Developing a National Minimum Data Set for Hospital Information Systems in the Islamic Republic of Iran

Developing a national minimum data set for hospital information systems in the Islamic Republic of Iran

Zahra Rampisheh, 1 Mohammad Esmaeil Kameli, 2 Javad Zarei, 3 Akram Vahedi Barzaki, 4 Marziyhe Meraji 5 and Ali Mohammadi6

1Preventive Medicine and Public Health Research Center, Department of Community Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Islamic Republic of Iran. 2Department of Community Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Islamic Republic of Iran. 3Department of Health Information Technology, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Islamic Republic of Iran. 4Health Information Management Research Center, Kashan University of Medical Sciences, Kashan, Islamic Republic of Iran. 5Department of Medical Records and Health Information Technology, Faculty of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran. 6Department of Health Information Technology, School of Paramedical, Kermanshah University of Medical Sciences, Kermanshah, Islamic Republic of Iran. (Correspondence to: Ali Mohammadi:[email protected]).

Abstract Background: Data standardization is the first step towards better decision‐making and improved care quality. Aims: The aim of this study was to design a minimum data set for hospital information systems in the Islamic Republic of Iran. Methods: This descriptive cross‐sectional study was conducted in 2015. The study resources were the documents retrieved from the Internet, hospital records, hospital information systems (HIS), and electronic health record systems in the Islamic Republic of Iran. Data elements were collected using a data extraction form. A full list of data elements was provided through combining the retrieved resources. Finally, a minimum data set was designed using the viewpoints of the technical offices experts of the Iranian Ministry of Health. Results: The data elements were divided into administrative and clinical sections with 9 and 18 classes and 166 and 684 data elements, respectively. Finally, 159 administrative and 621 clinical data elements were used for the Iranian HIS. Conclusion: Dissimilar structure of the data elements leads to incompatibility of the collected data. Therefore, standardization of data elements will provide homogeneity among different systems. Hence, establishing a minimum data set in the country is the first step towards standardizing the data and data structure in the health and hospital information system.

Keywords: Minimum data set, hospital information system, hospital, Iran

Citation: Rampisheh Z; Kameli M; Zarei J; Vahedi Barzaki A; Meraji M; Mohammadi A. Developing a national minimum data set for hospital information systems in the Islamic Republic of Iran. East Mediterr Health J. 2019;25(x):xxx–xxx. https://doi.org/10.26719/emhj.19.046

Received: 25/11/16; accepted: 26/07/18

Introduction Data quality in a hospital information system (HIS) plays an important role in health policy‐making. Low quality of the data increases the rate of medical errors and lowers the quality of care (1). Designing a structure for standardized data collection supports disease information management and leads to enhanced quality of care (2). Standard healthcare data usually indicate minimum data elements that should be collected (3).

A minimum data set (MDS) is a standard data collection tool (4,5). In each area, the MDS contains numerous data elements regarding demographic data, health and treatment status, reimbursement resources, and patient transfer location (6). The main objective of the MDS is to build a national database that can serve as an information management source to equip decision‐makers and policy‐makers with accurate and up‐to‐date information (7). The MDS of each area strengthens the relationship between the conducted studies and extraction of research results, improves the plans, strategies, and policies, and provides the opportunity for equity in the health system (8).

In the healthcare system, data sets identify data elements that should be collected for each patient and provide a similar and safe definition for each element based on standards. Data comparison is used for different purposes including external accreditation, evaluation of the internal performance, and research and statistical studies. Therefore, it is important to determine these standard data sets to manage the clinical performance of health organizations in every country (9).

Although minimum data sets are specific to each country, they should have the capability of data comparison at an international level. In this regard, many countries such as Qatar (QMDS2014) (10), Denmark (NPRMDS 1987), Germany (MDIM 1995), United Kingdom (NHS‐MDS1993), the Netherlands (LIS‐BDS1997), Australia (VEMD1995) (11), Canada (MDIS1998) (12), New Zealand (NMDS‐IS1992) (13), and the United States of America (UHDDS) (14) have developed national general or specialized minimum data sets for their health information systems (15).

The variable content of hospital records, electronic health record systems (Samaneh Parvande Electronic Salamat [SEPAS] established an electronic health record by the Iranian Ministry of Health for data collection), and hospital information systems indicate the incompatibility of the data elements of these systems and lack of any MDS. Collection of standard data and maximizing their quality in the Islamic Republic of Iran requires the development of an MDS for hospital information systems. Therefore, considering the lack of a standard set in the country, this study was conducted to design a minimum data set to be used in HIS development.

