods ...... 12 7.1 Number of Reasons for Encounter per Visit ...... 62 2.2 Data Collection and Follow-Up ...... 19 7.2 Reasons for Encounter by ICPC-2 Components ...... 63 2.3 Research Pack and Questionnaire ...... 19 7.3 Reasons for Encounter by ICPC-2 Chapters ...... 65 2.4 Data Management ...... 20 7.4 Most Common Reasons for Encounter in Public and Private Clinics ...... 67 2.5 Data Analysis ...... 25

2.6 Ethics Approval ...... 27 CHAPTER 8 DIAGNOSES ...... 69 2.7 Limitations ...... 27 8.1 Number of Diagnoses per Encounter ...... 70

8.2 Diagnoses by ICPC-2 Components ...... 71 CHAPTER 3 RESPONSE RATE ...... 29 8.3 Diagnoses by ICPC-2 Chapters ...... 72 3.1 Response Rate ...... 30 8.4 Most Common Diagnoses Managed in Public and Private Clinics ...... 75 3.2 The Encounters ...... 32

CHAPTER 9 MEDICATIONS ...... 79 CHAPTER 4 THE PRACTICES ...... 33 9.1 Number of Medications Prescribed per Encounter ...... 80 4.1 Primary Care Clinics in Malaysia ...... 34 9.2 Types of Medications Prescribed ...... 83 4.2 Attendances ...... 35 9.3 Most Frequently Prescribed Medications in Public and Private 4.3 Operating Days and Hours ...... 35 Clinics ...... 89 4.4 Type of Practice ...... 36

4.5 Provider Workload ...... 36 4.6 Computer Use ...... 37

4.7 Workforce ...... 38

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TABLE OF CONTENTS CHAPTER 5 THE DOCTORS ...... 41

CHAPTER 6 THE PATIENTS ...... 49 EXECUTIVE SUMMARY ...... 1 6.1 Characteristics of the Patients ...... 50

2.6 Ethics Approval ...... 27 CHAPTER 8 DIAGNOSES ...... 69 2.7 Limitations ...... 27 8.1 Number of Diagnoses per Encounter ...... 70

4.5 Provider Workload ...... 36 4.6 Computer Use ...... 37

4.7 Workforce ...... 38

iii

LIST OF TABLES CHAPTER 10 INVESTIGATIONS ...... 95 10.1 Number of Investigations per Encounter ...... 96 Table 2.1.1 Sample size (primary sampling units) for NMCS 2014 ...... 13 10.2 Types of Investigations Ordered ...... 96 Table 2.1.2 Inclusion and exclusion criteria for the clinics sampled in the survey ...... 14 10.3 Most Frequently Ordered Investigations in Public and Private Table 2.4.1 Data entry error rate for NMCS 2014 ...... 22 Clinics ...... 99 Table 2.4.2 ICPC-2 chapters ...... 23 10.4 Diagnoses with Investigations Ordered ...... 100 Table 2.4.3 ICPC-2 components ...... 24

Table 2.5.1 Strata according to state/region and sector ...... 25 CHAPTER 11 ADVICE/COUNSELLING AND PROCEDURES ...... 103 Table 3.1.1 Total number of clinics sampled and responded for NMCS 2014 ...... 30 11.1 Number of Advice/Counselling and Procedures ...... 104 Table 3.1.2 Total number of encounters received for NMCS 2014 ...... 31 11.2 Types of Advice/Counselling ...... 105 Table 3.2.1 Observed and weighted dataset for NMCS 2014 ...... 32 11.3 Most Common Advice/Counselling Provided in Public and Private Table 4.3.1 Operating days and hours of public clinics in 2014 ...... 35 Clinics ...... 106 Table 4.3.2 Operating days and hours of private clinics in 2014 ...... 36 11.4 Types of Procedures ...... 108 Table 4.4.1 Type of practice for private clinics in 2014 ...... 36 11.5 Most Common Procedures Performed in Public and Private Clinics ...... 109 Table 4.7.1 Healthcare workforce by sector in primary care clinics in 2014 ...... 38 11.6 Diagnoses with Advice/Counselling and Procedures ...... 110 Table 5.1.1 Characteristics of primary care doctors in 2014 ...... 43

Table 6.1.1 Characteristics of primary care patients in 2014 ...... 51 CHAPTER 12 FOLLOW-UPS AND REFERRALS ...... 113 Table 7.2.1 Reasons for encounter by ICPC-2 components in primary care clinics in 2014 ..... 63 12.1 Number of Follow-Ups and Referrals ...... 114 Table 7.2.2 Reasons for encounter by ICPC-2 components in public clinics in 2014 ...... 64 12.2 Types of Referrals ...... 115 Table 7.2.3 Reasons for encounter by ICPC-2 components in private clinics in 2014 ...... 64 12.3 Most Frequently Followed Up Diagnoses ...... 116 Table 7.3.1 Reasons for encounter by ICPC-2 chapters and the most common individual 12.4 Most Frequently Referred Diagnoses ...... 117 reasons for encounter within each chapter in primary care clinics in 2014 ...... 65

Table 8.2.1 Diagnoses by ICPC-2 components in primary care clinics in 2014 ...... 72 APPENDICES ...... 119 Table 8.3.1 Diagnosis by ICPC-2 chapters and the most common individual diagnoses Appendix 1: Additional Tables ...... 120 within each chapter in NMCS 2014 ...... 73 Appendix 2: NMCS 2014 Primary Care Provider’s Profile Questionnaire ...... 121 Table 8.4.1 Thirty most common diagnoses managed in public clinics in 2014 ...... 76 Appendix 3: NMCS 2014 Survey Form ...... 122 Table 8.4.2 Thirty most common diagnoses managed in private clinics in 2014 ...... 77 Appendix 4: ICPC-2 and ICPC-2 PLUS groups ...... 123 Table 9.1.1 Number of encounters with and without medical prescription in primary Appendix 5: Participants of NMCS 2014 ...... 133 care clinics in 2014 ...... 80 Appendix 6: List of Definitions ...... 143 Table 9.1.2 Number of medications prescribed in primary care clinics in 2014 ...... 81

Table 9.2.1 Prescribed medications by ATC levels in primary care clinics in 2014 ...... 84 Table 9.2.2 Prescribed medications by ATC level 1 in public clinics in 2014 ...... 88 Table 9.2.3 Prescribed medications by ATC level 1 in private clinics in 2014 ...... 89 Table 9.3.1 Thirty most frequently prescribed medications in public clinics in 2014 ...... 91 Table 9.3.2 Thirty most frequently prescribed medications in private clinics in 2014 ...... 92 Table 10.1.1 Number of encounters with investigations ordered in primary care clinics in 2014 ...... 96

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Table 10.2.1 Types of investigations by ICPC-2 process codes in primary care clinics in LIST OF FIGURES 2014 ...... 97 Table 10.4.1 Top 10 diagnoses for which investigations were most frequently ordered in Figure 2.1.1 Study design for NMCS 2014 ...... 16 primary care clinics in 2014 ...... 101 Figure 2.1.2 Consort diagram – public primary care clinics 2014 ...... 17 Table 11.1.1 Number of encounters managed with advice and counselling in primary care Figure 2.1.3 Consort diagram – private primary care clinics 2014 ...... 18 clinics in 2014 ...... 104 Figure 4.1.1 Number of primary care clinics per 10,000 population in 2012 ...... 34 Table 11.1.2 Number of encounters managed with procedures in primary care clinics in Figure 4.6.1 Types of computer use in primary care by sector in 2014 ...... 37 2014 ...... 104 Figure 4.7.1 Primary care clinics with family medicine specialists by sector in 2014 ...... 39 Table 11.2.1 Types of advice and counselling provided in primary care clinics in 2014 ...... 105 Figure 5.2.1 Distribution of public and private doctors by gender in 2014 ...... 44 Table 11.4.1 Types of procedures provided in primary care clinics in 2014 ...... 108 Figure 5.3.1 Distribution of public and private doctors by age group in 2014 ...... 45 Table 11.6.1 Ten most common diagnoses managed with advice/counselling in primary Figure 5.4.1 Distribution of public and private doctors by years of experience in 2014 ...... 46 care clinics in 2014 ...... 111 Figure 5.5.1 Distribution of public and private doctors by place of graduation in 2014 ...... 47 Table 11.6.2 Ten most common diagnoses managed with procedures in primary care Figure 5.6.1 Distribution of public and private doctors by postgraduate qualification in clinics in 2014 ...... 112 2014 ...... 48 Table 12.1.1 Visit dispositions of primary care patients by sector in 2014 ...... 114 Figure 6.2.1 Distribution of public patients by age and gender in 2014 ...... 53 Table 12.2.1 Types of referrals in primary care in 2014 ...... 115 Figure 6.2.2 Distribution of private patients by age and gender in 2014 ...... 54 Table 12.2.2 Types of referrals in public clinics in 2014 ...... 116 Figure 6.3.1 Distribution of public and private patients by nationality in 2014 ...... 55 Table 12.2.3 Types of referrals in private clinics in 2014 ...... 116 Figure 6.3.2 Distribution of public and private patients by ethnicity in 2014 ...... 55 Table 12.3.1 Top 10 diagnoses for follow-up in primary care in 2014 ...... 117 Figure 6.4.1 Distribution of private patients by mode of payment in 2014 ...... 56 Table 12.4.1 Top 10 diagnoses for referral in primary care in 2014 ...... 118 Figure 6.5.1 Distribution of public and private patients by type of income in 2014 ...... 57

Figure 6.5.2 Distribution of primary care patients by income and sector in 2014 ...... 57 Figure 6.6.1 Distribution of public and private patients by education level in 2014 ...... 58 Figure 6.7.1 Distribution of public and private patients by issuance of medical certificate in 2014 ...... 59 Figure 6.7.2 Distribution of public and private patients by duration of sick leave in 2014 ...... 59 Figure 7.1.1 Number of reasons for encounter per visit in primary care clinics in 2014 ...... 62 Figure 7.4.1 Top 10 reasons for encounter in public clinics in 2014 ...... 67 Figure 7.4.2 Top 10 reasons for encounter in private clinics in 2014 ...... 68 Figure 8.1.1 Number of diagnoses managed per encounter in primary care clinics in 2014 ...... 70 Figure 8.1.2 Age- and gender- specific rates of diagnoses managed per 100 encounters by sector in 2014 ...... 71 Figure 9.1.1 Number of medications prescribed per encounter in primary care clinics in 2014 ...... 81 Figure 9.1.2 Age- and gender- specific prescription rates per 100 encounters by sector in 2014 ...... 82 Figure 10.1.1 Number of investigations ordered per encounter in primary care clinics in 2014 ...... 97 Figure 10.3.1 Top 10 investigations ordered in public clinics in 2014 ...... 99

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vii

Figure 10.3.2 Top 10 investigations ordered in private clinics in 2014 ...... 100 Figure 11.3.1 Ten most common advice/counselling provided in public clinics in 2014 ...... 107 ACKNOWLEDGEMENTS Figure 11.3.2 Ten most common advice/counselling provided in private clinics in 2014 ...... 107 Figure 11.5.1 Ten most common procedures performed in public clinics in 2014 ...... 109 National Healthcare Statistics Initiative team would like to thank the Director General of Health Figure 11.5.2 Ten most common procedures performed in private clinics in 2014 ...... 110 Malaysia for his continuous support towards this survey and permission to publish this report.

We would like to express our sincere appreciation to the following contributors for participating, guiding, advising and supporting us in our endeavour:

• Deputy Director-General of Health (Research and Technical Support), Ministry of Health (MOH) • Deputy Director-General of Health (Medical), MOH • Deputy Director-General of Health (Public Health), MOH • Director of the Clinical Research Centre, National Institutes of Health, MOH • Health Informatics Centre, MOH • Director of the Family Health Development Division, MOH • Director of the Planning and Development Division, MOH • Director of the Private Medical Practice Division, MOH (Cawangan Kawalan Amalan Perubatan Swasta, CKAPS) • State level Private Medical Practice Control Units (Unit Kawalan Amalan Perubatan Swasta, UKAPS). • Malaysian Medical Council, Malaysian Medical Association, Academy of Family Physicians Malaysia.

This report would not have been possible without the support and participation of the primary care clinics’ providers and their patients in the National Medical Care Survey 2014. Our sincerest gratitude goes out to them in making this project a success.

Last but not least, we thank Ms. Lim Huy Ming for her contributions in editing this report.

National Healthcare Statistics Initiative (NHSI) Primary Care Team Healthcare Statistics Unit National Clinical Research Centre Ministry of Health, Malaysia.

viii National Medical Care Statistics 2014

We would like to express our sincere appreciation to the following contributors for participating, guiding, advising and supporting us in our endeavour:

Last but not least, we thank Ms. Lim Huy Ming for her contributions in editing this report.

National Healthcare Statistics Initiative (NHSI) Primary Care Team Healthcare Statistics Unit National Clinical Research Centre Ministry of Health, Malaysia.

NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM ABBREVIATIONS

ACE Angiotensin converting enzyme Principal Investigato r YBhg. Datuk Dr. Jeyaindran Tan Sri Sinnadu rai ATC WHO Anatomical Therapeutic Chemical classification system

BEACH Bettering the Evaluation and Care of Health

Dr. Sheamini Sivasam pu CI Confidence interval Principal Co -Investigato r Dr. Goh Pik Pi n CKAPS Cawangan Kawalan Amalan Perubatan Swasta (Private Medical Practice Division) FMS Family medicine specialist FOMEMA Foreign Workers Medical Examination Monitoring Agency Dr. Kamaliah Mohd. N oh FRACGP Fellowship of the Royal Australian College of General Practitioners Professor Dr. Khoo Ee Mi ng Research Evaluation Committee Professor Dr. Ng Chirk Je nn FRCGP Fellowship of the Royal College of General Practitioners (REC) Professo r Dr. Teng Cheong Lie ng FTE Full-time-equivalent Dr Baizury Basha h GP General practice or practitioner Ms. Siti Fauziah Ab u HbA1c Glycated haemoglobin ICPC International Classification of Primary Care IQR Interquartile range Dr. Yasmin Farhana Abdul Wa hab Project Manager s Mr. Ong Su Mii n MAFP Membership of the Academy of Family Physicians of Malaysia MOH Ministry of Health, Malaysia MRCGP Membership of the Royal College of General Practitioners Dr. Chin May Chie n MREC Medical Research and Ethics Committee, Ministry of Health Malaysia Dr. Kirubashni Moh an MYR Malaysian Ringgit Ms. Thilagaa Rajanthr en Members of Research Team Ms. Pavityra Velayutha m NCRC National Clinical Research Centre Mr. Amirul Amin Kamaruzzam an NEC Not elsewhere classified Ms. Nur Rafidah Mohd Noo r NHEWS National Healthcare Establishment & Workforce Survey (Primary Care) Ms. Juliana Mohd Noo r NHSI National Healthcare Statistics Initiative NMCS National Medical Care Survey Survey Coordinato r Ms. Siti Amina h Ism ail NOS Not otherwise specified PSU Primary sampling unit QSU Quaternary sampling unit Data Analysis Mr. Ong Su Mii n REC Research Evaluation Committee RFE Reason for encounter

Database SOCSO Social Security Organisation Altus Solutions Sdn. Bh d. Developers/Administrators SSU Secondary sampling unit TSU Tertiary sampling unit UKAPS Unit Kawalan Amalan Perubatan Swasta (Private Medical Practice Control Units) WHO World Health Organisation World Organization of National Colleges, Academies and Academic Associations of General WONCA Practitioners/Family Physicians WP Wilayah Persekutuan (Federal Territories)

x National Medical Care Statistics 2014

NATIONAL MEDICAL CARE SURVEY 2014 PROJECT TEAM ABBREVIATIONS

ACE Angiotensin converting enzyme Principal Investigato r YBhg. Datuk Dr. Jeyaindran Tan Sri Sinnadu rai ATC WHO Anatomical Therapeutic Chemical classification system

BEACH Bettering the Evaluation and Care of Health

SYMBOLS EXECUTIVE SUMMARY

– Not applicable The National Medical Care Survey (NMCS) is a provider-based survey which aims to study the characteristics and morbidity pattern of patients as well as healthcare activities in terms of > More than investigations, procedures, counselling and visit dispositions provided at primary care level in ≥ More than or equal to Malaysia. NMCS 2014 covered public and private clinics from 13 states and three federal < Less than territories in Malaysia. The clinics were stratified according to sector and state and selected % Percentage through random sampling. Healthcare providers from these clinics recorded details of patients they managed on the day of survey, which was randomly allocated between January and May 2014. All error bars in the figures included in this report represent 95% confidence intervals (CIs).

Primary care clinics

In NMCS 2014, a total of 129 public clinics out of 139 sampled (92.8%) and 416 private clinics out of 1,002 sampled (41.5%) responded. The survey data were weighted to produce unbiased national estimates for 664 public clinics and 4,810 private clinics in Malaysia which were staffed with medical doctors.

• The median attendance rate in public clinics was 111.5 visits per day, compared to 33.0 per day in private clinics. • A large majority (82.8%) of public clinics operated five days per week. After-hours services (extended-hours and/or on-call services) were provided in addition to the standard-hour operation in 47.9% of public clinics. • Most (54.0%) private clinics operated six days per week. Only 5.0% of the private clinics provided 24-hour services. • Three-quarters (75.3%) of the private clinics were solo practices. • The median number of patients seen per full time equivalent (FTE) doctor in the private sector was 25.9 patients per day. • Only 19.4% of public clinics had a functional computer system installed in the practice, compared to 71.6% for private clinics. Computer system was mainly used for registration (83.7%) and medical record keeping (83.3%) purposes in the public sector and for billing purpose (79.6%) in the private sector. • Public clinics were staffed with 26.4 health professionals on average, with a median of three doctors, six staff nurses, seven community nurses, three assistant medical officers and one pharmacist per clinic. In contrast, private practices had only 5.6 health professionals on average, with a median of one doctor and three clinic assistants in each clinic. • Family medicine specialists (FMS) were available in 40.1% of public clinics, compared to 2.9% in the private sector.

The doctors

A total of 936 doctors participated in NMCS 2014: 490 (52.4%) from public clinics and 446 (47.6%) from private clinics. The survey responses were weighted to produce national estimates for 10,964 doctors (2,992 public and 7,972 private) working in primary care in Malaysia.

• Female doctors accounted for a higher proportion of the doctor workforce in the public sector compared to the private sector (70.5% versus 39.7%, respectively). • The vast majority (79.9%) of the doctors in public clinics were between 25 and 34 years old, compared to only 4.2% in the private sector. In contrast, 69.9% of the doctors in private

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SYMBOLS EXECUTIVE SUMMARY

Primary care clinics

The doctors

clinics were 45 years or older, while only 6.2% of doctors in public clinics fell in the same age • In contrast, in private clinics, patient encounters were mostly for acute complaints: fever group. (28.3 per 100 encounters), cough (26.5 per 100 encounters) and runny nose/rhinorrhoea (19.4 • The majority (62.0%) of the doctors had been working in the primary care setting for 10 per 100 encounters). years or more (median: 13 years). • Overseas trained doctors accounted for the greater proportion (51.5%) of the primary care Diagnoses managed doctor workforce. • Nearly one-sixth (15.7%) of the doctors had at least one postgraduate qualification. Most of A total of 436,743 diagnoses were made in primary care clinics, at a rate of 134.0 diagnoses per these doctors specialised in family medicine (87.3% in the public sector and 38.9% in the 100 patient encounters (weighted data). private sector). • More diagnoses were managed overall at encounters in public clinics (154.9 diagnoses per 100 encounters) than in private clinics (119.9 diagnoses per 100 encounters). The patients • Only a single diagnosis was managed at 75.2% of the encounters (63.0% of encounters in public clinics and 83.5% in private clinics). A total of 27,587 encounters (15,470 in public clinics and 12,117 in private clinics) were captured • The number of diagnoses increased with patient age for both sectors, with the increase being in NMCS 2014. Post-stratification weighting translated this figure into a total of 325,818 more pronounced in the public sector, especially for age groups over 40 years. primary care encounters: 131,624 (40.4%) in public clinics and 194,194 (59.6%) in private clinics. • More than three-quarters (77.9%) of diagnoses were recorded as diagnoses or diseases; only • Females accounted for 53.6% of all primary care encounters. The proportions of male and 16.6% remained undiagnosed symptoms or complaints. female patients were similar across all age groups, except among the adult age groups (20– • The three most frequently managed diagnoses in public clinics were non-communicable 39 years and 40–59 years) in public clinics, for which significantly higher proportions of diseases: hypertension (33.1 per 100 encounters), diabetes (23.4 per 100 encounters) and females were reported. lipid disorder (22.1 per 100 encounters). These chronic illnesses were managed at much • The public clinics were utilised by a relatively older patient population compared to the lower rates in private clinics (6.5, 3.0 and 2.9 diagnoses per 100 encounters, respectively). private clinics. Patients aged 40–59 years accounted for the greatest proportion (30.3%) of • By comparison, majority of the cases managed by private primary care providers were acute public clinic encounters, while most (44.3%) private patients were between 20 and 39 years illnesses. The most common diagnoses in private clinics were upper respiratory tract of age. The elderly patients constituted a significantly higher proportion of the patient infections (22.7% of all diagnoses in private clinics and 27.2 per 100 encounters), population in the public sector than in the private sector (22.9% versus 9.7%, respectively). hypertension (6.5 per 100 encounters) and gastroenteritis (5.4 per 100 encounters). • Malays were the largest ethnic group utilising primary care (65.6% of encounters in public clinics and 60.4% in private clinics), followed by Chinese (14.4% in public clinics and 26.1% Medications prescribed in private clinics) and Indian patients (11.9% in public clinics and 10.0% in private clinics). • All patient encounters in the public sector were covered by government subsidies, while most A total of 864,552 medications were recorded, at rates of 265.3 medications per 100 encounters of the encounters in the private sector were paid for through out-of-pocket payments (59.7%) and 198.0 medications per 100 diagnoses (weighted data). and third-party payments (39.1%). • Medications were prescribed for 89.9% of all encounters (86.7% of encounters in public • More than half (55.2%) of the patients had a monthly personal income between MYR 1,000 clinics and 92.1% in private clinics). and MYR 2,999 (parental income excluded). In general, patients who visited private clinics The medication prescribing rates were higher in the private sector (276.8 medications per had higher incomes than those who utilised public clinics. • 100 encounters and 230.8 per 100 diagnoses) than in the public sector (248.5 per 100 • The vast majority (89.0%) of patients had received some form of formal education (primary encounters and 160.4 per 100 diagnoses). to tertiary levels). In general, the level of educational attainment was higher among private Nearly 60% of the encounters in private clinics were prescribed with three or more patients than among those who presented to public clinics. • medications, compared to 45.8% in the public sector. • Medical certificates were issued to 31.2% of patients (9.9% of patients in public clinics and The prescription rates were higher in the private sector for patients who were less than 40 33.4% in private clinics). The duration of sick leave given ranged from 0.5 to 20 days. • years old compared to those in the public sector regardless of gender. The trends were reversed for patients aged 40 years and above for both genders. Reasons for seeking treatment • The top three classes of medications prescribed in public clinics were cardiovascular agents (34.1%), alimentary tract and metabolism agents (24.7%) and respiratory agents (14.1%), A total of 597,563 patient-reported reasons for encounter (RFEs) were recorded at 325,818 while those most frequently prescribed in private clinics were respiratory agents (27.4%), encounters (252,050 RFEs in public clinics and 345,513 in private clinics), translating into an alimentary tract and metabolism agents (17.4%) and musculoskeletal medications (15.5%). average of 183.4 RFEs per 100 patient encounters (weighted data). • Seven out of the 10 most commonly prescribed medications in public clinics were for chronic • More than half (53.0%) of the patients presented with two or more RFEs per encounter. Most diseases (amlodipine, lovastatin, metformin, perindopril, gliclazide, hydrochlorothiazide and (61.4%) of the RFEs were expressed in terms of a symptom or complaint. simvastatin), accounting for 35.2% of all medications prescribed in public clinics. The three • The three most commonly recorded RFEs in public clinics were all chronic diseases: medications for acute conditions in the list were paracetamol, chlorphenamine and hypertension (31.3 per 100 encounters), diabetes (22.5 per 100 encounters) and lipid disorder diphenhydramine. (18.5 per 100 encounters).

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• In contrast, the 10 most frequently prescribed medications in private clinics were all Follow-ups and referrals medications for acute conditions (paracetamol, diclofenac, diphenhydramine, chlorphenamine, mefenamic acid, butylscopolamine, amoxicillin, pseudoephedrine, cetirizine About one-third (29.7%) of the patients presenting to primary care had a referral or follow-up and prednisolone). appointment (weighted data). Follow-up appointments were scheduled for 89,641 patients (27.5 per 100 encounters and 20.5 per 100 diagnoses), while referrals were issued for 11,068 patients (3.4 per 100 encounters and 2.5 per 100 diagnoses). Investigations ordered • Both follow-up rate and referrals rate were higher in the public sector compared to the Of all 325,818 primary care encounters, 22.6% had investigations ordered (39.6% in public clinics private sector (49.2% versus 12.9% and 5.8% versus 1.8%, respectively). and 11.1% in private clinics). A total of 143,758 orders for investigations were recorded, at rates • Referrals in public clinics were most often to medical specialists (34.0% of all referrals in of 44.1 per 100 encounters and 32.9 per 100 diagnoses (weighted data). public clinics, 2.0 per 100 encounters), followed by referrals within primary care (1.3 per 100 encounters) and those to hospitals (1.3 per 100 encounters). • The ordering rates of investigations were much higher in public clinics (82.5 investigations per 100 encounters and 53.2 per 100 diagnoses) than in private clinics (18.1 per 100 • Nearly half (47.7%) of all referrals recorded in the private sector were for medical specialists encounters and 15.1 per 100 diagnoses). (0.8 per 100 encounters), while hospital referrals constituted most of the other half (41.1%). The leading diagnoses for follow-up were hypertension (28.5% of all diagnoses with follow-up • Majority (82.0%) of the investigations recorded were pathological/laboratory tests. • Diagnostic radiology/imaging test constituted 9.3% of all investigations. appointments), diabetes (20.2%) and lipid disorder (18.5%). These three chronic diseases were also the three most commonly referred diagnoses (diabetes: 11.9%, hypertension: • Chemistry tests accounted for 55.8% of all investigations and 68.0% of all laboratory tests ordered. The most common chemistry tests ordered were glucose tests (7.6 per 100 10.2%, lipid disorder: 5.3%). encounters); tests for electrolytes, urea and creatinine (4.5 per 100 encounters); and lipid tests (4.5 per 100 encounters). Differences in primary care activities since NMCS 2012 • Glucose and/or glucose tolerance test was the most frequently ordered individual investigation in both public and private sectors (15.1 per 100 encounters in public clinics and The data presented in this report are by far the most comprehensive and detailed information on 2.5 per 100 encounters in private clinics). healthcare activities of both public and private primary care clinics in Malaysia. These data • Diabetes, hypertension and lipid disorder were the most common diagnoses for which confirm and extend the findings of the previous NMCS, which was conducted in three states and investigations were ordered. Together, these three chronic diseases represented half (49.9%) two regions in 2012. The findings of both NMCS 2012 and NMCS 2014 are largely similar. The of all diagnoses for which investigations were ordered. major changes are summarised below. Note that the classification of advice/counselling, procedures, follow-ups and referrals followed different approaches in the two surveys, and direct comparisons could not therefore be made for these primary care activities. Advice/counselling and procedures • Antenatal check-up was the fourth most common RFE recorded in public clinics in 2012, A total of 111,707 advice/counselling (34.3 per 100 encounters and 25.6 per 100 diagnoses) and accounting for 18.0% of all RFEs in public clinics. In 2014, antenatal examination 25,001 procedures (7.7 per 100 encounters and 5.7 per 100 diagnoses) were provided by primary represented only 9.3% of all RFEs in public clinics, ranking seventh among the top RFEs care providers (weighted data). recorded in the public sector. Metformin was the second most frequently prescribed medications (17.1 per 100 encounters) • Out of the 325,818 encounters recorded, 24.5% were managed with at least one form of • advice/counselling (37.5% in public clinics and 15.6% in private clinics), and 6.9% had some in the public sector in 2012, followed by amlodipine (15.9 per 100 encounters) and lovastatin procedures performed at the time of visit (5.0% in public clinics and 8.2% in private clinics). (14.8 per 100 encounters). In NMCS 2014, higher prescribing rates were recorded for all three medications, but the rates of increment were higher for amlodipine and lovastatin. As • The top three most frequently provided types of advice/counselling were general advice/education, advice/counselling on nutrition or weight management, and a result, amlodipine had become the second most frequently prescribed medication (20.0 per advice/counselling on lifestyle. Together, these accounted for 72.9% of all advice and 100 encounters) in public clinics in 2014, followed by lovastatin (17.5 per 100 encounters) counselling provided in primary care clinics. and metformin (17.4 per 100 encounters). The ordering rate for obstetric ultrasonography in public clinics had dropped from 9.2 per • Injection/infiltration was the most common procedure performed and accounted for 27.9% of • all procedures performed in primary care clinics, followed by procedure for dressing, 100 encounters in 2012 to 3.2 per 100 encounters in 2014. This corresponds with the reduced pressure or compression of wounds at 21.4%. number of antenatal encounters seen in public clinics in 2014. In private clinics, lipid profile test was ordered more frequently in 2014 than in 2012 (1.8 per • Advice/counselling and procedures were provided as part of the patient management for • 23.5% and 5.0% of all diagnoses, respectively. The most common diagnoses managed with 100 encounters versus 0.6 per 100 encounters, respectively). An opposite trend was observed advice and counselling were hypertension (20.6% of all diagnoses managed with advice and for the ordering rate of chest x-ray, which declined from 2.2 per 100 encounters in 2012 to counselling), diabetes (18.5%) and lipid disorder (13.9%), while asthma (8.5%), 0.7 per 100 encounters in 2014. musculoskeletal symptoms or complaints (5.4%) and skin laceration/cut (5.4%) were the three diagnoses most frequently managed with a procedure.

4 National Medical Care Statistics 2014

CHAPTER one Introduction

CHAPTER 1: INTRODUCTION Specific objectives

To collect information on clinical activities in primary care setting in Malaysia, including: 1.1 BACKGROUND • The characteristics of patients seen • Mode of payment for primary care services The National Healthcare Statistics Initiative (NHSI) is a family of surveys which aims to support • Reasons people seek medical care evidence-based health policy-making and research in Malaysia. It was initiated in 2009 by the • Problems managed, and for each problem managed: Healthcare Statistics Unit (HSU) of the National Clinical Research Centre (NCRC) in collaborations Pharmacological treatment prescribed, including the dose and frequency with various stakeholders. Over the past six years, the NHSI has grown and managed to gain local and o Non-pharmacological treatment provided, including procedures and counselling international recognition due to the usefulness of its reliable and timely data, which fill in the gap o Investigations ordered, including pathology and imaging between research and policy. Annual reports are published for the surveys under NHSI. o o Follow up in primary care and referrals to secondary or tertiary care o Issuance of medical certificate and duration of sick leave As one of the four members of NHSI, the National Medical Care Survey (NMCS) was first launched in 2010 and had its fair share of challenges. After consulting local and international researchers as well as stakeholders, a pilot study was conducted in 2012. The continued support from the Family Medicine 1.3 DEFINITIONS Research Centre team at the University of Sydney in Australia, which conducts a series of primary care research under the Bettering the Evaluation and Care of Health (BEACH) program,1 has been a major Definitions of primary care were adapted from the American Association of Family Physicians.4 The few contributing factor to NMCS. In addition, the revised methodology and an able steering Research terms that were taken are: Evaluation Committee had ensured the success of NMCS 2012. a) Primary care The questionnaire for NMCS 2014 was adapted from BEACH and NMCS 2012. Validation was done – The care provided by physicians specifically trained for and skilled in comprehensive first before proceeding with the improved forms for the 2014 project. The valuable information and contact and continuing care for persons with any undiagnosed sign, symptom, or health experience gained from NMCS 2012 contributed tremendously to the improvement of methodology, data concern (the "undifferentiated" patient) not limited by problem origin (biological, behavioural, collection strategies and analysis methods for NMCS 2014. or social), organ system, or diagnosis. – The care involved includes health promotion, disease prevention, health maintenance, counselling, patient education, diagnosis and treatment of acute and chronic illnesses in a While the NMCS 2012 was a pilot study that involved only three states and two regions, the NMCS variety of healthcare settings (e.g., office, inpatient, critical care, long-term care, home care, 2014 was conducted at national level. In fact, NMCS 2014 is the first nationwide study on public and day care, etc.). Primary care is performed and managed by a personal physician, often private primary care in Malaysia, where public and private clinics were randomly sampled from all 13 collaborating with other health professionals and utilising consultation or referral as states and three federal territories to be included in the survey. At the national level, NMCS 2014 is appropriate. providing information to the National Strategic Plan for Non-Communicable Disease (NSPNCD) b) Primary care setting 2010–2014 and the Malaysian Health System Reform (MHSR) research on the clinical management of – Primary care setting serves as the patient's first point of entry into the healthcare system and diseases and utilisation pattern in primary care settings.2,3 as the continuing focal point for all needed healthcare services. Primary care practices provide patients with ready access to their own personal physician or to an established back-up 1.2 OBJECTIVES physician when the primary physician is not available. c) Primary care doctors General objectives – Medical doctors or family medicine specialists (FMS) who provide primary care in the primary care setting. 1. To collect reliable and valid data in primary care setting. 2. To examine patient characteristics and utilisation pattern and the relationship these factors have Primary healthcare in Malaysia is provided by both public and private healthcare providers. with health service activities. Government clinics (Klinik Kesihatan) are funded by the government, while the private sector provides 3. To provide accurate and timely data to various stakeholders, including government bodies, primary services on a fee-for-service basis. In this report, the terms ‘public clinics’ and ‘private clinics’ are used care practitioners, consumers, researchers and the pharmaceutical industry. to describe these two types of primary care clinics. 4. To establish an on-going database of doctor-patient encounter information.

8 National Medical Care Statistics 2014

CHAPTER 1: INTRODUCTION Specific objectives

Chapter 1 : Introduction 9

1.4 RESEARCH QUESTIONS 1.41.4 Research RESEARCH Questions QUESTIO NS No. Question Answered by No.No. QuestionQuestion Answered byby 1 What types of patients are seen by primary care practitioners? Demographic characteristics 1 1 WhatWhat types types of ofpatients patients are are seen seen by by primary primary care care practitioners? practitioners? Demographic characteristicscharacteristics 2 What is the source of payment for primary care services? Mode of payment 2 2 WhatWhat is theis the source source of ofpayment payment for for primary primary care care services? services? Mode of payment 3 What motivates patients to seek care in the primary care setting? Patient’s reasons for visit 3 3 WhatWhat motivates motivates patients patients to to seek seek c arecare in in the the primary primary care care setting?setting? Patient’s reasons forfor visit visit What are the actual diagnoses/problems managed by primary care 4 WhatWhat are are the the actual actual diagnose diagnoses/s/problemsproblems managed managed by by primary primary carecare Doctor’s diagnosis/problems managed 4 4 practitioners? Doctor’s diagnosis/pdiagnosis/problemsroblems managed managed practitioners?practitioners? What are the pharmacological treatments prescribed by primary 5 WhatWhat are are the the pharmacological pharmacological treatments treatments prescribed prescribed by by primaryprimary Pharmacological interventions 5 5 care practitioners for each diagnosis? Pharmacological interventionsinterventions carecare practiti practitionersoners for for each each diagnosis? diagnosis? What are the procedures and imaging ordered by primary care 6 WhatWhat are are the the procedures procedures and and imaging imaging ordered ordered by by primary primary carecare Non-pharmacological interventions 6 6 practitioners for the diagnoses/problems? Non-pharmacological interventions interventions practitionerspractitioners for for the the diagnose diagnoses/s/problems?problems? What types of counselling are offered by primary care 7 WhatWhat types types of ofcounselling counselling are are offered offered by by primary primary care care Non-pharmacological interventions 7 7 practitioners for the diagnoses/problems? Non-pharmacological interventions interventions pracprtitionersactitioners for for the the diagnose diagnoses/s/problems?problems? 8 Is there any continuity of care in primary care setting? Referrals/follow-up 8 8 Is thereIs there any any continuity continuity of of care care in in primary primary care care setting? setting? Referrals/followollow--uupp WhatWhat is theis the extent extent of ofthe the loss loss of of productivity productivity for for the the morbidities morbidities inin Medical certificate (MC) (MC) and and duration duration 9 9 What is the extent of the loss of productivity for the morbidities in Medical certificate (MC) and duration 9 primaryprimary care care setting? setting? of sick leave primary care setting? of sick leave WhatWhat are are the the characteristics characteristics of of the the primary primary care care providers providers seeingseeing 10 10 What are the characteristics of the primary care providers seeing Providers’ characteristicscharacteristics 10 thethe patients? patients? Providers’ characteristics the patients? WhatWhat are are the the characteristics characteristics of of the the clinics clinics the the patients patients visit visit inin 11 11 What are the characteristics of the clinics the patients visit in Clinic establishmentss and and workforce workforce 11 primaryprimary care? care? Clinic establishments and workforce primary care?

AllAll research research question questions sare are addressed addressed in in this this report. report. WhileWhile mostmost questions are reportedreported inin aa chapter chapter of of All research questions are addressed in this report. While most questions are reported in a chapter of itsits own, own, some some related related questions questions are are discussed discussed together together withinwithin relevantrelevant chapters. its own, some related questions are discussed together within relevant chapters.