Methods This descriptive cross‐sectional study was conducted in 2015. The data were collected from SEPAS, HIS documents of the companies approved by the Iranian Ministry of Health and Medical Education (MoHME), and inpatient records used in the Islamic Republic of Iran. Moreover, a review of the literature was done to find relevant resources, including texts, reports, guidelines and websites related to data elements of hospital, disease, administrative, equipment, and medical intervention information systems using the Internet and print material. The retrieved materials were selected according to the research criteria and search strategy (Table 1).

The resources retrieved from the Internet were selected based on the criteria and evaluated until saturation was achieved. The SEPAS documents were similar and data elements of the records were standard; therefore, sampling was not done and the SEPAS system and one of the records were evaluated. Moreover, the data elements of the documents of 26 HIS companies approved by the MoHME were evaluated.

A data extraction sheet was used for data collection. The data elements retrieved from the Internet, SEPAS system, HIS companies, and hospital records were extracted separately and collected in four separate files: 1) domestic and foreign studies as electronic and print material; 2) SEPAS system; 3) HIS documents; and 4) medical records. The data elements retrieved from each source were categorized based on similar classes and subjects, and a complete file was provided through combining all four files. The new file was classified into administrative and clinical sections and each section was classified into different classes.

The files of administrative and clinical data elements were designed as a checklist with different columns, including the row number, data element in Persian, and data element in English. Moreover, in this checklist, two columns of “yes” and “no” were considered for each data element in order to survey whether or not to include the data element in the HIS.

The content validity of the checklist was assessed by 10 experts of the MoHME technical offices, including 4 health information management experts, 4 physicians, and 2 IT experts.

The developed checklist, together with an official letter from the Information and Statistics Management Office of MoHME, was presented to specialized technical offices and board bureaus and centres, and the experts’ agreement or disagreement with the data elements of special classes were collected. Twenty‐two experts working in eight different specialized technical offices and board bureaus and centres of MoHME, in addition to 3 physicians and 3 health information managers were selected purposively in a non‐randomized fashion through convenience sampling to complete the designed form.

Evaluation of domestic and foreign studies continued until no new data elements were discovered. The data elements of the SEPAS system, hospital records, and hospital information systems were also collected completely. Classification of data elements into administrative and clinical sections and their sub‐classes was performed according to information management standards; the classification proposed by American National Standards Institute (ANSI), American Society for Testing and Materials (ASTM) standards for Core Health Data Elements; reference books; classifications found in retrieved studies (4,16,17), hospital records, HIS, and SEPAS system; and the viewpoints of the Information and Statistics Management Office of MoHME. The final list of data elements in each class was provided based on the extracted data elements in the previous stages.

For each class, the data elements of different resources were reviewed. Among common data elements, those with a more complete and comprehensive definition, format, domain, justification, code, source, etc. were included in the class. All data elements that were not common were also fully included in the file. A Persian or English title and definition was provided for the elements that only appeared in English or Persian texts; in other words, all listed data elements had English and Persian titles and a definition in Persian.

The final data elements for the Iranian HIS were determined through consensus of technical offices experts, and board bureaus and centres of MoHME (Table 2) for relevant classes of data elements. The data classes prepared as checklists were forwarded to relevant technical offices along with a formal letter from the Statistics and Information Management Office of MoHME. The experts in the technical office discussed whether or not to include the data elements in the HIS and announced their agreement or disagreement regarding each data element. The agreed upon data elements were returned to the Statistics and Information Management Office in an official letter from the director of the technical office. In this way, the data elements of different classes were provided. In the end, the final data elements for the Iranian HIS were determined.

Results The national MDS for the Iranian HIS had two administrative and clinical sections with 9 and 18 classes, respectively. The total number of collected data elements was 166 for the administrative and 684 for the clinical section, which decreased to 159 data elements for the administrative and 621 data elements for the clinical section after the viewpoints of technical offices, board members, MoHME deputy offices, and specialized centres were obtained (Table 3).

The demographic class of the administrative section included the highest number of data elements (n=51). In this class, three data elements (mother’s first name, mother’s family name, and distance from home to hospital) were not agreed upon. The data elements of this class were related to ID, nationality, and religious and social characteristics of the patients. The class of admission had 20 data elements that were all agreed upon. This class contained admission information, including the date, time, ward, room, and admission number. The class of Incidence had 20 data elements in which other participants at the accident scene, accident mechanism, and the accident causing object or vehicle were not agreed upon. The data elements of this class were related to the date, time, and location of the accident. All proposed data elements in legal data, discharge, financial, organization identifier, and geographic classes were agreed upon. In the class of personnel identifier, the data element of service provider’s full name was not agreed upon (Table 4).

In the clinical section, some data elements in the classes of diagnosis, pre‐hospital and hospital emergency, medicine, nursing, and anesthesia were not agreed upon while all other data elements were. The highest disagreement was related to pre‐hospital emergency data elements.

The first data class of the clinical section was diagnosis. In this class, of 101 data elements, type of activity during the accident was not agreed upon. The data elements of this class included chief complaint; primary, during‐treatment, and final diagnosis; pre‐ and post‐ operative diagnosis; and ICD codes.

The second class was pre‐hospital emergency. Medical Emergency Management Center of MoHME rejected 42 out of 82 data elements in this class. The data elements of this class included the dispatch date and time, type of transfer, and pre‐hospital emergency procedures. The data class of hospital emergency had the highest number of clinical data elements (n=110) of which 104 were agreed upon. A consensus was not reached for the data elements of medical facilities provided for the patient, level of specialized services of the emergency department, role of service provider, and consultant identifier in this class. The data elements of current dose and dose unit for the data class of drug, and the data elements of post‐operative pain management methods and hypertension following the use of pre‐anesthetic drugs for the data class of anesthesia were not agreed upon. No consensus was achieved for the data elements of type of care, duration of ICU admission, drug code, drug permission, and treating physician in the data class of nursing. The data elements of other classes in the clinical section were confirmed by experts (Table 5).

Discussion The proposed MDS of the Iranian HIS had administrative and clinical sections. Some specialized texts (4,16) and studies on specialized minimum data sets have also used this classification (18,19). This classification has been performed based the nature of the data in different studies. Administrative data are used for patient registration, medical centre identification, insurance and reimbursement (17,20), medical research, outcome evaluation, and administrative reports (21,22).

In this study, the administrative data were proposed on nine different data classes. They were more comprehensive than similar hospital minimum data sets, such as Qatar (QMDS2014) (10), Australia (VEMD1995) (11), New Zealand (NMDS) (13), and United States (UHDDS) (14) and covered more data elements, especially in the legal, incidence, and geographic data class. The first class in this section was demographics. A number of other studies have considered this class as well (2,3,19,23–28).

There is a difference in demographic data elements between what we proposed in our study, the data elements currently used in hospital records, and the data elements of national data sets in other countries (29), indicating a need for more data elements for a more comprehensive coverage of the data elements. For example, the data of main income source, lifestyle, and monthly household income were proposed as part of demographic data.

Another difference is the data elements related to ethnicity and race. They were not suggested in the proposed demographic data because they did not have much use in the Islamic Republic of Iran due to the racial and ethnic composition of the Iranian population. However, data elements related to ethnicity and race are used in most minimum data sets in countries with ethnic and migratory populations such as the United States (14,30,31). In the class of admission, some data elements related to patient admission to the medical centre, such as like the date and time of admission, ward, room, bed, and transferring hospital or centre, were proposed. The majority of these data elements are similar to data elements for admission in some studies performed in the Islamic Republic of Iran (18,23) and minimum data sets of other countries (10,13,30,32).

As for the class of incidence, with the aim of assisting incidence registration, some data elements related to the person’s activity during the accident and accident location, mechanism, and intention were proposed. Registration of these data may help with implementing the system of International Classification of External Causes of Injury (ICECI) (33). Moreover, these data are among the main data of the MDS for traffic accidents and injuries (34,35). However, the proposed data set for the class of Incidence contained fewer data compared to specialized data sets for injuries like IDB‐MDS (36).

In the MDS designed for the Iranian HIS, with the objective of registering the data elements related to informed consent acquisition and informing legal authorities, the

class of legal data was proposed. This class has also been considered in an MDS for orthopaedic injuries, which also contains data elements regarding allergies and organ donation in addition to informed consent (18). Most data elements in this class do not exist in other minimum data sets (10,14,30,31,36).

The data elements of type of insurance coverage, costs, and care bill payment method were included in the class of financial data. The data elements of final diagnosis and disease code were also included in this class with the aim of supporting a prospective payment system. Registering these data has an important role in implementing DRGs in Iranian hospitals (37). These data are similar to financial data in most minimum data sets in other countries (10,14,29).