REFERENCESREFERENCES REFERENCES 1. 1.Bettering Bettering the the Evaluation Evaluation and and Care Care of of Health Health (BEACH) (BEACH) [Interne[Internet]. Sydney (Australia):(Australia): University University of of 1. Bettering the Evaluation and Care of Health (BEACH) [Internet]. Sydney (Australia): University of Sydney,Sydney, Family Family Medicine Medicine Research Research Centre; Centre; c2002c2002--20152015 [updated[updated 2015 SepSep 1515,, citedcited 20152015 Oct Oct 12]; 12]; Sydney, Family Medicine Research Centre; c2002-2015 [updated 2015 Sep 15, cited 2015 Oct 12]; [about[about 1 screen].1 screen]. Available Available from: from: http://sydney.edu.au/medicine/fmrc/beach/index.php http://sydney.edu.au/medicine/fmrc/beach/index.php 2.[aboutMinistry 1 screen]. of Health Available Malaysia from:. National http://sydney.edu.au/medicine/fmrc/beach/index.php Strategic Plan for Non-Communicable Disease (NSPNCD): 2. Ministry of Health Malaysia. National Strategic Plan for Non-Communicable Disease (NSPNCD): 2. Ministry of Health Malaysia. National Strategic Plan for Non-Communicable Disease (NSPNCD): mediummedium term term strategic strategic planplan toto furtherfurther strengthenstrengthen thethe cardiovascular diseasesdiseases && diabetesdiabetes mediumprevention term & controlstrategic program plan toin Malaysiafurther strengthen(2010–2014 ).the Putrajaya cardiovascular (Malaysia): diseases Ministry & of diabetesHealth prevention & control program in Malaysia (2010–2014). Putrajaya (Malaysia): Ministry of Health preventionMalaysia ,& Disease control C programontrol Division; in Malaysia 2010. 40 (2010 p. –2014). Putrajaya (Malaysia): Ministry of Health Malaysia, Disease Control Division; 2010. 40 p. 3.M alaysiaMalaysia, Disease Health Control Systems Division; Research 2010 Study. 40 [Internet]. p. Boston (MA): Harvard T.H. Chan School of 3. Malaysia Health Systems Research Study [Internet]. Boston (MA): Harvard T.H. Chan School of 3. MalaysiaPublic HealthHealth; Systems [cited Research 2015 StudyOct [Internet].12]; [about Boston (MA):3 screens].Harvard T.H.Available Chan Schoolfrom: of Public Health; [cited 2015 Oct 12]; [about 3 screens]. Available from: Publichttp://www.hsph.harvard.edu/global Health; [cited 2015 Oct 12];-health [ab-systemsout 3 -cluster/projects/malaysiascreens]. Available from:-health http://www.hsph-systems- . http://www.hsph.harvard.edu/global-health-systems-cluster/projects/malaysia-health-systems- harvard.edu/globalreform/ -health-systems-cluster/projects/malaysia-health-systems-reform/ reform/ 4. 4.American American Association Association of of Family Family PhysiciansPhysicians (AAFP).(AAFP). PrimaryPrimary Care [Internet][Internet].. LeadwoodLeadwood (KS):(KS): 4. American Association of Family Physicians (AAFP). Primary Care [Internet]. Leadwood (KS): AmericanAmerican Association Association of of Family Family Physicians Physicians; ;[ cited[cited 20152015 MarMar 23]; [about[about 44 screens]screens].. AvailableAvailable from: from: American Association of Family Physicians; [cited 2015 Mar 23]; [about 4 screens]. Available from: http://www.aafhttp://www.aafp.org/online/en/home/policy/policies/p/primarycare.htmlp.org/online/en/home/policy/policies/p/primarycare.htm http://www.aafp.org/online/en/home/policy/policies/p/primarycare.html

10 National Medical Care Statistics 2014

1.4 RESEARCH QUESTIONS 1.41.4 Research RESEARCH Questions QUESTIO NS No. Question Answered by No.No. QuestionQuestion Answered byby 1 What types of patients are seen by primary care practitioners? Demographic characteristics 1 1 WhatWhat types types of ofpatients patients are are seen seen by by primary primary care care practitioners? practitioners? Demographic characteristicscharacteristics 2 What is the source of payment for primary care services? Mode of payment 2 2 WhatWhat is theis the source source of ofpayment payment for for primary primary care care services? services? Mode of payment 3 What motivates patients to seek care in the primary care setting? Patient’s reasons for visit 3 3 WhatWhat motivates motivates patients patients to to seek seek c arecare in in the the primary primary care care setting?setting? Patient’s reasons forfor visit visit What are the actual diagnoses/problems managed by primary care 4 WhatWhat are are the the actual actual diagnose diagnoses/s/problemsproblems managed managed by by primary primary carecare Doctor’s diagnosis/problems managed 4 4 practitioners? Doctor’s diagnosis/pdiagnosis/problemsroblems managed managed practitioners?practitioners? What are the pharmacological treatments prescribed by primary 5 WhatWhat are are the the pharmacological pharmacological treatments treatments prescribed prescribed by by primaryprimary Pharmacological interventions 5 5 care practitioners for each diagnosis? Pharmacological interventionsinterventions carecare practiti practitionersoners for for each each diagnosis? diagnosis? What are the procedures and imaging ordered by primary care 6 WhatWhat are are the the procedures procedures and and imaging imaging ordered ordered by by primary primary carecare Non-pharmacological interventions 6 6 practitioners for the diagnoses/problems? Non-pharmacological interventions interventions practitionerspractitioners for for the the diagnose diagnoses/s/problems?problems? What types of counselling are offered by primary care 7 WhatWhat types types of ofcounselling counselling are are offered offered by by primary primary care care Non-pharmacological interventions 7 7 practitioners for the diagnoses/problems? Non-pharmacological interventions interventions pracprtitionersactitioners for for the the diagnose diagnoses/s/problems?problems? 8 Is there any continuity of care in primary care setting? Referrals/follow-up 8 8 Is thereIs there any any continuity continuity of of care care in in primary primary care care setting? setting? Referrals/followollow--uupp WhatWhat is theis the extent extent of ofthe the loss loss of of productivity productivity for for the the morbidities morbidities inin Medical certificate (MC)(MC) and and duration duration 9 9 What is the extent of the loss of productivity for the morbidities in Medical certificate (MC) and duration 9 primaryprimary care care setting? setting? of sick leave primary care setting? of sick leave WhatWhat are are the the characteristics characteristics of of the the primary primary care care providers providers seeingseeing 10 10 What are the characteristics of the primary care providers seeing Providers’ characteristicscharacteristics 10 thethe patients? patients? Providers’ characteristics the patients? WhatWhat are are the the characteristics characteristics of of the the clinics clinics the the patients patients visit visit inin 11 11 What are the characteristics of the clinics the patients visit in Clinic establishmentss and and workforce workforce 11 primaryprimary care? care? Clinic establishments and workforce primary care? AllAll research research question questions sare are addressed addressed in in this this report. report. WhileWhile mostmost questions are reportedreported inin aa chapter chapter of of CHAPTER two All research questions are addressed in this report. While most questions are reported in a chapter of itsits own, own, some some related related questions questions are are discussed discussed together together withinwithin relevantrelevant chapters. its own, some related questions are discussed together within relevant chapters.

REFERENCESREFERENCES REFERENCES Methodology 1. 1.Bettering Bettering the the Evaluation Evaluation and and Care Care of of Health Health (BEACH) (BEACH) [Interne[Internet]. Sydney (Australia):(Australia): University University of of 1. Bettering the Evaluation and Care of Health (BEACH) [Internet]. Sydney (Australia): University of Sydney,Sydney, Family Family Medicine Medicine Research Research Centre; Centre; c2002c2002--20152015 [updated[updated 2015 SepSep 1515,, citedcited 20152015 Oct Oct 12]; 12]; Sydney, Family Medicine Research Centre; c2002-2015 [updated 2015 Sep 15, cited 2015 Oct 12]; [about[about 1 screen].1 screen]. Available Available from: from: http://sydney.edu.au/medicine/fmrc/beach/index.php http://sydney.edu.au/medicine/fmrc/beach/index.php 2.[aboutMinistry 1 screen]. of Health Available Malaysia from:. National http://sydney.edu.au/medicine/fmrc/beach/index.php Strategic Plan for Non-Communicable Disease (NSPNCD): 2. Ministry of Health Malaysia. National Strategic Plan for Non-Communicable Disease (NSPNCD): 2. Ministry of Health Malaysia. National Strategic Plan for Non-Communicable Disease (NSPNCD): mediummedium term term strategic strategic planplan toto furtherfurther strengthenstrengthen thethe cardiovascular diseasesdiseases && diabetesdiabetes mediumprevention term & controlstrategic program plan toin Malaysiafurther strengthen(2010–2014 ).the Putrajaya cardiovascular (Malaysia): diseases Ministry & of diabetesHealth prevention & control program in Malaysia (2010–2014). Putrajaya (Malaysia): Ministry of Health preventionMalaysia ,& Disease control C programontrol Division; in Malaysia 2010. 40 (2010 p. –2014). Putrajaya (Malaysia): Ministry of Health Malaysia, Disease Control Division; 2010. 40 p. 3.M alaysiaMalaysia, Disease Health Control Systems Division; Research 2010 Study. 40 [Internet]. p. Boston (MA): Harvard T.H. Chan School of 3. Malaysia Health Systems Research Study [Internet]. Boston (MA): Harvard T.H. Chan School of 3. MalaysiaPublic HealthHealth; Systems [cited Research 2015 StudyOct [Internet].12]; [about Boston (MA):3 screens].Harvard T.H.Available Chan Schoolfrom: of Public Health; [cited 2015 Oct 12]; [about 3 screens]. Available from: Publichttp://www.hsph.harvard.edu/global Health; [cited 2015 Oct 12];-health [ab-systemsout 3 -cluster/projects/malaysiascreens]. Available from:-health http://www.hsph-systems- . http://www.hsph.harvard.edu/global-health-systems-cluster/projects/malaysia-health-systems- harvard.edu/globalreform/ -health-systems-cluster/projects/malaysia-health-systems-reform/ reform/ 4. 4.American American Association Association of of Family Family PhysiciansPhysicians (AAFP).(AAFP). PrimaryPrimary Care [Internet][Internet].. LeadwoodLeadwood (KS):(KS): 4. American Association of Family Physicians (AAFP). Primary Care [Internet]. Leadwood (KS): AmericanAmerican Association Association of of Family Family Physicians Physicians; ;[ cited[cited 20152015 MarMar 23]; [about[about 44 screens]screens].. AvailableAvailable from: from: American Association of Family Physicians; [cited 2015 Mar 23]; [about 4 screens]. Available from: http://www.aafhttp://www.aafp.org/online/en/home/policy/policies/p/primarycare.htmlp.org/online/en/home/policy/policies/p/primarycare.htm http://www.aafp.org/online/en/home/policy/policies/p/primarycare.html

CHAPTER 2: METHODOLOGY Table 2.1.1: Sample size (primary sampling units) for NMCS 2014

Public Private

State/federal territory The 2014 National Medical Care Survey (NMCS) is a national cross-sectional study of primary care Population Sample Population Sample activities. It utilised a multi-stage stratified cluster sampling design, with the primary care clinics acting as primary sampling units (PSUs). Random sampling of primary care clinics was performed for Johor 93 11 709 117 all states and federal territories in Malaysia, namely, Johor, Kedah, Kelantan, Melaka, Negeri Kedah 56 7 298 55

Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah, Sarawak, Selangor, Terengganu and Wilayah Kelantan 64 7 192 45 Persekutuan (WP) Kuala Lumpur. Two federal territories were combined with the neighbouring states Melaka 29 26 186 31 (WP Labuan with Sabah and WP Putrajaya with Selangor) in view of the geographical proximity and Negeri Sembilan 46 6 233 40 demographic similarities. Pahang 79 6 201 42

The data collection lasted 17 weeks, from 7 January 2014 to 15 May 2014. All sampled clinics were Perak 83 11 510 73 randomly allocated one day for data recording in their respective clinics, and all service providers Perlis 9 9 30 10 working on that particular day were involved in data collection. Pulau Pinang 30 5 398 70

Sabah & WP Labuan 92 9 311 65

2.1 SAMPLE SIZE CALCULATION AND SAMPLING METHODS Sarawak 196 10 225 34

Selangor & WP Putrajaya 76 15 1,520 270 Ideally, we would like to randomly sample the units of analysis which are the encounters; however this Terengganu 45 5 148 30 is not feasible in our current system. The reasons being we do not have an exhaustive list of primary WP Kuala Lumpur 13 12 685 120 care patients and it would not be practical, financially and logistically, to sample patients from all over the country. Hence the sampling could only be done via the clinics which act as a cluster of encounters. Total 911 139 5,646 1,002 The cluster effect of such sampling method will be adjusted in the analysis using statistical programme.

Sample size calculation Sampling methods

The number of encounters needed for the NMCS 2014 was first determined for each sector based on the The sampling frame of public and private clinics was generated by matching the list of clinics from formula proposed by Cochran1 by using the proportion of upper respiratory tract infection encounters National Healthcare Establishments and Workforce Survey (NHEWS) 2012 with several sources: from NMCS 2010. This number was then adjusted for the design effect (assumed to be 2) and expected • The list of public clinics (Klinik Kesihatan) from the Family Health Development Division, Ministry response rate from each sector. of Health (MOH) Malaysia. • The list of registered private clinics from the Private Medical Practice Division, Ministry of Health Subsequently, the adjusted number of encounters was proportionately distributed to each state and by Malaysia (often referred to as the Cawangan Kawalan Amalan Perubatan Swasta (CKAPS). using the average number of doctors per clinic and the average number of encounters per doctor from NHEWS Primary Care 2010, the number of clinics to be sampled for each stratum was calculated. We Both lists were updated as of 31st December 2012 and these were regarded as the most recent lists of expected a minimum of 30 encounters from each clinic. the public and private clinics at the period of survey.

The final sample consisted of 139 public clinics and 1,002 private clinics (Table 2.1.1). For Melaka and As for clinics that were not matched from the lists, subsequent verification by telephone calls was done Perlis, all public clinics were sampled because the total number of clinics in these strata was less than to determine the existence or current operational status of the establishments. Those that were found to 30, the minimum acceptable sample size for each stratum.2 be closed or do not meet our inclusion and exclusion criteria were removed from the sampling frame (Table 2.1.2).

12 National Medical Care Statistics 2014

CHAPTER 2: METHODOLOGY Table 2.1.1: Sample size (primary sampling units) for NMCS 2014

Public Private

Sabah & WP Labuan 92 9 311 65

2.1 SAMPLE SIZE CALCULATION AND SAMPLING METHODS Sarawak 196 10 225 34

Sample size calculation Sampling methods

Chapter 2 : Methodology 13

Table 2.1.2: Inclusion and exclusion criteria for the clinics sampled in the survey Stage 2: Sampling of survey date (secondary sampling unit)

Inclusion criteria • MOH Health Clinics (Klinik Kesihatan) which provide primary care services – Each sampled clinic was randomly assigned a date for data collection within the study period. • Private medical clinics registered with CKAPS and provide primary care – The following days were excluded: services o public holidays Exclusion criteria • Outpatient departments within hospital or maternity homes o weekends, including Friday, Saturday and Sunday • Public clinics with the following criteria: o Monday (Mondays are usually the busiest for public primary care clinics) – Health clinics without permanent medical doctors (Klinik Kesihatan) o a week before and during the festive season (Chinese New Year) – Clinics which provide only maternal and child health services (Klinik – If the clinic was closed on the date of survey, the doctor had the option to change the survey date to Kesihatan Ibu dan Anak) the next available working day, given that the research team was informed of the new survey date. – Rural health clinics (Klinik Desa) – 1 Malaysia clinics Stage 3: Sampling of doctors (including assistant medical officers & trained nurses in the • Private clinics with the following criteria: public clinics) (tertiary sampling unit) – Aesthetic clinics – Charity clinics – All doctors (including assistant medical officers and some trained nurses in public clinics) in the – Diagnostic centres sampled clinics who were on-duty on the day of survey were included. – Homeopathy clinics – Locum doctors were included. – In-house clinics/clinics which are affiliated with specific companies – As for doctors who are trained in clinical specialities, only family medicine specialists were – Specialist clinics /clinics which provide specialised care/ e.g. paediatric, included. cardiology, occupational therapy – Clinics which operate less than 5 days a week Sampling of encounters – Clinics which participated in NMCS 2012 – Record of all patient encounters seen by each health care personnel mentioned above on the survey date. Sample selection was conducted by stratified random cluster sampling, incorporating several stages. The details are described below. Following Figure 2.1.1 shows the study design of NMCS 2014, while Figure 2.1.2 and Figure 2.1.3 are consort diagrams which show the number of clinics sampled from each state for public and private Stratification sector respectively. Stage 1: Stratification by sector

– Each state or federal territory was stratified by either public or private sector.

Stage 2: Stratification by sampling regions

– Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah & WP Labuan, Sarawak, Selangor & WP Putrajaya, WP Kuala Lumpur and Terengganu.

Cluster sampling

Stage 1: Sampling of clinics (primary sampling unit)

– Random sampling of clinics was based on random numbers generated using Microsoft Excel 2007. – If a selected clinic was discovered to not fulfill the inclusion and exclusion criteria when contacted, the clinic was omitted and another clinic was randomly selected to replace it.

14 National Medical Care Statistics 2014

Table 2.1.2: Inclusion and exclusion criteria for the clinics sampled in the survey Stage 2: Sampling of survey date (secondary sampling unit)

– Each state or federal territory was stratified by either public or private sector.

Stage 2: Stratification by sampling regions

– Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Perlis, Pulau Pinang, Sabah & WP Labuan, Sarawak, Selangor & WP Putrajaya, WP Kuala Lumpur and Terengganu.

Cluster sampling

Stage 1: Sampling of clinics (primary sampling unit)

Chapter 2 : Methodology 15

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16 National Medical Care Statistics 2014

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Chapter 2 : Methodology 17

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g 2

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n g i i 0 u l n w

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a P c a m s t c

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i Various approaches were also taken to increase the acceptance and response rates of private clinics in

a l n s 0 i c i 37 2 00 2

m l 1 , l , particular, including: i

d r p 5 1 r 2012 =

e e

p l = r =

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p a m a) Approaching the top management of the chain clinics/group practices. e b n N s

m c b) Obtaining a written endorsement from the Malaysian Medical Association (MMA). a m 201 4 e i va t

c i S s

e r i c) Getting support and assistance from Malaysian Medical Association (MMA) at the state level. c 3 k l i p D 7

C f

st d) Presentation of the NMCS 2012 results through general practitioners’ seminar and a series of r = r o 1 li n e

3 c u r n P

articles in MMA bulletin. f p

e e o r b e) Organising private (individual) briefings alongside Medical Practice Division’s enforcement m s

a u m a c

u activities. L

y 12 0 n

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a l a t n m u PS i o Data was collected using a self-administered questionnaire. The details of the patients managed on the r K A

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C e

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l participants were given certificates, which they would later use to claim for continuing professional

i 4 e

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e education (CPD) points. A clinic-specific feedback, a satisfaction survey on the prescribers, and a copy of e r m e n p N e

w the National Medical Care Statistics 2014 report will also be sent to all participants.

– S

r e 2

m p 1

d a a 0 1 s e k 2 3 y

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ag r 2.3 RESEARCH PACK AND QUESTIONNAIRE u = d

i l e

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x i M 27 4 t

n e

r s N

s A pre-testing session of the questionnaire was carried out by convenience sampling of doctors from a

li n

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n h c

n c i s e

n t i i a l

i 5

c public and private clinics. The questionnaire was modified from the prior form developed in NMCS d n ur t i b s li n i d 4 d n li n o

s n c a li n h i e t e t o

c 2

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= c 2012 which was adapted from the Better Bettering the Evaluation and Care of Health (BEACH) survey t e s a C e i

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e j a K u n c

a c c e 1 i i

i i a o .

o r c t pre-testing were taken into consideration to further improvise the form. The NMCS 2014 form was c h h e m 2 5 r st h e s l

- o n p a 5 li n li n e a o p e

n modified based on these feedbacks and the finalised form is enclosed in Appendix 3. d P P U C C H I O S A =

e n K gu r

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18 National Medical Care Statistics 2014 u

0 ga n 3 g

= 2.2 DATA COLLECTION AND FOLLOW-UP n e n r e

T The sampled clinics were each sent an invitation letter to attend a briefing in major towns in each state.

g 2

n Briefings for doctors in the public clinics were held on weekdays, whereas briefings for private doctors 4 a

= h were conducted between October and December 2013 according to the convenience of the private doctors a n P

for maximum attendances. A research pack which contained the survey forms and instructions were

ya &

a distributed during the briefings. a j o r r 27 0 g t n u =

a To encourage further participation, representatives of clinics that did not attend the briefing were later P l n e

P contacted by telephone. If the doctor refused to participate, the team did not pursue further. However, if S

W k they agreed to participate the research pack was sent either by: a 4 3 a w = • courier service (Poslaju) followed by telephone call to ensure that the research kit is received.

) n e a r Briefing would be done over the phone to explain about the survey form s S

a b

• personal visit to the clinics (within the vicinity of Klang valley), where a short private briefing a an

64 6 t & , u 5 a would be given by the research team to the doctor/nurse in-charge 5 h 6 d

a b a = I =

L S

N n a b

H , P S

s A telephone call-reminder was made to the clinic about the project and to answer any questions c W N i h pertaining to the survey at two weeks and one day before the survey date. Instructions would be t

n g i i 0 u l n w

7 repeated when necessary. After the survey date, follow-up phone call(s) were made if the research pack a c

a l d = e e n u e was not returned after three weeks, and subsequently at five weeks. i r h n P a P c a m s t c

r c a f i y

m r n g i Various approaches were also taken to increase the acceptance and response rates of private clinics in

a l n s 0 i c i 37 2 00 2 m l 1 , l , particular, including: i d r p 5 1 r 2012 =

e e

p l = r =

n P e p a m a) Approaching the top management of the chain clinics/group practices. e b n N s m c b) Obtaining a written endorsement from the Malaysian Medical Association (MMA). a m 201 4 e i va t c i S s n e r i c) Getting support and assistance from Malaysian Medical Association (MMA) at the state level. c 3 k l i p D 7 a

C f

st d) Presentation of the NMCS 2012 results through general practitioners’ seminar and a series of r = r o 1 li n e

3 c u r n P

articles in MMA bulletin. f p e e o r b e) Organising private (individual) briefings alongside Medical Practice Division’s enforcement m s a u m a c

t u activities. L y 12 0 n r a li s l = a a l a t n m u PS i o Data was collected using a self-administered questionnaire. The details of the patients managed on the r K A

T p

P date assigned to each clinic were filled by the health providers. Upon completion of data collection,

C e i ( an W 0 r l participants were given certificates, which they would later use to claim for continuing professional i 4 e

va t b g k i =

e education (CPD) points. A clinic-specific feedback, a satisfaction survey on the prescribers, and a copy of e r m e n p N e

w the National Medical Care Statistics 2014 report will also be sent to all participants.

– S

r e 2 m p 1 d a a 0 1 s e k 2 3 y d a a l S

ag r 2.3 RESEARCH PACK AND QUESTIONNAIRE u = d

i l e

C s c d n 5 c

M x i M 27 4 t

n e r s N

s A pre-testing session of the questionnaire was carried out by convenience sampling of doctors from a li n c o s s c n h c n c i s e c n t i i a l i 5

c public and private clinics. The questionnaire was modified from the prior form developed in NMCS d n ur t i b s li n i d 4 d n li n o s n c a li n h i e t e t o

c 2 f t l e t

= c 2012 which was adapted from the Better Bettering the Evaluation and Care of Health (BEACH) survey t e s a C e i l c c l o r a : C l a n e e 4 t i p s e 3 li s t s h c t from Australia. A total of 30 encounters were recorded, and comments from the doctors based on the t i u . op a

e j a K u n c a c c e 1 i i i i a o . o r c t pre-testing were taken into consideration to further improvise the form. The NMCS 2014 form was c h h e m 2 5 r st h e s l

- o n p a 5 li n li n e a o p e n modified based on these feedbacks and the finalised form is enclosed in Appendix 3. d P P U C C H I O S A = e n K gu r i

F r o 11 7 h = o

J n

Chapter 2 : Methodology 19

Each research pack contained: Session 2: Question and answer

• Survey pads • Feedback was provided to data entry personnel on data entry and coding issues from the 20 test – 40 forms questionnaires – One set of instructions One case study – Standardisations to the data entry rules and coding systems were also periodically updated and One example of a completed form – conveyed to all data entry personnel. • NMCS 2014 summary information – Objectives of the NMCS 2014 Data quality assurance – Brief description of project and project team – Individual survey date of the clinics The data entry application was loaded with previous coding history from NMCS 2012 and also current • Public notice coding entry to ease the coding process and to ensure consistency of coding. – Notice to be displayed in the participating clinic to inform patients that the clinic is currently undertaking the NMCS survey Software based quality assurance measures were also built into the data entry applications either as a • ICPC-2-code list quality measure or to facilitate the data entry process. For example warnings prompt when there was a – ICPC-2-Code list duplication of identification card number being entered, warnings prompt of missing mandatory fields, auto-generation of date of birth and age through identification card number when available etc. Also included in the research pack:

• Call letter Validity checks were put in place during data entry to minimise entry of illogical data and warnings – Letter signed by the Director of the State Health Departments to inform the participating would pop-up if extreme values were entered to prompt the data entry personnel to re-check the data. clinics of the survey These include validation on the date of birth entered, gender counter check via identification card number when available, unable to enter the same diagnosis within the same encounter etc. • Prepaid envelope – One envelope for every two survey pads In addition to the aforementioned measures, double data entry was also incorporated as part of the quality assurance of the data. This form of quality check has been recommended and known to correct 2.4 DATA MANAGEMENT data entry errors from the original entry.5

Data entry Double data entry was done for more than 10% of the total entries (2,894 out of 27,808 forms) in six Prior to the start of data entry, all data entry personnel were given reference materials containing a batches, where Batch 1 was completed in June 2014 and Batch 6 in October 2014. Questionnaires that description of the study, examples of the questionnaire, classification and coding systems, data entry were to be entered a second time were identified by random selection of clinics. The data entry rules and regulations. This was followed by two sessions of data entry training of at least 2 hours each personnel were blinded to the assignment of clinics for double data entry. session. Data is then transferred from paper to an electronic format through a data entry web application by trained data entry personnel. For each batch of double data entry, all discrepancies between the first and second set of records were verified by checking either with the original forms or the coding definitions. Errors were defined as Session 1: Demonstration and practical session deviations of either the first or second entry from the original questionnaire by alphanumeric characters or assigning the wrong code for a variable. However those errors that were due illegible • Slide presentation on data entry module handwriting were not regarded as an error. A correct third record was then updated into the database. • Live demonstration of data entry module The percentage of data entry error for each available variable was then calculated by obtaining the • Live demonstration of coding systems proportion of errors per total cases within the variable. The variables with the highest rates of data • Discussion on data entry and coding systems entry error were then compared. • Practical session – practice data entry and coding of 20 test questionnaires per data entry personnel

20 National Medical Care Statistics 2014

Each research pack contained: Session 2: Question and answer

Chapter 2 : Methodology 21

TableTable 2.4.1:2.4.1: DataData entryentry errorerror raterate forfor NMCSNMCS 20142014 Classification of data (data coding)

DataDataData entry entry entry error error error (%) (%) (%) VariablesVariables International Classification of Primary Care (ICPC) BatchBatchBatch 1 1 1 BatchBatchBatch 2 2 2 BatchBatchBatch 3 3 3 Batch BatchBatch 4 4 4Batch BatchBatch 5 5 Batch5 BatchBatch 6 6 6 CodedCoded variables variables The International Classification of Primary Care Second Edition (ICPC-2) was used to classify the following data elements: ICPCICPC--2+2+ code code 3.53.53.5 1.5 1.51.5 4.8 4.84.8 3.0 3.03.0 6.0 6.06.0 1.9 1.91.9 ATCATC code code 1.31.31.3 0.9 0.90.9 1.5 1.51.5 2.3 2.32.3 1.2 1.21.2 1.8 1.81.8 • Reasons for encounter • Diagnoses NonNon--codedcoded variables variables • Investigations NationalityNationality 16.316.316.3 0.0 0.00.0 0.0 0.00.0 0.4 0.40.4 0.7 0.70.7 0.3 0.30.3 • Procedures Procedures/otherProcedures/other treatments/ treatments/ 8.98.98.9 1.2 1.21.2 1.1 1.11.1 2.0 2.02.0 3.0 3.03.0 1.5 1.51.5 • Advice/counselling counsellingcounselling

DiagnosisDiagnosis not not specified specified for for which which The ICPC-2 is accepted by the World Health Organization (WHO) as a member of the WHO Family of 6.26.26.2 2.1 2.12.1 0.0 0.00.0 1.3 1.31.3 0.2 0.20.2 0.5 0.50.5 medicalmedical certificated certificated was was issued issued International Classifications.9 It was published in 1987 by the World Organisation of Family Doctors (WONCA) and used in more than 45 countries as the standard for data classification in primary care. The ICPC-2 has a bi-axial structure, with 17 chapters based on body systems (Table 2.4.2) and seven TheThe threethree variablesvariables forfor thethe nonnon--codingcoding sectionsection werewere thethe variablesvariables withwith thethe highesthighest datadata entryentry errorerror raterate components (Table 2.4.3) with rubrics bearing a letter and two-digit numeric code. forfor batchbatch 1.1. ThereThere waswas markedmarked improvementimprovement inin errorerror raterate forfor thesethese variablesvariables fromfrom batchesbatches 11 toto 5.5. IncreaseIncrease ofof datadata entryentry errorerror raterate forfor thethe codedcoded variablesvariables cancan bebe attributedattributed toto recruitmentrecruitment ofof newnew datadata The data were entered and coded using ICPC-2 PLUS, an extended clinical terminology classified entryentry personnel,personnel, resultingresulting inin moremore variationsvariations inin coding.coding. WhileWhile manymany ofof thethe errorserrors werewere randomrandom errorserrors according to ICPC-2. ICPC-2 PLUS coding system contains extended terms commonly used in general butbut codingcoding errorserrors werewere largelylargely occurringoccurring inin aa systematicsystematic manner;manner; wherewhere aa datadata entryentry personnelpersonnel withwith aa practice that are more specific, and helps to ensure accurate classification to ICPC-2 during data entry. misconceptionmisconception ofof thethe correctcorrect codescodes forfor certaincertain diseases/medications,diseases/medications, makesmakes aa consistentconsistent errorerror throughoutthroughout ICPC-2 PLUS was developed in 1995, and is maintained and regularly updated by the Family Medicine allall forms forms entered. entered. Research Centre (FMRC) of the University of Sydney.10 Also known as BEACH coding system, ICPC-2 PLUS is primarily used in Australia especially for the national study of general practice activity, the ThereThere doesdoes notnot appearappear toto havehave aa generalgeneral consensusconsensus ofof acceptableacceptable datadata entryentry errorerror raterate worldwide.worldwide. BEACH program.4 PreviousPrevious studystudy shownshown thatthat ererrorror ratesrates detecteddetected byby doubledouble--entryentry methodmethod forfor clinicalclinical databasesdatabases rangedranged fromfrom 2.32.32.3 to toto 5.2% 5.2%5.2% for for fordemographic demographicdemographic data datadata while whilewhile for treatment forfor treatmenttreatment data, itdata,data, ranged itit rangedfromranged 10.0 fromfrom to 26.9% 10.010.0 6to.to Similarly, 26.9%6.26.9%6. Table 2.4.2: ICPC-2 chapters Similarly,FontaineSimilarly, P Fontaine Fontaineet. al reported PP et.et. alanal reportedoverallreported rate anan ofoveralloverall 7.3% forraterate data ofof 7.3% 7.3%entry for forstrategies datadata entryentry used strategiesstrategies in clinical uu trial.sedsed inin7 clinicalclinical trial.trial.77 Code ICPC-2 chapter Code ICPC-2 chapter Double entry has been recognised as the gold standard in transferring of data into an electronic A General B Blood, immune system DoubledatabaseDouble entryentry but it hashas substantially beenbeen recognisedrecognised increases asas thethe amountgoldgold standardstandard of time inandin transferringtransferring costs of data ofof entry. datadata intoCostsinto an anof electronicresourceselectronic D Digestive F Eye databasehavedatabase been but butreported itit substantiallysubstantially to be increas increasesincreasesed by up thethe to 2.5amountamount times of ofwith timetime double andand costs costsdata ofentryof datadata compared entry.entry. CostsCosts to single ofof resourcesresources entry5. H Ear K Circulatory haveAlso,have beenadditionalbeen reportedreported software toto bebe increas increassolutionseded bybyand upup manual toto 2.52.5 timestimes checking withwith doublemechanismsdouble datadata entry entryare required comparedcompared when toto singlesingle performing entry5.entry5. Also,checksAlso, additionaladditional on discrepancies softwaresoftware and solutionssolutions putting andinand corrections. manualmanual checkingchecking mechanismsmechanisms areare requiredrequired whenwhen performingperforming L Musculoskeletal N Neurological checkschecks on on discrepancies discrepancies and and putting putting in in corrections. corrections. P Psychological R Respiratory An alternative recommendation is a trade-off between acceptable data accuracy and cost-effectiveness S Skin T Endocrine, nutritional & metabolic AnusingAn alternativealternative single data recommendationrecommendation entry with concurrent isis aa tradetrade quality--offoff betweenbetween control acceptable acceptablemeasures, datadataexploratory accuracyaccuracy data andand analysis costcost--effectivenesseffectiveness and post- U Urological W Women’s health, pregnancy, family planning 5,6 usingentryusing logicsinglesingle checks. datadata entryentry It is withwith also concurrentconcurrent recognised qualityquality that double controlcontrol entry measures,measures, detects exploratoryexploratory errors where datadata explo analysisanalysisratory and andanalysis postpost-- X Female genital Y Male genital entrymissesentry logic logicwhile checks.checks. on the5,65,6 other ItIt isis hand alsoalso recognisedrecognisednot all discrepancies thatthat doubledouble found entryentry by detects detectsexploratory errorserrors data wherewhere analysis exploexplo ratoryisratory identified analysisanalysis by Z Social problems missesdoublemisses whileentry.while 8 onon Hence, thethe otherother suggests handhand that notnot alldoubleall discrepanciesdiscrepancies data entry foundfound alone byby may exploratoryexploratory not necessarily datadata analysisanalysis be sufficient isis identifiedidentified as a sole byby doubledatadouble quality entry.entry. checking88 Hence,Hence, method. suggestssuggests thatthat doubledouble datadata entryentry alonealone maymay notnot necessarilynecessarily bebe sufficientsufficient asas aa solesole datadata quality quality checking checking method. method.

All the errors which were detected (coded and non-coded) were corrected by referring to the original AformsAllll thethe and errorserrors by discussion whichwhich werewere among detecteddetected the investigators (coded(coded andand nonandnon- -coded)thecoded) Research werewere corrected correctedEvaluation byby Committee. referringreferring toto Further thethe originaloriginal logic formschecksforms and andand by byexploratory discussion discussion analysesamong among the the were investigators investigators also conducted and and the thedur Research Researching data Evaluation cleaningEvaluation to Committee. Committee.question the Further Further plausibility logic logic checksandchecks ensure andand exploratoryexploratorythe validity analysesanalyses of the data. werewere alsoAalso protocol conductedconducted with durdur validationinging datadata cleaningrulescleaning for to tocleaning questionquestion as thethe well plausibilityplausibility as data andinconsistencyand ensureensure thethe rules validityvalidity was compiled ofof thethe data.fordata. the AA purpose protocolprotocol of withdatawith cleaning.validationvalidation rulesrules forfor cleaningcleaning asas wellwell asas datadata inconsistencyinconsistency rules rules was was compiled compiled for for the the purpose purpose of of data data cleaning. cleaning.

22 National Medical Care Statistics 2014

Table 2.4.1: Data entry error rate for NMCS 2014 Classification of data (data coding) Classification of data (data coding) DataData entry entry error error (%) (%) Variables International Classification of Primary Care (ICPC) BatchBatch 1 1 BatchBatch 2 2 BatchBatch 3 3 BatchBatch 4 4Batch Batch 5 5Batch Batch 6 6 International Classification of Primary Care (ICPC) Coded variables The International Classification of Primary Care Second Edition (ICPC-2) was used to classify the followingThe International data elements: Classification of Primary Care Second Edition (ICPC-2) was used to classify the ICPC-2+ code 3.53.5 1.5 1.5 4.8 4.8 3.0 3.0 6.0 6.0 1.9 1.9 following data elements: ATC code 1.31.3 0.9 0.9 1.5 1.5 2.3 2.3 1.2 1.2 1.8 1.8 • Reasons for encounter Reasons for encounter •• Diagnoses Non-coded variables Diagnoses •• Investigations Nationality 16.316.3 0.0 0.0 0.0 0.0 0.4 0.4 0.7 0.7 0.3 0.3 Investigations •• Procedures Procedures/other treatments/ • Procedures 8.98.9 1.2 1.2 1.1 1.1 2.0 2.0 3.0 3.0 1.5 1.5 • Advice/counselling counselling • Advice/counselling

Diagnosis not specified for which The ICPC-2 is accepted by the World Health Organization (WHO) as a member of the WHO Family of 6.26.2 2.1 2.1 0.0 0.0 1.3 1.3 0.2 0.2 0.5 0.5 medical certificated was issued InternationalThe ICPC-2 isClassifications accepted by the.9 It World was published Health Organization in 1987 by the(WHO) World as aOrganisation member of theof FamilyWHO Family Doctors of 9 (WONCA)International and Classificationsused in more than. It was45 countries published as in the 1987 standard by the for World data Organisation classification ofin Family primary Doctors care. The(WONCA) ICPC-2 and has useda bi -axialin more structure, than 45 with countries 17 chapters as the standardbased on forbody data systems classification (Table 2.4.2) in primary and seven care. The three variables for the non-coding section were the variables with the highest data entry error rate componentsThe ICPC-2 (Table has a 2.4.3) bi-axial with structure, rubrics bearing with 17 a chaptersletter and based two- digiton body numeric systems code. (Table 2.4.2) and seven for batch 1. There was marked improvement in error rate for these variables from batches 1 to 5. components (Table 2.4.3) with rubrics bearing a letter and two-digit numeric code. Increase of data entry error rate for the coded variables can be attributed to recruitment of new data The data were entered and coded using ICPC-2 PLUS, an extended clinical terminology classified entry personnel, resulting in more variations in coding. While many of the errors were random errors accordingThe data to were ICPC entered-2. ICPC and-2 PLUScoded codingusing systemICPC-2 containsPLUS, anextended extended terms clinical commonly terminology used in classifiedgeneral but coding errors were largely occurring in a systematic manner; where a data entry personnel with a practiceaccording that to areICPC more-2. ICPCspecific,-2 PLUS and helps coding to ensuresystem accuratecontains classificationextended terms to ICPC commonly-2 during used data in generalentry. misconception of the correct codes for certain diseases/medications, makes a consistent error throughout ICPCpractice-2 PLUS that arewas more developed specific, in 1995,and helps and isto maintainedensure accurate and regularlyclassification updated to ICPC by the-2 during Family data Medicine entry. all forms entered. ResearchICPC-2 PLUS Centre was (FMRC) developed of the in University1995, and isof maintainedSydney.10 Also and knownregularly as BEACHupdated codingby the Familysystem, Medicine ICPC-2 10 PLUSResearch is primarily Centre (FMRC) used in ofAustralia the University especially of Sydney. for the nati Alsoonal known study as of BEACH general coding practice system, activity, ICPC the-2 There does not appear to have a general consensus of acceptable data entry error rate worldwide. BEACHPLUS is program. primarily4 used in Australia especially for the national study of general practice activity, the Previous study shown that error rates detected by double-entry method for clinical databases ranged BEACH program.4 from 2.32.3 toto 5.2% 5.2% for for demographic demographic data data while while for treatment for treatment data, itdata, ranged it rangedfrom 10.0 from to 26.9%10.0 6to. Similarly, 26.9%6. Table 2.4.2: ICPC-2 chapters Similarly,Fontaine P Fontaine et. al reported P et. alan reportedoverall rate an ofoverall 7.3% forrate data of 7.3% entry for strategies data entry used strategies in clinical u trial.sed in7 clinical Table 2.4.2: ICPC-2 chapters trial.7 Code ICPC-2 chapter Code ICPC-2 chapter Code ICPC-2 chapter Code ICPC-2 chapter Double entry has been recognised as the gold standard in transferring of data into an electronic A General B Blood, immune system A General B Blood, immune system Doubledatabase entry but ithas substantially been recognised increases as the amountgold standard of time inand transferring costs of data of entry.data intoCosts an of electronicresources D Digestive F Eye databasehave been but reported it substantially to be increas increasesed by up the to 2.5amount times of with time double and costs data ofentry data compared entry. Costs to single of resources entry5. D Digestive F Eye H Ear K Circulatory haveAlso, beenadditional reported software to be increas solutionsed by and up manualto 2.5 times checking with doublemechanisms data entry are requiredcompared when to single performing entry5. H Ear K Circulatory Also,checks additional on discrepancies software and solutions putting andin corrections. manual checking mechanisms are required when performing L Musculoskeletal N Neurological L Musculoskeletal N Neurological checks on discrepancies and putting in corrections. P Psychological R Respiratory P Psychological R Respiratory An alternative recommendation is a trade-off between acceptable data accuracy and cost-effectiveness S Skin T Endocrine, nutritional & metabolic S Skin T Endocrine, nutritional & metabolic Anusing alternative single data recommendation entry with concurrent is a trade quality-off between control acceptable measures, dataexploratory accuracy data and analysis cost-effectiveness and post- U Urological W Women’s health, pregnancy, family planning 5,6 U Urological W Women’s health, pregnancy, family planning usingentry logicsingle checks. data entry It iswith also concurrent recognised quality that double control entry measures, detects exploratory errors where data explo analysisratory and analysis post- X Female genital Y Male genital entrymisses logic while checks. on the5,6 other It is handalso recognisednot all discrepancies that double found entry by detects exploratory errors data where analysis explo ratoryis identified analysis by X Female genital Y Male genital Z Social problems 8 missesdouble whileentry. on Hence, the other suggests hand thatnot alldouble discrepancies data entry found alone by may exploratory not necessarily data analysis be sufficient is identified as a sole by Z Social problems 8 doubledata quality entry. checking Hence, method.suggests that double data entry alone may not necessarily be sufficient as a sole data quality checking method.

All the errors which were detected (coded and non-coded) were corrected by referring to the original Aformsll the and errors by discussion which were among detected the investigators (coded and nonand- coded)the Research were corrected Evaluation by Committee.referring to Further the original logic formschecks and and by exploratory discussion analysesamong the were investigators also conducted and the dur Researching data Evaluationcleaning to Committee.question the Further plausibility logic checksand ensure and exploratorythe validity analyses of the data.were alsoA protocol conducted with dur validationing data cleaningrules for to cleaning question as the well plausibility as data andinconsistency ensure the rules validity was compiled of the data.for the A purpose protocol of withdata cleaning.validation rules for cleaning as well as data inconsistency rules was compiled for the purpose of data cleaning.

Chapter 2 : Methodology 23

Table 2.4.3: ICPC-2 components 2.5 DATA ANALYSIS

ICPC-2 components Code Weighting 1. Complaints and symptoms 01–29 The data presented in this report were weighted to adjust for over and under representativeness of any 2. Diagnostics, screening and preventive 30–49 strata in the sample as well as to account for non-respondents. Table 2.5.1 shows the 28 weighting 3. Medication, treatment, procedures 50–59 strata that were defined for the study population, by state/region and sector. The components 4. Test results 60–61 incorporated in the estimation of total weights are described below. 5. Administrative 62 6. Referrals 63–69 Table 2.5.1: Strata according to state/region and sector 7. Diagnoses, diseases 70–99 – infectious State/federal territory Sector Stratum

– neoplastic Public J1 Johor – injuries Private J2

– congenital anomalies Public K1 Kedah – others Private K2

Public D1 Kelantan The National Clinical Research Centre has been granted a free research licence from WONCA for the Private D2 usage of ICPC-2 codes in the NHSI project which is valid from February 2011 till end of 2014 whereas Public M1 Melaka the ICPC-2 PLUS was obtained under a free licence from the University of Sydney. Private M2 Public N1 Negeri Sembilan Results were reported at the ICPC-2 classification level. Some of the diagnoses were grouped together Private N2 by combining several ICPC-2 or ICPC-2 PLUS codes (Appendix 4). Classification of pathology and Public C1 imaging test according to ICPC-2 can be very broad (e.g. HbA1c test is classified under T34 - Blood test Pahang Private C2 endo/metabolic). Hence, results for Chapter 10 were presented as ICPC-2 PLUS. Public A1 Perak Private A2 Anatomical Therapeutic Chemical (ATC) classification Public R1 Perlis Medications were coded and classified using the Anatomical Therapeutic Chemical (ATC) classification Private R2 system. ATC has been recommended by the WHO and used in many countries including Malaysia, as a Public P1 Pulau Pinang global standard for classifying medications for drug utilisation research, evaluating trend of drug Private P2 consumption and for international comparisons.11,12 Medications are classified into groups at five Public SB1 Sabah & WP Labuan different levels, with the following example: Private SB2 Public SW1 Sarawak • Level 1: C - Cardiovascular system Private SW2 • Level 2: C10 - Serum lipid reducing agents Public B1 • Level 3: C10A - Cholesterol of triglyceride reducers Selangor & WP Putrajaya Private B2 • Level 4: C10AA - HMG CoA reductase inhibitors Public W1 • Level 5: C10AA01 – Simvastatin WP Kuala Lumpur Private W2

The ATC licence was purchased from the WHO Collaborating Centre for Drug Statistics Methodology. Medications were entered as free text in generic (non-proprietary) or brand name, and coded by trained data entry personnel according to the Guidelines for ATC Classification and DDD assignment 2012.11 In certain cases, the doctors might not specify the medications down to the generic level hence it could only be coded to ATC level 3 or 4.

24 National Medical Care Statistics 2014

Table 2.4.3: ICPC-2 components 2.5 DATA ANALYSIS

– neoplastic Public J1 Johor – injuries Private J2

– congenital anomalies Public K1 Kedah – others Private K2

Chapter 2 : Methodology 25

Sampling weight Statistical analysis

15 16 Sampling weight is the inverse of the probability of selecting a unit.13 The sampling weight of each Analysis was done in R with an R package called "survey: analysis of complex survey samples". stratum calculated as follow14: Results are presented as number of unweighted counts, weighted counts, proportions and rate per 100 encounters along with 95% confidence interval (CI). Rate per 100 diagnoses are reported for management that can occur at more than once per diagnosis.

𝑴𝑴𝒋𝒋 𝑺𝑺𝑺𝑺𝒋𝒋 = 2.6 ETHICS APPROVAL 𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 + 𝒎𝒎𝒋𝒋.𝒏𝒏𝒏𝒏𝒏𝒏 + 𝒎𝒎𝒋𝒋.𝒆𝒆𝒆𝒆𝒆𝒆 where Mj is the total number of primary care clinics that can be sampled in the jth strata (population), The study was approved by the Medical Research and Ethics Committee (MREC) (Approval Number: mj.res is the number of primary care clinics responded for strata j, mj.non is the number of primary care NMRR-09-842-4718). As per previous study, a public notice was placed at each participating clinic to clinics who did not respond in the jth strata, and mj.exc is the number of clinics excluded after being sampled for strata j. inform patients that their prescription data would be collected for research purposes. Patients had the right to decline to participate at any point of time throughout the study period.

Activity weight 2.7 LIMITATIONS The activity weight for each clinic was calculated to account for the different level of activities of each clinic. It was calculated as follows: 1. The survey is self-administered and therefore precision of data depends largely on the completeness of recording by respondents, hence may not accurately reflect true practice. 2. The survey is encounter-based and reflects the morbidity pattern observed in the primary care setting rather than the prevalence of disease in the community. 𝑵𝑵𝒋𝒋𝒋𝒋 𝒋𝒋𝒋𝒋 3. The morbidity patterns reflect only those morbidities managed during the recorded encounters. 𝑨𝑨𝑨𝑨 = 𝒋𝒋𝒋𝒋 𝒏𝒏 There may be co-morbidity in the same patient which was not expected to be managed during the where Njk is the expected patients’ visits per day of the kth clinic in the jth strata while njk is the number encounter and hence was not recorded. of encounters we received from the kth clinic in the jth strata. 4. This is a cross-sectional study. Therefore, no conclusions may be generated on the outcomes of management of acute and chronic diseases in the primary care setting. Prescriptions, procedures, Adjustment for non-response imaging and referrals reported were those provided at the present point of encounter and did not necessarily indicate that the patient has not already received them in a previous encounter. 12 To account for less than 100% response rate, adjustment for the non-response is required. The non- 5. Maternal child health encounters in public clinics were mostly attended by trained nurses. NMCS response adjustment weight was calculated as follows: 2014 might miss those cases as not all the trained nurses were involved in the study. 6. The sampling of public clinics can be improved by incorporating the classification of the type of clinics, which is based on the workload of the clinic. 7. Verification of data received via audit process was not done. All data received were presumed to be 𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 + 𝒎𝒎𝒋𝒋.𝒏𝒏𝒏𝒏𝒏𝒏 𝑨𝑨𝒋𝒋 = accurate and precise. 𝒎𝒎𝒋𝒋.𝒓𝒓𝒓𝒓𝒓𝒓 8. Benchmarking the sample against population data cannot be performed as there is no readily where mj.res is the number of primary care clinics responded for strata j and mj.non is the number of primary care clinics who did not respond in the jth strata. available primary care population data, be it the providers or the patients. 9. Non-respondent details were not recorded; hence non-response analysis to compare the sample and the non-respondent cannot be performed. Total weight

The final weight for each stratum was calculated as the multiplication of the sampling weight, activity weight and adjustment for non-response.

𝐹𝐹𝐹𝐹!" = 𝑆𝑆𝑆𝑆!×𝐴𝐴𝐴𝐴!"×𝐴𝐴! The weighted estimates were generated using the survey package in R.

26 National Medical Care Statistics 2014

Sampling weight Statistical analysis

The final weight for each stratum was calculated as the multiplication of the sampling weight, activity weight and adjustment for non-response.

𝐹𝐹𝐹𝐹!" = 𝑆𝑆𝑆𝑆!×𝐴𝐴𝐴𝐴!"×𝐴𝐴! The weighted estimates were generated using the survey package in R.

Chapter 2 : Methodology 27

REFERENCES

1. Cochran WG. Sampling techniques. 2nd ed. New York: John Wiley and Sons, Inc; 1963. 2. Meza RA, Angelis M, Britt H, Miles DA, Seneta E, Bridges-Webb C. Development of sample size models for national general practice surveys. Aust J Public Health. 1995 Feb;19(1):34-40. 3. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia. 4. Britt H, Miller GC, Henderson J, Charles J, Valenti L, Harrison C, et al. General practice activity in Australia 2011–12. Sydney (Australia): Sydney University Press; 2012. p. 184-5. (General practice series; no. 31). 5. Büchele G, Och B, Bolte G, Weiland SK. Single vs. double data entry. Epidemiology. 2005 Jan;16(1);130-1. 6. Goldberg SI, Niemierko A, Turchin A. Analysis of data errors in clinical research databases. AMIA Annu Symp Proc. 2008 Nov 6:242-6. 7. Fontaine P, Mendenhall TJ, Peterson K, Speedie SM. The “Measuring Outcomes of Clinical Connectivity” (MOCC) trial: investigating data entry errors in the Electronic Primary Care Research Network (ePCRN). J Am Board Fam Med. 2007 Mar-Apr;20(2):151-9. 8. Day S, Fayers P, Harvey D. Double data entry: what value, what price? Control Clin Trials. 1998 Feb;19(1):15-24. 9. World Health Organization. World Health Organization family of international classifications [Internet]. Geneva (Switzerland): World Health Organization; 2004 June [cited 2014 Feb 8]. Available from: http://www.who.int/classifications/en/WHOFICFamily.pdf 10. ICPC-2 - International Classification for Primary Care [Internet]. Sydney (Australia): University of Sydney, Family Medicine Research Centre; c2002-2015 [updated 2012 Nov 22, cited 2014 Jan 12]; [about 1 screen]. Available from: http://sydney.edu.au/medicine/fmrc/icpc-2/index.php 11. WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment 2012. Oslo (Norway): WHO Collaborating Centre for Drug Statistics Methodology; 2011. 12. Lian LM, Kamarudin A, Siti Fauziah A, Nik Nor Aklima NO, Norazida AR, editors. Malaysian Statistics on Medicine 2008. Kuala Lumpur (Malaysia): Ministry of Health Malaysia, Pharmaceutical Services Division and Clinical Research Centre; 2013. 166 p. 13. Hahs-Vaughn DL. A primer for using and understanding weights with national datasets. J Exp Educ. 2005;73(3):221-48. 14. Foy P. Calculation of sampling weights. In: Martin MO, Kelly DL, editors. Third International Mathematics and Science Study technical report. Vol. 2, Implementation and analysis – primary and middle school years. Chestnut Hill (MA): Boston College, Center for the Study of Testing, Evaluation, and Educational Policy; c1997. p. 71-9. 15. R Development Core Team. R: a language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing; 2015. Available from: https://www.R-project.org 16. Lumley T. Analysis of complex survey samples. J Stat Softw. 2004 Apr;9(8):1-19.

28 National Medical Care Statistics 2014

REFERENCES

1. Cochran WG. Sampling techniques. 2nd ed. New York: John Wiley and Sons, Inc; 1963. 2. Meza RA, Angelis M, Britt H, Miles DA, Seneta E, Bridges-Webb C. Development of sample size models for national general practice surveys. Aust J Public Health. 1995 Feb;19(1):34-40. 3. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia. 4. Britt H, Miller GC, Henderson J, Charles J, Valenti L, Harrison C, et al. General practice activity in Australia 2011–12. Sydney (Australia): Sydney University Press; 2012. p. 184-5. (General practice series; no. 31). 5. Büchele G, Och B, Bolte G, Weiland SK. Single vs. double data entry. Epidemiology. 2005 Jan;16(1);130-1. 6. Goldberg SI, Niemierko A, Turchin A. Analysis of data errors in clinical research databases. AMIA Annu Symp Proc. 2008 Nov 6:242-6. 7. Fontaine P, Mendenhall TJ, Peterson K, Speedie SM. The “Measuring Outcomes of Clinical Connectivity” (MOCC) trial: investigating data entry errors in the Electronic Primary Care Research Network (ePCRN). J Am Board Fam Med. 2007 Mar-Apr;20(2):151-9. 8. Day S, Fayers P, Harvey D. Double data entry: what value, what price? Control Clin Trials. 1998 Feb;19(1):15-24. 9. World Health Organization. World Health Organization family of international classifications [Internet]. Geneva (Switzerland): World Health Organization; 2004 June [cited 2014 Feb 8]. Available from: http://www.who.int/classifications/en/WHOFICFamily.pdf 10. ICPC-2 - International Classification for Primary Care [Internet]. Sydney (Australia): University of Sydney, Family Medicine Research Centre; c2002-2015 [updated 2012 Nov 22, cited 2014 Jan 12]; CHAPTER three [about 1 screen]. Available from: http://sydney.edu.au/medicine/fmrc/icpc-2/index.php 11. WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment 2012. Oslo (Norway): WHO Collaborating Centre for Drug Statistics Methodology; 2011. 12. Lian LM, Kamarudin A, Siti Fauziah A, Nik Nor Aklima NO, Norazida AR, editors. Malaysian Response Rate

Statistics on Medicine 2008. Kuala Lumpur (Malaysia): Ministry of Health Malaysia, Pharmaceutical Services Division and Clinical Research Centre; 2013. 166 p. 13. Hahs-Vaughn DL. A primer for using and understanding weights with national datasets. J Exp Educ. 2005;73(3):221-48. 14. Foy P. Calculation of sampling weights. In: Martin MO, Kelly DL, editors. Third International Mathematics and Science Study technical report. Vol. 2, Implementation and analysis – primary and middle school years. Chestnut Hill (MA): Boston College, Center for the Study of Testing, Evaluation, and Educational Policy; c1997. p. 71-9. 15. R Development Core Team. R: a language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing; 2015. Available from: https://www.R-project.org 16. Lumley T. Analysis of complex survey samples. J Stat Softw. 2004 Apr;9(8):1-19.

Table 3.1.2: Total number of encounters received for NMCS 2014 CHAPTER 3: RESPONSE RATE Public Private

Number State/federal Number of Number of Number of 3.1 RESPONSE RATE Response of Response territory encounters encounter encounters rate (%) encounter rate (%) expected responded expected This chapter describes the survey sample and the response rate for NMCS 2014. A total of 139 public responded clinics and 1,002 private clinics were sampled in NMCS 2014. The clinics are listed in Appendix 5. The Johor 1,164 1,753 100.0 3,597 1,295 36.0 response rates were calculated as the number of clinics that responded by returning the NMCS 2014 Kedah 746 627 84.0 1,694 803 47.4 questionnaire divided by the number of clinics in the sample. Table 3.1.1 shows the number of clinics Kelantan 778 621 79.8 1,395 607 43.5 sampled, number of clinics responded to the survey and the clinic response rate for each state or federal Melaka 450 2,357 100.0 941 325 34.5 territory. Negeri Sembilan 697 510 73.2 1,223 739 60.4

Pahang 698 494 70.8 1,277 532 41.7 Table 3.1.1: Total number of clinics sampled and responded for NMCS 2014 Perak 1,174 1,375 100.0 2,228 807 36.2 Public Private Perlis 152 581 100.0 320 323 100.0

Number Number of Number Number of Pulau Pinang 581 794 100.0 2,139 917 42.9 State/federal territory Response Response of clinics clinics of clinics clinics rate (%) rate (%) Sabah& WP sampled responded sampled responded 927 709 76.5 1,997 736 36.9 Labuan Johor 11 10 90.9 117 43 36.7 Sarawak 1,062 947 89.2 1,056 567 53.7

Selangor & WP Kedah 7 7 100.0 55 22 40.0 1,627 1,707 100.0 8,265 2,691 32.6 Putrajaya Kelantan 7 7 100.0 45 22 48.9 Terengganu 498 383 76.9 929 575 61.9 Melaka 26 23 88.5 31 14 45.2 WP Kuala Lumpur 397 2,612 100.0 3,671 1,200 32.7 Negeri Sembilan 6 5 83.3 40 19 47.5 Total 10,951 15,470 100.0 30,732 12,117 39.4 Pahang 6 6 100.0 42 18 42.9

Perak 11 11 100.0 73 30 41.1 Response rate by encounters obtained from public clinics of all thirteen states and three federal Perlis 9 7 77.8 10 7 70.0 territories were overwhelming and some exceeded 100.0%. WP Kuala Lumpur recorded the highest Pulau Pinang 5 5 100.0 70 33 47.1 response rate with more than six times encounters that were required for the study, while the lowest

Sabah & WP Labuan 9 7 77.8 65 26 40.0 was 70.8% from Pahang. As for private sector, the minimum response rate by encounters was 32.7%

Sarawak 10 10 100.0 34 16 47.1 from WP Kuala Lumpur, while Perlis recorded the maximum response rate of 100.0%. The overall response rate for public and private sector was 100.0% and 39.4%, respectively. Selangor & WP Putrajaya 15 14 93.3 270 102 37.8

Terengganu 5 5 100.0 30 18 60.0 The low response rate however, has already been anticipated and accounted for. When calculating WP Kuala Lumpur 12 12 100.0 120 46 38.3 sample size, the sampling matrix had included an estimation of a 30.0% drop-out rate from the public Total 139 129 92.8 1,002 416 41.5 and a 70.0% drop-out rate from the private sector.

Overall, more than three quarters of public clinics from thirteen states and three federal territories This huge estimated rate of drop-out from the private sector was expected based on previous studies responded to NMCS 2014. The maximum response rate was 100.0% while the minimum is 77.8%, which conducted comparing public and private health sectors in Malaysia. The reported response rate from gave the overall response rate of 92.8% in public sector. As for private sector, the lowest response rate private clinics in these studies was between 26.0% and 33.0%.1,2 The same observation was made in was only 37.6%, bringing the overall response rate to 41.5%, in spite of our fervent attempts to persuade Australia in the BEACH survey, with only 25.9% and 25.2% of the contactable general practitioners the GPs to participate. agreed and completed the survey in 2013-14 and 2012-13 respectively.3,4

Response rates by encounters are reported in Table 3.1.2. These response rates were calculated as the number of encounters that were recorded for NMCS 2014 divided by the expected number of encounters in the sample for each stratum to form a national representative data.

30 National Medical Care Statistics 2014

Table 3.1.2: Total number of encounters received for NMCS 2014 CHAPTER 3: RESPONSE RATE Public Private

Pahang 698 494 70.8 1,277 532 41.7 Table 3.1.1: Total number of clinics sampled and responded for NMCS 2014 Perak 1,174 1,375 100.0 2,228 807 36.2 Public Private Perlis 152 581 100.0 320 323 100.0

Sabah & WP Labuan 9 7 77.8 65 26 40.0 was 70.8% from Pahang. As for private sector, the minimum response rate by encounters was 32.7%

Chapter 3 : Response Rate 31

3.2 THE ENCOUNTERS

A total of 27,813 encounters were collected for NMCS 2014. Of these, 226 encounters were excluded from analysis; 61 of incomplete forms and 165 with data inconsistencies. The final encounters for analysis were 27,587; 15,470 from public and 12,117 from private. The dataset were weighted to adjust for over and under representativeness of data (see Section 2.5). Table 3.2.1 shows the observed and weighted total for each data element. The final weighted patient encounters were 325,818, and the results are presented as weighted estimates in this report.

Table 3.2.1: Observed and weighted dataset for NMCS 2014

Observed Weighted Variable Overall Public Private Overall Public Private

Encounters 27,587 15,470 12,117 325,818 131,624 194,194

Reasons for encounter 50,642 29,478 21,164 597,563 252,050 345,513

Diagnoses 38,151 23,760 14,391 436,743 203,868 232,874

Medications 70,711 38,296 32,415 864,552 327,087 537,465

Investigations 14,208 12,182 2,026 143,758 108,557 35,201

Advice/counselling and 12,926 9,500 3,426 136,708 77,670 59,038 procedures Follow-up and referrals 9,841 8,143 1,698 100,709 72,418 28,291

REFERENCES

1. Teng CL, Tong SF, Khoo EM, Lee V, Zailinawati AH, Mimi O, et al. Antibiotics for URTI and UTI – prescribing in Malaysian primary care settings. Aust Fam Physician. 2011 May;40(5):325-9. 2. Mimi O, Tong SF, Nordin S, Teng CL, Khoo EM, Abdul-Rahman A, et al. A comparison of morbidity patterns in public and private primary care clinics in Malaysia. Malays Fam Physician. 2011 Apr 30;6(1):19-25. 3. Britt H, Miller GC, Henderson J, Bayram C, Harrison C, Valenti L, et al. General practice activity in Australia 2013–14. Sydney (Australia): Sydney University Press; 2014. (General practice series; no. 36). 4. Britt H, Miller GC, Henderson J, Bayram C, Valenti L, Harrison C, et al. General practice activity in Australia 2012–13. Sydney (Australia): Sydney University Press; 2013. (General practice series; no. 33).

32 National Medical Care Statistics 2014

3.2 THE ENCOUNTERS

Table 3.2.1: Observed and weighted dataset for NMCS 2014

Observed Weighted Variable Overall Public Private Overall Public Private

Encounters 27,587 15,470 12,117 325,818 131,624 194,194

Reasons for encounter 50,642 29,478 21,164 597,563 252,050 345,513

Diagnoses 38,151 23,760 14,391 436,743 203,868 232,874

Medications 70,711 38,296 32,415 864,552 327,087 537,465

Investigations 14,208 12,182 2,026 143,758 108,557 35,201

Advice/counselling and 12,926 9,500 3,426 136,708 77,670 59,038 procedures Follow-up and referrals 9,841 8,143 1,698 100,709 72,418 28,291

REFERENCES

1. Teng CL, Tong SF, Khoo EM, Lee V, Zailinawati AH, Mimi O, et al. Antibiotics for URTI and UTI – CHAPTER four prescribing in Malaysian primary care settings. Aust Fam Physician. 2011 May;40(5):325-9. 2. Mimi O, Tong SF, Nordin S, Teng CL, Khoo EM, Abdul-Rahman A, et al. A comparison of morbidity patterns in public and private primary care clinics in Malaysia. Malays Fam Physician. 2011 Apr 30;6(1):19-25. The Practices 3. Britt H, Miller GC, Henderson J, Bayram C, Harrison C, Valenti L, et al. General practice activity in Australia 2013–14. Sydney (Australia): Sydney University Press; 2014. (General practice series; no. 36). 4. Britt H, Miller GC, Henderson J, Bayram C, Valenti L, Harrison C, et al. General practice activity in Australia 2012–13. Sydney (Australia): Sydney University Press; 2013. (General practice series; no. 33).

CHAPTER 4: THE PRACTICES In the NMCS 2014 survey, a total of 129 public clinics out of 139 sampled (92.8%) and 409 private clinics out of 1,002 sampled (40.8%) responded to the healthcare provider profile questionnaire. These clinics were nationally representative by sector with regard to facilities, services and workforce, and This chapter reports the characteristics of public and private primary care clinics. The data was survey data were weighted to produce unbiased national estimates. obtained through the healthcare provider profile form (Appendix 2), which was completed by the healthcare providers during data collection. Information captured included the practice characteristics and the sociodemographic characteristics of the healthcare providers, the latter of which will be 4.2 ATTENDANCES reported in the next chapter. Private clinics outnumber public clinics in quantity nationwide. However, data from NMCS 2014 show that more patients were seen in the public clinics, which reported a median attendance rate of 111.5 4.1 PRIMARY CARE CLINICS IN MALAYSIA presentations per day (IQR: 71.9–264.3), compared to 33.0 per day (IQR: 25.0–50.0) in private clinics. These findings extend our previous results from 2012, which showed similar patterns of primary care Primary care services in Malaysia exist in two parallel systems—a heavily subsidised public sector and attendances in all five states studied.5 a private sector largely funded by out-of-pocket payments. According to data from the Ministry of Health Malaysia, there were 911 public clinics and 5,646 private clinics in Malaysia in 2012 (see Chapter 2), corresponding to a public-to-private ratio of 1:6. 4.3 OPERATING DAYS AND HOURS

Public clinics With a population of about 29.2 million, the density of primary care clinics in Malaysia was 2.2 clinics per 10,000 population in 2012 (Figure 4.1.1), with the highest density recorded in WP Kuala Lumpur Table 4.3.1 shows the operating days and hours of public clinics in 2014. (4.1 clinics per 10,000 population). Majority of the more urbanised West Coast states (Selangor, Pulau As with other government establishments in Malaysia, a large majority (82.8%) of public clinics Pinang, Negeri Sembilan, Melaka, Perak and Johor) had a density of 2.3–2.8 clinics per 10,000 • operated five days in a week (Monday to Friday). population. In comparison, Singapore reported a density of 2.8 general practitioner practices per 10,000 About one-eighth (12.6%) of the public clinics reported operating seven days per week, while the population in 2013,1,2 whereas Australia had 3.3 general practitioner practices per 10,000 population in • remaining 4.7% had a six-day-per-week operation. 2011.3,4 • Slightly more than half (52.1%) of the public clinics operated during the standard office hours (between 8.00 a.m. to 5.00 p.m.) only. Figure 4.1.1: Number of primary care clinics per 10,000 population in 2012 • The remaining 47.9% of public clinics also provided after-hours services in addition to the standard-hour operation. On-call services (at least one healthcare provider could be called to help WP Labuan 1.1 in cases of emergency) were provided in 39.6% of clinics, while extended-hours services (regular Sabah 1.1 clinic operation beyond the standard office hours) were available in 8.5% of the clinics. Kelantan 1.6 Perlis 1.6 Table 4.3.1: Operating days and hours of public clinics in 2014 Sarawak 1.7 WP Putrajaya 1.8 Unweighted Weighted Percent of clinics Clinic operation count count (95% CI) Terengganu 1.8 (n = 129) (n = 664) (n = 664) Kedah 1.8 Pahang 1.8 Operating days Johor 2.3 5 days/week 110 550 82.8 (75.4–90.2) Perak 2.5 6 days/week 8 31 4.7 (1.1–8.2) Melaka 2.6 7 days/week 11 83 12.6 (5.8–19.3) Negeri Sembilan 2.6 Operating hours Pulau Pinang 2.7 Office hours 77 346 52.1 (42.5–61.7) Selangor 2.8 Office hours + on call services 37 262 39.4 (30.3–48.5) WP Kuala Lumpur 4.1 Office hours + extended hours 14 55 8.3 (3.5–13.1) Malaysia 2.2 Office hours + extended hours + on call services 1 1 0.2 (0.0–0.4) 0 1 2 3 4 5

Number of clinics per 10,000 population

34 National Medical Care Statistics 2014

Number of clinics per 10,000 population

Chapter 4 : The Practices 35

Private clinics 4.6 COMPUTER USE

The operating days and hours of private clinics are shown in Table 4.3.2. Note that private clinics which The implementation of health information technology, such as electronic health records, may appear operated less than five days in a week were excluded from NMCS 2014. As a result, the operating days difficult and cumbersome. However, significant benefits can be reaped from the adoption of health and hours of these clinics were not captured by the survey. information technology, including improved technical efficiency, increased adherence to guidelines, enhanced disease surveillance, reduced medication errors, decreased utilisation of care and reduction in • More than half (54.0%) of the clinics in the private sector operated six days per week. healthcare costs.6,7 • Clinics which operated Monday through Sunday represented 40.2% of all private clinics, while only 5.8% of the private clinics operated five days in a week. • Only 5.0% of the clinics in the private sector provided 24-hour services. Only 19.4% of public clinics (n = 129) reported having a functional computer system in the practice. In contrast, 71.6% of the private clinics surveyed (n = 3,443) reported the use of computers in the practice. Figure 4.6.1 illustrates the extent of computer use in each sector. Table 4.3.2: Operating days and hours of private clinics in 2014 • Amongst the clinics which reported the use of computers, only 18.1% of public clinics and 36.6% of Percent of clinics private clinics were fully computerised. Unweighted count Weighted count Clinic operation (95% CI) (n = 409) (n = 4,810) • In the public sector, the computer system was mainly used for registration (83.7%) and medical (n = 4,810) record keeping (83.3%) purposes, whereas in the private sector the main reason for using a Operating days computer system was for billing purpose (79.6%).

5 days/week 24 280 5.8 (3.6–8.0) 6 days/week 222 2,597 54.0 (49.3–58.7) Figure 4.6.1: Types of computer use in primary care by sector in 2014 7 days/week 163 1,933 40.2 (35.5–44.9) 100 Operating hours 83.3 83.7

< 24 hours/day 390 4,570 95.0 (92.9–97.1) 90 79.6 24 hours/day 19 240 5.0 (2.9–7.1) 80 63.8 69.8 70 4.4 TYPE OF PRACTICE 57.3 60

• All public clinics were collaborative practices staffed with multiple healthcare providers who 44.7 worked under salaried employment with the government. 50 • About a quarter (24.7%) of the private clinics operated as group practices, while the remaining 36.6 40 27.2 were solo practices (Table 4.4.1). A similar figure has been reported in our previous report.5 30 18.1 18.1 Percent of clinics (%) Table 4.4.1: Type of practice for private clinics in 2014 20 16.0

Percent of clinics Unweighted count Weighted count 10 Type of practice (95% CI) (n = 409) (n = 4,810) (n = 4,810) 0 Fully Billing Dispensing Medical Registration Others Group 98 1,188 24.7 (20.6–28.8) computerised records Individual 311 3,622 75.3 (71.2–79.4) Public Private

4.5 PROVIDER WORKLOAD

• Overall, the median number of patients seen per full-time-equivalent (FTE) doctor in the private sector was 25.9 (IQR: 17.1–40.0) patients per day. • The public clinic attendances were recorded at the clinic level and could not be disaggregated by healthcare providers. Hence, the patient volume per FTE doctor could not be calculated for the public clinics.

36 National Medical Care Statistics 2014

Private clinics 4.6 COMPUTER USE

< 24 hours/day 390 4,570 95.0 (92.9–97.1) 90 79.6 24 hours/day 19 240 5.0 (2.9–7.1) 80 63.8 69.8 70 4.4 TYPE OF PRACTICE 57.3 60

4.5 PROVIDER WORKLOAD

4.7 WORKFORCE Figure 4.7.1: Primary care clinics with family medicine specialists by sector in 2014

2.9 Information regarding the workforce, which was gathered through the healthcare provider profile 100 questionnaire (see Section 3 of Appendix 2), is reported here. Table 4.7.1 shows the distribution of 40.1 97.1 primary care workforce in the public and private sectors by their designation. Doctors with 90 postgraduate qualifications other than family medicine specialists (FMS) were included in the non-FMS 80 category of doctors.

• A median of three doctors, six staff nurses, three assistant medical officers, seven community 70 nurses and one pharmacist were working in a public clinic in 2014. 60 • In the private clinics, a median of one doctor and three clinic assistants were present in each clinic. 59.9 50 Yes Table 4.7.1: Healthcare workforce by sector in primary care clinics in 2014 No 40 Public Private

Percent of clinics (%) 30 Number of Number of personnel personnel Designation Unweighted Weighted Unweighted Weighted 20 per clinic, per clinic, count count count count median median 10 (IQR) (IQR)

FMS 58 268 0 (0–1) 12 140 0 (0–0) 0 Public Private Doctor 606 2,734 3 (2–6) 659 7,856 1 (1–2)

Assistant 433 2,038 3 (2–3) 5 49 0 (0–0) medical officer Pharmacist 338 1,394 1 (1–2) 4 33 0 (0–0) REFERENCES Nurses 1. Singapore Department of Statistics. Population trends 2014. Singapore: Singapore Ministry of Staff nurse 1,029 4,699 6 (4–9) 233 2,922 0 (0–0) Trade and Industry, Department of Statistics; 2014. Community 1,341 6,398 7 (5–12) 6 83 0 (0–0) 2. Primary healthcare services [Internet]. Singapore: Singapore Ministry of Health; [updated 2015 nurse Jan 2, cited 2015 Sep 13]; [about 1 screen]. Available from: Clinic 4 26 NA 1,363 15,667 3 (2–4) https://www.moh.gov.sg/content/moh_web/home/our_healthcare_system/Healthcare_Services/Prima assistant ry_Care.html Note: FMS – Family medicine specialist; NA – Not applicable. 3. Hordacre AL, Howard S, Moretti C, Kalucy E. Moving ahead. Report of the 2006–2007 Annual Survey of Divisions of General Practice. Adelaide (Australia): Primary Health Care Research and Family medicine specialists (FMS) constitute an integral part of the provision of quality primary care Information Service; 2008. Supported by the Australian Government Department of Health and service to the public. The distribution of clinics with family medicine specialist is shown in Figure 4.7.1. Ageing. Other doctors with postgraduate qualifications will be discussed in the next chapter. 4. Australian Government Department of Immigration and Border Protection. The people of Australia: statistics from the 2011 Census. Canberra (Australia): Department of Immigration and Border • Two out of every five public clinics had a family medicine specialist in the practice. Protection (AU); 2014. • In comparison, only three out of 100 private clinics reported having a family medicine specialist in 5. Hwong WY, Sivasampu S, Aisyah A, Shantha Kumar C, Goh PP, Hisham AN, editors. National the practice. Healthcare Establishment & Workforce Statistics (Primary Care) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 44 p. Report No.: NCRC/HSU/2013.2. Grant No.: NMRR-09-842-4718. Supported by the Ministry of Health Malaysia. 6. DesRoches CM, Campbell EG, Rao SR, Donelan K, Ferris TG, Jha A, et al. Electronic health records in ambulatory care — a national survey of physicians. N Engl J Med. 2008 Jul 3;359(1):50- 60. 7. Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006 May 16;144(10):742-52.

38 National Medical Care Statistics 2014

4.7 WORKFORCE Figure 4.7.1: Primary care clinics with family medicine specialists by sector in 2014

Percent of clinics (%) 30 Number of Number of personnel personnel Designation Unweighted Weighted Unweighted Weighted 20 per clinic, per clinic, count count count count median median 10 (IQR) (IQR)

FMS 58 268 0 (0–1) 12 140 0 (0–0) 0 Public Private Doctor 606 2,734 3 (2–6) 659 7,856 1 (1–2)

Chapter 4 : The Practices 39

CHAPTER five The Doctors

CHAPTER 5: THE DOCTORS Table 5.1.1: Characteristics of primary care doctors in 2014

Unweighted Weighted Percent of doctors Characteristics count count A recent report published by the Association of American Medical Colleges projected that by 2025 the (95% CI) (n = 936) (n = 10,964) primary care physician demand in the United States will grow by 17% and exceed supply by 12,500 to 31,100 physicians, with population aging and growth accounting for the majority of the increase in Sector demand.1 Malaysia will likely face a similar trend of primary care doctor shortage, with the proportion Public 490 2,992 27.3 (24.0–30.6) of the elderly population (people aged 60 and over) projected to increase from 8.8% in 2014 to 12.2% in Private 446 7,972 72.7 (69.4–76.0) 2025 and 16.3% in 2040.2 A multi-pronged strategy, which should include innovation in healthcare Private 446 7,972 72.7 (69.4–76.0) delivery models, expansion of health professional training capacity, and greater and more effective use Gender of health technologies, is required to address the looming crisis in primary care doctor shortage. Male 426 5,668 51.9 (47.2–56.6) Female 508 5,263 48.2 (43.4–52.9) The supply and quality of primary healthcare workforce is highly influenced by the undergraduate and Missinga 2 33 - postgraduate education of health professionals. Malaysia has a well-established undergraduate health Age (years) professional education system to support the development of primary care workforce.3 Postgraduate 25–34 392 2,714 25.1 (22.0–28.3) training programmes in family medicine have also been in existence since the late 1980s and early 25–34 392 2,714 25.1 (22.0–28.3) 1990s to support and promote the provision of comprehensive and continuing primary care.4 However, it 35–44 185 2,444 22.6 (18.8–26.5) was only in 1997 that the first graduates of the Masters in Family Medicine programme from the local 45–54 190 3,313 30.7 (25.6–35.7) universities entered the public system. Nonetheless, the rapid proliferation of training institutions for 55–64 120 1,634 15.1 (12.2–18.0) health professionals with limited quality assurance, the changing demography and disease burdens, the ≥ 65 40 696 6.5 (4.0–8.9) increasing feminisation of healthcare workforce, and the rising community expectations continue to Missinga 9 162 - present significant challenges to the delivery of quality primary healthcare.3,5-7 Missing 9 162 - Experience in primary care (years)

This chapter reports the characteristics of primary care doctors in both public and private sectors. The < 5 383 2,790 25.8 (22.5–29.2) information on the participating doctors was acquired through the healthcare provider profile 5–9 122 1,312 12.2 (9.2–15.1) questionnaire (Appendix 2). ≥ 10 422 6,699 62.0 (57.8–66.3) Missinga 9 162 - 5.1 CHARACTERISTICS OF THE DOCTORS Place of graduation

Local 456 5,314 48.5 (43.8–53.2) A total of 936 doctors from public (n = 490) and private clinics (n = 446) participated in NMCS 2014. Foreign 479 5,641 51.5 (46.8–56.2) Nine (1.0%) of the returned healthcare provider profile questionnaires included incomplete responses to Missinga 1 9 - survey items. Analyses were performed using all available data, with missing values excluded from the Missing 1 9 - analysis of the corresponding parameters. The survey responses were weighted to produce national Postgraduate qualification estimates. With postgraduate qualifications 120 1,717 15.7 (12.3–19.0) Table 5.1.1 shows the characteristics of primary care doctors in Malaysia for 2014. Masters in family medicine 25 135 7.9 (4.2–11.6) MAFP/FRACGP 8 99 5.7 (1.2–10.3) • The majority (72.7%) of primary care doctors were working in the private sector. MAFP/FRACGP 8 99 5.7 (1.2–10.3) • Slightly more than half (51.9%) of the doctors were male. MRCGP/FRCGP 4 54 3.2 (0.0–6.3) • Nearly half (47.7%) of the doctors were less than 45 years old (median age: 45.0 years, IQR: 34–53 Diploma in family medicine 31 486 28.3 (18.1–38.5) years). Others 55 1,017 59.2 (48.6–69.9) • The majority (62.0%) of the doctors had been working in the primary care setting for 10 years or No postgraduate qualifications 816 9,247 84.3 (81.0–87.7) more (median: 13 years, IQR: 4–21 years). • Overseas trained doctors accounted for the greater proportion (51.5%) of the primary care doctor Working hours per week Median (IQR)

workforce. Overall - - 45 (40–50) • Nearly one-sixth (15.7%) of the doctors had at least one postgraduate qualification. Public - - 44 (40–45) • Median working hours was 45 hours per week (IQR: 40–50 hours per week). Private - - 48 (40–55) a a Missing data excluded from analysis Note: MAFP – Membership of the Academy of Family Physicians of Malaysia; FRACGP – Fellowship of the Royal Australian College of General Practitioners; MRCGP – Membership of the Royal College of General Practitioners; FRCGP – Fellowship of the Royal College of General Practitioners; IQR – interquartile range.

42 National Medical Care Statistics 2014

CHAPTER 5: THE DOCTORS Table 5.1.1: Characteristics of primary care doctors in 2014

Chapter 5 : The Doctors 43

5.2 GENDER 5.3 AGE DISTRIBUTION

Figure 5.2.1 shows the distribution of public and private doctors by gender. The age distribution of primary care doctors is shown in Figure 5.3.1. • Most (30.7%) of the primary care doctors in Malaysia fell in the age group of 45–54 years, followed • Overall, more than half of the primary care doctors in Malaysia were males (51.9%). by those aged 25–34 years old (25.1%). • More than two-thirds (70.5%) of the public primary care doctors were females. • The vast majority (79.9%) of doctors practising in the public sector were within the youngest age • In comparison, the proportion of female doctors in the private sector was 39.7%. group (25–34 years). Only 6.2% of the public doctors were 45 years or older. • In contrast, most (40.2%) of the doctors in the private sector were between the ages of 45 and 54, Figure 5.2.1: Distribution of public and private doctors by gender in 2014 while those aged 25–34 years accounted for only 4.2% of doctors in private practices. • The median age for doctors in public sector was 30 years old (IQR: 28–33 years), whereas the 100 private sector was 49 years old (IQR: 43–57 years). 90 70.5 39.7 Figure 5.3.1: Distribution of public and private doctors by age group in 2014 80 100 4.2 70 79.9 26.0 90 60 60.3 Female 50 80 Male 40 70 40.2

Percent of doctors (%) 30 29.5 60 25–34 years 20 35–44 years 50 10 45–54 years

0 40 55–64 years Public Private ≥ 65 years Percent of doctors (%) 30 Note: Missing data excluded from analysis. 20.8 20 13.9

5.9 0.3 8.9 0 Public Private

Note: Missing data excluded from analysis.