In the class of organization identifier, some data elements like the institute name, identity, and organizational affiliation were similar to the data determined for the service‐ providing organization in other studies (2,18,19,38) and minimum data sets in other countries (10,29,30,32). However, the data elements of longitude and latitude, website and email address of the health centre were also proposed in our study. The longitude and latitude are also registered in emergency‐related data sets in many countries and in traffic accidents in the Islamic Republic of Iran (12,35), and their registration helps to conduct different studies for planning, accessing, and distributing health services based on geographic information systems (39). This data element was proposed with regards to the importance of hospital websites in assisting the delivery of health services to patients and its role in the future (40).

In the class of personnel identifier, data elements related to identification of the health service provider, including the first and last name, identity, role, academic major, and electronic signature, were considered. The class of geographic data elements was proposed with the aim of accurate registration of the location data related to the patient’s living place according to geographical divisions of the country. The proposed clinical data set in the clinical section comprised 18 data classes. Compared to similar MDSs in other countries (10,14,29,32), our proposed clinical dataset has more data elements. To propose the clinical data, it was tried to include as many clinical data elements of the patient’s medical record as possible.

Diagnosis was the first class of the clinical section with 101 data elements. This class included different diagnoses, their codes, and disease signs. The ICD codes of different diseases were an important data element in this class which have also been considered in many MDSs, as well (18,19,23,24,32,38).

The class of history data and systems evaluation with 21 data elements was related to the personal and family history of the patients and evaluation of different organs. Some other studies have also considered this class under other names such as history (23), patient status evaluation (3), or physical examination and injury report (41).

The class of pre‐hospital emergency data contained unconfirmed data related to the characteristics of the vehicle for patient transfer, and the transfer method. The aim of this class was to register the patient transfer method, procedures performed on the patient, information of the dispatching unit, and date and time of the contact and dispatch.

The class of hospital emergency data included the information of the emergency department, diagnoses, date and time of the procedures, and the patient’s status when emergency procedures finished. This class contained the highest number of data elements because of the extensiveness of emergency data in some evaluated data sets (11,12) and the importance of these data in hospital emergency information systems (42). The class of diagnostic–therapeutic procedures data with 78 data elements fully described the diagnostic and therapeutic procedures performed on the patient. These data elements were related to the type, method, date, and time of procedures (both start and end), and the codes related to the procedures. Some of these data elements have been mentioned in most studies related to minimum data sets (18,19,23,24,38). The data elements that are related to procedures, especially surgical intervention, are among the most widely used data elements in clinical follow‐ups (43). The aim of the class of orders data with 17 data elements was to support the registration of the details of the orders of medical staff, especially the treating physician.

In the class of nursing data, some data elements like interventions performed by nurses, nurse’s evaluation at admission, laboratory tests and imaging studies were not approved because they were included in other classes. Some of these data elements were also in line with the data of nursing services in a study by Rafii et al. known as the nursing MDS (44) and were used in a study by Ahmadi et al. for developing an MDS for orthopaedic injuries (18).

Two classes of medical imaging and laboratory were proposed for para‐clinical data. The data elements of medical imaging included the type of radiography, technique, code, anatomical location, radiologist’s name, and interpretation. In addition to these data, Ahmadi et al. used the radiation dose, contrast medium, and image identification code in their MDS (23).

The laboratory data class included the test name, test group, code, number, and test result. Some related studies have used the majority of these data (18,19,38). The anesthesia data elements included the time of the start and end and the duration of anaesthesia, drugs used for anaesthesia, type of anaesthesia, and patient’s status at the end of anaesthesia. A separate class with 34 data elements was considered for the administered drugs, including the name, code, administration route, and dose. A number of domestic studies on data sets have also considered a separate class for drugs (2,3,18,19,41), indicating the importance of drug data.

Medical prostheses and blood products comprised two other classes. The class of medical prostheses included the data of the prostheses used for the patient, and the class of blood products covered the data of the blood transfusion and blood products. Ahmadi et al. considered both classes of medical prostheses and blood products for developing an MDS for orthopaedic injuries (18), but we proposed more comprehensive data elements when compared with HIS document, SEPAS system, and hospital records. Eleven data elements were proposed for the class of consultation, which covered the data of specialized consultations with the patient and its data elements were similar to the data elements of consultation request forms used in the Islamic Republic of Iran. Eight data elements were suggested for the class of follow‐up data. A number of domestic studies have also used follow‐up data, as well (2,18,19).

Although there was a class for discharge data in the administrative section, a separate class was considered in the clinical section to show the status of patient discharge with a clinical approach. The focus of these data elements was on medical recommendations for treatment follow‐up at the time of discharge.

A number of studies have reported some problems in filling and documentation of the death certificate (45–48); therefore, the data elements of the class of death included the data available in the certificate of death beyond 7 days, stillbirth certificate, and death certificate for children aged 0–6 days. It was attempted to organize the data elements of this class in accordance with WHO and international death certificates (49).