5.4 EXPERIENCE

Figure 5.4.1 presents the distribution of public and private doctors by years of experience in primary care.

• Nearly two-thirds (62.0%) of the primary care doctors had practised in primary care for 10 years or more. • The vast majority (74.8%) of the public sector doctors had less than five years of primary care experience. Conversely, in the private practice, 81.1% of the doctors had more than 10 years of experience in primary care.

44 National Medical Care Statistics 2014

5.2 GENDER 5.3 AGE DISTRIBUTION

Percent of doctors (%) 30 29.5 60 25–34 years 20 35–44 years 50 10 45–54 years

0 40 55–64 years Public Private ≥ 65 years Percent of doctors (%) 30 Note: Missing data excluded from analysis. 20.8 20 13.9

5.9 0.3 8.9 0 Public Private

Note: Missing data excluded from analysis.

5.4 EXPERIENCE

Figure 5.4.1 presents the distribution of public and private doctors by years of experience in primary care.

Chapter 5 : The Doctors 45

Figure 5.4.1: Distribution of public and private doctors by years of experience in 2014 Figure 5.5.1: Distribution of public and private doctors by place of graduation in 2014

100 100 74.8 7.1

90 11.8 90

80 80 81.1 49.9 48.0 70 70

60 60 < 5 years Local 50 50 5–9 years Foreign 40 ≥ 10 years 40 Percent of doctors (%)

Percent of doctors (%) 30 30 50.1 52.0 20 20 13.0 10 10 12.2 0 0 Public Private Public Private

Note: Missing data excluded from analysis. Note: Missing data excluded from analysis.

These findings were consistent with the age distribution of doctors in the public and private sectors. 5.6 POSTGRADUATE QUALIFICATION The public-private differences in age structure and experience could be plausibly attributed to the regulations governing medical practice in Malaysia. Medical graduates are required to fulfil several Primary care doctors may specialise in family medicine via Master of Family Medicine programmes, years of mandatory public service before they are allowed to move to private practice. This could have Membership of the Academy of Family Physicians of Malaysia (MAFP), Fellowship of the Royal profound implications for patient care, with a greater burden being placed on senior doctors who remain Australian College of General Practitioners (FRACGP), or Membership or Fellowship of the Royal in the public sector, while the expertise of the more experienced doctors is underutilised in the private College of General Practitioners (MRCGP/FRCGP). To qualify as a family medicine specialist in sector.3 Malaysia, the postgraduate degree must be credentialed by the Ministry of Health. Other postgraduate qualifications include Diploma in Family Medicine, diplomas in occupational health, dermatology, diagnostic ultrasound/radiography, master’s degrees in public health, and Membership of the Royal 5.5 PLACE OF GRADUATION College of Physicians.

Undergraduate medical degrees awarded by 33 local medical schools (11 public and 22 private) and 375 Figure 5.6.1 shows the distribution of primary care doctors by postgraduate qualification. accredited foreign medical schools are recognised by the Malaysian Medical Council.8 Graduates from recognised institutions are eligible for registration to practise medicine in Malaysia, while international • Only 15.7% of the primary care doctors held at least one postgraduate qualification. medical graduates who hold unrecognised degrees must pass the qualifying examination to be eligible • A higher proportion of doctors in the private sector held at least one postgraduate qualification for registration. Figure 5.5.1 shows the distribution of primary care doctors by their place of graduation. compared to the public sector (18.8% versus 7.3%, respectively).

• More than half (51.5%) of the doctors in primary care obtained their medical degree from a foreign country. • The proportions of locally trained and overseas trained doctors were about the same within and across sectors, with 49.9% of doctors in the public sector and 48.0% of private sector doctors graduated from medical schools in Malaysia.

46 National Medical Care Statistics 2014

Figure 5.4.1: Distribution of public and private doctors by years of experience in 2014 Figure 5.5.1: Distribution of public and private doctors by place of graduation in 2014

100 100 74.8 7.1

90 11.8 90

80 80 81.1 49.9 48.0 70 70

60 60 < 5 years Local 50 50 5–9 years Foreign 40 ≥ 10 years 40 Percent of doctors (%)

Percent of doctors (%) 30 30 50.1 52.0 20 20 13.0 10 10 12.2 0 0 Public Private Public Private

Note: Missing data excluded from analysis. Note: Missing data excluded from analysis.

Chapter 5 : The Doctors 47

Figure 5.6.1: Distribution of public and private doctors by postgraduate qualification in 2014

100 7.3 18.8 90

60 With postgraduate 50 qualification 92.7 40 81.2 No postgraduate qualification 30 Percent of doctors (%) 20

0 Public Private

5.7 WORKING HOURS

• Overall, the median working hours per week for primary care doctors was 45.0 (IQR: 40.0–50.0). • The median working hours per week was 44.0 (IQR: 40.0–45.0) in public clinics and 48.0 (IQR: 40.0–55.0) in private clinics. • Generally, doctors in the public sector had more stable working hours compared with their counterparts in the private sector, as reflected in the smaller IQR of hours worked per week for the public sector.

REFERENCES

1. Dall T, West T, Chakrabarti R, Lacobucci W; IHS Inc. The complexities of physician supply and demand: projections from 2013 to 2025. Washington, DC: Association of American Medical Colleges; 2015. 59 p. 2. Department of Statistics Malaysia. Population projections Malaysia 2010-2040. Kuala Lumpur (Malaysia): Department of Statistics (MY); 2013 Jan. 3. World Health Organization Regional Office for the Western Pacific. Human resources for health country profiles: Malaysia. Geneva (Switzerland): World Health Organization; 2014. 47 p. 4. Kwa SK. Family medicine specialisation in Malaysia [Internet]. Kuala Lumpur (Malaysia): Family Medicine Specialists Association of Malaysia; [cited 2015 Sep 18]; [about 4 screens]. Available from: http://fms-malaysia.org/home/?page_id=175 5. Truglio J1, Graziano M, Vedanthan R, Hahn S, Rios C, Hendel-Paterson B, et al. Global health and primary care: increasing burden of chronic diseases and need for integrated training. Mt Sinai J Med. 2012 Jul-Aug;79(4):464-74. 6. Hedden L, Barer ML, Cardiff K, McGrail KM, Law MR, Bourgeault IL. The implications of the feminization of the primary care physician workforce on service supply: a systematic review. Hum Resour Health. 2014 Jun 4;12:32. 7. KPMG. Health workforce in Australia and factors for current shortages. Adelaide (Australia): National Health Workforce Taskforce (AU); 2009 Apr. 8. Medical Act 1971. Second Schedule: List of Registrable Qualifications (Nov. 9, 2011).

48 National Medical Care Statistics 2014

Figure 5.6.1: Distribution of public and private doctors by postgraduate qualification in 2014

100 7.3 18.8 90

60 With postgraduate 50 qualification 92.7 40 81.2 No postgraduate qualification 30 Percent of doctors (%) 20

0 Public Private

5.7 WORKING HOURS

REFERENCES 1. Dall T, West T, Chakrabarti R, Lacobucci W; IHS Inc. The complexities of physician supply and The Patients demand: projections from 2013 to 2025. Washington, DC: Association of American Medical Colleges; 2015. 59 p. 2. Department of Statistics Malaysia. Population projections Malaysia 2010-2040. Kuala Lumpur (Malaysia): Department of Statistics (MY); 2013 Jan. 3. World Health Organization Regional Office for the Western Pacific. Human resources for health country profiles: Malaysia. Geneva (Switzerland): World Health Organization; 2014. 47 p. 4. Kwa SK. Family medicine specialisation in Malaysia [Internet]. Kuala Lumpur (Malaysia): Family Medicine Specialists Association of Malaysia; [cited 2015 Sep 18]; [about 4 screens]. Available from: http://fms-malaysia.org/home/?page_id=175 5. Truglio J1, Graziano M, Vedanthan R, Hahn S, Rios C, Hendel-Paterson B, et al. Global health and primary care: increasing burden of chronic diseases and need for integrated training. Mt Sinai J Med. 2012 Jul-Aug;79(4):464-74. 6. Hedden L, Barer ML, Cardiff K, McGrail KM, Law MR, Bourgeault IL. The implications of the feminization of the primary care physician workforce on service supply: a systematic review. Hum Resour Health. 2014 Jun 4;12:32. 7. KPMG. Health workforce in Australia and factors for current shortages. Adelaide (Australia): National Health Workforce Taskforce (AU); 2009 Apr. 8. Medical Act 1971. Second Schedule: List of Registrable Qualifications (Nov. 9, 2011).

CHAPTER 6: THE PATIENTS Table 6.1.1: Characteristics of primary care patients in 2014

Unweighted Weighted count Percent of patients Characteristics count (n = 325,818) (95% CI) The characteristics of patients presenting to primary care are reported in this chapter. These include (n = 27,587) the sociodemographic characteristics (age, gender, nationality, ethnicity, individual income and Sector education level) and mode of payment. Issuance of medical certificates and duration of sick leaves given Public 15,470 131,624 40.4 (34.9–45.9) (if any) during primary care visits are also reported here. Private 12,117 194,194 59.6 (54.1–65.1) Gender

6.1 CHARACTERISTICS OF THE PATIENTS Male 12,108 149,026 46.4 (45.1–47.8) Female 15,030 171,904 53.6 (52.2–54.9) A total of 27,587 encounters (15,470 in public clinics and 12,117 in private clinics) were captured in Missinga 449 4,889 - NMCS 2014. Post-stratification weighting translated this figure into a total of 325,818 primary care Age (years) encounters: 131,624 (40.4%) in public clinics and 194,194 (59.6%) in private clinics. < 1 776 7,611 2.3 (1.9–2.8)

Table 6.1.1 shows the characteristics of primary care patients in Malaysia for 2014. 1–4 1,599 18,582 5.7 (5.1–6.3) 5–19 3,599 38,060 11.7 (10.9–12.6) • Females accounted for the greater proportion (53.6%) of all encounters. 20–39 8,899 120,897 37.3 (35.1–39.4) • The median age of the patients was 35.7 years (IQR: 23.5–52.7 years), and the age distribution was 40–59 7,728 90,706 28.0 (26.7–29.2) as follows: infants < 1 year: 2.3%, 1–4 years: 5.7%, 5–19 years: 11.7%, 20–39 years: 37.3%, 40–59 years: 28.0%, and ≥ 60 years: 15.0%. ≥ 60 4,882 48,610 15.0 (13.5–16.4) • Malaysians made up 93.3% of all encounters. Majority of the patients were Malay (62.6%), followed Missinga 104 1,352 - by Chinese (21.2%), Indian (10.8%) and other ethnic groups (5.4%). Nationality

• Most (43.0%) patient encounters were paid for by government subsidies, followed by out-of-pocket Malaysian 25,622 297,259 93.3 (91.9–94.6) payments (34.1%) and third-party payments (22.3%). Non-Malaysian 1,424 21,487 6.7 (5.4–8.1) • About two-thirds (64.0%) of patients reported having personal income. More than half (55.2%) of Missinga 541 7,073 - the patients had a monthly personal income between MYR 1,000 and MYR 2,999 (parental income Ethnicity excluded). Malay 16,428 188,777 62.6 (59.0–66.2) • The vast majority (89.0%) of patients had received some form of formal education: 20.8% had primary education, 46.9% had completed at least some secondary education, and 21.3% had Chinese 5,234 63,959 21.2 (18.2–24.2) tertiary education. Indian 2,673 32,551 10.8 (9.1–12.5) • Medical certificates were issued to 31.2% of patients. Most (83.3%) of the issuances took place in Othersb 1,634 16,367 5.4 (3.8–7.0) the private sector. The duration of sick leave given ranged from 0.5 to 20 days. Missinga 1,618 24,164 - Mode of payment

Government subsidies 15,473 131,653 43.0 (37.3–48.6) Out of pocket 7,005 104,435 34.1 (30.4–37.7) Third party payer 3,903 68,332 22.3 (19.3–25.3) Combinationsc 53 1,007 0.3 (0.2–0.4) Othersd 61 1,035 0.3 (0.2–0.5) Missinga 1,092 19,356 - Type of income

No income 9,466 96,344 36.0 (33.3–38.7) Income 11,846 155,607 58.1 (55.3–61.0) Pension 1,333 14,110 5.3 (4.5–6.1) Parental incomee 142 1,581 0.6 (0.3–0.8) Missinga 4,800 58,176 -

50 National Medical Care Statistics 2014

CHAPTER 6: THE PATIENTS Table 6.1.1: Characteristics of primary care patients in 2014

No income 9,466 96,344 36.0 (33.3–38.7) Income 11,846 155,607 58.1 (55.3–61.0) Pension 1,333 14,110 5.3 (4.5–6.1) Parental incomee 142 1,581 0.6 (0.3–0.8) Missinga 4,800 58,176 -

Table 6.1.1 (continued): Characteristics of primary care patients in 2014 6.2 AGE-GENDER DISTRIBUTION

Unweighted Figure 6.2.1 and Figure 6.2.2 show the age-gender distribution of patients attending public clinics and Weighted count Percent of patients Characteristics count (n = 325,818) (95% CI) private clinics, respectively. (n = 27,587) • Females accounted for 59.6% of encounters in public clinics. The proportion of female patients was Monthly income (MYR)f significantly higher among the adult age groups (20–39 years: 19.0% versus 8.1%; 40–59 years:

< 400 398 3,657 2.3 (1.6–2.9) 18.4% versus 11.8%), while no significant gender differences were observed among infants, children, 400–499 139 1,351 0.8 (0.6–1.1) adolescents and the elderly. 500–699 539 5,364 3.3 (2.6–4.1) • In the private sector, the proportions of male and female patients were similar, both overall and 700–999 1,519 18,198 11.3 (9.7–12.9) across all age groups. • Patients aged 40–59 years accounted for the greatest proportion (30.3%) of encounters recorded in 1,000–1,999 4,298 51,678 32.1 (29.2–35.0) public clinics, while most (44.3%) patients who presented to private clinics were between 20 and 39 2,000–2,999 2,643 37,155 23.1 (21.4–24.7) years of age. 3,000–3,999 1,596 22,948 14.3 (13.2–15.3) • Nearly one-quarter (22.9%) of the patients who visited public clinics were 60 years and older, about 4,000–4,999 557 9,477 5.9 (4.2–7.6) 2.6 times higher than the projected proportion of elderly in the general population for 2014 ≥ 5,000 728 11,180 6.9 (5.9–8.0) reported by the Department of Statistics Malaysia (8.8%).1 In contrast, the proportion of elderly Missinga 762 8,709 - patients in private clinics (9.7%) was similar to the projected proportion of elderly population. Education level

No formal education 2,756 28,109 11.0 (9.7–12.2) Figure 6.2.1: Distribution of public patients by age and gender in 2014 Primary 4,855 53,200 20.8 (19.5–22.1) 45 Secondary 10,264 119,959 46.9 (45.1–48.6)

Tertiary 3,962 54,601 21.3 (19.2–23.5) 40 Missinga 5,750 69,949 - Issuance of medical certificate 35

Yes 5,224 77,884 31.2 (28.6–33.7) 30 Public 1,636 12,972 5.2 (3.9–6.5) Private 3,588 64,912 26.0 (22.7–29.3) 25 No 15,397 171,917 68.8 (66.3–71.4) 20 Missinga 6,966 76,017 -

Duration of sick leave (days)g 15

0.5–1 3,978 59,532 79.9 (76.1–83.6) Percent of encounters (%) 1.5–2 840 12,622 16.9 (13.9–20.0) 10 3–7 140 2,138 2.9 (1.8–3.9) 5 > 7 14 245 0.3 (0.0–0.7) Missinga 252 3,347 - 0 < 1 1–4 5–19 20–39 40–59 ≥ 60 a Missing data excluded from analysis b Include all ethnic groups that do not fall into the three groups listed Female 1.5 2.5 6.0 19.0 18.4 12.3 c Combination of two or more modes of payment Male 1.6 2.4 5.9 8.1 11.8 10.7 d Includes Foreign Workers Medical Examination Monitoring Agency (FOMEMA), Social Security Organisation (SOCSO) and no Age group (years) payment e Patients below age 15 with income recorded f Patients with missing income, patients who reported no income and patients below age 15 were excluded Note: Missing data excluded from analysis. g Encounters with missing sick leave entry or without sick leave were excluded

52 National Medical Care Statistics 2014

Table 6.1.1 (continued): Characteristics of primary care patients in 2014 6.2 AGE-GENDER DISTRIBUTION

Tertiary 3,962 54,601 21.3 (19.2–23.5) 40 Missinga 5,750 69,949 - Issuance of medical certificate 35

Yes 5,224 77,884 31.2 (28.6–33.7) 30 Public 1,636 12,972 5.2 (3.9–6.5) Private 3,588 64,912 26.0 (22.7–29.3) 25 No 15,397 171,917 68.8 (66.3–71.4) 20 Missinga 6,966 76,017 -

Duration of sick leave (days)g 15

Chapter 6 : The Patients 53

Figure 6.2.2: Distribution of private patients by age and gender in 2014 Figure 6.3.1: Distribution of public and private patients by nationality in 2014

45 100

40 90

35 80

30 70

25 60 90.9 96.7 Malaysian 20 50 Non-Malaysian 15 40 Percent of encounters (%) 10 Percent of patients (%) 30

5 20

0 10 < 1 1–4 5–19 20–39 40–59 ≥ 60 9.1 Female 1.0 2.9 5.5 22.7 12.6 5.0 0 3.3 Male 0.8 3.3 6.0 21.6 13.9 4.7 Public Private

Age group (years) Note: Missing data excluded from analysis.

Note: Missing data excluded from analysis. Figure 6.3.2: Distribution of public and private patients by ethnicity in 2014

100 6.3 NATIONALITY AND ETHNICITY 90 Figure 6.3.1 and Figure 6.3.2 show the breakdown of patient encounters in public and private clinics by nationality and ethnicity, respectively. 80 • Majority of the patients in both public and private clinics were Malaysians; non-Malaysians 70 60.4 (permanent residents and foreigners) constituted only 3.3% of the public patient population and 9.1% 65.6 of the private patient population. The distribution of patients in the private sector was similar to 60 Malay the projected population composition for 2014 reported by the Department of Statistics Malaysia (Malaysians: 92.0%; non-Malaysians: 8.0%),1 while the public sector recorded a proportion of non- 50 Chinese Malaysians smaller than that in the general population. Indian • Malay patients were the largest ethnic group utilising primary care (65.6% of encounters in public 40 Others* clinics and 60.4% in private clinics), followed by Chinese (14.4% in public clinics and 26.1% in

Percent of patients (%) 30 private clinics) and Indian patients (11.9% in public clinics and 10.0% in private clinics). In 14.4 26.1 comparison with the projected ethnic composition of the Malaysian population for 2014 (Malay: 20 50.6%; Chinese: 21.9%; Indian: 6.6%; other ethnic groups: 20.8%),1 a greater proportion of Malays 11.9 was seen in both public and private clinics, while the opposite held true for the Indian population. 10 10.0 The proportion of Chinese was lower in the public patient population and higher in the private 8.1 patient population compared to that in the general population. 0 3.5 Public Private

* Include all ethnic groups that do not fall into the three groups listed Note: Missing data excluded from analysis.

54 National Medical Care Statistics 2014

Figure 6.2.2: Distribution of private patients by age and gender in 2014 Figure 6.3.1: Distribution of public and private patients by nationality in 2014

45 100

40 90

35 80

30 70

25 60 90.9 96.7 Malaysian 20 50 Non-Malaysian 15 40 Percent of encounters (%) 10 Percent of patients (%) 30

5 20

0 10 < 1 1–4 5–19 20–39 40–59 ≥ 60 9.1 Female 1.0 2.9 5.5 22.7 12.6 5.0 0 3.3 Male 0.8 3.3 6.0 21.6 13.9 4.7 Public Private

Age group (years) Note: Missing data excluded from analysis.

Note: Missing data excluded from analysis. Figure 6.3.2: Distribution of public and private patients by ethnicity in 2014

* Include all ethnic groups that do not fall into the three groups listed Note: Missing data excluded from analysis.

Chapter 6 : The Patients 55

6.4 MODE OF PAYMENT Figure 6.5.1: Distribution of public and private patients by type of income in 2014

The provision of primary care was funded by different mechanisms in different sectors. 100

• All patient encounters in public clinics were paid for by government subsidies. 90 • In the private sector, more than half (59.7%) of the encounters were paid for through out-of-pocket 28.6 80 payments, while nearly all of the remaining encounters (39.1%) were paid, either fully or partially, 45.5 by third party payers, such as private insurance, employers and managed care organisations 70 (Figure 6.4.1). 60 No income

Figure 6.4.1: Distribution of private patients by mode of payment in 2014 50 Income Pension 40 Combination* Others† 66.9 0.6% 0.6% Parental income* 30 46.8 Percent of Patients (%) 20

10 0.7 0.5 7.0 4.0 0 Third party Public Private payer 39.1% Out of pocket a Patients below age 15 with income recorded 59.7% Note: Missing data excluded from analysis.

Figure 6.5.2: Distribution of primary care patients by income and sector in 2014

30 Public * Combination of two or more modes of payment 12.6 Private † Includes Foreign Workers Medical Examination Monitoring Agency (FOMEMA), Social Security Organisation (SOCSO) and no 25 payment Note: Missing data excluded from analysis. 20 6.8

6.5 INDIVIDUAL INCOME 15 3.6 Individual income of patients presenting to primary care was captured in NMCS 2014. For patients less Percent of encounters (%) 10 8.4 than 15 years old who had income reported in the survey questionnaires, the type of income was 19.5 16.3 0.9 assumed to be parental income. Figure 6.5.1 shows the distribution of public and private patients by 1.1 10.7 type of income, while the income distribution of patients who reported having a personal income is 5 6.2 6.0 presented in Figure 6.5.2. 2.8 0.3 4.8 0 • Nearly half (45.5%) of the patients seen in public clinics reported having no income. In contrast, more than two-thirds (70.9%) of private patients reported having personal income, including 4.0% who were on pension. • In general, patients who visited private clinics had higher incomes than those who presented to public clinics. Nearly two-thirds (63.0%) of the patients who earned less than MYR 1,000 per Monthly income (MYR) month attended public clinics, while private patients constituted 79.3% of the patients who had a monthly income of MYR 3,000 or over. Note: Patients with missing income, patients who reported no income and patients below age 15 were excluded.

56 National Medical Care Statistics 2014

6.4 MODE OF PAYMENT Figure 6.5.1: Distribution of public and private patients by type of income in 2014

The provision of primary care was funded by different mechanisms in different sectors. 100

Figure 6.4.1: Distribution of private patients by mode of payment in 2014 50 Income Pension 40 Combination* Others† 66.9 0.6% 0.6% Parental income* 30 46.8 Percent of Patients (%) 20

10 0.7 0.5 7.0 4.0 0 Third party Public Private payer 39.1% Out of pocket a Patients below age 15 with income recorded 59.7% Note: Missing data excluded from analysis.

Figure 6.5.2: Distribution of primary care patients by income and sector in 2014

Chapter 6 : The Patients 57

6.6 EDUCATION LEVEL Figure 6.7.1: Distribution of public and private patients by issuance of medical certificate in 2014 Patient education level is an important determinant of patient outcomes.2-4 Figure 6.6.1 presents the distribution of patients by educational level for both public and private sectors. 100 13.9 • In general, private patients reported higher levels of educational attainment compared to those 90 who presented to public clinics. • More than one-quarter (28.0%) of patients in the private sector had attained or completed 80 41.5 education at the tertiary level, compared to only 12.3% in the public sector. • Patients who had not undertaken any formal education accounted for a higher proportion of 70 encounters in public clinics than in private clinics (13.4% versus 9.2%, respectively). 60 • Nearly half of the patients seen in public and private clinics (47.6% and 46.3%, respectively) had completed at least some secondary education. 50 Yes 86.1 No Figure 6.6.1: Distribution of public and private patients by education level in 2014 40

100 Percent of patients (%) 30 58.5 9.2 13.4 20 90

16.5 10 80

26.7 0 70 Public Private

60 Note: Missing data excluded from analysis. No formal education

46.3 Primary 50 Figure 6.7.2: Distribution of public and private patients by duration of sick leave in 2014 Secondary 40 100 47.6 Tertiary

Percent of patients (%) 30 90

20 80

28.0 70 10 12.3 60 80.1 79.8 0.5–1 day 0 Public Private 50 1.5–2 days

3–7 days Note: Missing data excluded from analysis. 40 > 7 days

Percent of patients (%) 30 6.7 MEDICAL CERTIFICATE AND DURATION OF SICK LEAVE 20 A total of 77,884 (31.2%) patients were issued medical certificates during their visit to primary care 13.9 10 17.5 clinics. 1.1 0.2 4.9 2.5 • Medical certificates were issued three times more frequently in private clinics than in the public 0 settings (41.5% versus 13.9% of encounters, respectively) (Figure 6.7.1). Public Private

• About 80% of the medical certificates issued in both public and private clinics entitled the patient Note: Encounters with missing sick leave entry or without sick leave were excluded to a sick leave of half to one day (Figure 6.7.2).

58 National Medical Care Statistics 2014

100 Percent of patients (%) 30 58.5 9.2 13.4 20 90

16.5 10 80

26.7 0 70 Public Private

60 Note: Missing data excluded from analysis. No formal education

46.3 Primary 50 Figure 6.7.2: Distribution of public and private patients by duration of sick leave in 2014 Secondary 40 100 47.6 Tertiary

Percent of patients (%) 30 90

20 80

28.0 70 10 12.3 60 80.1 79.8 0.5–1 day 0 Public Private 50 1.5–2 days

3–7 days Note: Missing data excluded from analysis. 40 > 7 days

Chapter 6 : The Patients 59

REFERENCES

1. Department of Statistics Malaysia. Population projections Malaysia 2010-2040. Kuala Lumpur (Malaysia): Department of Statistics (MY); 2013 Jan. 2. Paksima N, Pahk B, Romo S, Egol KA. The association of education level on outcome after distal radius fracture. Hand (N Y). 2014 Mar;9(1):75-9. 3. Khattak M, Sandhu GS, Desilva R, Goldfarb-Rumyantzev AS. Association of education level with dialysis outcome. Hemodial Int. 2012 Jan;16(1):82-8. 4. Konski A, Berkey BA, Kian Ang K, Fu KK. Effect of education level on outcome of patients treated on Radiation Therapy Oncology Group Protocol 90-03. Cancer. 2003 Oct 1;98(7):1497-503.

60 National Medical Care Statistics 2014

REFERENCES

CHAPTER seven Reasons for Encounter

CHAPTER 7: REASONS FOR ENCOUNTER 7.2 REASONS FOR ENCOUNTER BY ICPC-2 COMPONENTS

All reasons for encounter were coded using the International Classification of Primary Care Second This chapter concerns the reasons for encounter (RFEs), which refer to the reasons why patients Edition (ICPC-2) coding system (see Appendix 4). As detailed in Chapter 2, the biaxial classification present to primary care clinics. The RFEs could be a symptom or complaint, planned or unplanned system allows for the classification of patients’ reasons for encounter according to the aspects of the follow-up on a known health condition or problem, health screening or medical check-up request (by consultation (components) and the body systems involved (chapters). This section is devoted to the patients or their employers), or a need for investigative, therapeutic and/or administrative procedures. distributions of reasons for presentation to primary care providers according to the seven ICPC-2 This study adopted a patient-centred approach and aimed to identify the reasons for seeking health components. The distributions of reasons for encounters based on the 17 ICPC-2 chapters will be care from the patients’ perspective. presented in the next section.

Table 7.2.1 presents the overall distribution of RFEs by ICPC-2 components. 7.1 NUMBER OF REASONS FOR ENCOUNTER PER VISIT • Out of the 597,563 RFEs captured, 61.4% were symptom- and complaint-based, making “symptoms In NMCS 2014, a total of 597,563 reasons for encounter (weighted count) were captured. Figure 7.1.1 and complaints” the top RFE. shows the number of RFEs per visit by sector (public and private) in 2014. • The second most common RFE was “diagnosis/diseases”, which constituted 27.4% of all RFEs. Most (90.9%) of the RFEs classified under this component were for “other diagnosis/diseases”, a • About half of the patients included in the survey presented with only a single reason for encounter classification for diagnosis/diseases which did not fit into the categories of infectious diseases, (44.1% in public clinics and 49.1% in private clinics). injuries, neoplasms and congenital anomalies. • RFEs were also expressed as processes of care, which accounted for 11.2% of all RFEs. These Figure 7.1.1: Number of reasons for encounter per visit in primary care clinics in 2014 included diagnostic and preventive procedures as well as requests for medications, test results, 60 medical certificates and referrals.

50 Table 7.2.1: Reasons for encounter by ICPC-2 components in primary care clinics in 2014

Rate per 100 Percent of Unweighted Weighted encounters 40 RFE (ICPC-2 component) total RFEs count count (95% CI) (n = 597,563) (n = 325,818) 30 Symptom & complaint 28,502 366,841 61.4 112.6 (106.1–119.1) Diagnosis, diseases 16,008 163,666 27.4 50.2 (45.0–55.4) 20 Infectious diseases 641 8,781 1.5 2.7 (2.2–3.2) Injuries 485 5,852 1.0 1.8 (1.5–2.1)

Percent of encounters (%) 10 Neoplasms 16 165 0.0 0.1 (0.0–0.1) Congenital anomalies 10 52 0.0 0.0 (0.0–0.0) 0 One Two Three ≥ Four Other diagnoses/diseases 14,856 148,816 24.9 45.7 (40.4–51.0) Diagnostic screening & Public 44.1 27.8 20.3 7.8 5,298 56,610 9.5 17.4 (15.3–19.5) preventive Private 49.1 27.5 17.0 6.4 Medication, treatment 464 6,062 1.0 1.9 (1.5–2.2) procedures Number of RFEs per encounter Test results 226 2,225 0.4 0.7 (0.4–1.0) Note: Missing data excluded from analysis. Referrals & other reason for 110 1,551 0.3 0.5 (0.3–0.7) encounter Administrative 34 607 0.1 0.2 (0.0–0.3)

Total 50,642 597,563 100.0 183.4 (178.1–188.7)

Table 7.2.2 and Table 7.2.3 show the breakdown of RFE distribution by sectors (public and private, respectively). In public clinics, “diagnosis/diseases” was the main RFE (44.4% of all RFEs, 85.0 per 100 encounters), whereas patients presented to private clinics mainly for symptom-based complaints (77.9%). These results are consistent with the findings of NMCS 2012.1

62 National Medical Care Statistics 2014 CHAPTER 7: REASONS FOR ENCOUNTER 7.2 REASONS FOR ENCOUNTER BY ICPC-2 COMPONENTS

50 Table 7.2.1: Reasons for encounter by ICPC-2 components in primary care clinics in 2014

Total 50,642 597,563 100.0 183.4 (178.1–188.7)

Chapter 7 : Reasons for Encounter 63 Table 7.2.2: Reasons for encounter by ICPC-2 components in public clinics in 2014 7.3 REASONS FOR ENCOUNTER BY ICPC-2 CHAPTERS Table 7.2.2: Reasons for encounter by ICPC-2 components in public clinics in 2014 Table 7.3.1 shows the overall distribution of RFEs when categorised according to ICPC-2 chapters. Note Rate per 100 Percent of Unweighted Weighted encounters that in some instances, related RFEs within a certain ICPC-2 chapter were collapsed into a single RFE. RFE (ICPC-2 component) total RFEs Rate per 100 count count Percent of (95% CI) Unweighted Weighted (n = 597,563) encounters RFE (ICPC-2 component) total RFEs (n = 325,818) • The most common RFEs were respiratory conditions, which accounted for 26.8% of all RFEs count count (95% CI) (n = 597,563) (49.2 per 100 patient encounters). (n = 325,818) Symptom & complaint 12,211 97,843 38.8 74.3 (69.3–79.4) • General and unspecified conditions were the second most frequent RFEs (20.3% of all RFEs). Diagnosis,Symptom & diseases complaint 12,74712,211 111,92597,843 44.438.8 85.074.3 (77.2(69.3–79.4)92.9) Among these conditions, fever was the most frequently reported reason for visit (62.9% of all general and unspecified conditions). Diagnosis, Infectious diseases diseases 12,747210 111,9251,957 44.40.8 85.01.5 (1.2(77.2––1.8)92.9) • Chronic conditions under the endocrine, metabolic and nutritional category accounted for 12.7% of InjuriesInfectious diseases 194210 1,5351,957 0.60.8 1.21.5 (0.9(1.2–1.8)1.4) all RFEs, with 10.9 RFEs per 100 encounters recorded for diabetes and 9.1 per 100 encounters for NeoplasmsInjuries 1948 1,53533 0.00.6 0.01.2 (0.0(0.9–1.4)0.1) lipid disorder. For reference, the National Health Morbidity Survey (NHMS) 2011 reported the CongenitalNeoplasms anomalies 78 2333 0.0 0.0 (0.0–0.1)0.0) prevalence for diabetes and hypercholesterolemia in Malaysia to be at 15.2% and 35.1%, respectively.2 OtherCongenital diagnoses/diseases anomalies 12,3287 108,37623 43.00.0 82.30.0 (74.4(0.0–0.0)–90.3) Diagnostic Other diagnoses/diseases screening & 12,328 108,376 43.0 82.3 (74.4–90.3) 3,977 36,986 14.7 28.1 (24.2–32.0) preventive Table 7.3.1: Reasons for encounter by ICPC-2 chapters and the most common individual Diagnostic screening & 3,977 36,986 14.7 28.1 (24.2–32.0) Medication,preventive treatment reasons for encounter within each chapter in primary care clinics in 2014 227 1,875 0.7 1.4 (0.9–1.9) procedures Medication, treatment 227 1,875 0.7 1.4 (0.9–1.9) procedures Rate per 100 Test results 196 1,784 0.7 1.4 (0.7–2.1) Percent of Unweighted Weighted encounters ReferralsTest results & other reason for 196 1,784 0.7 1.4 (0.7–2.1) RFE (ICPC-2 chapter) total RFEs 88 1,108 0.4 0.8 (0.4–1.3) count count (95% CI) encounter (n = 597,563) Referrals & other reason for (n = 325,818) 88 1,108 0.4 0.8 (0.4–1.3) Administrativeencounter 32 529 0.2 0.4 (0.0–0.8) Respiratory 12,660 160,186 26.8 49.2 (46.1–52.2) TotalAdministrative 29,47832 252,050529 100.00.2 191.50.4 (182.5(0.0–0.8)–200.5) Total 29,478 252,050 100.0 191.5 (182.5–200.5) Cough 6,022 74,905 12.5 23.0 (21.7–24.3) Table 7.2.3: Reasons for encounter by ICPC-2 components in private clinics in 2014 Runny nose/rhinorrhoea 4,328 53,469 9.0 16.4 (15.1–17.7) Table 7.2.3: Reasons for encounter by ICPC-2 components in private clinics in 2014 Pain/sore throat* 982 14,030 2.4 4.3 (3.5–5.2) Asthma 623 7,834 1.3 2.4 (1.9–2.9) Percent of Rate per 100 encounters Unweighted Weighted RFE (ICPC-2 component) total RFEs (95% CI) General & unspecified 9,740 121,203 20.3 37.2 (35.3–39.1) count count Percent of Rate per 100 encounters Unweighted Weighted (n = 597,563) (n = 325,818) RFE (ICPC-2 component) total RFEs (95% CI) Fever 6,071 76,242 12.8 23.4 (22.0–24.8) count count (n = 597,563) (n = 325,818) Medical examination* 878 10,273 1.7 3.2 (2.5–3.8) Symptom & complaint 16,291 268,998 77.9 138.5 (131.3–145.8) Blood test 576 6,524 1.1 2.0 (1.5–2.5) Diagnosis,Symptom & diseases complaint 16,2913,261 268,99851,742 15.077.9 138.526.6 (24.3(131.3––29.0)145.8) Dressing/pressure/compress/tamponade* 310 4,106 0.7 1.3 (1.0–1.5) Diagnosis,Infectious diseases diseases 3,261431 51,7426,825 15.02.0 26.63.5 (2.8(24.3–4.3)–29.0) Pain general/multiple sites 258 3,642 0.6 1.1 (0.9–1.3) InjuriesInfectious diseases 291431 4,3166,825 1.32.0 2.23.5 (1.9(2.8–2.6)4.3) Endocrine, metabolic and nutritional 7,831 76,009 12.7 23.3 (19.4–27.3) NeoplasmsInjuries 2918 4,316132 0.01.3 0.12.2 (0.0(1.9–0.1)2.6) Diabetes - non-gestational* 3,588 35,390 5.9 10.9 (9.0–12.7) CongenitalNeoplasms anomalies 38 13228 0.0 0.00.1 (0.0–0.0)0.1) Diabetes type 2 2,986 29,437 4.9 9.0 (7.2–10.8) OtherCongenital diagnoses/diseases anomalies 2,5283 40,44128 11.70.0 20.80.0 (18.6(0.0––0.0)23.0) Diabetes - unspecified 510 5,228 0.9 1.6 (1.0–2.3) DiagnosticOther diagnoses/diseases screening & 2,528 40,441 11.7 20.8 (18.6–23.0) 1,321 19,624 5.7 10.1 (8.2–12.0) preventive Lipid disorder 3,194 29,520 4.9 9.1 (7.3–10.9) Diagnostic screening & 1,321 19,624 5.7 10.1 (8.2–12.0) Medication,preventive treatment Blood test endocrine/metabolic 664 7,211 1.2 2.2 (1.6–2.9) 237 4,187 1.2 2.2 (1.7–2.7) procedures Medication, treatment Cardiovascular 6,029 58,483 9.8 18.0 (15.8–20.1) 237 4,187 1.2 2.2 (1.7–2.7) Testprocedures results 30 442 0.1 0.2 (0.1–0.4) Hypertension - cardiovascular* 5,518 53,495 9.0 16.4 (14.5–18.4) ReferralsTest results & other reason for 30 442 0.1 0.2 (0.1–0.4) 22 443 0.1 0.2 (0.1–0.4) encounter Referrals & other reason for 22 443 0.1 0.2 (0.1–0.4) Administrativeencounter 2 77 0.0 0.0 (0.0–0.1) TotalAdministrative 21,1642 345,51377 100.00.0 177.90.0 (171.4(0.0–0.1)–184.4) Total 21,164 345,513 100.0 177.9 (171.4–184.4)

64 National Medical Care Statistics 2014 Table 7.2.2: Reasons for encounter by ICPC-2 components in public clinics in 2014 7.3 REASONS FOR ENCOUNTER BY ICPC-2 CHAPTERS Table 7.2.2: Reasons for encounter by ICPC-2 components in public clinics in 2014 Table 7.3.1 shows the overall distribution of RFEs when categorised according to ICPC-2 chapters. Note Rate per 100 Percent of Unweighted Weighted encounters that in some instances, related RFEs within a certain ICPC-2 chapter were collapsed into a single RFE. RFE (ICPC-2 component) total RFEs Rate per 100 count count Percent of (95% CI) Unweighted Weighted (n = 597,563) encounters RFE (ICPC-2 component) total RFEs (n = 325,818) • The most common RFEs were respiratory conditions, which accounted for 26.8% of all RFEs count count (95% CI) (n = 597,563) (49.2 per 100 patient encounters). (n = 325,818) Symptom & complaint 12,211 97,843 38.8 74.3 (69.3–79.4) • General and unspecified conditions were the second most frequent RFEs (20.3% of all RFEs). Diagnosis,Symptom & diseases complaint 12,74712,211 111,92597,843 44.438.8 85.074.3 (77.2(69.3–92.9)79.4) Among these conditions, fever was the most frequently reported reason for visit (62.9% of all general and unspecified conditions). Diagnosis, Infectious diseases diseases 12,747210 111,9251,957 44.40.8 85.01.5 (1.2(77.2–1.8)–92.9) • Chronic conditions under the endocrine, metabolic and nutritional category accounted for 12.7% of InjuriesInfectious diseases 194210 1,5351,957 0.60.8 1.21.5 (0.9(1.2–1.4)1.8) all RFEs, with 10.9 RFEs per 100 encounters recorded for diabetes and 9.1 per 100 encounters for NeoplasmsInjuries 1948 1,53533 0.00.6 0.01.2 (0.0(0.9–0.1)1.4) lipid disorder. For reference, the National Health Morbidity Survey (NHMS) 2011 reported the CongenitalNeoplasms anomalies 78 2333 0.0 0.0 (0.0–0.0)0.1) prevalence for diabetes and hypercholesterolemia in Malaysia to be at 15.2% and 35.1%, respectively.2 OtherCongenital diagnoses/diseases anomalies 12,3287 108,37623 43.00.0 82.30.0 (74.4(0.0––0.0)90.3) Diagnostic Other diagnoses/diseases screening & 12,328 108,376 43.0 82.3 (74.4–90.3) 3,977 36,986 14.7 28.1 (24.2–32.0) preventive Table 7.3.1: Reasons for encounter by ICPC-2 chapters and the most common individual Diagnostic screening & 3,977 36,986 14.7 28.1 (24.2–32.0) Medication,preventive treatment reasons for encounter within each chapter in primary care clinics in 2014 227 1,875 0.7 1.4 (0.9–1.9) procedures Medication, treatment 227 1,875 0.7 1.4 (0.9–1.9) procedures Rate per 100 Test results 196 1,784 0.7 1.4 (0.7–2.1) Percent of Unweighted Weighted encounters ReferralsTest results & other reason for 196 1,784 0.7 1.4 (0.7–2.1) RFE (ICPC-2 chapter) total RFEs 88 1,108 0.4 0.8 (0.4–1.3) count count (95% CI) encounter (n = 597,563) Referrals & other reason for (n = 325,818) 88 1,108 0.4 0.8 (0.4–1.3) Administrativeencounter 32 529 0.2 0.4 (0.0–0.8) Respiratory 12,660 160,186 26.8 49.2 (46.1–52.2) TotalAdministrative 29,47832 252,050529 100.00.2 191.50.4 (182.5(0.0–0.8)–200.5) Total 29,478 252,050 100.0 191.5 (182.5–200.5) Cough 6,022 74,905 12.5 23.0 (21.7–24.3) Table 7.2.3: Reasons for encounter by ICPC-2 components in private clinics in 2014 Runny nose/rhinorrhoea 4,328 53,469 9.0 16.4 (15.1–17.7) Table 7.2.3: Reasons for encounter by ICPC-2 components in private clinics in 2014 Pain/sore throat* 982 14,030 2.4 4.3 (3.5–5.2) Asthma 623 7,834 1.3 2.4 (1.9–2.9) Percent of Rate per 100 encounters Unweighted Weighted RFE (ICPC-2 component) total RFEs (95% CI) General & unspecified 9,740 121,203 20.3 37.2 (35.3–39.1) count count Percent of Rate per 100 encounters Unweighted Weighted (n = 597,563) (n = 325,818) RFE (ICPC-2 component) total RFEs (95% CI) Fever 6,071 76,242 12.8 23.4 (22.0–24.8) count count (n = 597,563) (n = 325,818) Medical examination* 878 10,273 1.7 3.2 (2.5–3.8) Symptom & complaint 16,291 268,998 77.9 138.5 (131.3–145.8) Blood test 576 6,524 1.1 2.0 (1.5–2.5) Diagnosis,Symptom & diseases complaint 16,2913,261 268,99851,742 15.077.9 138.526.6 (24.3(131.3–29.0)–145.8) Dressing/pressure/compress/tamponade* 310 4,106 0.7 1.3 (1.0–1.5) Diagnosis,Infectious diseases diseases 3,261431 51,7426,825 15.02.0 26.63.5 (2.8(24.3–4.3)–29.0) Pain general/multiple sites 258 3,642 0.6 1.1 (0.9–1.3) InjuriesInfectious diseases 291431 4,3166,825 1.32.0 2.23.5 (1.9(2.8–2.6)4.3) Endocrine, metabolic and nutritional 7,831 76,009 12.7 23.3 (19.4–27.3) NeoplasmsInjuries 2918 4,316132 0.01.3 0.12.2 (0.0(1.9–0.1)2.6) Diabetes - non-gestational* 3,588 35,390 5.9 10.9 (9.0–12.7) CongenitalNeoplasms anomalies 38 13228 0.0 0.00.1 (0.0–0.0)0.1) Diabetes type 2 2,986 29,437 4.9 9.0 (7.2–10.8) OtherCongenital diagnoses/diseases anomalies 2,5283 40,44128 11.70.0 20.80.0 (18.6(0.0––0.0)23.0) Diabetes - unspecified 510 5,228 0.9 1.6 (1.0–2.3) DiagnosticOther diagnoses/diseases screening & 2,528 40,441 11.7 20.8 (18.6–23.0) 1,321 19,624 5.7 10.1 (8.2–12.0) preventive Lipid disorder 3,194 29,520 4.9 9.1 (7.3–10.9) Diagnostic screening & 1,321 19,624 5.7 10.1 (8.2–12.0) Medication,preventive treatment Blood test endocrine/metabolic 664 7,211 1.2 2.2 (1.6–2.9) 237 4,187 1.2 2.2 (1.7–2.7) procedures Medication, treatment Cardiovascular 6,029 58,483 9.8 18.0 (15.8–20.1) 237 4,187 1.2 2.2 (1.7–2.7) Testprocedures results 30 442 0.1 0.2 (0.1–0.4) Hypertension - cardiovascular* 5,518 53,495 9.0 16.4 (14.5–18.4) ReferralsTest results & other reason for 30 442 0.1 0.2 (0.1–0.4) 22 443 0.1 0.2 (0.1–0.4) encounter Referrals & other reason for 22 443 0.1 0.2 (0.1–0.4) Administrativeencounter 2 77 0.0 0.0 (0.0–0.1) TotalAdministrative 21,1642 345,51377 100.00.0 177.90.0 (171.4(0.0–0.1)–184.4) Total 21,164 345,513 100.0 177.9 (171.4–184.4)

Chapter 7 : Reasons for Encounter 65 Table 7.3.1 (continued): Reasons for encounter by ICPC-2 chapters and the most common 7.4 MOST COMMON REASONS FOR ENCOUNTER IN PUBLIC AND PRIVATE CLINICS individual reasons for encounter within each chapter in primary care clinics in 2014 NMCS 2012 reported that the main reason for utilisation of primary care in the public sector was non- communicable diseases, with hypertension being the top reason for encounter, followed by diabetes and Rate per 100 Percent of Unweighted Weighted encounters lipid disorder.1 Similar pattern was observed in NMCS 2014 (Figure 7.4.1). RFE (ICPC-2 chapter) total RFEs count count (95% CI) (n = 597,563) (n = 325,818) • Patients who visited public clinics reported 191.5 RFEs per 100 encounters, slightly more than those in private clinics (177.9 per 100 encounters). Digestive 3,903 50,539 8.5 15.5 (14.4–16.7) • A distinct difference observed between the two sectors when comparing the 10 commonest RFEs is Abdominal pain* 1,193 16,010 2.7 4.9 (4.4–5.4) the pattern of diseases presenting to each sector. The top three RFEs reported in public clinics were chronic diseases, whereas in private clinics, patient encounters were mostly for acute Diarrhoea 1,149 15,285 2.6 4.7 (4.3–5.1) complaints. Vomiting 440 4,988 0.8 1.5 (1.3–1.8) • Blood tests related to endocrine/metabolic conditions were among the top 10 reasons for visit to Musculoskeletal 2,628 36,097 6.0 11.1 (10.1–12.1) public clinics. This utilisation could be due to periodic check-up on existing non-communicable Musculoskeletal diseases and demonstrates the utilisation of primary health care other than for consultations and 1,533 20,217 3.4 6.2 (5.4–7.0) symptom/complaints* medications. Back problems* 726 10,720 1.8 3.3 (2.8–3.7) Skin 1,930 25,111 4.2 7.7 (6.5–8.9) Figure 7.4.1: Top 10 reasons for encounter in public clinics in 2014 Rash* 535 7,006 1.2 2.2 (1.5–2.8) Pruritus 474 5,972 1.0 1.8 (1.2–2.5) Hypertension - all* 31.3 Neurological 1,578 21,824 3.7 6.7 (5.9–7.5) Diabetes - all* 22.5 Headache - all* 1,015 14,788 2.5 4.5 (4.0–5.1) Headache 975 13,901 2.3 4.3 (3.8–4.8) Lipid disorder 18.5

Vertigo/dizziness 382 5,003 0.8 1.5 (1.2–1.9) Cough 17.8 Pregnancy, childbearing, family 1,902 17,628 3.0 5.4 (4.4–6.4) planning Fever 16.2

Medical examination - pregnancy* 1,567 14,412 2.4 4.4 (3.5–5.3) Runny nose/rhinorrhoea 12.0 Urological 602 7,352 1.2 2.3 (1.8–2.7) Medical examination - pregnancy* 9.3 Urinary problem* 228 2,862 0.5 0.9 (0.7–1.1) Eye 632 7,322 1.2 2.3 (1.9–2.6) Musculoskeletal symptom/complaints* 4.4 Symptom/complaint eye* 458 5,095 0.9 1.6 (1.2–1.9) Medical examination* 4.2 Female genital 377 5,214 0.9 1.6 (1.3–1.9) Blood test endo/metabolic 3.9 Menstrual problems* 193 3,109 0.5 1.0 (0.7–1.2) 0 5 10 15 20 25 30 35 40 Psychological 296 4,281 0.7 1.3 (0.8–1.8) Ear 256 3,244 0.5 1.0 (0.8–1.2) Rate per 100 encounters Blood, blood forming organs & 221 2,430 0.4 0.8 (0.5–1.0) immune mechanism *Comprise multiple ICPC-2 codes (see Appendix 4) Male genital 56 639 0.1 0.2 (0.1–0.3) Social problems 1 2 0.0 0.0 (0.0–0.0) Total 50,642 597,563 100.0 183.4 (178.1–188.7) *Comprise multiple ICPC-2 codes (see Appendix 4)

66 National Medical Care Statistics 2014 Table 7.3.1 (continued): Reasons for encounter by ICPC-2 chapters and the most common 7.4 MOST COMMON REASONS FOR ENCOUNTER IN PUBLIC AND PRIVATE CLINICS individual reasons for encounter within each chapter in primary care clinics in 2014 NMCS 2012 reported that the main reason for utilisation of primary care in the public sector was non- communicable diseases, with hypertension being the top reason for encounter, followed by diabetes and Rate per 100 Percent of Unweighted Weighted encounters lipid disorder.1 Similar pattern was observed in NMCS 2014 (Figure 7.4.1). RFE (ICPC-2 chapter) total RFEs count count (95% CI) (n = 597,563) (n = 325,818) • Patients who visited public clinics reported 191.5 RFEs per 100 encounters, slightly more than those in private clinics (177.9 per 100 encounters). Digestive 3,903 50,539 8.5 15.5 (14.4–16.7) • A distinct difference observed between the two sectors when comparing the 10 commonest RFEs is Abdominal pain* 1,193 16,010 2.7 4.9 (4.4–5.4) the pattern of diseases presenting to each sector. The top three RFEs reported in public clinics were chronic diseases, whereas in private clinics, patient encounters were mostly for acute Diarrhoea 1,149 15,285 2.6 4.7 (4.3–5.1) complaints. Vomiting 440 4,988 0.8 1.5 (1.3–1.8) • Blood tests related to endocrine/metabolic conditions were among the top 10 reasons for visit to Musculoskeletal 2,628 36,097 6.0 11.1 (10.1–12.1) public clinics. This utilisation could be due to periodic check-up on existing non-communicable Musculoskeletal diseases and demonstrates the utilisation of primary health care other than for consultations and 1,533 20,217 3.4 6.2 (5.4–7.0) symptom/complaints* medications. Back problems* 726 10,720 1.8 3.3 (2.8–3.7) Skin 1,930 25,111 4.2 7.7 (6.5–8.9) Figure 7.4.1: Top 10 reasons for encounter in public clinics in 2014 Rash* 535 7,006 1.2 2.2 (1.5–2.8) Pruritus 474 5,972 1.0 1.8 (1.2–2.5) Hypertension - all* 31.3 Neurological 1,578 21,824 3.7 6.7 (5.9–7.5) Diabetes - all* 22.5 Headache - all* 1,015 14,788 2.5 4.5 (4.0–5.1) Headache 975 13,901 2.3 4.3 (3.8–4.8) Lipid disorder 18.5

Vertigo/dizziness 382 5,003 0.8 1.5 (1.2–1.9) Cough 17.8 Pregnancy, childbearing, family 1,902 17,628 3.0 5.4 (4.4–6.4) planning Fever 16.2

Chapter 7 : Reasons for Encounter 67 Figure 7.4.2: Top 10 reasons for encounter in private clinics in 2014

Fever 28.3

Cough 26.5

Runny nose/rhinorrhoea 19.4

Musculoskeletal symptom/complaints* 7.5

Abdominal pain* 6.4

Hypertension - cardiovascular* 6.3

Pain/sore throat* 6.2

Diarrhoea 6.2

Headache - all* 6.2

Back problems* 4.5

0 5 10 15 20 25 30 35 40

Rate per 100 encounters

*Comprise multiple ICPC-2 codes (see Appendix 4)

REFERENCES

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-4718. Supported by the Ministry of Health Malaysia. 2. Institute for Public Health (IPH). National Health and Morbidity Survey 2011 (NHMS 2011). Vol. 2: Non Communicable Diseases; 2011. 188 p. Report No.: MOH/S/IKU/04.12(TR). Grant No.: NMRR- 10-757-6837. Supported by the Ministry of Health Malaysia.

68 National Medical Care Statistics 2014 Figure 7.4.2: Top 10 reasons for encounter in private clinics in 2014

Fever 28.3

Cough 26.5

Runny nose/rhinorrhoea 19.4

Musculoskeletal symptom/complaints* 7.5

Abdominal pain* 6.4

Hypertension - cardiovascular* 6.3

Pain/sore throat* 6.2

Diarrhoea 6.2

Headache - all* 6.2

Back problems* 4.5

0 5 10 15 20 25 30 35 40

Rate per 100 encounters

*Comprise multiple ICPC-2 codes (see Appendix 4)

REFERENCES

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research CHAPTER eight Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-4718. Supported by the Ministry of Health Malaysia. 2. Institute for Public Health (IPH). National Health and Morbidity Survey 2011 (NHMS 2011). Vol. 2: Non Communicable Diseases; 2011. 188 p. Report No.: MOH/S/IKU/04.12(TR). Grant No.: NMRR- Diagnoses 10-757-6837. Supported by the Ministry of Health Malaysia.

CHAPTER 8: DIAGNOSES Figure 8.1.2 shows the age- and gender-specific rate of diagnoses in public and private clinics in 2014. In keeping with our previous findings in 2012,1 the number of diagnoses increased with increasing age for both sectors, with the increase being more pronounced in the public sector, especially for age groups In this chapter, diagnoses reported by primary care providers at the time of visit are presented and over 40 years. discussed. During an encounter, a patient might present with an existing or new problem(s), and the healthcare provider would record the problems as symptoms or diagnoses. Healthcare providers could Figure 8.1.2: Age- and gender- specific rates of diagnoses managed per 100 encounters by record more than one diagnosis for each encounter. Note that only diagnoses managed and reported for sector in 2014 each encounter were captured.

250 8.1 NUMBER OF DIAGNOSES PER ENCOUNTER 209.6 A total of 436,743 diagnoses were recorded in NMCS 2014, at a rate of 134.0 diagnoses per 100 encounters. Distributions of recorded diagnoses according to sectors were as follows: 200

• Public clinics: 154.9 diagnoses per 100 encounters 192.8 • Private clinics: 119.9 diagnoses per 100 encounters 145.8 150

Figure 8.1.1 presents the number of diagnoses per visit by sectors in 2014. 139.9 More than three-quarters (83.5%) of patients who presented to private clinics had a single • 100 diagnosis per visit, compared with 63.0% of their counterparts in public clinics. Public; male

Rate per 100 encounters Public; female Figure 8.1.1: Number of diagnoses managed per encounter in primary care clinics in 2014 50 Private; male Private; female 90

80 0 < 1 1–4 5–19 20–39 40–59 ≥ 60 70 Age group (years)

60 Note: Missing data excluded from analysis.

50 8.2 DIAGNOSES BY ICPC-2 COMPONENTS

40 Diagnoses managed in primary care were categorised by ICPC-2 components (based on the aspects of 30 the consultation). Table 8.2.1 shows the distribution of diagnoses by these components in terms of

Percent of encounters (%) proportion of all diagnoses and rate per 100 encounters. 20 • Diagnosis of diseases accounted for 77.9% of all diagnoses. Nearly half (47.4%) of all diagnoses were categorised as “other diagnosis/diseases”, a classification for diagnoses which did not fit into 10 the categories of infectious diseases, injuries, neoplasms and congenital anomalies. This was 0 followed by infectious diseases (27.5%), which were recorded at a rate of 36.9 diagnoses per One Two Three ≥ Four 100 encounters. Public 63.0 20.4 15.5 1.2 • The second most frequent diagnosis by ICPC-2 component was the “symptoms and complaints” Private 83.5 13.4 2.9 0.3 category, which was reported at a rate of 22.2 diagnoses per 100 encounters.

Number of diagnoses per encounter

Note: Missing data excluded from analysis.

70 National Medical Care Statistics 2014

• Public clinics: 154.9 diagnoses per 100 encounters 192.8 • Private clinics: 119.9 diagnoses per 100 encounters 145.8 150

Rate per 100 encounters Public; female Figure 8.1.1: Number of diagnoses managed per encounter in primary care clinics in 2014 50 Private; male Private; female 90

80 0 < 1 1–4 5–19 20–39 40–59 ≥ 60 70 Age group (years)

60 Note: Missing data excluded from analysis.

50 8.2 DIAGNOSES BY ICPC-2 COMPONENTS

Number of diagnoses per encounter

Note: Missing data excluded from analysis.

Chapter 8 : Diagnoses 71

Table 8.2.1: Diagnoses by ICPC-2 components in primary care clinics in 2014 Table 8.3.1: Diagnosis by ICPC-2 chapters and the most common individual diagnoses within each chapter in NMCS 2014 Percent of Rate per 100 Diagnosis Unweighted Weighted total encounters Percent of Rate per 100 (ICPC-2 component) count count diagnoses (95% CI) Diagnosis Unweighted Weighted total encounters (n = 436,743) (n = 325,818) (ICPC-2 chapter) count count diagnoses (95% CI) (n = 436,743) (n = 325,818) Diagnosis, diseases 30,297 340,229 77.9 104.4 (100.2–108.7) Infectious diseases 9,625 120,114 27.5 36.9 (34.8–38.9) Respiratory 8,164 102,329 23.4 31.4 (29.9–32.9) Injuries 1,006 12,720 2.9 3.9 (3.4–4.4) Upper respiratory tract infection 5,928 73,345 16.8 22.5 (21.1–23.9) Neoplasms 35 374 0.1 0.1 (0.1–0.2) Asthma 718 9,343 2.1 2.9 (2.3–3.4) Congenital anomalies 21 190 0.0 0.1 (0.0–0.1) Tonsillitis 416 4,662 1.1 1.4 (1.2–1.7) Other 19,610 206,830 47.4 63.5 (58.0–69.0) Cough 283 3,468 0.8 1.1 (0.8–1.3) Symptom & complaint 5,597 72,384 16.6 22.2 (20.5–23.9) Acute bronchitis 146 2,069 0.5 0.6 (0.4–0.8) Endocrine, metabolic and Diagnostic screening & preventive 2,070 21,669 5.0 6.7 (5.7–7.6) 7,880 75,929 17.4 23.3 (19.6–27.0) nutritional Medication, treatment procedures 110 1,573 0.4 0.5 (0.3–0.7) Non-gestational diabetes* 3,609 35,443 8.1 10.9 (9.0–12.8) Test results 11 141 0.0 0.0 (0.0–0.1) Diabetes type 2 2,993 29,024 6.7 8.9 (7.0–10.8) Referrals & other reason for 54 648 0.2 0.2 (0.1–0.3) encounter Diabetes - unspecified 518 5,680 1.3 1.7 (1.1–2.4) Administrative 12 99 0.0 0.0 (0.0–0.1) Lipid disorder 3,693 34,668 7.9 10.6 (8.7–12.6) Total 38,151 436,743 100.0 134.0 (130.6–137.5) Cardiovascular 6,337 62,233 14.3 19.1 (16.9–21.3) Hypertension - cardiovascular* 5,747 55,940 12.8 17.2 (15.1–19.3) Ischaemic heart disease* 236 2,160 0.5 0.7 (0.5–0.8) 8.3 DIAGNOSES BY ICPC-2 CHAPTERS General & unspecified 3,449 42,278 9.7 13.0 (11.8–14.1) Table 8.3.1 presents the distribution of diagnoses according to ICPC-2 chapters (classified based on the Fever 900 11,267 2.6 3.5 (2.9–4.1) body systems involved) and the most frequent diagnoses within each chapter. The conditions are Medical examination* 711 7,509 1.7 2.3 (1.8–2.8) reported in descending order of percentage of all diagnoses. Disease/condition of unspecified 400 5,330 1.2 1.6 (1.2–2.1) nature/site • The most frequent problem that presented to primary care was respiratory-related. This amounted to 23.4% of all diagnoses and 31.4% of all patient encounters in primary care. Majority of the Digestive 2,833 37,011 8.5 11.4 (10.6–12.2) patients (71.7%) were managed for an upper respiratory tract infection. Asthma only accounted for Gastroenteritis* 981 13,139 3.0 4.0 (3.5–4.6) 2.9 diagnoses per 100 patient encounters recorded in primary care. Stomach function disorder 687 8,748 2.0 2.7 (2.3–3.1) • The second most frequently managed problem was under the endocrine, metabolic and nutritional Abdominal pain* 171 2,573 0.6 0.8 (0.6–1.0) chapter (17.4% of all diagnoses), which includes diabetes and lipid disorder. Non-gestational diabetes (type 1, type 2 and unspecified type inclusive) accounted for 8.1% of all diagnoses, while lipid Diarrheoa 186 2,387 0.6 0.7 (0.6–0.9) disorder was reported at a rate of 10.6 diagnoses per 100 patient encounters (7.9% of all diagnoses). Musculoskeletal 2,015 28,890 6.6 8.9 (8.0–9.7) • Cardiovascular diseases ranked third among the leading diagnoses in primary care, representing Musculoskeletal 1,101 13,551 3.1 4.2 (3.7–4.6) 14.3% of all diagnoses. Hypertension, the cardiovascular disease which was also the second most symptom/complaints* frequent condition seen in primary care, accounted for 12.8% of all diagnoses and 17.2% of all patient Back problems* 414 6,812 1.6 2.1 (1.7–2.5) encounters. Arthritis - all* 257 4,278 1.0 1.3 (0.7–1.9) Osteoarthritis* 176 3,215 0.7 1.0 (0.4–1.6) Sprain/strain* 134 2,242 0.5 0.7 (0.5–0.9)

72 National Medical Care Statistics 2014

Chapter 8 : Diagnoses 73

Table 8.3.1 (continued): Diagnosis by ICPC-2 chapters and the most common individual 8.4 MOST COMMON DIAGNOSES MANAGED IN PUBLIC AND PRIVATE CLINICS diagnoses within each chapter in NMCS 2014 Significant differences were observed in the types of problems most commonly managed in the public and private spheres of Malaysia’s two-tier health system. Table 8.4.1 and Table 8.4.2 list the top 30 Percent of Rate per 100 Diagnosis (ICPC-2 Unweighted Weighted total encounters diagnoses in descending order of frequency for public and private clinics, respectively, reflecting the chapter) count count diagnoses (95% CI) general morbidity pattern among primary care patients in 2014. (n = 436,743) (n = 325,818)

Skin 2,225 27,587 6.3 8.5 (7.7–9.2) Public clinics Dermatitis* 585 7,298 1.7 2.2 (1.9–2.6) The top three diseases managed in the public sector were all chronic diseases. Together, they accounted Dermatitis, contact/allergic 560 7,070 1.6 2.2 (1.8–2.5) for 50.8% of all diagnoses managed in government health clinics (Table 8.4.1). Dermatitis, atopic eczema 18 155 0.0 0.1 (0.0–0.1) • Hypertension, which was reported at a rate of 33.1 diagnoses per 100 encounters, accounted for Injury skin - all* 226 3,018 0.7 0.9 (0.7–1.2) 21.4% of all diagnoses. Urticaria 165 2,951 0.7 0.9 (0.5–1.4) • The second most frequent condition was diabetes, which accounted for 15.1% of all diagnoses, Pregnancy, childbearing, family followed by lipid disorder at 14.3%. 1,916 18,213 4.2 5.6 (4.6–6.6) planning • Approximately one-sixth (15.6%) of patients who sought treatment in public clinics were diagnosed Medical examination - with an upper respiratory tract infections (10.1% of all diagnoses). 990 9,458 2.2 2.9 (2.3–3.6) pregnancy* • Antenatal check-ups accounted for 3.9% of all diagnoses and ranked fifth among the top diagnoses Neurological 996 14,103 3.2 4.3 (3.7–4.9) managed in public primary care clinics. Headache - all* 627 9,097 2.1 2.8 (2.4–3.2) Headache 351 5,106 1.2 1.6 (1.2–1.9) Private clinics

Migraine 187 2,878 0.7 0.9 (0.7–1.1) Table 8.4.2 lists the 30 most frequently managed diagnoses in private clinics in 2014. Together, these Vertigo/dizziness 208 3,036 0.7 0.9 (0.7–1.2) diagnoses accounted for approximately two-thirds (76.0%) of all diagnoses in private clinics; the top 10 Eye 548 5,981 1.4 1.8 (1.6–2.0) diagnoses amounted to 52.9% of all diagnoses. Conjunctivitis* 310 3,343 0.8 1.0 (0.9–1.2) • More than one-quarter (27.2%) of patients seeking treatment in private clinics were diagnosed with Urological 486 5,969 1.4 1.8 (1.6–2.1) an upper respiratory tract infection, which accounted for 22.7% of all diagnoses. Urinary tract infection* 302 3,729 0.9 1.1 (0.9–1.3) • Hypertension is the second most common condition managed in private clinics, occurring at rate of 6.5 diagnoses per 100 encounters (5.4% of all diagnoses). Female genital 388 5,114 1.2 1.6 (1.3–1.8) • Ranking third to fifth among the top diagnoses in private clinics were acute conditions— Menstrual problems* 207 2,929 0.7 0.9 (0.7–1.1) gastroenteritis (4.5% of all diagnoses), musculoskeletal symptoms/complaints (3.7%) and fever Psychological 363 4,674 1.1 1.4 (0.9–1.9) (3.2%)—which accounted for 28.7% of the top five diagnoses. Ear 269 3,389 0.8 1.0 (0.9–1.2) • Diabetes and lipid disorders, which were the second and third most common diagnoses in public clinics, accounted for only 2.5% and 2.4% of all diagnoses managed in private clinics, respectively. Blood, blood forming organs & 210 2,226 0.5 0.7 (0.5–0.8) immune mechanism

Male genital 57 684 0.2 0.2 (0.1–0.3)

Social problems 15 135 0.0 0.0 (0.0–0.1) Total 38,151 436,743 100.0 134.0 (130.6–137.5) * Comprise multiple ICPC-2 codes (see Appendix 4)

The range and frequency of diagnoses managed in primary care have been studied internationally, and similar patterns were observed across countries. The 10 most commonly managed problems in general practice in Australia were hypertension, immunisation, upper respiratory tract infection, depression, diabetes, lipid disorder, general check-up, osteoarthritis, back complaint and prescription request.2 Closer to home, the top primary diagnoses seen in primary care clinics in Singapore were upper respiratory infection (13%), essential hypertension (7%), type 2 diabetes mellitus (6%) and hyperlipidaemia (5%).3

74 National Medical Care Statistics 2014

Male genital 57 684 0.2 0.2 (0.1–0.3)

Social problems 15 135 0.0 0.0 (0.0–0.1) Total 38,151 436,743 100.0 134.0 (130.6–137.5) * Comprise multiple ICPC-2 codes (see Appendix 4)

Chapter 8 : Diagnoses 75

Table 8.4.1: Thirty most common diagnoses managed in public clinics in 2014 Table 8.4.2: Thirty most common diagnoses managed in private clinics in 2014

Percent of Rate per 100 Percent of Rate per 100 Unweighted Weighted Unweighted Weighted total encounters total encounters Rank Diagnosis count count Rank Diagnosis count count diagnoses (95% CI) diagnoses (95% CI) (n = 23,760) (n = 203,868) (n = 14,391) (n = 232,874) (n = 203,868) (n = 131,624) (n = 232,874) (n = 194,194)

1 Hypertension - all* 4,966 43,597 21.4 33.1 (29.8–36.4) 1 Upper respiratory tract infection 3,241 52,818 22.7 27.2 (25.5–28.9) Hypertension - Cardiovascular* 4,927 43,292 21.2 32.9 (29.6–36.2) 2 Hypertension - cardiovascular* 820 12,648 5.4 6.5 (5.7–7.3) Hypertension in pregnancy 39 305 0.2 0.2 (0.1–0.4)

2 Diabetes - all* 3,334 30,776 15.1 23.4 (20.1–26.7) 3 Gastroenteritis* 620 10,398 4.5 5.4 (4.6–6.2)

Diabetes type 2 2,691 24,798 12.2 18.8 (15.4–22.3) Musculoskeletal 4 549 8,523 3.7 4.4 (3.8–5.0) Diabetes - unspecified 435 4,337 2.1 3.3 (1.7–4.9) symptom/complaints*

Gestational diabetes 141 1,152 0.6 0.9 (0.6–1.2) 5 Fever 480 7,397 3.2 3.8 (3.0–4.7) 3 Lipid disorder 3,366 29,115 14.3 22.1 (19.3–25.0) 4 Upper respiratory tract infection 2,687 20,527 10.1 15.6 (14.2–17.0) 6 Headache - all* 404 7,249 3.1 3.7 (3.1–4.3) Headache 217 3,953 1.7 2.0 (1.5–2.6) 5 Medical examination - pregnancy* 881 7,864 3.9 6.0 (4.3–7.6) Migraine 137 2,449 1.1 1.3 (0.9–1.6) 6 Musculoskeletal 552 5,028 2.5 3.8 (3.1–4.6) symptom/complaints* 7 Stomach function disorder 368 6,248 2.7 3.2 (2.7–3.8) 7 Asthma 420 4,272 2.1 3.3 (2.4–4.1) 8 Back problems* 331 6,141 2.6 3.2 (2.5–3.8) 8 Fever 420 3,870 1.9 2.9 (2.1–3.8) 9 Dermatitis* 387 5,959 2.6 3.1 (2.5–3.7) 9 Medical examination* 404 3,488 1.7 2.7 (1.9–3.4) Dermatitis, contact/allergic 370 5,783 2.5 3.0 (2.4–3.6)

10 Gastroenteritis* 361 2,741 1.3 2.1 (1.7–2.5) 10 Diabetes - all* 416 5,818 2.5 3.0 (2.5–3.5) 11 Stomach function disorder 319 2,500 1.2 1.9 (1.6–2.2) Diabetes type 2 302 4,225 1.8 2.2 (1.7–2.6)

12 High risk pregnancy* 235 1,873 0.9 1.4 (0.8–2.0) Diabetes - unspecified 83 1,343 0.6 0.7 (0.4–0.9)

13 Headache - all* 223 1,849 0.9 1.4 (1.0–1.8) 11 Lipid disorder 327 5,552 2.4 2.9 (1.8–4.0) Headache 134 1,153 0.6 0.9 (0.6–1.2) 12 Asthma 298 5,071 2.2 2.6 (1.9–3.4)

14 Ischaemic heart disease* 215 1,821 0.9 1.4 (1.0–1.7) 13 Medical examination* 307 4,021 1.7 2.1 (1.5–2.7)

15 Disease/condition of unspecified 167 1,712 0.8 1.3 (0.9–1.7) 14 Disease/condition of unspecified 233 3,617 1.6 1.9 (1.2–2.5) nature/site nature/site 16 Urinary tract infection* 166 1,460 0.7 1.1 (0.8–1.4) 15 Arthritis - all* 164 3,400 1.5 1.8 (0.7–2.8) 17 Tonsillitis 194 1,396 0.7 1.1 (0.8–1.4) Osteoarthritis* 95 2,473 1.1 1.3 (0.3–2.3)

18 Dermatitis* 198 1,340 0.7 1.0 (0.7–1.3) 16 Tonsillitis 222 3,266 1.4 1.7 (1.3–2.1) Dermatitis, contact/allergic 190 1,287 0.6 1.0 (0.7–1.3) 17 Menstrual problems* 146 2,509 1.1 1.3 (1.0–1.6)

19 Conjunctivitis* 164 1,167 0.6 0.9 (0.7–1.1) 18 Cough 185 2,496 1.1 1.3 (0.9–1.6) 20 Cough 98 972 0.5 0.7 (0.3–1.1) 19 Vertigo/dizziness 144 2,493 1.1 1.3 (0.9–1.7) 21 Anaemia* 98 964 0.5 0.7 (0.4–1.0) 20 Urticaria 109 2,414 1.0 1.2 (0.5–2.0) 22 Viral disease 84 910 0.5 0.7 (0.4–1.0) 21 Abdominal pain* 133 2,332 1.0 1.2 (0.9–1.5) 23 Contraception, female* 96 906 0.4 0.7 (0.4–1.0) 22 Urinary tract infection* 136 2,269 1.0 1.2 (0.9–1.4) 24 Arthritis - all* 93 878 0.4 0.7 (0.4–0.9) 23 Conjunctivitis* 146 2,175 0.9 1.1 (0.9–1.4) 25 Perinatal morbidity, other 151 872 0.4 0.7 (0.3–1.0) 24 Diarrheoa 146 2,147 0.9 1.1 (0.8–1.4) 26 Fear of infection; general 60 731 0.4 0.6 (0.1–1.0) 25 Sprain/strain* 102 2,017 0.9 1.0 (0.8–1.3) 27 Gout 93 707 0.4 0.5 (0.4–0.7) 26 Acute bronchitis 131 1,959 0.8 1.0 (0.7–1.3) 28 Back problems* 83 672 0.3 0.5 (0.3–0.7) Medical examination - 27 109 1,593 0.7 0.8 (0.6–1.1) 29 Fear of respiratory disease 61 635 0.3 0.5 (0.2–0.8) pregnancy*

30 Allergy/allergic reaction 72 610 0.3 0.6 (0.3–0.6) 28 Dermatophytosis 111 1,538 0.7 0.8 (0.6–1.0) 29 Respiratory infection* 43 1,433 0.6 0.7 (0.0–1.9) * Comprise multiple ICPC-2 codes (see Appendix 4) 30 Sinusitis 79 1,422 0.6 0.7 (0.5–1.0) * Comprise multiple ICPC-2 codes (see Appendix 4)

76 National Medical Care Statistics 2014

Table 8.4.1: Thirty most common diagnoses managed in public clinics in 2014 Table 8.4.2: Thirty most common diagnoses managed in private clinics in 2014

2 Diabetes - all* 3,334 30,776 15.1 23.4 (20.1–26.7) 3 Gastroenteritis* 620 10,398 4.5 5.4 (4.6–6.2)

Diabetes type 2 2,691 24,798 12.2 18.8 (15.4–22.3) Musculoskeletal 4 549 8,523 3.7 4.4 (3.8–5.0) Diabetes - unspecified 435 4,337 2.1 3.3 (1.7–4.9) symptom/complaints*

12 High risk pregnancy* 235 1,873 0.9 1.4 (0.8–2.0) Diabetes - unspecified 83 1,343 0.6 0.7 (0.4–0.9)

13 Headache - all* 223 1,849 0.9 1.4 (1.0–1.8) 11 Lipid disorder 327 5,552 2.4 2.9 (1.8–4.0) Headache 134 1,153 0.6 0.9 (0.6–1.2) 12 Asthma 298 5,071 2.2 2.6 (1.9–3.4)

14 Ischaemic heart disease* 215 1,821 0.9 1.4 (1.0–1.7) 13 Medical examination* 307 4,021 1.7 2.1 (1.5–2.7)

Chapter 8 : Diagnoses 77

REFERENCES

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia. 2. Cooke G, Valenti L, Glasziou P, Britt H. Common general practice presentations and publication frequency. Aust Fam Physician. 2013 Jan-Feb;42(1-2):65-8. 3. National Healthcare Group Polyclinics (SG). Advancing family medicine, transforming primary healthcare [Internet]. Singapore: National Healthcare Group Polyclinics; c2014 [cited 2015 Apr 8]. Available from: https://www.nhgp.com.sg/uploadedFiles/About_Us/NHGP_Corporate%20brochure_DPS_Web.pdf

78 National Medical Care Statistics 2014

REFERENCES

1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research Centre (MY), National Healthcare Statistics Initiative; 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia. 2. Cooke G, Valenti L, Glasziou P, Britt H. Common general practice presentations and publication frequency. Aust Fam Physician. 2013 Jan-Feb;42(1-2):65-8. 3. National Healthcare Group Polyclinics (SG). Advancing family medicine, transforming primary healthcare [Internet]. Singapore: National Healthcare Group Polyclinics; c2014 [cited 2015 Apr 8]. Available from: https://www.nhgp.com.sg/uploadedFiles/About_Us/NHGP_Corporate%20brochure_DPS_Web.pdf

CHAPTER nine Medications

CHAPTER 9: MEDICATIONS Table 9.1.2: Number of medications prescribed in primary care clinics in 2014

Percent of Rate per 100 Rate per 100 prescribed During primary care encounters, patients were prescribed medications for their conditions as deemed Number of Unweighted Weighted encounters diagnoses medications medications count count (95% CI) (95% CI) necessary by the respective healthcare providers. The providers were instructed to record the (95% CI) (n = 325,818) (n = 436,743) medications prescribed in generic or brand names, the dosage form, route of administration, dose, (n = 864,552) frequency and duration of therapy. Note that NMCS 2014 captured only the medications prescribed and Overall 70,711 864,552 100.0 265.3 (256.7–274.0) 198.0 (190.8–205.1) not the medications dispensed. Hence, the data presented here do not reflect the actual consumption of medications in the primary care setting. Public 38,296 327,087 37.8 (31.8–43.8) 248.5 (236.7–260.3) 160.4 (156.5–164.4) Private 32,415 537,465 62.2 (56.2–68.2) 276.8 (265.3–288.2) 230.8 (221.7–239.9)

9.1 NUMBER OF MEDICATIONS PRESCRIBED PER ENCOUNTER Number of medications prescribed per encounter Number of encounters with medical prescription Below is the pattern of prescription in the public and private sectors as presented in Figure 9.1.1.

Table 9.1.1 presents the number of encounters with and without medical prescription in primary care • Generally, the primary care prescription pattern observed in NMCS 2014 was similar to the clinics in 2014. pattern observed in NMCS 2012.1 • A total of 292,906 (89.9%) encounters were prescribed with at least one medication. • More encounters in the public sector (13.4%) were not prescribed with any medication compared to • The percentage of encounters during which medications were prescribed was higher in private the private sector (7.9%). This may be explained by the fact that the public sector had more clinics compared to public clinics (92.1% versus 86.6%, respectively). diagnostic, screening and preventive encounters, which most likely did not require any medication. • Nearly 60% of the encounters in private clinics were prescribed with three or more medications, compared to 45.8% in the public sector. Table 9.1.1: Number of encounters with and without medical prescription in primary care • The highest number of medications prescribed per encounter was 15 and 13 in the public and the clinics in 2014 private sectors, respectively.