The last class of the clinical section was transfer, with the aim of registering the data of patient transfer between health centres, especially hospitals.

Conclusion In the present study we evaluated the data sets of other countries’ medical forms used in Iranian health centres, SEPAS system, and HIS companies (although some HIS companies submitted incomplete data elements, which caused some limitations in the study), and the viewpoints of experts in MoHME, and suggested 27 classes for the administrative and clinical data. Comparison of the data elements proposed in each class with similar studies showed that the suggested data were more comprehensive and could help hospitals as well as other healthcare centres to register and report health data efficiently. Incorporation of the data proposed in our study into other specialized data sets developed for the Islamic Republic of Iran in previous studies may be useful in developing and expanding a national health data set. Moreover, it can be used by the MoHME, HIS companies, and health surveillance centres for more efficient health data management.

Acknowledgements This study was a national project supported by Ministry of Health and approved in Kashan University of Medical Sciences (grant No: 94113).

Funding: This study was funded by the Iranian Ministry of Health.

Competing interests: None declared.

References

1. Mohammed SA, Yusof MM. Towards an evaluation framework for information quality management (IQM) practices for health information systems–evaluation criteria for effective IQM practices. J Eval Clin Pract. 2013;19(2):379‐87.doi: 10.1111/j.1365‐2753.2012.01839.x. Epub 2012 Apr 15 .

2. Karimi S, Saghaeiannejad IS, Farzandipour M, Esmaeili Ghayoumabadi M. Comparative study of minimum data sets of health information management of organ transplantation in selected countries and presenting appropriate solution for Iran. Health Information Management. 2011;7(Special Issue):497‐505

3. Hosseini A, Moghaddasi H, Jahanbakhsh M. Designing Minimum Data sets of Diabetes Mellitus: Basis of Effectiveness Indicators of Diabetes Management. Health Information Management 2010;7(3):330-40

4. Abdelhak M, Grostick S, Hanken MA, Ellen J. Health Information: Management of a Strategic Resource. 4 ed. Philadelphia: Elsevier ‐Health Sciences Division; 2012.

5. Johns ML. Health information management technology: an applied approach. Chicago: AHIMA, 2002.

6. Cai S, Mukamel DB, Veazie P, Temkin‐Greener H. Validation of the Minimum Data Set in identifying hospitalization events and payment source. Journal of the American Medical Directors Association. 2011;12(1):38‐43

7. Kowal PR, Wolfson LJ, Dowd JE. Creating a minimum data set on ageing in sub‐ Saharan Africa. S Afr J Gerontol. 2000;9:18‐23

8. Ghaneie M, Rezaie A, Ghorbani N, Heidari R, Arjomandi M, Zare M. Designing a Minimum Data Set for Breast Cancer: a Starting Point for Breast Cancer Registration in Iran. Iran J Public Health. 2013;42(Supple1):66‐73PMID: 23865019 [PubMed] PMCID: PMC3712595.

9. Sadoughi F, Ghazisaeidi M, Mehraji M, Kimiafar Kh, Ramezanghorbani N. Health Information Management Technology. Tehran: Jafari Publication; 2011.

10. Supreme Council of Health. Qatar Patient Minimum Data Set (MDS). State of Qatar: National Health Insurance Company (NHIC), 2015 Contract No.: SCH/HFID/MDS/V4 2015.

11. Victorian Emergency Minimum Dataset (VEMD). Melbourne, Victoria, Australia: Department of Health & Human Services; 2012.

12. Emergency Health Services – Patient Care Reporting Minimum Data Set. Alberta, Canada: Health Information Standards Committee for Alberta; 2011.

13. National Health Board. National Minimum Dataset (Hospital Events) Data Dictionary. Wellington: Ministry of Health, 2014 Contract No.: PO Box 5013, Wellington, New Zealand.

14. National Committee on Vital and Health Statistics. Preliminary Recommendations for Core Health Data Elements 1996 [cited 2017 25 September]. (https://www.cdc.gov/nchs/data/ncvhs/nchvs94.pdf)

15. Bloemhoff A, Hoyinck S, Dekker R, Mulder S. Development of minimum data sets on injuries: background report. Consumer Safety Institute, Amsterdam. 2001

16. Davis N , LaCour M Health Information Technology. 3 ed: Elsevier; 2014.

17. Wager KA, Lee FW ,Glaser JP. ManagingÂ Health Care Information Systems: A Practical Approach for Health Care Executives: John Wiley & Sons; 2005.