Unweighted Percent of encounters Number of encounters Weighted count count (95% CI) Figure 9.1.1: Number of medications prescribed per encounter in primary care clinics in 2014 Overall With medication 24,523 292,906 89.9 (88.9–90.9) 40 Without medication 3,064 32,912 10.1 (9.1–11.1) 35 Public 30 With medication 13,387 114,048 86.7 (84.8–88.5) Without medication 2,083 17,576 13.4 (11.5–15.2) 25 Private 20 With medication 11,136 178,857 92.1 (91.0–93.2) 15 Without medication 981 15,337 7.9 (6.8–9.0) Percent of encounters (%) 10 Number of medications prescribed 5

Table 9.1.2 shows the total number of medications prescribed and the prescription rates by encounters 0 and by diagnoses in primary care clinics in 2014. Nil One Two Three ≥ Four Public 13.4 18.5 22.4 20.1 25.7 • A total of 864,552 medications were prescribed, of which 37.8% were prescribed in the public sector Private 7.9 12.5 21.1 27.0 31.5 while the remaining 62.2% were prescribed in the private sector. • The medication prescribing rate in the public sector was 248.5 medications per 100 encounters, Number of medications per encounter which was lower compared to the private sector, which recorded a rate of 276.8 medications per 100 encounters. • The public-private difference was even greater when the prescription rate per diagnosis was examined. For every 100 diagnoses, approximately 70 more medications were prescribed in the private sector than in the public sector (230.8 medications versus 160.4 medications, respectively).

80 National Medical Care Statistics 2014

CHAPTER 9: MEDICATIONS Table 9.1.2: Number of medications prescribed in primary care clinics in 2014

Chapter 9 : Medications 81

Age- and gender-specific prescription rate 9.2 TYPES OF MEDICATIONS PRESCRIBED

Age- and gender-specific prescription rates per 100 encounters in public and private clinics are The implication of the escalating healthcare costs in Malaysia, driven by the rising burden of chronic presented in Figure 9.1.2. diseases and the hike in drug prices, has been the subject of much discussion. Table 9.2.1 shows the distribution of medications prescribed to primary care patients by the Anatomical Therapeutic • The prescription rates were higher in the private sector for patients who were less than 40 years Chemical (ATC) classification in 2014. The medications are reported according to their anatomical main old compared to those in the public sector regardless of the gender. The trends were reversed for group (ATC level 1), pharmacological subgroup (ATC level 3) and chemical substance (ATC level 5) in patients aged 40 years and above for both genders. decreasing order of frequency. Only medications which accounted for at least 0.5% of all prescribed • The lowest prescription rate was recorded in the infant age group (less than one year old) for both medications were included in the table. sectors. Nevertheless, the prescription rate for infants was more than two times higher in the private sector compared to the public sector for both genders. • Consistent with our findings in NMCS 2012,1 the most common medications prescribed were • No marked differences in prescription rate were observed between genders in different age groups respiratory system agents (22.4% of all medications), and systemic antihistamines contributed to for both sectors, except for the 20–39 and the 60 and above age groups in the public sector. In these more than half of all respiratory agents prescribed. two age groups, the differences were approximately 40 medications per 100 encounters. Similar • The second most frequently prescribed drugs were the alimentary tract and metabolism agents trends were observed in NMCS 2012.1 (20.2% of all medications), which were prescribed at a rate of 53.6 medications per 100 encounters. • For both sectors, elderly females (aged 60 years and above) were prescribed more medications than Blood glucose lowering agents like metformin, gliclazide and glibenclamide, which were prescribed their male counterparts: 353.8 versus 312.8 medications per 100 encounters in public clinics and at a rate of 14.3 per 100 encounters, represented 26.7% of the alimentary tract and metabolism 295.0 versus 268.3 medications per 100 encounters in private clinics. agents prescribed. • Of all age and gender groups, the elderly female patients in public clinics had the highest • Medications for cardiovascular system were prescribed at a rate of 41.0 per 100 encounters, making prescription rate (353.8 medications per 100 encounters, as reported above). them the third most commonly prescribed drugs. This group of drugs constituted 15.4% of all medications prescribed in primary care clinics. Figure 9.1.2: Age- and gender- specific prescription rates per 100 encounters by sector in 2014 Table 9.2.2 and Table 9.2.3 present the distribution of the prescribed medications according to the ATC level 1 index classification in the public and private sectors, respectively. 400 • The top three medications prescribed in public clinics were cardiovascular agents (34.1%), alimentary tract and metabolism agents (24.7%) and respiratory system agents (14.1%). Among 350 353.8 these three categories, oral hypoglycaemic agents, lipid modifying agents and calcium channel blockers were the predominant therapeutic agents prescribed in public clinics (see Table 9.3.1). 312.8 300 295.0 • Respiratory medications were the most frequently prescribed medications in private clinics, accounting for 27.4% of all medications prescribed in private clinics. This was followed by 268.3 alimentary tract and metabolism agents at 17.4% (48.2 per 100 encounters) and musculoskeletal 250 227.2 medications at 15.5% (43.0 per 100 encounters). • Prescription drugs for cardiovascular system were recorded at a rate of 11.3 medications per 200 211.4 100 encounters, amounting to 4.1% of all medications prescribed in private clinics.

150 Public; male The prescription patterns in both public and private clinics were reflective of the types of diseases Public; female managed in the respective spheres of primary care, where chronic diseases such as dyslipidaemia, Rate per 100 encounters 97.4 100 Private; male hypertension and diabetes were the predominant diagnoses managed in public clinics, while respiratory and cardiovascular diseases were the most common diagnoses in private clinics (see Chapter 8). Private; female 80.1 50

0 < 1 1–4 5–19 20–39 40–59 ≥ 60 Age group (years)

82 National Medical Care Statistics 2014

Age- and gender-specific prescription rate 9.2 TYPES OF MEDICATIONS PRESCRIBED

0 < 1 1–4 5–19 20–39 40–59 ≥ 60 Age group (years)

Chapter 9 : Medications 83

Table 9.2.1: Prescribed medications by ATC levels in primary care clinics in 2014 Table 9.2.1 (continued): Prescribed medications by ATC levels in primary care clinics in 2014

Rate per ATC Level 1 Percent of Rate per 100 Rate per 100 Percent of Rate per 100 Unweighted Weighted prescribed encounters diagnoses Unweighted Weighted prescribed 100 encounters diagnoses ATC Level 3 ATC Level 1 count count medications (95% CI) (95% CI) count count medications (95% CI) (95% CI) (n = 864,552) (n = 325,818) (n = 436,743) ATC Level 5 (n = 864,552) (n = 325,818) (n = 436,743) Belladonna and 965 14,710 1.7 4.5 (3.7–5.3) 3.4 (2.8–4.0) Respiratory system 14,485 193,365 22.4 59.4 (55.2–63.5) 44.3 (40.6–47.9) derivatives, plain Antihistamines for 8,203 105,576 12.2 32.4 (30.1–34.7) 24.2 (22.2–26.2) Butylscopolamine 960 14,672 1.7 4.5 (3.7–5.3) 3.4 (2.7–4.0) systemic use Drugs for peptic ulcer Diphenhydramine, and gastro- 2,477 30,118 3.5 9.2 (8.2–10.3) 6.9 (6.0–7.8) 914 13,608 1.6 4.2 (3.5–4.8) 3.1 (2.6–3.6) combinations oesophageal reflux disease (GORD) Chlorphenamine 2,514 29,057 3.4 8.9 (7.6–10.3) 6.7 (5.6–7.7) Ranitidine 432 5,221 0.6 1.6 (1.4–1.9) 1.2 (1.0–1.4) Cetirizine 757 11,290 1.3 3.5 (2.9–4.1) 2.6 (2.1–3.1) Antacids 1,037 13,066 1.5 4.0 (3.5–4.6) 3.0 (2.6–3.4) Dexchlorpheniramine 549 9,951 1.2 3.1 (2.3–3.8) 2.3 (1.7–2.9) Magnesium silicate 502 5,581 0.7 1.7 (1.4–2.0) 1.3 (1.0–1.5) Loratadine 627 9,817 1.1 3.0 (2.5–3.6) 2.3 (1.8–2.7) Electrolytes with 956 12,000 1.4 3.7 (3.3–4.1) 2.8 (2.4–3.1) Diphenhydramine 745 9,112 1.1 2.8 (2.2–3.4) 2.1 (1.6–2.5) carbohydrates Expectorants, excl. Insulins and 1,159 10,860 1.3 3.3 (2.7–4.0) 2.5 (2.0–2.9) combinations with cough 1,832 22,078 2.6 6.8 (6.0–7.5) 5.1 (4.5–5.7) analogues suppressants Insulin (human) 508 4,787 0.6 1.5 (1.1–1.8) 1.1 (0.8–1.4) Bromhexine 1,055 12,368 1.4 3.8 (3.2–4.4) 2.8 (2.4–3.3) Antipropulsives 690 9,841 1.1 3.0 (2.7–3.4) 2.3 (2.0–2.6) Nasal decongestants for 826 12,993 1.5 4.0 (3.2–4.8) 3.0 (2.3–3.6) systemic use Loperamide 325 5,137 0.6 1.6 (1.3–1.9) 1.2 (0.9–1.4) Pseudoephedrine, 797 12,677 1.5 3.9 (3.1–4.7) 2.9 (2.3–3.6) Diphenoxylate 365 4,704 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.3) combinations Stomatological 774 8,638 1.0 2.7 (2.2–3.1) 2.0 (1.7–2.3) Throat preparations 677 12,339 1.4 3.8 (3.0–4.6) 2.8 (2.2–3.4) preparations

Cough suppressants, Various 543 5,831 0.7 1.8 (1.4–2.2) 1.3 (1.0–1.6) excl. combinations with 716 11,590 1.3 3.6 (2.9–4.2) 2.7 (2.2–3.2) expectorants Propulsives 484 6,880 0.8 2.1 (1.8–2.4) 1.6 (1.3–1.8)

Combinations 349 5,556 0.6 1.7 (1.3–2.2) 1.3 (0.9–1.6) Intestinal adsorbents 432 6,685 0.8 2.1 (1.6–2.5) 1.5 (1.2–1.9)

Adrenergics, inhalants 592 7,241 0.8 2.2 (1.7–2.8) 1.7 (1.3–2.0) Medicinal charcoal 285 4,451 0.5 1.4 (1.1–1.7) 1.0 (0.8–1.3)

Salbutamol 469 5,355 0.6 1.6 (1.2–2.1) 1.2 (0.9–1.5) Vitamin B-complex, 473 4,837 0.6 1.5 (1.1–1.9) 1.1 (0.8–1.4) incl. combinations Adrenergics for 534 6,843 0.8 2.1 (1.7–2.5) 1.6 (1.3–1.9) Vitamin B1, plain and systemic use in combination with 360 4,756 0.6 1.5 (1.1–1.9) 1.1 (0.8–1.4) Salbutamol 454 5,861 0.7 1.8 (1.4–2.2) 1.3 (1.1–1.6) vitamin B6 and B12

Alimentary tract and Cardiovascular system 14,164 133,445 15.4 41.0 (35.0–46.9) 30.6 (26.8–34.3) 14,875 174,469 20.2 53.6 (50.7–56.4) 40.0 (38.3–41.6) metabolism Lipid modifying 3,976 37,790 4.4 11.6 (9.5–13.7) 8.7 (7.3–10.1) Blood glucose lowering agents, plain 4,758 46,613 5.4 14.3 (11.5–17.1) 10.7 (8.8–12.6) drugs, excl. insulins Lovastatin 2,451 23,230 2.7 7.1 (5.5–8.8) 5.3 (4.2–6.4) Metformin 2,666 25,477 3.0 7.8 (6.2–9.4) 5.8 (4.7–6.9) Simvastatin 1,102 8,507 1.0 2.6 (2.0–3.2) 2.0 (1.5–2.4) Gliclazide 1,285 11,964 1.4 3.7 (2.9–4.5) 2.7 (2.2–3.3) Selective calcium channel blockers with Glibenclamide 412 4,872 0.6 1.5 (1.0–2.0) 1.1 (0.8–1.5) 3,577 34,436 4.0 10.6 (9.0–12.1) 7.9 (6.9–8.9) mainly vascular effects

Amlodipine 3,215 30,846 3.6 9.5 (8.0–11.0) 7.1 (6.1–8.1)

84 National Medical Care Statistics 2014

Table 9.2.1: Prescribed medications by ATC levels in primary care clinics in 2014 Table 9.2.1 (continued): Prescribed medications by ATC levels in primary care clinics in 2014

Combinations 349 5,556 0.6 1.7 (1.3–2.2) 1.3 (0.9–1.6) Intestinal adsorbents 432 6,685 0.8 2.1 (1.6–2.5) 1.5 (1.2–1.9)

Adrenergics, inhalants 592 7,241 0.8 2.2 (1.7–2.8) 1.7 (1.3–2.0) Medicinal charcoal 285 4,451 0.5 1.4 (1.1–1.7) 1.0 (0.8–1.3)

Amlodipine 3,215 30,846 3.6 9.5 (8.0–11.0) 7.1 (6.1–8.1)

Chapter 9 : Medications 85

Table 9.2.1 (continued): Prescribed medications by ATC levels in primary care clinics in 2014 Table 9.2.1 (continued): Prescribed medications by ATC levels in primary care clinics in 2014

Percent of Rate per 100 Rate per 100 Percent of Rate per 100 Rate per 100 Unweighted Weighted prescribed encounters diagnoses Unweighted Weighted prescribed encounters diagnoses ATC Level 1 ATC Level 1 count count medications (95% CI) (95% CI) count count medications (95% CI) (95% CI) (n = 864,552) (n = 325,818) (n = 436,743) (n = 864,552) (n = 325,818) (n = 436,743) Other beta-lactam ACE inhibitors, plain 2,485 22,681 2.6 7.0 (5.8–8.1) 5.2 (4.4–6.0) 1,001 16,855 2.0 5.2 (4.0–6.3) 3.9 (3.0–4.8) antibacterials Perindopril 2,024 18,030 2.1 5.5 (4.6–6.5) 4.1 (3.5–4.8) Cephalexin 633 9,378 1.1 2.9 (2.3–3.4) 2.2 (1.7–2.6) Beta blocking agents 1,648 14,752 1.7 4.5 (3.8–5.2) 3.4 (2.9–3.9) Macrolides, lincosamides and 921 11,940 1.4 3.7 (3.2–4.2) 2.7 (2.3–3.1) Atenolol 818 7,076 0.8 2.2 (1.8–2.6) 1.6 (1.4–1.9) streptogramins

Metoprolol 650 5,571 0.6 1.7 (1.3–2.1) 1.3 (1.0–1.6) Erythromycin 638 7,167 0.8 2.2 (1.9–2.5) 1.6 (1.4–1.9) Quinolone Low-ceiling diuretics, 296 5,359 0.6 1.6 (1.1–2.2) 1.2 (0.8–1.7) 1,010 8,836 1.0 2.7 (2.1–3.3) 2.0 (1.6–2.5) thiazides antibacterials Dermatologicals 2,144 26,878 3.1 8.3 (7.3–9.2) 6.2 (5.4–6.9) Hydrochlorothiazide 1,008 8,819 1.0 2.7 (2.1–3.3) 2.0 (1.6–2.4) Corticosteroids, plain 515 7,036 0.8 2.2 (1.8–2.6) 1.6 (1.3–1.9) Nervous system 8,661 106,751 12.4 32.8 (31.1–34.4) 24.4 (22.8–26.1) Emollients and 579 6,956 0.8 2.1 (1.7–2.6) 1.6 (1.3–1.9) Other analgesics and protectives 7,501 90,649 10.5 27.8 (26.5–29.2) 20.8 (19.4–22.1) antipyretics Blood and blood 2,079 19,347 2.2 5.9 (5.0–6.9) 4.4 (3.8–5.1) forming organs Paracetamol 7,413 89,591 10.4 27.5 (26.1–28.9) 20.5 (19.2–21.9) Iron preparations 746 6,615 0.8 2.0 (1.6–2.5) 1.5 (1.2–1.9) Musculoskeletal system 6,733 99,136 11.5 30.4 (28.0–32.9) 22.7 (20.6–24.8) Antithrombotic agents 749 6,447 0.8 2.0 (1.6–2.4) 1.5 (1.2–1.8) Antiinflammatory and Acetylsalicylic acid 650 5,406 0.6 1.7 (1.3–2.0) 1.2 (1.0–1.5) antirheumatic products, 4,246 63,320 7.3 19.4 (17.6–21.2) 14.5 (13.0–16.0) Vitamin B12 and folic non-steroids 505 5,244 0.6 1.6 (1.2–2.0) 1.2 (0.9–1.5) acid Diclofenac 1,714 24,928 2.9 7.7 (6.6–8.7) 5.7 (4.9–6.6) Folic acid 450 4,479 0.5 1.4 (1.0–1.8) 1.0 (0.8–1.3) Mefenamic Acid 1,291 17,775 2.1 5.5 (4.8–6.1) 4.1 (3.5–4.6) Systemic hormonal 959 16,183 1.9 5.0 (3.6–6.3) 3.7 (2.7–4.7) preparations Ibuprofen 398 5,707 0.7 1.8 (1.4–2.1) 1.3 (1.0–1.6) Corticosteroids for Topical products for joint 823 15,079 1.7 4.6 (3.3–6.0) 3.5 (2.4–4.5) 1,101 14,241 1.7 4.4 (3.7–5.0) 3.3 (2.8–3.7) systemic use, plain and muscular pain Prednisolone 618 10,950 1.3 3.4 (2.4–4.3) 2.5 (1.8–3.3) Muscle relaxants, 603 10,648 1.2 3.3 (2.6–3.9) 2.4 (1.9–3.0) Sensory organs 796 8,961 1.0 2.8 (2.4–3.1) 2.1 (1.8–2.3) centrally acting agents Antiinfectives 442 4,633 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.2) Orphenadrine, 501 9,180 1.1 2.8 (2.2–3.5) 2.1 (1.6–2.6) Genitourinary system combinations 418 5,787 0.7 1.7 (1.3–2.2) 1.3 (1.0–1.7) and sex hormones Other drugs for disorders of the musculoskeletal 580 8,352 1.0 2.6 (2.2–2.9) 1.9 (1.6–2.2) Antiparasitic system products, insecticides 235 3,278 0.4 1.0 (0.8–1.2) 0.8 (0.6–0.9) and repellents Antiinfectives for 5,112 76,253 8.8 23.4 (20.7–26.1) 17.5 (15.2–19.7) systemic use Various 45 609 0.1 0.2 (0.1–0.3) 0.1 (0.1–0.2) Beta-lactam 2,057 30,007 3.5 9.2 (8.2–10.2) 6.9 (6.0–7.7) Antineoplastic and antibacterials, penicillins immunomodulating 5 89 0.0 0.0 (0.0–0.1) 0.0 (0.0–0.0) agents Amoxicillin 1,100 14,729 1.7 4.5 (3.9–5.1) 3.4 (2.9–3.9)

Amoxicillin and 416 8,046 0.9 2.5 (1.6–3.3) 1.8 (1.2–2.5) Total 70,711 864,552 100.0 265.4 (256.7–274.0) 198.0 (190.8–205.1) enzyme inhibitor Note: ACE – Angiotensin converting enzyme.

86 National Medical Care Statistics 2014

Table 9.2.1 (continued): Prescribed medications by ATC levels in primary care clinics in 2014

Percent of Rate per 100 Rate per 100 Unweighted Weighted prescribed encounters diagnoses ATC Level 1 count count medications (95% CI) (95% CI) (n = 864,552) (n = 325,818) (n = 436,743) Other beta-lactam 1,001 16,855 2.0 5.2 (4.0–6.3) 3.9 (3.0–4.8) antibacterials Cephalexin 633 9,378 1.1 2.9 (2.3–3.4) 2.2 (1.7–2.6) Macrolides, lincosamides and 921 11,940 1.4 3.7 (3.2–4.2) 2.7 (2.3–3.1) streptogramins Erythromycin 638 7,167 0.8 2.2 (1.9–2.5) 1.6 (1.4–1.9) Quinolone 296 5,359 0.6 1.6 (1.1–2.2) 1.2 (0.8–1.7) antibacterials Dermatologicals 2,144 26,878 3.1 8.3 (7.3–9.2) 6.2 (5.4–6.9) Corticosteroids, plain 515 7,036 0.8 2.2 (1.8–2.6) 1.6 (1.3–1.9) Emollients and 579 6,956 0.8 2.1 (1.7–2.6) 1.6 (1.3–1.9) protectives Blood and blood 2,079 19,347 2.2 5.9 (5.0–6.9) 4.4 (3.8–5.1) forming organs Iron preparations 746 6,615 0.8 2.0 (1.6–2.5) 1.5 (1.2–1.9) Antithrombotic agents 749 6,447 0.8 2.0 (1.6–2.4) 1.5 (1.2–1.8) Acetylsalicylic acid 650 5,406 0.6 1.7 (1.3–2.0) 1.2 (1.0–1.5) Vitamin B12 and folic 505 5,244 0.6 1.6 (1.2–2.0) 1.2 (0.9–1.5) acid Folic acid 450 4,479 0.5 1.4 (1.0–1.8) 1.0 (0.8–1.3) Systemic hormonal 959 16,183 1.9 5.0 (3.6–6.3) 3.7 (2.7–4.7) preparations Corticosteroids for 823 15,079 1.7 4.6 (3.3–6.0) 3.5 (2.4–4.5) systemic use, plain Prednisolone 618 10,950 1.3 3.4 (2.4–4.3) 2.5 (1.8–3.3) Sensory organs 796 8,961 1.0 2.8 (2.4–3.1) 2.1 (1.8–2.3) Antiinfectives 442 4,633 0.5 1.4 (1.2–1.7) 1.1 (0.9–1.2) Genitourinary system 418 5,787 0.7 1.7 (1.3–2.2) 1.3 (1.0–1.7) and sex hormones Antiparasitic products, insecticides 235 3,278 0.4 1.0 (0.8–1.2) 0.8 (0.6–0.9) and repellents Various 45 609 0.1 0.2 (0.1–0.3) 0.1 (0.1–0.2)

Antineoplastic and immunomodulating 5 89 0.0 0.0 (0.0–0.1) 0.0 (0.0–0.0) agents

Total 70,711 864,552 100.0 265.4 (256.7–274.0) 198.0 (190.8–205.1)

Note: ACE – Angiotensin converting enzyme.

Chapter 9 : Medications 87

Table 9.2.2: Prescribed medications by ATC level 1 in public clinics in 2014 Table 9.2.3: Prescribed medications by ATC level 1 in private clinics in 2014

Cardiovascular system 12,782 111,547 34.1 84.8 (75.8–93.7) 54.7 (50.6–58.8) Respiratory system 8,779 147,151 27.4 75.8 (71.2–80.3) 63.2 (59.4–66.9) Alimentary tract and Alimentary tract and 9,092 80,813 24.7 61.4 (55.9–66.9) 39.6 (37.1–42.2) 5,783 93,656 17.4 48.2 (45.6–50.8) 40.2 (38.0–42.5) metabolism metabolism Respiratory system 5,706 46,214 14.1 35.1 (31.7–38.5) 22.7 (20.2–25.1) Musculoskeletal system 4,900 83,534 15.5 43.0 (40.2–45.9) 35.9 (33.5–38.2) Nervous system 4,059 32,857 10.1 25.0 (23.1–26.8) 16.1 (14.6–17.6) Nervous system 4,602 73,894 13.8 38.1 (36.2–39.9) 31.7 (30.1–33.4) Musculoskeletal Antiinfectives for systemic 1,833 15,602 4.8 11.9 (9.5–14.2) 7.7 (6.0–9.3) 3,892 65,337 12.2 33.7 (30.4–36.9) 28.1 (25.3–30.9) system use Blood and blood Cardiovascular system 1,382 21,898 4.1 11.3 (9.5–13.1) 9.4 (8.0–10.8) 1,831 15,282 4.7 11.6 (9.5–13.7) 7.5 (6.1–8.9) forming organs Dermatologicals 1,319 20,992 3.9 10.8 (9.5–12.1) 9.0 (7.9–10.1) Antiinfectives for 1,220 10,917 3.3 8.3 (7.2–9.4) 5.4 (4.5–6.2) Systemic hormonal 731 14,328 2.7 7.4 (5.3–9.5) 6.2 (4.4–7.9) systemic use preparations Dermatologicals 825 5,886 1.8 4.5 (3.7–5.2) 2.9 (2.4–3.4) Sensory organs 362 5,691 1.1 2.9 (2.4–3.4) 2.4 (2.0–2.9) Sensory organs 434 3,270 1.0 2.5 (2.1–2.9) 1.6 (1.3–1.9) Genitourinary system and 245 4,119 0.8 2.1 (1.4–2.8) 1.8 (1.2–2.4) Systemic hormonal sex hormones 228 1,855 0.6 1.4 (1.1–1.7) 0.9 (0.7–1.1) preparations Blood and blood forming 248 4,065 0.8 2.1 (1.6–2.5) 1.8 (1.4–2.1) Genitourinary system organs 173 1,668 0.5 1.3 (0.9–1.7) 0.8 (0.6–1.1) and sex hormones Antiparasitic products, 138 2,257 0.4 1.2 (0.8–1.5) 1.0 (0.7–1.2) Antiparasitic products, insecticides and repellents insecticides and 97 1,021 0.3 0.8 (0.5–1.1) 0.5 (0.3–0.7) Various 29 455 0.1 0.2 (0.1–0.4) 0.2 (0.1–0.3) repellents Antineoplastic and 5 89 0.0 0.1 (0.0–0.1) 0.0 (0.0–0.1) Various 16 155 0.1 0.1 (0.0–0.2) 0.1 (0.0–0.1) immunomodulating agents Total 38,296 327,087 100.0 248.5 (236.7–260.3) 160.4 (156.5–164.4) Total 32,415 537,465 100.0 276.8 (265.3–288.2) 230.8 (221.7–239.9)

9.3 MOST FREQUENTLY PRESCRIBED MEDICATIONS IN PUBLIC AND PRIVATE CLINICS

The most commonly prescribed medications by ATC level 5 classification are described below. The medication topping the top 30 list for both public and private sectors was paracetamol, which accounted for 8.8% of all medications prescribed in public clinics (Table 9.3.1) and 11.3% in private clinics (Table 9.3.2).

Public clinics

• The top 30 medications contributed to 74.6 % of all medicines prescribed in public clinics. A similar observation was reported in NMCS 2012.1 • Out of the 10 most commonly prescribed medications, seven were for chronic diseases, accounting for more than one-third (35.2%) of all medications prescribed in public clinics. • Erythromycin and amoxicillin, the most common antibiotics prescribed, represented only 1.7% of all medications prescribed in public clinics. • Other medications in the top 30 list included respiratory system agents such as antihistamines and bronchodilators, musculoskeletal system agents such as salicylic acid preparations and nonsteroidal antiinflammatory drugs (NSAIDS), and supplements which included vitamin-B complex, folic acid and ascorbic acid (vitamin C).

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Table 9.2.2: Prescribed medications by ATC level 1 in public clinics in 2014 Table 9.2.3: Prescribed medications by ATC level 1 in private clinics in 2014

9.3 MOST FREQUENTLY PRESCRIBED MEDICATIONS IN PUBLIC AND PRIVATE CLINICS

Public clinics

Chapter 9 : Medications 89

Private clinics Table 9.3.1: Thirty most frequently prescribed medications in public clinics in 201 4

Percent of Rate per 100 Rate per 100 • The top 30 medications accounted for 59.3% of all medications prescribed in the private sector. Unweighted Weighted prescribed encounters diagnoses • The 10 most frequently prescribed medications in private clinics were all medications for acute Rank Medication count count medications (95% CI) (95% CI) (n = 38,296) (n = 327,087) conditions, including an antiinfective (amoxicillin, 2.3%) and a steroid (prednisolone, 1.9%). (n = 327,087) (n = 131,624) (n = 203,868) • The top 10 list comprised the same medications in NMCS 2012 and 2014, except for prednisolone, 1 Paracetamol 3,604 28,665 8.8 21.8 (20.1–23.5) 14.1 (12.7–15.4) which displaced loratadine from the list in 2014.1 2 Amlodipine 2,906 26,382 8.1 20.0 (17.4–22.7) 12.9 (11.5–14.3) • In addition to amoxicillin, other systemic antiinfectives among the 30 most frequently prescribed medications included cephalexin (1.6%), amoxicillin and enzyme inhibitor (1.5%), erythromycin 3 Lovastatin 2,434 22,981 7.0 17.5 (14.8–20.1) 11.3 (9.9–12.7) (0.8%), ciprofloxacin (0.8%) and cefuroxime (0.7%). Together, antiinfectives amounted to 7.7% of all 4 Metformin 2,471 22,901 7.0 17.4 (14.4–20.4) 11.2 (9.6–12.9) medications prescribed in the private sector. 5 Perindopril 1,977 17,294 5.3 13.1 (11.5–14.8) 8.5 (7.6–9.4) 6 Chlorphenamine 1,519 12,041 3.7 9.2 (7.9–10.4) 5.9 (5.1–6.7) 7 Gliclazide 1,168 10,261 3.1 7.8 (6.1–9.5) 5.0 (4.0–6.0) Diphenhydramine, 8 1,342 9,838 3.0 7.5 (6.4–8.6) 4.8 (4.1–5.6) combinations

9 Hydrochlorothiazide 975 8,407 2.6 6.4 (5.2–7.6) 4.1 (3.4–4.9) 10 Se imvastatin 989 7,022 2.2 5.3 (4.0–6.6) 3.4 (2.6–4.3) 11 Atenolol 720 5,563 1.7 4.2 (3.5–5.0) 2.7 (2.3–3.2)

12 Metoprolol 641 5,474 1.7 4.2 (3.4–5.0) 2.7 (2.2–3.2)

13 Acetylsalicylic acid 629 5,093 1.6 3.9 (3.2–4.6) 2.5 (2.1–2.9) Preparations with 14 salicylic acid 602 5,054 1.6 3.8 (2.9–4.8) 2.5 (1.9–3.1) derivatives* 15 Bromhexine 653 5,021 1.5 3.8 (3.0–4.6) 2.5 (1.9–3.0) Insulin (human); 16 508 4,787 1.5 3.6 (3.0–4.3) 2.4 (1.9–2.8) intermediate-acting

17 Glibenclamide 364 4,254 1.3 3.2 (2.3–4.2) 2.1 (1.5–2.7) Insulin (human); intermediate- or 18 long-acting 414 4,063 1.2 3.1 (2.3–3.9) 2.0 (1.5–2.5) combined with fast- acting 19 Diclofenac 443 4,049 1.2 3.1 (2.2–4.0) 2.0 (1.4–2.6) 20 Salbutamol 390 3,811 1.2 2.9 (2.2–3.6) 1.9 (1.4–2.3) 21 Diphenhydramine 394 3,562 1.1 2.7 (1.7–3.7) 1.8 (1.1–2.4) Other agents for 22 local oral 406 3,543 1.1 2.7 (1.9–3.5) 1.7 (1.2–2.2) treatment; various

Vitamin B-complex, 23 401 3,540 1.1 2.7 (1.8–3.6) 1.7 (1.2–2.3) plain* Oral rehydration 24 450 3,475 1.1 2.6 (2.2–3.1) 1.7 (1.4–2.0) salt formulations* 25 Folic acid 390 3,413 1.0 2.6 (1.7–3.5) 1.7 (1.1–2.3) 26 Mefenamic acid 381 3,058 0.9 2.3 (1.7–3.0) 1.5 (1.1–1.9) 27 Erythromycin 346 2,953 0.9 2.2 (1.8–2.7) 1.5 (1.1–1.8)

28 Enalapril 265 2,751 0.8 2.1 (1.5–2.7) 1.4 (1.0–1.7) 29 Amoxicillin 271 2,47 6 0.8 1.9 (1.5–2.3) 1.2 (1.0–1.5) Ascorbic acid 30 259 2,37 8 0.7 1.8 (1.1–2.5) 1.2 (0.7–1.6) (Vitamin C) * ATC level 4

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Private clinics Table 9.3.1: Thirty most frequently prescribed medications in public clinics in 201 4

9 Hydrochlorothiazide 975 8,407 2.6 6.4 (5.2–7.6) 4.1 (3.4–4.9) 10 Se imvastatin 989 7,022 2.2 5.3 (4.0–6.6) 3.4 (2.6–4.3) 11 Atenolol 720 5,563 1.7 4.2 (3.5–5.0) 2.7 (2.3–3.2)

12 Metoprolol 641 5,474 1.7 4.2 (3.4–5.0) 2.7 (2.2–3.2)

Chapter 9 : Medications 91

Table 9.3.2: Thirty most frequently prescribed medications in private clinics in 2014 REFERENCE

Percent of Rate per 100 Rate per 100 Unweighted Weighted 1. Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN, editors. National prescribed encounters diagnoses Rank Medication count count medications (95% CI) (95% CI) Medical Care Statistics (NMCS) 2012. Kuala Lumpur (Malaysia): National Clinical Research (n = 32,415) (n = 537,465) (n = 537,465) (n = 194,194) (n = 232,874) Centre (MY), National Healthcare Statistics Initiative, 2014. 95 p. Report No.: NCRC/HSU/2013.3. Grant No.: NMRR-09-842-718. Supported by the Ministry of Health Malaysia. 1 Paracetamol 3,809 60,926 11.3 31.4 (29.8–33.0) 26.2 (24.7–27.6) 2 Diclofenac 1,271 20,879 3.9 10.8 (9.2–12.3) 9.0 (7.7–10.3)

Diphenhydramine, 3 1,135 20,280 3.8 10.4 (8.9–12.0) 8.7 (7.4–10.0) combinations 4 Chlorphenamine 995 17,017 3.2 8.8 (6.6–10.9) 7.3 (5.6–9.1) 5 Mefenamic acid 910 14,717 2.7 7.6 (6.6–8.6) 6.3 (5.5–7.2) 6 Butylscopolamine 703 12,857 2.4 6.6 (5.6–7.7) 5.5 (4.6–6.4) 7 Amoxicillin 829 12,253 2.3 6.3 (5.3–7.3) 5.3 (4.4–6.1) 8 Pseudoephedrine, 650 11,464 2.1 5.9 (4.7–7.1) 4.9 (4.0–5.9) combinations 9 Cetirizine 756 11,289 2.1 5.8 (4.9–6.7) 4.9 (4.1–5.6) 10 Prednisolone 516 10,006 1.9 5.2 (3.7–6.7) 4.3 (3.1–5.5) 11 Dexchlorpheniramine 543 9,929 1.9 5.1 (4.0–6.2) 4.3 (3.3–5.2) 12 Orphenadrine, 501 9,180 1.7 4.7 (3.8–5.7) 3.9 (3.2–4.7) combinations 13 Cephalexin 540 8,668 1.6 4.5 (3.6–5.3) 3.7 (3.0–4.4) 14 Loratadine 505 8,536 1.6 4.4 (3.5–5.3) 3.7 (2.9–4.4) 15 Oral rehydration salt 506 8,524 1.6 4.4 (3.8–5.0) 3.7 (3.2–4.2) formulations* 16 Amoxicillin and enzyme 411 7,985 1.5 4.1 (2.8–5.4) 3.4 (2.3–4.5) inhibitor 17 Bromhexine 402 7,347 1.4 3.8 (3.0–4.6) 3.2 (2.5–3.8) 18 Preparations with 372 6,745 1.3 3.5 (2.7–4.2) 2.9 (2.3–3.5) salicylic acid derivatives* 19 Enzymes* 378 6,524 1.2 3.4 (2.8–3.9) 2.8 (2.4–3.2) 20 Throat preparations** 322 6,391 1.2 3.3 (2.2–4.4) 2.7 (1.9–3.6) 21 Opium alkaloids and 349 5,556 1.0 2.9 (2.2–3.6) 2.4 (1.8–3.0) derivatives; combinations 22 Diphenhydramine 351 5,550 1.0 2.9 (2.1–3.6) 2.4 (1.7–3.0) 23 Ibuprofen 340 5,275 1.0 2.7 (2.1–3.3) 2.3 (1.7–2.8) 24 Loperamide 325 5,137 1.0 2.7 (2.2–3.1) 2.2 (1.8–2.6) 25 Salbutamol 324 4,745 0.9 2.4 (1.9–3.0) 2.0 (1.6–2.5) 26 Amlodipine 309 4,464 0.8 2.3 (1.9–2.7) 1.9 (1.6–2.3) 27 Medicinal charcoal 250 4,297 0.8 2.2 (1.7–2.7) 1.9 (1.4–2.3) 28 Erythromycin 292 4,214 0.8 2.2 (1.7–2.6) 1.8 (1.4–2.2) 29 Ciprofloxacin 202 4,082 0.8 2.1 (1.4–2.9) 1.8 (1.1–2.4) 30 Cefuroxime 192 4,007 0.8 2.1 (1.2–3.0) 1.7 (1.0–2.5) * ATC level 4 ** ATC level 3

92 National Medical Care Statistics 2014

Table 9.3.2: Thirty most frequently prescribed medications in private clinics in 2014 REFERENCE

CHAPTER ten Investigations

CHAPTER 10: INVESTIGATIONS Figure 10.1.1: Number of investigations ordered per encounter in primary care clinics in 2014

Laboratory and other medical investigations are essential for the diagnosis and management of many 100 conditions. In the primary care setting, the tests are generally requested to aid in diagnosis, establish a 90 baseline before commencing treatment, monitor long-term conditions for disease control, ensure a medication dose is within the therapeutic range, detect adverse effects to treatment and monitor or 80 predict the response to treatment.1 While these investigations can help in the management or monitoring of patients, it must also be remembered that the rates at which the investigations are 70 ordered can directly affect the healthcare expenditure. This chapter reports the investigations ordered 60 by primary care providers at the point of patient encounter, which include all blood and urine pathological tests, imaging studies and other diagnostic tests. 50

40 10.1 NUMBER OF INVESTIGATIONS PER ENCOUNTER 30 Percent of encounters (%) Table 10.1.1 shows the number of encounters in primary clinics during which at least one investigation 20 was ordered. Of all 325,818 encounters recorded in primary care, 22.6% had investigations ordered. The higher proportion of investigations in public clinics (39.6%) as compared to private (11.1%) can be due to 10 the higher proportion of chronic diseases managed in public sector. 0 Nil One Two Three ≥ Four Table 10.1.1: Number of encounters with investigations ordered in primary care clinics in 2014 Public 60.4 20.8 8.2 3.5 7.0 Private 88.9 8.1 1.8 0.4 0.7

Number of investigations per encounter Unweighted Percent of encounters Sector Weighted count count (95% CI)

Overall (n = 325,818) 7,272 73,540 22.6 (19.7–25.4) Table 10.2.1: Types of investigations by ICPC-2 process codes in primary care clinics in 2014 Public (n = 131,624) 5,945 52,060 39.6 (35.4–43.7) Rate per 100 Rate per 100 Percent of Private (n = 194,194) 1,327 21,480 11.1 (9.6–12.5) Unweighted Weighted encounters diagnoses Investigations investigations count count (95% CI) (95% CI) (n = 143,758) (n = 325,818) (n = 436,743) The highest numbers of investigations ordered per encounter in public clinics and private clinics were 14 and 18, respectively. Investigations were ordered more frequently in the public clinics, with about Pathology test 12,926 117,889 82.0 36.2 (30.5–41.9) 27.0 (23.2–30.8) one-fifth (18.7%) of the encounters had two or more investigations ordered per encounter, compared to Chemistry 9,210 80,153 55.8 24.6 (19.7–29.5) 18.4 (15.1–21.7) only 2.9% in the private sector (Figure 10.1.1). Glucose/glucose 2,515 24,704 17.2 7.6 (5.7–9.4) 5.7 (4.4–6.9) tolerance Electrolytes, urea & 1,805 14,659 10.2 4.5 (3.3–5.7) 3.4 (2.5–4.2) 10.2 TYPES OF INVESTIGATIONS ORDERED creatinine* Lipids 1,623 14,503 10.1 4.5 (3.5–5.4) 3.3 (2.6–4.0) Table 10.2.1 shows the distribution of the most common investigations ordered in primary care in decreasing order of frequency. A total of 143,758 investigations were ordered in primary care, at a rate Liver function* 1,191 8,853 6.2 2.7 (2.0–3.4) 2.0 (1.5–2.5) of 44.1 investigations per 100 encounters and 32.9 investigations per 100 diagnoses. HbA1c 961 8,227 5.7 2.5 (1.6–3.4) 1.9 (1.2–2.5) Chemistry; other* 495 3,883 2.7 1.2 (0.8–1.6) 0.9 (0.6–1.2) • More than four-fifths (82.0%) of all investigations ordered were laboratory/pathological tests. Glucose and/or glucose tolerance test constituted one fifth of these investigations. Urate/uric acid 351 2,372 1.6 0.7 (0.4–1.1) 0.5 (0.3–0.8) • Imaging studies accounted for 9.3% of the total investigations. Obstetric ultrasound was the most Thyroid function 144 1,674 1.2 0.5 (0.4–0.7) 0.4 (0.3–0.5) frequently ordered imaging modality, recorded at 4.0% of all investigations ordered (1.8 per 100 encounters and 1.3 per 100 diagnoses).