18. Ahmadi M, Mohammadi A, Chraghbaigi R, Fathi T, Baghini MS. Developing a minimum data set of the information management system for orthopedic injuries in iran. Iranian Red Crescent Medical Journal. 2014;16(7)

19. Ahmadi M, Alipour J, Mohammadi A, Khorami F. Development a minimum data set of the information management system for burns. Burns. 2015;41(5):1092‐9

20. De Coster C ,Quan H, Finlayson A, Gao M, Halfon P, Humphries KH, et al. Identifying priorities in methodological research using ICD‐9‐CM and ICD‐10 administrative data: report from an international consortium. BMC health services research. 2006;6(1):77

21. Weingart SN ,Iezzoni LI, Davis RB, Palmer RH, Cahalane M, Hamel MB, et al. Use of administrative data to find substandard care: validation of the complications screening program. Medical care. 2000;38(8):796‐806

22. Zhan C, Miller M. Administrative data based patient safety research: a critical review. Quality and Safety in Health Care. 2003;12(suppl 2):ii58‐ii63

23. Ahmadi M, Bashiri A. A minimum data set of radiology reporting system for exchanging with electronic health record system in Iran. Journal of Payavard Salamat. 2014;8(2):121‐33

24. Sadoughi F, Safdari R, Meraji M, Ramzan Ghorbani N, Ghazisaeedi M. Designing a minimum data set for national cancer registry in Iran. Journal of Urmia Nursing And Midwifery Faculty. 2013;11(8):622‐9

25. Arastoo AA, Nickbakht M, Ghasemzadeh R, Azizi A, Zahednejad S, Latifi SM. Developing a National Minimum Data Set for Physiotherapy in Iran: A Delphi Study.

26. Ahmadi M, Rafii F, Habibi Koolaee M, Mirkarimi A. A Comparison of Data Elements of Nursing Minimum Data Set. Iranian Journal of Nursing Research. 2012;7(24):45‐ 52

27. Kalankesh LR, Dastgiri S, Rafeey M, Rasouli N, Vahedi L. Minimum Data Set for Cystic Fibrosis Registry: a Case Study in Iran. Acta Informatica Medica. 2015;23(1):18

28. Arastoo AA, Nickbakht M, Ghasemzadeh R, Azizi A, Zahednejad S, Latifi SM. Standardization of data elements of audiology records: a suitable model for Iran. Bimonthly Audiology‐Tehran University of Medical Sciences. 2012;21(1):26‐37

29. National minimum data sets Australian Institute of Health and Welfare: Authoritative information and statistics to promote better health and wellbeing; 2015. (http://meteor.aihw.gov.au/content/index.phtml/itemId/344846).

30. Pollock DA, Adams DL, Bernardo LM, Bradley V, Brandt MD, Davis TE, et al. Data elements for emergency department systems, Release 1.0 (DEEDS): a summary report. Journal of Emergency Nursing. 1998;24(1):35‐44

31. Centers for Medicare & Medicaid Services. Long‐term Care Facility Resident Assessment Instrument 3.0 User’s Manual, Version 1.13. October 2015. 2015

32. Australian Institute of Health and Welfare. Admitted patient care NMDS 2016‐17 2017 (http://meteor.aihw.gov.au/content/index.phtml/itemId/61217)

33. International Classification of External Causes of Injury (ICECI). Geneva: World Health Organization; 2003

34. Injury surveillance National Minimum Data Set, National Health Data Dictionary, Version 12. National Health Data Committee,Australian Institute of Health and Welfare Canberra; 2003.

35. Ali Mohammadi, Maryam Ahmadi, Alireza Gharagozlu. Developing a Minimum Data Set for an Information Management System to Study Traffic Accidents in Iran. Iran Red Crescent Med J. 2016;18(3).doi: 10.5812/ircmj.23677 .

36. European Association for Injury Prevention and Safety Promotion Office. IDB‐ JAMIE Minimum Data Set (IDB‐MDS) Data Dictionary. Netherlands, Amsterdam: 2013.

37. Ghaffari Sh , Abolhallaj M , Pouragha B. Feasibility of Implementing Diagnosis Related Groups: A Case Study in Iran’s Hospitals. Hakim. 2012;15(2):147‐57

38. Safdari R, Shahmoradi L, Ebrahimi M. Minimum Data Set Of Anatomical Pathology Information System From The Perspective Of Experts. Payavard Salamat. 2015;9(3):300‐14

39. Zhan FB, Lu Y, Giordano A, Hanford EJ ,editors. Geographic information system (GIS) as a tool for disease surveillance and environmental health research. Proceedings of ICSSSM'05 2005 International Conference on Services Systems and Services Management, 2005; 2005: IEEE.