96 National Medical Care Statistics 2014

CHAPTER 10: INVESTIGATIONS Figure 10.1.1: Number of investigations ordered per encounter in primary care clinics in 2014

Number of investigations per encounter Unweighted Percent of encounters Sector Weighted count count (95% CI)

Table 10.2.1 (continued): Types of investigations by ICPC-2 process codes in primary care 10.3 MOST FREQUENTLY ORDERED INVESTIGATIONS IN PUBLIC AND PRIVATE clinics in 2014 CLINICS

Rate per 100 Rate per 100 Percent of The ordering rate of investigations differed significantly between the public and private sectors. Unweighted Weighted encounters diagnoses Investigations investigations Nonetheless, the two sectors shared six of the investigations listed among their top 10 list of count count (95% CI) (95% CI) (n = 143,758) (n = 325,818) (n = 436,743) investigations ordered (Figure 10.3.1 and Figure 10.3.2).

Other NEC 1,395 14,987 10.4 4.6 (4.0–5.2) 3.4 (3.0–3.9) Public clinics Urine test* 900 9,504 6.6 2.9 (2.4–3.4) 2.2 (1.8–2.6)

Blood test 274 2,920 2.0 0.9 (0.6–1.2) 0.7 (0.4–0.9) • The most frequently ordered test in the public sector was glucose and/or glucose tolerance test Urine pregnancy (15.1 per 100 encounters). 107 1,698 1.2 0.5 (0.3–0.8) 0.4 (0.2–0.6) test • Electrolytes, urea and creatinine test, ordered at a rate of 10.1 tests per 100 encounters, was the Haematology 1,534 14,890 10.4 4.6 (3.7–5.5) 3.3 (3.2–3.3) second most frequently ordered test, followed by lipid profile test (8.4 per 100 encounters). Full blood count 1,216 11,636 8.1 3.6 (2.8–4.4) 2.7 (2.1–3.2) Blood; other* 121 941 0.7 0.3 (0.2–0.4) 0.2 (0.1–0.3) Private clinics Haemoglobin 70 702 0.5 0.2 (0.1–0.3) 0.2 (0.1–0.3) • Generally, the ordering rates of investigations were much lower for the private sector. Glucose Microbiology 716 7,143 5.0 2.2 (1.5–2.8) 1.6 (1.2–2.1) and/or glucose tolerance test, the most frequently ordered test in the private sector, was ordered Hepatitis serology 183 1,932 1.3 0.6 (0.3–0.9) 0.4 (0.2–0.7) only at the same rate as the tenth most frequently ordered investigation in the public sector Tuberculosis* 203 1,761 1.2 0.5 (0.3–0.8) 0.4 (0.2–0.6) (2.5 tests per 100 encounters). Urine test (2.0 per 100 encounters) and lipid profile test (1.8 per 100 encounters) were the second HIV 129 1,187 0.8 0.4 (0.2–0.5) 0.3 (0.2–0.4) • and third most frequently ordered tests in private clinics, respectively. Venereal disease 99 1,106 0.8 0.3 (0.2–0.5) 0.3 (0.1–0.4) Imaging 1,287 13,427 9.3 4.1 (3.3–4.9) 3.1 (2.5–3.7) Figure 10.3.1: Top 10 investigations ordered in public clinics in 2014 Ultrasound 746 7,226 5.0 2.2 (1.7–2.7) 1.7 (1.3–2.1) Obstetric 612 5,715 4.0 1.8 (1.3–2.2) 1.3 (0.9–1.7) ultrasound Glucose/glucose tolerance 15.1 Diagnostic radiology 533 6,097 4.2 1.9 (1.2–2.6) 1.4 (0.9–1.9) Electrolytes, urea & creatinine* 10.1 Chest X-ray 349 4,040 2.8 1.2 (0.7–1.8) 0.9 (0.5–1.3) Other investigation 1,286 11,070 7.7 3.4 (2.3–4.5) 2.5 (1.8–3.3) Lipids 8.4

Physical function test 454 4,552 3.2 1.4 (0.7–2.1) 1.0 (0.6–1.5) Full blood count 7.0 Blood pressure* 287 3,167 2.2 1.0 (0.4–1.6) 0.7 (0.3–1.2) Liver function* 6.1 Vision 101 854 0.6 0.3 (0.1–0.4) 0.2 (0.1–0.3) Electrical tracing 538 4,179 2.9 1.3 (0.9–1.7) 1.0 (0.7–1.3) HbA1c 5.5 Electrocardiogram 536 4,113 2.9 1.3 (0.8–1.7) 0.9 (0.6–1.2) Urine test* 4.3 Diagnostic procedure 294 2,339 1.6 0.7 (0.4–1.0) 0.5 (0.3–0.7) Other diagnostic Obstetric ultrasound 3.2 190 1,578 1.1 0.5 (0.3–0.7) 0.4 (0.2–0.5) procedure; NEC* Electrocardiogram 2.7 Medical exam 128 1,372 1.0 0.4 (0.2–0.6) 0.3 (0.2–0.5) Medical Chemistry; other* 2.5 examination/health 128 1,372 1.0 0.4 (0.2–0.6) 0.3 (0.2–0.5) evaluation 0 2 4 6 8 10 12 14 16 18 20 22 complete/partial Rate per 100 encounters Total 15,627 143,758 100.0 44.1 (37.4–50.8) 32.9 (28.5–37.3) * Comprise multiple ICPC-2 codes (see Appendix 4) * Comprise multiple ICPC-2 codes (see Appendix 4) Note: NEC – Not elsewhere classified.

98 National Medical Care Statistics 2014

Table 10.2.1 (continued): Types of investigations by ICPC-2 process codes in primary care 10.3 MOST FREQUENTLY ORDERED INVESTIGATIONS IN PUBLIC AND PRIVATE clinics in 2014 CLINICS

Other NEC 1,395 14,987 10.4 4.6 (4.0–5.2) 3.4 (3.0–3.9) Public clinics Urine test* 900 9,504 6.6 2.9 (2.4–3.4) 2.2 (1.8–2.6)

Chapter 10 : Investigations 99

Figure 10.3.2: Top 10 investigations ordered in private clinics in 2014 Table 10.4.1: Top 10 diagnoses for which investigations were most frequently ordered in primary care clinics in 2014

Glucose/glucose tolerance 2.5 Percent of Rate per 100 Unweighted Weighted diagnoses contacts with Urine test* Rank Diagnosis count count with 2.0 each diagnosis (n = 8,599) (n = 82,978) investigation (95% CI) Lipids 1.8 (n = 82,978) 1 Diabetes - all* 1,958 20,157 24.3 55.1 (47.9–62.3) Full blood count 1.2 Non-gestational diabetes* 1,884 19,648 23.7 55.4 (47.9–63.0)

Blood test 1.1 Gestational diabetes 74 509 0.6 44.2 (30.3–58.1)

Obstetric ultrasound 0.8 2 Hypertension - all* 1,613 13,248 16.0 23.6 (19.0–28.1) Hypertension - Chest X-ray 0.7 1,605 13,174 15.9 23.5 (18.9–28.2) cardiovascular* Hypertension in Electrolytes, urea & creatinine* 0.7 8 74 0.1 24.3 (4.4–44.3) pregnancy Urine pregnancy test 0.7 3 Lipid disorder 938 8,004 9.6 23.1 (17.1–29.1) Medical examination - 4 538 5,129 6.2 54.2 (44.7–63.7) Hepatitis serology 0.6 pregnancy* Upper respiratory tract 0 2 4 6 8 10 12 14 16 18 20 22 5 475 3,793 4.6 5.2 (3.8–6.6) infection Rate per 100 encounters 6 Medical examination* 313 3,371 4.1 44.9 (36.2–53.6) 7 Fever 213 2,311 2.8 20.5 (15.2–25.9) * Comprise multiple ICPC-2 codes (see Appendix 4) 8 Urinary tract infection* 187 2,294 2.8 61.5 (52.6–70.5) 9 Pregnancy 101 1,264 1.5 73.3 (62.3–84.2) 10.4 DIAGNOSES WITH INVESTIGATIONS ORDERED 10 Blood test 56 1,204 1.5 96.8 (93.1–100.0) Table 10.4.1 reports the most common diagnoses for which investigations were ordered in primary care * Comprise multiple ICPC-2 codes (see Appendix 4) in 2014.

• The top 10 diagnoses for which investigations were most frequently ordered accounted for 73.2% of REFERENCE all diagnoses accompanied by tests. • Diabetes accounted for a quarter (24.3%) of the diagnoses with at least one investigation ordered. 1. Best tests? The general principles of laboratory investigations in primary care [Internet]. Dunedin This corresponds with another finding in NMCS 2014 that glucose and/or glucose tolerance test (New Zealand): Best Practice Advocacy Centre New Zealand; 2013 Feb [cited 2015 May 7];p.3-9. was the most frequently ordered investigation in primary care (see Section 10.2). Available from: • The second most common diagnosis for which investigations were ordered was hypertension, which http://www.bpac.org.nz/BT/2013/February/docs/best_tests_feb2013_general_principles_pages_4- amounted to 16.0% of all diagnoses accompanied by tests, followed by lipid disorder at 9.6%. 11.pdf • Together, the three aforementioned chronic diseases represented half (49.9%) of all diagnoses for which investigations were ordered, a finding which could be attributed to the high burden of the three metabolic syndrome-related conditions in primary care (see Chapter 8).

100 National Medical Care Statistics 2014

Figure 10.3.2: Top 10 investigations ordered in private clinics in 2014 Table 10.4.1: Top 10 diagnoses for which investigations were most frequently ordered in primary care clinics in 2014

Blood test 1.1 Gestational diabetes 74 509 0.6 44.2 (30.3–58.1)

Chapter 10 : Investigations 101

CHAPTER eleven Advice/Counselling and Procedures CHAPTER 11: ADVICE/COUNSELLING AND PROCEDURES 11.2 TYPES OF ADVICE/COUNSELLING

The different types of advice/counselling provided in primary care clinics are shown in Table 11.2.1. In this chapter, advice/counselling and procedures provided to patients in primary care clinics are • About one-third (32.7%) of advice and counselling provided in primary care clinics were general reported. Advice or counselling captured in NMCS 2014 refers to any health education, advice advice/counselling. pertaining to the presenting problem, or counselling rendered by healthcare providers at the time of • Advices on nutrition/weight (21.7%) and lifestyle advices (18.5 %) were the second and third most presentation to bring about effective behavioural changes in patients and enhance their wellbeing. common advice/counselling given, respectively. Similarly, procedures include any administrative, therapeutic or rehabilitative procedures performed during the encounters and recorded by the providers. Note that the classification of advice/counselling and procedures followed an approach which differs from that used in NMCS 2012. Table 11.2.1: Types of advice and counselling provided in primary care clinics in 2014

Percent of Rate per 100 Rate per 100 11.1 NUMBER OF ADVICE/COUNSELLING AND PROCEDURES Unweighted Weighted advice and encounters diagnoses Advice/counselling count count counselling (95% CI) (95%CI) Out of the 325,818 encounters recorded, 24.5% were managed with at least one form of (n = 111,707) (n = 325,818) (n = 436,743) advice/counselling (Table 11.1.1). A higher frequency of advice and counselling was reported in the Advice/counselling; 3,457 36,524 32.7 11.2 (9.4–13.1) 8.4 (7.1–9.6) public sector (37.5% of public clinic encounters), more than double the frequency in private clinics NEC* (15.6%). Advice/counselling; 2,666 24,269 21.7 7.4 (6.2–8.7) 5.6 (4.6–6.5) nutrition/weight* Table 11.1.1: Number of encounters managed with advice and counselling in primary care Advice/counselling; 1,958 20,642 18.5 6.3 (4.9–7.8) 4.7 (3.7–5.7) clinics in 2014 lifestyle Advice/counselling; 983 9,269 8.3 2.8 (2.2–3.5) 2.1 (1.6–2.6) Unweighted Percent of encounters treatment* Sector Weighted count count (95% CI) Advice/counselling; 502 4,929 4.4 1.5 (1.1–1.9) 1.1 (0.9–1.4) medication* Overall (n = 325,818) 7,993 79,770 24.5 (21.6–27.4) Advice/counselling; 394 4,286 3.8 1.3 (0.9–1.7) 1.0 (0.7–1.3) Public (n = 131,624) 6,169 49,394 37.5 (32.4–42.6) exercise Advice/counselling; Private (n = 194,194) 1,824 30,376 15.6 (13.1–18.2) 285 3,193 2.9 1.0 (0.7–1.3) 0.7 (0.5–1.0) health/body* Advice/counselling; 328 2,853 2.6 0.9 (0.6–1.2) 0.7 (0.4–0.9) Table 11.1.2 shows the percentage of encounters that had some procedures performed at the time of pregnancy* visit. In private clinics, 8.2% of patients underwent at least one procedure during the visit, compared to Advice/counselling; 109 1,240 1.1 0.4 (0.2–0.5) 0.3 (0.2–0.4) 5.0% in public clinics. smoking Advice/counselling; 66 1,121 1.0 0.3 (0.1–0.6) 0.3 (0.1–0.4) Table 11.1.2: Number of encounters managed with procedures in primary care clinics in 2014 other* Advice/counselling; 63 858 0.8 0.3 (0.1–0.4) 0.2 (0.1–0.3) Unweighted Percent of encounters prevention* Sector Weighted count count (95% CI) Family planning* 66 632 0.6 0.2 (0.1–0.3) 0.1 (0.1–0.2) Advice/counselling; 43 498 0.4 0.2 (0.1–0.2) 0.1 (0.1–0.2) Overall (n = 325,818) 1,681 22,471 6.9 (6.1–7.7) relaxation* Public (n = 131,624) 766 6,550 5.0 (4.2–5.8) Reassurance/support 43 474 0.4 0.1 (0.1–0.2) 0.1 (0.0–0.2) Private (n = 194,194) 915 15,922 8.2 (7.0–9.4) Advice/counselling; 45 439 0.4 0.1 (0.0–0.3) 0.1 (0.0–0.2) drug abuse Advice/counselling; 10 296 0.3 0.1 (0.0–0.2) 0.1 (0.0–0.2) alcohol

104 National Medical Care Statistics 2014 CHAPTER 11: ADVICE/COUNSELLING AND PROCEDURES 11.2 TYPES OF ADVICE/COUNSELLING

Chapter 11 : Advice/Counselling and Procedures 105 Table 11.2.1 (continued): Types of advice and counselling provided in primary care clinics in Figure 11.3.1: Ten most common advice/counselling provided in public clinics in 2014 2014

Advice/counselling; NEC* 17.9 Percent of Rate per 100 Rate per 100 Unweighted Weighted advice and encounters diagnoses Advice/counselling count count counselling (95% CI) (95%CI) Advice/counselling; nutrition/weight* 11.9 (n = 111,707) (n = 325,818) (n = 436,743) Advice/counselling; lifestyle 11.2 Result 11 115 0.1 0.0 (0.0–0.1) 0.0 (0.0–0.0) test/procedure* Advice/counselling; treatment* 4.1

Observe/wait* 2 42 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0) Advice/counselling; medication* 2.7 Advice/counselling; 1 16 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0) psychological Advice/counselling; pregnancy* 1.8 Referral* 2 11 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0) Advice/counselling; exercise 1.5 Consultation with primary care 1 3 0.0 0.0 (0.0–0.0) 0.0 (0.0–0.0) Advice/counselling; health/body* 0.7 provider* Total 11,035 111,707 100.0 34.3 (30.0–38.6) 25.6 (22.8–28.4) Advice/counselling; smoking 0.4 * Comprise multiple ICPC-2 codes (see Appendix 4) Note: NEC – Not elsewhere classified. Family planning* 0.4

0 5 10 15 20 25 11.3 MOST COMMON ADVICE/COUNSELLING PROVIDED IN PUBLIC AND PRIVATE Rate per 100 encounters CLINICS *Comprise multiple ICPC-2 codes (see Appendix 4) The most common advice/counselling provided in public and private clinics are presented in Figure 11.3.1 and Figure 11.3.2, respectively. Figure 11.3.2: Ten most common advice/counselling provided in private clinics in 2014 • The top four advice/counselling provided for both public and private clinics were, in descending order of frequency, general advice and counselling, advices on nutrition/weight, lifestyle education and education on treatment. Advice/counselling; NEC* 6.7 • The rates of advice/counselling provision were evidently higher in the public sector. For instance, Advice/counselling; nutrition/weight* 4.4 general advice/counselling was provided at a rate of 17.9 per 100 encounters in public clinics, compared to 6.7 per encounters in private clinics. Advice/counselling; lifestyle 3.1 • Other advice/counselling provided in both public and private clinics included advice and counselling on medication, pregnancy, exercise, general health and smoking. Advice/counselling; treatment* 2.0

Advice/counselling; exercise 1.2

Advice/counselling; health/body* 1.2

Advice/counselling; medication* 0.7

Advice/counselling; other* 0.4

Advice/counselling; smoking 0.3

Advice/counselling; pregnancy* 0.3

0 5 10 15 20 25 Rate per 100 encounters

*Comprise multiple ICPC-2 codes (see Appendix 4)

106 National Medical Care Statistics 2014 Table 11.2.1 (continued): Types of advice and counselling provided in primary care clinics in Figure 11.3.1: Ten most common advice/counselling provided in public clinics in 2014 2014

Advice/counselling; exercise 1.2

Advice/counselling; health/body* 1.2

Advice/counselling; medication* 0.7

Advice/counselling; other* 0.4

Advice/counselling; smoking 0.3

Advice/counselling; pregnancy* 0.3

0 5 10 15 20 25 Rate per 100 encounters

*Comprise multiple ICPC-2 codes (see Appendix 4)

Chapter 11 : Advice/Counselling and Procedures 107 11.4 TYPES OF PROCEDURES 11.5 MOST COMMON PROCEDURES PERFORMED IN PUBLIC AND PRIVATE CLINICS

Table 11.4.1 shows the different types of procedures provided in primary care clinics in 2014. • In public clinics, a total of 6,550 encounters (5.0%) had at least one procedure performed. Dressing/pressure/compression/tamponade was the most frequently performed procedure, recorded • The most common procedure performed in primary care clinics was injection/infiltration, at a rate of 1.1 per 100 encounters (Figure 11.5.1). accounting for 27.9% of all procedures, followed by procedure for dressing, pressure or compression • The same procedure was performed at rate of 2.0 per 100 encounters in private clinics of wounds at 21.4%. (Figure 11.5.2), second to injection/infiltration (3.0 per 100 encounters). • Immunisation, an important measure for disease prevention, accounted for 10.4% of all procedures Immunisation was provided at similar rates in public and private clinics (0.7 versus 0.9 per performed in primary care. • 100 encounters, respectively).

Table 11.4.1: Types of procedures provided in primary care clinics in 2014 Figure 11.5.1: Ten most common procedures performed in public clinics in 2014

Rate per 100 Rate per 100 Percent of Unweighted Weighted encounters diagnoses Procedure procedures count count (95% CI) (95% CI) (n = 25,001) Dressing/pressure/compression/tamponade* 1.1 (n = 325,818) (n = 436,743)

Injection/infiltration* 419 6,977 27.9 2.1 (1.5–2.8) 1.6 (1.1–2.1) Injection/infiltration* 0.9 Dressing/pressure/ Other therapeutic medication/procedures/ minor 429 5,345 21.4 1.6 (1.4–1.9) 1.2 (1.0–1.4) 0.9 compression/tamponade* surgery* Other therapeutic Administrative procedure* 0.8 medication/procedures/ 310 3,953 15.8 1.2 (1.0–1.5) 0.9 (0.7–1.1) minor surgery* Immunisation* 0.7 Immunisation* 217 2,601 10.4 0.8 (0.6–1.0) 0.6 (0.4–0.8)

Administrative procedure* 134 1,493 6.0 0.5 (0.3–0.6) 0.3 (0.2–0.4) Medical examination complete/partial* 0.3 Excision/removal Repair/fixation - suture/cast/prosthetic device tissue/biopsy/destruction/ 79 1,122 4.5 0.3 (0.2–0.4) 0.3 (0.2–0.3) 0.3 debridement/cauterisation* (apply/remove)*

Repair/fixation - Contraception procedure* 0.2 suture/cast/prosthetic device 66 1,002 4.0 0.3 (0.2–0.4) 0.2 (0.1–0.3) (apply/remove)* Incision/drainage/flushing/aspiration/removal body fluid* 0.2 Contraception procedure* 57 724 2.9 0.2 (0.1–0.3) 0.2 (0.1–0.2) Incision/drainage/flushing/ Physical medicine/rehabilitation* 0.1 aspiration/removal body 52 722 2.9 0.2 (0.1–0.3) 0.2 (0.1–0.2) fluid* 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Medical examination Rate per 100 encounters 93 637 2.5 0.2 (0.1–0.3) 0.1 (0.1–0.2) complete/partial*

Physical 35 425 1.7 0.1 (0.1–0.2) 0.1 (0.0–0.1) *Comprise multiple ICPC-2 codes (see Appendix 4) medicine/rehabilitation* Total 1,891 25,001 100.0 7.7 (6.8–8.6) 5.7 (5.0–6.5) *Comprise multiple ICPC-2 codes (see Appendix 4)

108 National Medical Care Statistics 2014 11.4 TYPES OF PROCEDURES 11.5 MOST COMMON PROCEDURES PERFORMED IN PUBLIC AND PRIVATE CLINICS

Table 11.4.1: Types of procedures provided in primary care clinics in 2014 Figure 11.5.1: Ten most common procedures performed in public clinics in 2014

Chapter 11 : Advice/Counselling and Procedures 109 Figure 11.5.2: Ten most common procedures performed in private clinics in 2014 Table 11.6.1: Ten most common diagnoses managed with advice/counselling in primary care clinics in 2014

Percent of Injection/infiltration* 3.0 diagnoses Rate per 100 Rate per 100 Unweighted Weighted with advice encounters contacts with Rank Diagnosis count count and (95%CI) each diagnosis Dressing/pressure/compression/tamponade* 2.0 (n = 102,779) (n = 10,634) counselling (n = 325,818) (95% CI) Other therapeutic medication/procedures/ minor (n = 102,779) surgery* 1.4 1 Hypertension - all* 2,394 21,128 20.6 6.5 (5.2–7.8) 37.6 (32.6–42.6) Immunisation* 0.9 Hypertension - 2,378 20,998 20.4 6.4 (5.1–7.8) 37.5 (32.5–42.5) Excision/removal tissue/biopsy/destruction/ cardiovascular* 0.5 debridement/cauterisation* Hypertension in 16 130 0.1 0.0 (0.0–0.1) 42.5 (20.4–64.7) Repair/fixation - suture/cast/prosthetic device pregnancy (apply/remove)* 0.3 2 Diabetes - all* 2,014 19,018 18.5 5.8 (4.3–7.4) 52.0 (45.1–58.9) Incision/drainage/flushing/aspiration/removal body fluid* 0.3 Diabetes - non- 1,927 18,282 17.8 5.6 (4.1–7.1) 51.6 (44.5–58.6) gestational* Administrative procedure* 0.2 Gestational diabetes 87 737 0.7 0.2 (0.1–0.3) 64.0 (49.8–78.2)

Contraception procedure* 0.2 3 Lipid disorder 1,562 14,286 13.9 4.4 (3.2–5.6) 41.2 (34.6–47.8)

Medical examination complete/partial* 0.1 Upper respiratory tract 4 879 8,290 8.1 2.5 (2.0–3.1) 11.3 (8.9–13.7) infection 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Rate per 100 encounters 5 Asthma 183 2,537 2.5 0.8 (0.4–1.1) 27.2 (18.1–36.2)

Medical examination - 6 224 2,127 2.1 0.7 (0.4–0.9) 22.5 (14.6–30.4) pregnancy* *Comprise multiple ICPC-2 codes (see Appendix 4) 7 Gastroenteritis* 197 2,106 2.0 0.6 (0.5–0.8) 16.0 (12.0–20.1)

Stomach function 11.6 DIAGNOSES WITH ADVICE/COUNSELLING AND PROCEDURES 8 178 1,660 1.6 0.5 (0.4–0.6) 19.0 (13.9–24.1) disorder Musculoskeletal Table 11.6.1 and Table 11.6.2 list the top 10 diagnoses managed with advice/counselling and procedures, 9 158 1,623 1.6 0.5 (04–0.6) 12.0 (8.7–15.2) symptom/complaints* respectively. 10 Fever 169 1,569 1.5 0.5 (0.3–0.7) 13.9 (8.3–19.6) • The three diagnoses for which advice and counselling were provided most frequently were all chronic diseases: hypertension (20.6% of all advice/counselling provided), diabetes (18.5%) and lipid *Comprise multiple ICPC-2 codes (see Appendix 4) disorder (13.9%). Together, these three conditions accounted for over half (52.9%) of all advice/counselling given as part of patient management in primary care. • Patients with asthma, for whom nebulisation forms an important part of the treatment procedure, contributed to the largest proportion (8.5%) of all diagnoses managed with a procedure.

110 National Medical Care Statistics 2014 Figure 11.5.2: Ten most common procedures performed in private clinics in 2014 Table 11.6.1: Ten most common diagnoses managed with advice/counselling in primary care clinics in 2014

Contraception procedure* 0.2 3 Lipid disorder 1,562 14,286 13.9 4.4 (3.2–5.6) 41.2 (34.6–47.8)

Chapter 11 : Advice/Counselling and Procedures 111 Table 11.6.2: Ten most common diagnoses managed with procedures in primary care clinics in 2014

Percent of Rate per 100 Rate per 100 Unweighted Weighted diagnoses encounters contacts with Rank Diagnosis count count with (95%CI) each diagnosis (n = 1,665) (n = 21,886) procedure (n = 325,818) (95% CI) (n = 21,886)

1 Asthma 154 1,864 8.5 0.6 (0.4–0.7) 20.0 (14.5–25.4)

Musculoskeletal 2 100 1,178 5.4 0.4 (0.3–0.5) 8.7 (6.4–11.0) symptom/ complaints* Injury skin 3 76 1,177 5.4 0.4 (0.2–0.6) 80.6 (69.1–92.1) (laceration/cut) Upper respiratory tract 4 63 894 4.1 0.3 (0.2–0.4) 1.2 (0.7–1.7) infection Preventive 5 immunisations/ 46 738 3.4 0.2 (0.1–0.3) 55.2 (37.0–73.4) medications; NOS

6 Contraception, female 53 607 2.8 0.2 (0.1–0.3) 35.2 (25.1–45.3)

Dressing/pressure/ 7 29 579 2.6 0.2 (0.1–0.3) 64.9 (36.0–93.9) compress/ tamponade

8 Gastroenteritis 27 536 2.4 0.2 (0.0–0.3) 4.1 (1.0–7.2)

9 Skin infections 42 534 2.4 0.2 (0.1–0.2) 28.5 (18.8–38.2)

10 Trauma/injury 39 466 2.1 0.1 (0.1–0.2) 31.3 (20.0–42.7)

*Comprise multiple ICPC-2 codes (see Appendix 4)

112 National Medical Care Statistics 2014 Table 11.6.2: Ten most common diagnoses managed with procedures in primary care clinics in 2014

1 Asthma 154 1,864 8.5 0.6 (0.4–0.7) 20.0 (14.5–25.4)

6 Contraception, female 53 607 2.8 0.2 (0.1–0.3) 35.2 (25.1–45.3)

Dressing/pressure/ 7 29 579 2.6 0.2 (0.1–0.3) 64.9 (36.0–93.9) compress/ tamponade

8 Gastroenteritis 27 536 2.4 0.2 (0.0–0.3) 4.1 (1.0–7.2)

9 Skin infections 42 534 2.4 0.2 (0.1–0.2) 28.5 (18.8–38.2)

10 Trauma/injury 39 466 2.1 0.1 (0.1–0.2) 31.3 (20.0–42.7) *Comprise multiple ICPC-2 codes (see Appendix 4) CHAPTER twelve Follow-Ups and Referrals

CHAPTER 12: FOLLOW-UPS AND REFERRALS 12.2 TYPES OF REFERRALS

Referrals captured in NMCS 2014 included referrals within the primary care sphere (which included Depending on the diagnosis and patient needs, primary healthcare providers may schedule follow-up referrals to family medicine specialists, non-specialist doctors, assistant medical officers, maternal and appointments for patients or refer them to other healthcare providers or services. These visit child health services, quit smoking clinics and diabetes medical therapy adherence clinics), those to dispositions (follow-ups and referrals) and their related diagnoses were documented in NMCS 2014 and medical specialists other than family medicine specialists, allied health services, hospitals, and other are reported here. Note that the classification of follow-ups and referrals followed a different approach services (which included social welfare services for the public sector and diagnostic imaging services for than that used in NMCS 2012. the private sector). Table 12.2.1 shows the distribution of referrals by type in primary care clinics in 2014.

• Out of the 11,068 patients who had at least one referral recorded, 38.2% were referred to medical 12.1 NUMBER OF FOLLOW-UPS AND REFERRALS specialists (1.3 per 100 encounters and 1.0 per 100 diagnoses). • Referrals to hospitals accounted for 27.6% of all referrals (0.9 per 100 encounters and 0.7 per Table 12.1.1 shows the visit dispositions of primary care patients in 2014. 100 diagnoses), followed by those within the primary care sphere at 17.2% (0.6 per 100 encounters • About one-third (29.7%) of the patients presenting to primary care had a referral or follow-up and 0.4 per 100 diagnoses) and those to allied health services at 13.9% (0.5 per 100 encounters and appointment. 0.4 per 100 diagnoses). • Almost half (49.2%) of all encounters in public clinics had a follow-up appointment scheduled, compared to only 12.9% in private clinics. This finding could be attributed to the fact that the bulk Table 12.2.1: Types of referrals in primary care in 2014 of the public clinic encounters were of patients with chronic diseases (see Chapter 8), who were more likely to require some form of follow-up. Percent of Rate per 100 Rate per 100 • Only 3.4% of all encounters were issued referrals. The referral rate was higher in the public sector Unweighted Weighted total encounters diagnoses Type of referrals compared to the private sector (5.8% versus 1.8%, respectively). count count referrals (95% CI) (95% CI) (n = 11,068) (n = 325,818) (n = 436,743) Table 12.1.1: Visit dispositions of primary care patients by sector in 2014 Specialist 386 4,229 38.2 1.3 (0.9–1.7) 1.0 (0.7–1.2) Hospital 278 3,052 27.6 0.9 (0.7–1.1) 0.7 (0.6–0.8) Unweighted Weighted Percent of encounters Visit disposition count count (95% CI) Primary care 237 1,900 17.2 0.6 (0.3–0.9) 0.4 (0.2–0.6) Allied health services 173 1,543 13.9 0.5 (0.3–0.7) 0.4 (0.2–0.5) Overall Other services 25 344 3.1 0.1 (0.0–0.2) 0.1 (0.0–0.1) Follow-up 8,742 89,641 27.5 (24.4–30.8) Total 1,099 11,068 100.0 3.4 (2.3–4.5) 2.5 (1.7–3.4) At least one referral 1,099 11,068 3.4 (2.8–4.0) Follow-up or at least one referral 9,425 96,853 29.7 (26.4–33.1) Table 12.2.2 and Table 12.2.3 show the distribution of referrals by type in public and private clinics, Public respectively. Follow-up 7,224 64,737 49.2 (45.1–53.3) At least one referral 919 7,681 5.8 (4.6–7.1) Public clinics Follow-up or at least one referral 7,745 68,737 52.2 (48.0–56.5) • Referrals in public clinics were most often to medical specialists (34.0% of referrals in the public Private sector), recorded at a rate of 2.0 specialist referrals per 100 encounters (1.3 referrals per 100 diagnoses). Follow-up 1,518 24,904 12.9 (10.7–15.1) • Referrals within primary care accounted for 22.4% of all referrals in public clinics, followed closely At least one referral 180 3,387 1.8 (1.4–2.2) by referrals to hospitals at 21.6% and allied health services at 19.3%. Follow-up or at least one referral 1,680 28,116 14.5 (12.3–16.7) Private clinics • Nearly half (47.7%) of all referrals recorded in the private sector were for medical specialists, while

hospital referrals constituted most of the other half (41.1% of total referrals). • Referrals to another primary healthcare centre, the third most common type of referrals made in private clinics, accounted for a smaller proportion of referrals in the private sector than in the public sector (5.2% versus 22.4%, respectively).

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CHAPTER 12: FOLLOW-UPS AND REFERRALS 12.2 TYPES OF REFERRALS

Chapter 12 : Follow-Ups and Referrals 115

Table 12.2.2: Types of referrals in public clinics in 2014 Table 12.3.1: Top 10 diagnoses for follow-up in primary care in 2014 Percent of Rate per 100 Rate per 100 Unweighted Weighted total encounters diagnoses Type of referrals Percent of count count referrals (95% CI) (95% CI) Unweighted Weighted Rate per 100 Rate per 100 diagnoses with encounters contacts with (n = 7,681) (n = 131,624) (n = 203,868) Rank Diagnosis count count follow-up (95% CI) each diagnosis (n = 13,832) (n = 137,991) (n = 325,818) (95% CI) Specialist 303 2,615 34.0 2.0 (1.3–2.7) 1.3 (0.8–1.7) (n = 137,991) Primary care 228 1,724 22.4 1.3 (0.6–2.0) 0.8 (0.4–1.3) 1 Hypertension - all 4,132 39,319 28.5 12.1 (10.0–14.2) 70.0 (64.3–75.7) Hospital 205 1,662 21.6 1.3 (0.9–1.6) 0.8 (0.6–1.0) Hypertension - Allied health services 169 1,485 19.3 1.1 (0.6–1.6) 0.7 (0.4–1.0) 4,110 39,128 28.4 12.0 (9.9–14.2) 70.0 (64.3–75.7) cardiovascular Other services 14 195 2.5 0.1 (0.0–0.3) 0.1 (0.0–0.2) Hypertension in 22 192 0.1 0.1 (0.0–0.1) 62.8 (42.7–83.0) pregnancy Total 919 7,681 100.0 5.8 (3.5–8.2) 3.8 (2.2–5.3) 2 Diabetes - all 2,842 27,869 20.2 8.6 (6.6–10.6) 76.2 (70.3–82.1)

Diabetes - non- 2,744 27,054 19.6 8.3 (6.4–10.3) 76.4 (70.3–82.4) gestational Table 12.2.3: Types of referrals in private clinics in 2014 Gestational 98 816 0.6 0.3 (0.2–0.4) 70.8 (56.9–84.8) diabetes Percent of Rate per 100 Rate per 100 3 Lipid disorder 2,656 25,589 18.5 7.9 (6.0–9.7) 73.8 (67.9–79.8) Unweighted Weighted total encounters diagnoses Type of referrals count count referrals (95% CI) (95% CI) 4 Medical examination 537 4,752 3.4 1.5 (1.0–1.9) 50.3 (40.9–59.6) (n = 3,387) (n = 194,194) (n = 232,874) - pregnancy 5 Asthma 291 3,553 2.6 1.1 (0.7–1.5) 38.2 (29.5–46.8) Specialist 83 1,614 47.7 0.8 (0.6–1.1) 0.7 (0.5–0.9)

Hospital 73 1,390 41.1 0.7 (0.5–1.0) 0.6 (0.4–0.8) 6 Upper respiratory 242 2,464 1.8 0.8 (0.6–1.0) 3.4 (2.5–4.3) tract infection Primary care 9 176 5.2 0.1 (0.0–0.2) 0.1 (0.0–0.1) 7 Medical examination 175 1,660 1.2 0.5 (0.3–0.8) 22.1 (13.0–31.3) Other services 11 149 4.4 0.1 (0.0–0.1) 0.1 (0.0–0.1) Allied health services 4 57 1.7 0.0 (0.0–0.1) 0.0 (0.0–0.1) 8 Fever 106 1,406 1.0 0.4 (0.3–0.6) 12.5 (8.5–16.6) Total 180 3,387 100.0 1.7 (1.1–2.4) 1.5 (0.9–2.0) 9 Ischaemic heart 153 1,291 0.9 0.4 (0.3–0.5) 59.8 (50.0–69.7) disease 10 Substance abuse 90 1,161 0.8 0.4 (0.0–0.7) 78.1 (57.8–98.4) 12.3 MOST FREQUENTLY FOLLOWED UP DIAGNOSES

In NMCS 2014, healthcare providers could link the scheduled follow-up appointments and the referrals reported to the diagnoses for which the appointments and referrals were made. Table 12.3.1 presents 12.4 MOST FREQUENTLY REFERRED DIAGNOSES the top 10 diagnoses most frequently followed up in primary care in 2014. . As mentioned in the previous section, the referrals were linked to the corresponding diagnoses in • The leading diagnosis for follow-up was hypertension (including hypertension in pregnancy), which NMCS 2014. Table 12.4.1 presents the top 10 diagnoses most frequently referred in primary care in accounted for more than one-quarter (28.5%) of all diagnoses with follow-up appointments in 2014. primary care. • Diabetes and hypertension were the two diagnoses for which referrals were most frequently made, • The second most frequently followed up diagnosis was diabetes, which represented 20.2% of all accounting for 11.9% and 10.2% of all diagnoses referred, respectively. diagnoses accompanied with follow-up appointments, followed by lipid disorder at 18.5%. • The third most commonly referred diagnosis was lipid disorder, representing 5.3% of all diagnoses for which referrals were made.