40. Salarvand Sh, Sheikh Abumasoudi R, Kashani F, Samadbeik M, Salarvand H. Assessing the Necessitate Quality Indicators of Hospitals' Websites (A literature review). Journal of Hospital. 2016;15(1):87‐100

41. Safdari R, Dargahi H, Halabchi F, Shadanfar K, Abdolkhani R. A Comparative Study Of The Athlete Health Records’ Minimum Data Set In Selected Countries And Presenting A Model For Iran. Payavard Salamat. 2015;8(2):134‐45

42. Moghaddasi H, Rabiei R, Mastaneh Z. Pre‐Hospital Emergency Information System in America and England: A Review. Payesh. 2014;13(4):383‐91

43. Jangi M, Azizi A, Kamali Yousef Abad M, Tara SM. Systematic Design of the Minimum Data Set Storage: An Essential Need to Create Purposed for Archiving. Journal of Health and Biomedical Informatics. 2015;1(2:(113-21)

44. Rafii F, Ahmadi M, Hoseini A. Nursing minimum data set: An essential need for Iranian Health Care System. Iran Journal of Nursing. 2011;24(71):19‐27

45. Meraji M, Barabadi M. Errors in the Documentation of the Death Certificate: A Case Study. Journal of Health and Biomedical Informatics. 2015;2(3):168‐75

46. Akbarzadeh Bagheban A, Maserat E, Hemmati M. Studying the Degree of Diagnostic Agreement between Medical Records and Death Certificates in Loghman Hospital in 2005. Iranian Journal of Epidemiology. 2007;3(1):39‐46

47. Hayavi Haghighi MH, Khorami F, Hosseini Teshizi S, Dehghani M. The Impact of Documentation Errors on Accuracy of Cause of Death Coding in Shahid Mohammadi Hospital of Bandarabbas. IJFM. 2011;17(3):157‐64

48. Keyvanara M, Zardoeigolanbar S, Karimi S, Isfahani SS. The Quality of Death Certificates Record in the Educational and non‐Educational Hospitals in Kermanshah, Iran. Health Information Management. 2011;8(1):36

49. World Health Organisation. International Statistical Classification of Diseases and Related Health Problems. 10th Revision. Geneva, Switzerland: World Health Organisation; 2010.

Table 1. Search strategy for retrieving data elements of MDS for HIS in the Islamic Republic of Iran

Sites, Criteria, Strategy Descriptions, Characteristics Websites World Health Organization,

Search engines Yahoo, Google, Google Scholar

Pub Med, ISI Web of Science, Scopus, EMBASE, IEEE, Cochrane, Database SID, Mag Iran. IranMedex, Civilica, Irandoc. (up to 2015, September) Inclusion criteria: Literature in the English and Persian language. Papers, annual reports, reports, guidelines and forms of research published up to September 2015, in the full text, from Inclusion and Exclusion valid sources, with a clearly stated purpose, Keywords in title or criteria abstract. Exclusion criteria: Non peer‐ reviewed papers, reports and forms that retrieved from personal weblogs and abstracts with not accessible full text. "Patient Minimum Data Set”, “ Patient Data Element”, “Hospital Information System” And “ Data Element”, Hospital Information Strategy System” And “Minimum Data Set”, “ Health Information System” And “Minimum Data Set”, “ Hospital Information Data Base”

Table 2: Technical office for determining administrative and clinical data elements

Department/Office/Center of Ministry of Data classes Health and Medical Education Demographic Admission Legal Hospital Information and Statistics Management Office ‐

Discharge Hospital Management and Clinical Excellence Department Personnel Identifier Organization Identifier Geographic Incidence Medical Emergency Management Center Administrative Tariff Office ‐ Health Technology Assessment, Standardization and Tariff Department, Supreme Council Financial for income distribution Economic Planning and health insurance group

Per‐hospital emergency Medical Emergency Management Center Hospital emergency Diagnosis Diagnostic\ Therapeutic procedure Orders 5 physician in: Hospital Information and Statistics Medical imaging Management Office‐ Curative Resource Management Follow up Office ‐ Hospital management and clinical excellence System History and Department

review Consultation Clinical Anesthesia Laboratory Health Reference Laboratory Blood Products medicine Food & Drug Administration Medical Prosthetics Rehabilitation Medicine Specialist Discharge status Hospital Information and Statistics Management Office ‐ Transfer Hospital Management and Clinical Excellence Department Nursing Nursing Deputy Death Network Management Center