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Chapter 12 : Follow-Ups and Referrals 117

Table 12.4.1: Top 10 diagnoses for referral in primary care in 2014

Percent of Unweighted Weighted Rate per 100 Rate per 100 diagnoses with encounters contacts with each Rank Diagnosis count count referral (95% CI) diagnosis (n = 1,186) (n = 12,075) (n = 12,075) (n = 325,818) (95% CI) 1 Diabetes - all 155 1,432 11.9 0.4 (0.3–0.6) 3.9(2.6 –5.3) Diabetes – 122 1,200 9.9 0.4 (0.2–0.5) 3.4(2.2 –4.6) Non-gestational Gestational 33 232 1.9 0.1 (0.0–0.1) 20.2(8.0 –32.3) diabetes 2 Hypertension - all 128 1,226 10.2 0.4 (0.2–0.6) 2.2(1.1 –3.2)

Hypertension - 120 1,180 10.1 0.4 (0.2–0.6) 2.1(1.1 –3.2) cardiovascular

3 Lipid disorder 58 645 5.3 0.2 (0.1–0.3) 1.9(1.0 –2.8)

Medical examination 4 34 359 2.9 0.1 (0.1–0.2) 3.8(2.0 –5.6) - pregnancy

Musculoskeletal 5 30 333 2.7 0.1 (0.1–0.1) 2.5(1.5 –3.4) symptom/complaints

6 High risk pregnancy 41 321 2.6 0.1 (0.0–0.2) 16.9(6.6 –27.1)

7 Fever 20 319 2.6 0.1 (0.0–0.2) 2.8(0.9 –4.8)

8 Gastroenteritis 8 221 1.8 0.1 (0.0–0.2) 1.7(0.0 –4.5)

9 Viral disease 17 217 1.8 0.1 (0.0–0.1) 14.3(5.6 –23.1)

10 Injury eye 4 209 1.7 0.1 (0.0–0.2) 72.1(32.3 –100.0)

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Table 12.4.1: Top 10 diagnoses for referral in primary care in 2014

Hypertension - 120 1,180 10.1 0.4 (0.2–0.6) 2.1(1.1 –3.2) cardiovascular

3 Lipid disorder 58 645 5.3 0.2 (0.1–0.3) 1.9(1.0 –2.8)

Medical examination 4 34 359 2.9 0.1 (0.1–0.2) 3.8(2.0 –5.6) - pregnancy

Musculoskeletal 5 30 333 2.7 0.1 (0.1–0.1) 2.5(1.5 –3.4) symptom/complaints

6 High risk pregnancy 41 321 2.6 0.1 (0.0–0.2) 16.9(6.6 –27.1)

7 Fever 20 319 2.6 0.1 (0.0–0.2) 2.8(0.9 –4.8)

8 Gastroenteritis 8 221 1.8 0.1 (0.0–0.2) 1.7(0.0 –4.5)

9 Viral disease 17 217 1.8 0.1 (0.0–0.1) 14.3(5.6 –23.1) APPENDICES

10 Injury eye 4 209 1.7 0.1 (0.0–0.2) 72.1(32.3 –100.0)

APPENDIX 2: NMCS 2014 PRIMARY CARE PROVIDER’S PROFILE QUESTIONNAIRE APPENDIX 1: ADDITIONAL TABLES

Table A1.1: Top 10 reasons for encounter in public clinics in 2014

Rate per 100 Percent of Unweighted Weighted encounters Rank Reasons for encounter total RFEs count count (95% CI) (n = 252,050) (n = 131,624)

1 Hypertension - all* 4,743 41,261 16.4 31.4 (28.2–34.5) Hypertension -cardiovascular* 4,737 41,236 16.4 31.3 (28.2–34.5)

2 Diabetes - all* 3,204 29,625 11.8 22.5 (19.3–25.7) Diabetes type2 2,651 24,537 9.7 18.6 (15.4–21.9)

Diabetes - unspecified 464 4,415 1.8 3.4 (1.8–4.9)

3 Lipid disorder 2,883 24,391 9.7 18.5 (15.8–21.3) 4 Cough 2,900 23,469 9.3 17.8 (16.3–19.4) 5 Fever 2,568 21,339 8.5 16.2 (14.5–17.9) 6 Runny nose/rhinorrhoea 2,023 15,785 6.3 12.0 (10.7–13.3) Medical examination - 7 1,413 12,180 4.8 9.3 (6.9–11.6) pregnancy* Musculoskeletal 8 676 5,728 2.3 4.4 (3.3–5.4) symptom/complaints* 9 Medical examination* 539 5,561 2.2 4.2 (3.1–5.4) 10 Blood test endo/metabolic 530 5,141 2.0 3.9 (2.5–5.3) *Comprise multiple ICPC-2 codes (see Appendix 4)

Table A1.2: Top 10 reasons for encounter in private clinics 2014

Rate per 100 Percent of Weighted encounters Rank Reasons for encounter Unweighted total RFEs count (95% CI) count (n = 345,513) (n = 194,194)

1 Fever 3,503 54,903 15.9 28.3 (26.6–29.9) 2 Cough 3,122 51,437 14.9 26.5 (24.9–28.1) 3 Runny nose/rhinorrhoea 2,305 37,684 10.9 19.4 (17.8–21.1) Musculoskeletal 4 857 14,489 4.2 7.5 (6.4–8.6) symptom/complaints* 5 Abdominal pain* 723 12,466 3.6 6.4 (5.7–7.2) 6 Hypertension - cardiovascular* 781 12,259 3.6 6.3 (5.5–7.2) 7 Pain/sore throat* 707 12,033 3.5 6.2 (4.9–7.5) 8 Diarrhoea 743 11,999 3.5 6.2 (5.6–6.8) 9 Headache - all* 646 11,948 3.5 6.2 (5.4–6.9) Headache 612 11,120 3.2 5.7 (5.0–6.4)

10 Back problems* 491 8,668 2.5 4.5 (3.8–5.1) *Comprise multiple ICPC-2 codes (see Appendix 4)

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APPENDIX 2: NMCS 2014 PRIMARY CARE PROVIDER’S PROFILE QUESTIONNAIRE APPENDIX 1: ADDITIONAL TABLES

Table A1.1: Top 10 reasons for encounter in public clinics in 2014

Rate per 100 Percent of Unweighted Weighted encounters Rank Reasons for encounter total RFEs count count (95% CI) (n = 252,050) (n = 131,624)

1 Hypertension - all* 4,743 41,261 16.4 31.4 (28.2–34.5) Hypertension -cardiovascular* 4,737 41,236 16.4 31.3 (28.2–34.5)

2 Diabetes - all* 3,204 29,625 11.8 22.5 (19.3–25.7) Diabetes type2 2,651 24,537 9.7 18.6 (15.4–21.9)

Diabetes - unspecified 464 4,415 1.8 3.4 (1.8–4.9)

Table A1.2: Top 10 reasons for encounter in private clinics 2014

Rate per 100 Percent of Weighted encounters Rank Reasons for encounter Unweighted total RFEs count (95% CI) count (n = 345,513) (n = 194,194)

10 Back problems* 491 8,668 2.5 4.5 (3.8–5.1) *Comprise multiple ICPC-2 codes (see Appendix 4)

Appendices 121

APPENDIX 3: NMCS 2014 SURVEY FORM APPENDIX 4: ICPC-2 AND ICPC-2 PLUS GROUPS

Reasons for Encounter and Diagnoses

ICPC-2 Group ICPC-2 Description PLUS Abdominal pain D01 Abdominal pain/cramps, general D02 Abdominal pain, epigastric D06 Abdominal pain, localised, other Arthritis – all L88 Rheumatoid/seropositive arthritis L89 Osteoarthrosis of hip L90 Osteoarthrosis of knee L91 Osteoarthrosis, other Anaemia B78 Hereditary haemolytic anaemia B80 Iron deficiency anaemia B82 Anaemia other/unspecified Back problems L02 Back symptom/complaint L03 Low back symptom/complaint L84 Back syndrome without radiating pain L86 Back syndrome with radiating pain Conjunctivitis F70 Conjunctivitis, infectious F71 Conjunctivitis, allergic Contraception – female W11 Contraception, oral W12 Contraception, intrauterine W14 Contraception female, other Dermatitis S86 Dermatitis, seborrhoeic S87 Dermatitis, atopic eczema S88 Dermatitis, contact/allergic Diabetes – non-gestational T89 Diabetes, insulin dependent T90 Diabetes, non-insulin dependent N94012 Neuropathy; diabetic U88011 Nephropathy; diabetic Dressing/pressure/ A56001 Dressing compress/tamponade L56003 Bandage/strap S56004 Dressing; wound Gastroenteritis D70 Gastrointestinal infection D73 Gastroenteritis, presumed infection Headache – all N01 Headache N89 Migraine N90 Cluster headache N95 Tension headache

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APPENDIX 3: NMCS 2014 SURVEY FORM APPENDIX 4: ICPC-2 AND ICPC-2 PLUS GROUPS

Reasons for Encounter and Diagnoses

Appendices 123

Reasons for Encounter and Diagnoses (continued) Reasons for Encounter and Diagnoses (continued)

ICPC-2 ICPC-2 Group ICPC-2 Description Group ICPC-2 Description PLUS PLUS High risk pregnancy W81008 Proteinuria in pregnancy Musculoskeletal L01 Neck symptom/complaint W84014 RH; iso-immunisation symptom/complaints L04 Chest symptom/complaint W84020 Anaemia in pregnancy L05 Flank/axilla symptom/complaint Hypertension – all K86 Hypertension, uncomplicated L07 Jaw symptom/complaint K87 Hypertension, complicated L08 Shoulder symptom/complaint W81003 Hypertension in pregnancy L09 Arm symptom/complaint Hypertension – K86 Hypertension, uncomplicated L10 Elbow symptom/complaint cardiovascular K87 Hypertension, complicated L11 Wrist symptom/complaint Injury skin – all S14 Burn/scald L12 Hand/finger symptom/complaint S17 Abrasion/scratch/blister L13 Hip symptom/complaint S18 Laceration/cut L14 Leg/thigh symptom/complaint S19 Skin injury, other L15 Knee symptom/complaint Ischaemic heart disease K74 Ischaemic heart disease with angina L16 Ankle symptom/complaint K75 Acute myocardial infarction L17 Foot/toe symptom/complaint K76 Ischaemic heart disease without angina L18 Muscle pain Medical examination A30 Medical examination/health evaluation complete L19 Muscle symptom/complaint NOS A31 Medical examination/health evaluation partial L20 Joint symptom/complaint NOS D31 Medical examination/health evaluation partial L28 Limited function/disability (limb) digestive L29 Musculoskeletal symptom/complaint other P31 Medical examination/health evaluation partial S19004 Injury; soft tissue psychological Osteoarthritis L84004 Osteoarthritis; spine R31 Medical examination/health evaluation partial respiratory L89001 Osteoarthritis; hip S31 Medical examination/health evaluation partial skin L90001 Osteoarthritis; knee A98001 Health maintenance L91003 Osteoarthritis Medical examination – W30 Medical examination/health evaluation complete L91015 Osteoarthritis; wrist pregnancy pregnancy L92007 Osteoarthritis; shoulder W41 Diagnostic radiology/imaging pregnancy Pain/sore throat R21004 Pain; throat W31010 Antenatal care R21005 Sore throat Menstrual problems X02 Menstrual pain Rash S06 Rash localised X03 Intermenstrual pain S07 Rash generalised X05 Menstruation absent/scanty S89 Diaper rash X06 Menstruation excessive S92004 Rash; heat X07 Menstruation irregular/frequent S92006 Prickly heat X08 Intermenstrual bleeding S92008 Rash; sweat X10 Postponement of menstruation Respiratory infection R81 Pneumonia X89 Premenstrual tension syndrome R82 Pleurisy/pleural effusion R83 Respiratory infection, other

124 National Medical Care Statistics 2014

Reasons for Encounter and Diagnoses (continued) Reasons for Encounter and Diagnoses (continued)

Appendices 125

Reasons for Encounter and Diagnoses (continued) Investigations, Advice/Counselling and Procedures

ICPC-2 ICPC-2 Group ICPC-2 Description Group ICPC-2 Description PLUS PLUS Sprain/strain L77 Sprain/strain of ankle Administrative procedure A62 Administrative procedure L78 Sprain/strain of knee A63 Follow-up encounter; unspecified L79 Sprain/strain of joint NOS F62 Administrative procedure; eye L83 Neck syndrome K62 Administrative procedure; cardiovascular Symptom/complaint eye F01 Eye pain R62 Administrative procedure; respiratory F02 Red eye S62 Administrative procedure; skin F03 Eye discharge T62 Administrative procedure; endo/metabolic F04 Visual floaters/spots U62 Administrative procedure; urinary F13 Eye sensation abnormal W62 Administrative procedure; pregnancy F15 Eye appearance abnormal Y62 Administrative procedure; genital (male) F16 Eyelid symptom/complaint Z11 Compliance/being ill problem F29 Eye symptom/complaint, other Advice/counselling; A45005 Advice/education; health Urinary problem U01 Dysuria/painful urination health/body A45009 Health promotion U02 Urinary frequency/urgency A45026 Advice/education; hygiene U04 Incontinence urine D45004 Advice/education; oral health U05 Urinary problems, other L45 Observe/health education/advice/diet U06 Haematuria musculoskeletal U07 Urine symptom/complaint, other S45005 Advice/education; sun protection U08 Urinary retention Advice/counselling; A45015 Advice/education; medication medication U13 Bladder symptom/complaint, other A48 Clarification/discussion on RFE/demand Urinary tract infection U70 Pyelonephritis/pyelitis Advice/counselling; NEC A45 Observe/health education/advice/diet U71 Cystitis/urinary infection, other B45 Observe/health education/advice/diet; blood Note: NOS – Not otherwise specified. D45 Observe/health education/advice/diet; digestive F45 Observe/health education/advice/diet; eye H45 Observe/health education/advice/diet; ear K45 Observe/health education/advice/diet; cardiovascular L45002 Advice/education; musculoskeletal N45 Observe/health education/advice/diet; neurological P45001 Advice/education; psychological R45 Observe/health education/advice/diet; respiratory S45 Observe/health education/advice/diet; skin T45 Observe/health education/advice/diet; endocrine/metabolic U45 Observe/health education/advice/diet; urology

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Reasons for Encounter and Diagnoses (continued) Investigations, Advice/Counselling and Procedures

Appendices 127

Investigations, Advice/Counselling and Procedures (continued) Investigations, Advice/Counselling and Procedures (continued)

ICPC-2 ICPC-2 Group ICPC-2 Description Group ICPC-2 Description PLUS PLUS

Advice/counselling; NEC W45 Observe/health education/advice/diet; reproductive Blood pressure K31001 Check-up; blood pressure (continued) (female) K39 Physical function test; cardiovascular X45 Observe/health education/advice/diet; genital Blood; other test A33042 Lymphocyte type & count test (female) A34035 Blood film test Y45 Observe/health education/advice/diet; genital (male) A34036 Thick blood film test L58001 Counselling; problem; musculoskeletal B33 Microbiological/immunological test; blood/lymph Advice/counselling; A45006 Advice/education; diet B34 Blood test; blood/lymph nutrition/weight T45005 Advice/education; nutritional Chemistry; other test A33 Microbiological/immunological test T45007 Advice/education; weight management A34 Blood test T45010 Weight management A35 Urine test T58 Counselling; weight management T34 Blood test; endocrine/metabolic Advice/counselling; other A45014 Advice/education; travel D34002 Alanine aminotransferase test A45022 Advice; care of sick 3rd person Contraception procedure W11 Contraception, oral A45036 Advice/education; sex W12 Contraception, intrauterine A45037 Advice/education; work practice W14 Contraception female, other A58016 Consult; family member Dressing/pressure/ A56 Dressing/pressure/compress/tamponade Z45 Observe/health education/advice/diet; social compression/tamponade F56 Dressing/pressure/compress/tamponade; eye Z58 Therapeutic counselling/listening; social S56 Dressing/pressure/compress/tamponade; skin Advice/counselling; W42 Electrical tracing; pregnancy W56 Dressing/pressure/compress/tamponade; pregnancy pregnancy W45009 Advice/education; pregnancy Electrolytes, urea & A34008 Test; electrolytes W45010 Advice/education; breastfeeding creatinine A34014 Test; potassium Advice/counselling; A45025 Advice/education; immunisation U34 Blood test; urinary prevention A58 Therapeutic counselling/listening U38 Other laboratory test NEC; urinary X45004 Advice/education; breast self-exam Excision/removal A52 Excise/remove/biopsy/destruct/debridement/ X45007 Advice/education; Pap smear tissue/biopsy/ destruction/ cauterise Z45005 Advice/education; environment debridement/ cauterisation F52 Excise/remove/biopsy/destruct/debridement/ Advice/counselling; P45007 Advice/education; relaxation cauterise; eye relaxation P58 Therapeutic counselling/listening; psychological H52 Excise/remove/biopsy/destruct/debridement/ Advice/counselling; A45016 Advice/education; treatment cauterise; ear treatment A45020 Advice/education; rest/fluids L52 Excise/remove/biopsy/destruct/debridement/ cauterise; musculoskeletal A45035 Advice/education; isolate R52 Excise/remove/biopsy/destruct/debridement/ A45039 Advice/education; fluid intake cauterise; respiratory L45004 Advice/education; RICE S19 Skin injury, other P45 Observe/health education/advice/diet; psychological S52 Excise/remove/biopsy/destruct/debridement/ T45 Observe/health education/advice/diet; cauterise; skin endocrine/metabolic X52 Excise/remove/biopsy/destruct/debridement/ cauterise; genital (female) Y52 Excise/remove/biopsy/destruct/debridement/ cauterise; genital (male)

128 National Medical Care Statistics 2014

Investigations, Advice/Counselling and Procedures (continued) Investigations, Advice/Counselling and Procedures (continued)

ICPC-2 ICPC-2 Group ICPC-2 Description Group ICPC-2 Description PLUS PLUS

Appendices 129

Investigations, Advice/Counselling and Procedures (continued) Investigations, Advice/Counselling and Procedures (continued)

ICPC-2 ICPC-2 Group ICPC-2 Description Group ICPC-2 Description PLUS PLUS Family planning W45006 Advice/education; preconceptual Injection/infiltration U50 Medication/prescription/renewal/inject; urinary W45007 Advice/education; contraception (female) (continued) W50 Medication/prescription/renewal/inject; pregnancy W58013 Counselling; family planning (female) Y50 Medication/prescription/renewal/inject; genital Y45006 Advice/education; family plan (male) (male) Immunisation A44 Preventive immunisations/medications Liver function test D34 Blood test; digestive A55004 Inject; childhood immunisation A34004 Albumin test A55005 Inject; immunisation Medical examination A30 Medical examination/health evaluation complete complete/partial D44 Preventive immunisations/medications; digestive A31 Medical examination/health evaluation partial N44 Preventive immunisations/medications; neurological D31 Medical examination/health evaluation partial; digestive R44 Preventive immunisations/medications; respiratory F30 Medical examination/health evaluation complete; R55 Local injection/infiltration; respiratory eye Incision/drainage/ A51 Incision & drainage/flush/aspiration F31 Medical examination/health evaluation partial; eye flushing/aspiration/ removal F51 Incision & drainage/flush/aspiration; eye body fluid K31 Medical examination/health evaluation partial; H51 Incision & drainage/flush/aspiration; ear cardiovascular S51 Incision & drainage/flush/aspiration; skin W30 Medical examination/health evaluation complete; Injection/infiltration A50 Medication/prescription/renewal/inject pregnancy A55 Local injection/infiltration W31 Medical examination/health evaluation partial; pregnancy B50 Medication/prescription/renewal/inject; blood X31 Medical examination/health evaluation partial; D50 Medication/prescription/renewal/inject; digestive genital (female) F50 Medication/prescription/renewal/inject; eye Observe/wait T45001 Observe/wait; endocrine/metabolic H50 Medication/prescription/renewal/inject; ear W45003 Observe/wait; reproductive K50 Medication/prescription/renewal/inject; Other diagnostic procedure; A43001 Diagnostic procedures cardiovascular NEC F43001 Diagnostic procedure; eye K55 Local injection/infiltration; cardiovascular W43002 Diagnostic procedure; reproductive system L50 Medication/prescription/renewal/inject; musculoskeletal X43001 Diagnostic procedure; genital system L55 Local injection/infiltration; musculoskeletal H43001 Diagnostic procedure; ear N50 Medication/prescription/renewal/inject; neurological Other therapeutic A50010 Medication; given medication/ N55 Local injection/infiltration; neurological A53 Instrument/catheter/intubate/dilate procedures/minor surgery P50 Medication/prescription/renewal/inject; psychological A59 Other therapeutic procedures/minor surgery; NEC R50 Medication/prescription/renewal/inject; respiratory B59 Other therapeutic procedures/minor surgery NEC; blood S50 Medication/prescription/renewal/inject; skin D50007 Treatment; worms T50 Medication/prescription/renewal/inject; endocrine/metabolic D53 Instrument/catheter/intubate/dilate; digestive F59 Other therapeutic procedures/minor surgery; eye

130 National Medical Care Statistics 2014

Investigations, Advice/Counselling and Procedures (continued) Investigations, Advice/Counselling and Procedures (continued)

Appendices 131

Investigations, Advice/Counselling and Procedures (continued) APPENDIX 5: PARTICIPANTS OF NMCS 2014

ICPC-2 Group ICPC-2 Description Public clinics PLUS

Other therapeutic H59 Other therapeutic procedures/minor surgery; ear Public Clinics (Johor) medication/ L59 Other therapeutic procedures/minor surgery; 1 Klinik Kesihatan Bukit Besar 6 Klinik Kesihatan Mahmoodiah procedures/minor surgery musculoskeletal (continued) 2 Klinik Kesihatan Jalan Mengkibol 7 Klinik Kesihatan Majidee R59 Other therapeutic procedures/minor surgery; respiratory 3 Klinik Kesihatan Kahang Batu 22 8 Klinik Kesihatan Pasir Gudang S59 Other therapeutic procedures/minor surgery; skin 4 Klinik Kesihatan Kulai Besar 9 Klinik Kesihatan Sungai Rengit

U53 Instrument/catheter/intubate/dilate; urinary 5 Klinik Kesihatan Larkin 10 Klinik Kesihatan Tenggaroh U59 Other therapeutic procedures/minor surgery; urinary W59 Other therapeutic procedures/minor surgery; pregnancy Public Clinics (Kedah) Physical medicine/ A57 Physical medicine/rehabilitation 1 Klinik Kesihatan Ayer Hangat 5 Klinik Kesihatan Tunjang rehabilitation L57 Physical medicine/rehabilitation; musculoskeletal Referral A68 Other referral NEC 2 Klinik Kesihatan Bandar Baharu 6 Klinik Kesihatan Jalan Putra K68 Other referral NEC; cardiovascular 3 Klinik Kesihatan Guar Chempedak 7 Klinik Kesihatan Alor Janggus Repair/fixation – L54 Repair/fix – suture/cast/prosthetic device; 4 Klinik Kesihatan Malau suture/cast/prosthetic device musculoskeletal (apply/remove) S54 Repair/fix – suture/cast/prosthetic device; skin T54 Repair/fix – suture/cast/prosthetic device; Public Clinics (Negeri Sembilan) endo/metabolic 1 Klinik Kesihatan Bukit Pelanduk 4 Klinik Kesihatan Pasir Panjang Result test/procedure A60 Result test/procedures B60 Result test/procedures; blood/lymph 2 Klinik Kesihatan Lenggeng 5 Klinik Kesihatan Terachi K60 Result test/procedures; cardiovascular 3 Klinik Kesihatan Palong 9,10,11 N60 Result test/procedures; neurological Tuberculosis R32001 Mantoux test R32002 Tuberculin test Public Clinics (Terengganu) R33001 Culture; tuberculosis 1 Klinik Kesihatan Jabi 4 Klinik Kesihatan Permaisuri

Urine test A35001 Urine test 2 Klinik Kesihatan Kemasek 5 Klinik Kesihatan Jabi A35002 Urinalysis 3 Klinik Kesihatan Kuala Kemaman Note: NEC – Not elsewhere classified; RICE – rest, ice, compression, elevation.

Public Clinics (Perak)

1 Klinik Kesihatan Bidor 6 Klinik Kesihatan Tronoh 2 Klinik Kesihatan Buntong 7 Klinik Kesihatan Jalan Baru

3 Klinik Kesihatan Gunung Semanggol 8 Klinik Kesihatan Sitiawan

4 Klinik Kesihatan Karai 9 Klinik Kesihatan Trolak Selatan

5 Klinik Kesihatan Lawin 10 Klinik Kesihatan Kedai Empat

132 National Medical Care Statistics 2014

Investigations, Advice/Counselling and Procedures (continued) APPENDIX 5: PARTICIPANTS OF NMCS 2014

ICPC-2 Group ICPC-2 Description Public clinics PLUS

Public Clinics (Perak)

1 Klinik Kesihatan Bidor 6 Klinik Kesihatan Tronoh 2 Klinik Kesihatan Buntong 7 Klinik Kesihatan Jalan Baru

3 Klinik Kesihatan Gunung Semanggol 8 Klinik Kesihatan Sitiawan

4 Klinik Kesihatan Karai 9 Klinik Kesihatan Trolak Selatan

5 Klinik Kesihatan Lawin 10 Klinik Kesihatan Kedai Empat

Appendices 133

Public Clinics (Melaka) Public Clinics (Perlis)

1 Klinik Kesihatan Ayer Keroh 13 Klinik Kesihatan Merlimau 1 Klinik Kesihatan Arau 5 Klinik Kesihatan Kuala Perlis

2 Klinik Kesihatan Ayer Molek 14 Klinik Kesihatan Padang Sebang 2 Klinik Kesihatan Beseri 6 Klinik Kesihatan Padang Besar

3 Klinik Kesihatan Bukit Rambai 15 Klinik Kesihatan Peringgit 3 Klinik Kesihatan Kg. Gial 7 Klinik Kesihatan Simpang Empat

4 Klinik Kesihatan Cheng 16 Klinik Kesihatan Selandar 4 Klinik Kesihatan Kangar

5 Klinik Kesihatan Durian Tunggal 17 Klinik Kesihatan Simpang Empat

6 Klinik Kesihatan Hutan Percha 18 Klinik Kesihatan Simpang Bekoh Public Clinics (Pulau Pinang) 7 Klinik Kesihatan Jalan Gereja 19 Klinik Kesihatan Sungai Rambai 1 Klinik Kesihatan Kubang Semang 4 Klinik Kesihatan Nibong Tebal 8 Klinik Kesihatan Kemendor 20 Klinik Kesihatan Sungai Udang 2 Klinik Kesihatan Bandar Baru Air Itam 5 Klinik Kesihatan Prai 9 Klinik Kesihatan Klebang Besar 21 Klinik Kesihatan Tanjung Kling 3 Klinik Kesihatan Mak Mandin 10 Klinik Kesihatan Kuala Sungai Baru 22 Klinik Kesihatan Ujong Pasir

11 Klinik Kesihatan Lubok China 23 Klinik Kesihatan Umbai

12 Klinik Kesihatan Macap Baru Public Clinics (Sabah)

1 Klinik Kesihatan Kemabong 5 Klinik Kesihatan Nangoh Rumedi

2 Klinik Kesihatan Menggatal 6 Klinik Kesihatan Taginambur Public Clinics (Kelantan) 3 Klinik Kesihatan Menumbok 7 Klinik Kesihatan Tenghilan 1 Klinik Kesihatan Bandar Gua Musang 5 Klinik Kesihatan Pengkalan Kubor 4 Klinik Kesihatan Nabawan 2 Klinik Kesihatan Gual Ipoh 6 Klinik Kesihatan Peringat

3 Klinik Kesihatan Kuala Betis 7 Klinik Kesihatan Tendong

4 Klinik Kesihatan Pengkalan Chepa Public Clinics (Sarawak)

1 Klinik Kesihatan Bako 6 Klinik Kesihatan Kota Samarahan

2 Klinik Kesihatan Bario 7 Klinik Kesihatan Kota Sentosa Public Clinics (Pahang) 3 Klinik Kesihatan Debak 8 Klinik Kesihatan Pusa 1 Klinik Kesihatan Bandar Jengka 4 Klinik Kesihatan Kuala Tahan 4 Klinik Kesihatan Jalan Oya 9 Klinik Kesihatan Sadong Jaya 2 Klinik Kesihatan Chini 5 Klinik Kesihatan Pos Betau 5 Klinik Kesihatan Kabong 10 Klinik Kesihatan Sematan 3 Klinik Kesihatan Dong 6 Klinik Kesihatan Tanjung Gemok

Public Clinics (WP Kuala Lumpur) Public Clinics (Selangor) 1 Klinik Kesihatan Bandar Tun Razak 7 Klinik Kesihatan Kampung Pandan 1 Klinik Kesihatan AU2 8 Klinik Kesihatan Seksyen 19 Shah Alam 2 Klinik Kesihatan Batu 8 Klinik Kesihatan Petaling Bahagia 2 Klinik Kesihatan Bukit Kuda 9 Klinik Kesihatan Selayang Baru 3 Klinik Kesihatan Cheras 9 Klinik Kesihatan Sentul 3 Klinik Kesihatan Gombak Utara (Bt. 8) 10 Klinik Kesihatan Semenyih 4 Klinik Kesihatan Cheras Baru 10 Klinik Kesihatan Setapak 4 Klinik Kesihatan Kalumpang 11 Klinik Kesihatan Sijangkang 5 Klinik Kesihatan Dato Keramat 11 Klinik Kesihatan Sungai Besi 5 Klinik Kesihatan Klang 12 Klinik Kesihatan Sungai Air Tawar 6 Klinik Kesihatan Jinjang 12 Klinik Kesihatan Tanglin 6 Klinik Kesihatan Pulau Ketam 13 Klinik Kesihatan Sungai Sekamat

7 Klinik Kesihatan Rantau Panjang 14 Klinik Kesihatan Tanjung Karang

134 National Medical Care Statistics 2014

Public Clinics (Melaka) Public Clinics (Perlis)

1 Klinik Kesihatan Ayer Keroh 13 Klinik Kesihatan Merlimau 1 Klinik Kesihatan Arau 5 Klinik Kesihatan Kuala Perlis

2 Klinik Kesihatan Ayer Molek 14 Klinik Kesihatan Padang Sebang 2 Klinik Kesihatan Beseri 6 Klinik Kesihatan Padang Besar

3 Klinik Kesihatan Bukit Rambai 15 Klinik Kesihatan Peringgit 3 Klinik Kesihatan Kg. Gial 7 Klinik Kesihatan Simpang Empat

4 Klinik Kesihatan Cheng 16 Klinik Kesihatan Selandar 4 Klinik Kesihatan Kangar

5 Klinik Kesihatan Durian Tunggal 17 Klinik Kesihatan Simpang Empat

11 Klinik Kesihatan Lubok China 23 Klinik Kesihatan Umbai

12 Klinik Kesihatan Macap Baru Public Clinics (Sabah)

1 Klinik Kesihatan Kemabong 5 Klinik Kesihatan Nangoh Rumedi

3 Klinik Kesihatan Kuala Betis 7 Klinik Kesihatan Tendong

4 Klinik Kesihatan Pengkalan Chepa Public Clinics (Sarawak)

1 Klinik Kesihatan Bako 6 Klinik Kesihatan Kota Samarahan

7 Klinik Kesihatan Rantau Panjang 14 Klinik Kesihatan Tanjung Karang

Appendices 135

Private clinics Private Clinics (Kelantan)

1 Klinik Ariffin 12 Klinik Goh Private Clinics (Johor) 2 Klinik Azhar 13 Klinik Ikhtiar Kota Jembal 1 Kelinik Malaysia 23 Klinik Waqaf An-Nur 2 Klinik Adham Cawangan Indahpura 24 Klinik Wawasan Perdana 3 Klinik Balkhis 14 Klinik Insaf 3 Klinik Aiswarya 25 Klinik Yeoh Dan Surgeri 4 Klinik Bima Sakti 15 Klinik Mahmood 4 Klinik Amir 26 Klinik Zaiton 5 Klinik Dr. Alwani 16 Klinik Perdana 5 Klinik Asia Rawang Sg. Mati 27 Klinik Zohar & Surgeri 6 Klinik Dr. Haydar Ali 17 Klinik Primer Tanah Merah

28 Kumpulan Perubatan Asia Sdn Bhd 7 Klinik Dr. Roshadah 18 Klinik Wakaf Siku 6 Klinik Dan Surgeri Taman Daya - Klinik Asia Skudai 8 Klinik Dr. Wan 19 Klinik Zainal Aziz 29 Kumpulan Perubatan Asia Sdn Bhd 7 Klinik Dedap Sdn. Bhd. 9 Klinik Dr. Wan Mohd. Noor 20 Klinik Ziad Pasir Tumbuh -Klinik Asia Taman Daya 8 Klinik Ilham & Surgeri 30 Poliklinik Dr. Abdullah 10 Klinik Ehsan 21 Kumpulan Klinik M.I.R 9 Klinik Intan 31 Poliklinik Impian 11 Klinik Fatah & Abdullah 22 Poliklinik Dr Azhar Dan Rakan-Rakan 10 Klinik Jay 32 Poliklinik Khoo & Surgeri 11 Klinik Kamal 33 Poliklinik Krishna 12 Klinik Keluarga (Segamat) 34 Poliklinik Lee Private Clinics (Melaka) 13 Klinik Koh Dan Surgeri 35 Poliklinik Mustakizah 1 Klinik Bukit Beruang 8 Klinik Noh 14 Klinik Kwang 36 Poliklinik Penawar 2 Klinik Chin 9 Klinik Nurussyifa' Perubatan Dan Surgeri

15 Klinik Medic Care 37 Poliklinik Penawar Seri Alam 3 Klinik Famili 10 Klinik Peringgit Point Sdn Bhd

16 Klinik Mohan Dan Surgeri 38 Poliklinik Rozikin 4 Klinik Keluarga 11 Klinik Wira Medik Sdn Bhd 17 Klinik Pantai 39 Poliklinik Rozikin 5 Klinik Kuan Sdn. Bhd. 12 Poliklinik & Surgeri Merlimau 18 Klinik Ria 40 Poliklinik Sejahtera Sdn Bhd 6 Klinik Melaka Raya 13 Poliklinik Dan Surgeri Cosmopoint 19 Klinik Tee 41 Poliklinik Yuslina (Taman Istimewa) 7 Klinik Mesra 14 Poliklinik Perdana 20 Klinik Teo ( Klinik Teo & Tan Sdn Bhd ) 42 Polyklinik Termuzi

21 Klinik TJ 43 Poliklinik Penawar 22 Klinik Utama Private Clinics (Negeri Sembilan)

1 Klinik Ang & Ang Sdn Bhd 11 Klinik Zaaba

Private Clinics (Kedah) 2 Klinik An-Nur 12 Poliklinik Foo Dan Yong 1 Kelinik Muhibbah 12 Klinik Topcare 3 Klinik Bistari 13 Poliklinik Hidayah Sdn Bhd (Jln Cattleya)

2 Klinik C. S. Ooi 13 Klinik Ummi 4 Klinik Keluarga 14 Poliklinik Hidayah Sdn. Bhd. 3 Klinik Cheng & Su 14 Klinik Wawasan 5 Klinik Keluarga Darul Syifa' 15 Poliklinik Ibnu Sina 4 Klinik Doreen Khoo 15 Lim Poliklinik 6 Klinik Mediviron 16 Poliklinik Jasa 5 Klinik Dr Chong 16 Mediklinik Ehsan Alor Setar 7 Klinik Mediviron (Klinik Seremban 2) 17 Poliklinik Publik 6 Klinik Dr Robetah 17 Poliklinik Dr. Azhar & Rakan-Rakan 7 Klinik Dr. Roslan 18 Poliklinik Dr. Azhar Dan Rakan-Rakan 8 Klinik Mesra Bayu 18 Poliklinik Sakti 8 Klinik Dr. Salina 19 Poliklinik Ihsan Pusat Rawatan Dr Mahmud & Dr Zanariah 9 Klinik Pantai 19 9 Klinik Dr.Chua 20 Poliklinik Keluarga (Poliklinik & Surgeri) 10 Klinik Foong 21 Poliklinik Kenanga 10 Klinik Seremban 11 Klinik Liew Yin Fong 22 Poliklinik Mahkota

136 National Medical Care Statistics 2014

Private clinics Private Clinics (Kelantan)

15 Klinik Medic Care 37 Poliklinik Penawar Seri Alam 3 Klinik Famili 10 Klinik Peringgit Point Sdn Bhd

21 Klinik TJ 43 Poliklinik Penawar 22 Klinik Utama Private Clinics (Negeri Sembilan)

1 Klinik Ang & Ang Sdn Bhd 11 Klinik Zaaba

Private Clinics (Kedah) 2 Klinik An-Nur 12 Poliklinik Foo Dan Yong 1 Kelinik Muhibbah 12 Klinik Topcare 3 Klinik Bistari 13 Poliklinik Hidayah Sdn Bhd (Jln Cattleya)

Appendices 137

Private Clinics (Pahang) Private Clinics (Pulau Pinang)

1 Ananda Klinik 10 Klinik Sulaiman 1 Glugor Klinik 18 Klinik Pillar

2 Kinik Ganesh & Surgery 11 Klinik Sulaiman 2 H.S. Khoo Clinic Sdn. Bhd 19 Klinik Rashidi

3 Klinik Efendi 12 Klinik Sulaiman 3 Klinik 1 Utama 20 Klinik Roberts

4 Klinik Ehsan 13 Klinik Syed Badaruddin 4 Klinik 6 21 Klinik Sentosa Sdn Bhd

5 Klinik Lee 14 Klinik Syed Badaruddin 5 Klinik Bersatu 16 Jam 22 Klinik Seri Pulau

6 Klinik Low 15 Klinik Wira 6 Klinik Dr. Abd Aziz 23 Klinik Singapore

7 Klinik Mutiara 16 Klinik Yu Sdn Bhd 7 Klinik Dr. Lee Hock Huat 24 Klinik Syed Alwi Dan Chandran

8 Klinik Ng 17 Poliklinik & Surgeri Shankar 8 Klinik England 25 Klinik Topcare (Raja Uda) Sdn Bhd

9 Klinik Philip Dan Rakan 18 Poliklinik Maran 9 Klinik Gurney 26 Klinik Wong

10 Klinik Harmony 27 Poliklinik Bestari

11 Klinik Joe Fernandez 28 Poliklinik Chiah Private Clinics (Perak) Poliiklinik Dr Azhar & Rakan- Rakan 12 Klinik Joe Fernandez (Seberang Jaya) 29 1 Chua Kelinik 16 Klinik Setia (Kepala Batas)

2 Kelinik Che Wan (Medan Polyclinic & Surgery) 17 New Town Poliklinik 13 Klinik Kenari 30 Poliklinik Dr Azhar & Rakan- Rakan (Gelugor)

3 Kelinik Che Wan (UTP Health Centre) 18 Klinik Teoh & Chan Sdn Bhd 14 Klinik Lee 31 Poliklinik Dr Velu

4 Kelinik Majid 19 Perak Medical Centre Sdn. Bhd, Ipoh 15 Klinik Malaysia 32 Poliklinik HL

5 Klinik Aman 20 Polikelinik Bakti 16 Klinik Munnir 33 Poliklinik Pan

6 Klinik Berkat 21 Poliklinik & Surgeri Batu Gajah 17 Klinik Pertama 7 Klinik C.K. Chan 22 Poliklinik & Surgeri Kumar

23 Poliklinik Dr. Azhar & Rakan-Rakan 8 Klinik Dr. Sharul (Parit Buntar) Private Clinics (Sabah & WP Labuan)

9 Klinik Dr. Tiong 24 Poliklinik Dr. Azhar & Rakan-Rakan (Manjung) 1 Clinic Chua 14 Klinik Lo & Wah

10 Klinik E.C. Lee 25 Poliklinik Dr. C.Y. Ong Sdn. Bhd. 2 Klinik BSI 15 Klinik Malaysia (Cawangan SESB)

11 Klinik Edina 26 Poliklinik Fitrah 3 Klinik Dan Surgeri Dr Gan 16 Klinik Nasir & Surgeri

12 Klinik Greentown 27 Poliklinik Gemilang (Dr. Thomas) 4 Klinik Dr. C.H. Kong 17 Klinik Ramlee & Partners

13 Klinik Lau & Sharon 28 Poliklinik Gomez-UTAR 5 Klinik Dr. Gan & Surgeri 18 Klinik S. K. Lo Sdn. Bhd.

14 Klinik Perubatan Zalfa 29 Poliklinik Manjit 6 Klinik Dr. Lilian Hong 19 Klinik Sabah

15 Klinik Rawatan Ahsan 30 Sitiawan Surgery 7 Klinik Dr. Loi Yew June 20 Klinik Surgeri Dr. Toh

8 Kelinik Ong 21 Klinik Wawasan

9 Klinik Dr. Selvam Sdn. Bhd. 22 Permai Polyclinics Private Clinics (Perlis) 10 Klinik Dr. T. L. Chaw 23 Poliklinik Mesra & Surgeri (Putatan Branch) 1 Klinik & Dispensari Dr. Rohimi Osman 5 Klinik Refflesia 11 Klinik Elopura Sdn. Bhd. 24 Poliklinik Rakyat(Cawangan Putatan) 2 Klinik Dr. Mohadzir 6 Klinik Tan & Lee 12 Klinik Keluarga Keningau 25 Putatan Klinik Dan Surgeri 3 Klinik Faizah 7 Poliklinik Dr Azhar Dan Rakan-Rakan 13 Klinik Layong 26 Sinsuran Clinic 4 Klinik Menon Sdn. Bhd.

138 National Medical Care Statistics 2014