Table 3. Results of consensus for administrative and clinical data elements for minimum data set for HIS in the Islamic Republic of Iran Data classes The Number of Accepted Rejected Data Elements Demographic 51 48 3 Admission 20 20 0

Administrative Incidence 20 17 3 Legal 9 9 0 Discharge 10 10 0 Financial 25 25 0 Personnel Identifier 7 6 1 Organization Identifier 16 16 0 Geographic 8 8 0 Total 166 159 7

Diagnosis 101 100 1 Per‐hospital emergency 82 40 42 Hospital emergency 110 104 6 Diagnostic\ Therapeutic procedure 78 78 0 Orders 17 17 0 Medical imaging 22 22 0 Laboratory 13 13 0 Medicine 36 34 2

Clinical Medical Prosthetics 15 15 0 Blood products 10 10 0

Discharge status 10 10 0 Transfer 28 28 0 Follow up 8 8 0 System History and review 21 21 0 Nursing 58 48 10 Consultation 11 11 0 Death 34 34 0 Anesthesia 30 28 2 Total 684 621 63

Table 4. Examples of administrative data elements for a minimum data set for HIS in the Islamic Republic of Iran

Data classes Data elements National Identity Number, Patient First \Last\ Nick and Middle Name, Demographic Father's Name, Sex, Date of Birth, Religion, Labor Force Status, Telephone Number, Mobile Phone Number, Patient Email Address Type of Entry, Type of Admission, Admission Date\ Hour, Admission Admission Ward, Room, Bed Number Date\ Hour of Incidence, Place Address, ICD‐10 Injury Place, Incidence longitude, latitude, Site of Injury, Nature of Injury, Final Outcome Reported to the Police, Advance Directives, Informed Consent, Type Legal Of Informed Consent, Informed Consent Date, Witness First Name, Witness Last Name Discharge Date\Hour, Ward, Patient Discharge Status, Discharge Type, Discharge Length of Stay, Discharger Physician Insurance Organization, Insurance Fund, Other Insurance Financial Organization, Complementary Insurance, Insurance Serial Number, Insurance Expiration Date, Service Name, Service Code, Service Unit Healthcare Provider‐ First Name, Healthcare Provider ID, Healthcare Personnel Identifier Provider‐ Role, Healthcare Provider‐ Specialty, Healthcare Provider‐ Last Name Healthcare Center Name, Healthcare Center Type, Healthcare Center Organization Identifier ID, Longitude\ Latitude, Health Care Center Affiliation Patient Location‐Geographic Position, Country, City, Province, District, Geographic Rural Area, Town, Village

Table 5. Examples of clinical data elements for a minimum data set for HIS in the Islamic Republic of Iran Data classes Data elements Chief Complaint , Clinical Finding Data Source, Primary Diagnosis, Interim Diagnosis Diagnosis, Pre‐ Operation Diagnosis, Post‐ Operation Diagnosis, Final Diagnosis, Pain Scale, Stroke Scale, Patient Disability Per‐hospital Mode of Transport to ED, Source of Referral to ED, Vehicle Dispatch GPS emergency Location, Accident or Onset Date/Time, Dispatch Notified Date/Time Type of Emergency Department Visit, Outcome of Emergency Department Hospital emergency Visit, Patient Problem Assessed in ED, Outcome Observation, Date\ Time of Patients Entering the Emergency, GCS Diagnostic\ Procedure Type (Medical\ Diagnostic Procedures), Date\ Time of Therapeutic Procedure, Procedure Name by ICD‐9CM, Principal Procedure Code, Start\ procedure End Of Operation, Total Time of Operation Order Group, Inpatient Order, Blood Reserve Order, Consultations Orders, Orders Lab‐Tests Orders, Radiography Orders, Order Date\ Time Type of Requested Radiography, Limb’s Name, Limb’s Direction, Technique, Medical imaging Date of Radiography, Radiologist Notes, Radiography Result, Authentication Test Name, Main Group of Test, Test Code, Blood Group, Number, Routine Laboratory Test Name of Medications, Medications Code, Name and Type of Medications, medicine Value, Dose, Type of Prescription Device Name, Device ID, Model Number, Device Purchase Date, Name of Medical Prosthetics the Requested Instruments, Size, Number for Each, Device Serial Number, Code Blood Request, Blood Type, Blood Group, Date/Time of Start of Injection, Blood products Date/Time of End of Injection, Unit, Blood Pack Serial Number Revenue Codes, Discharge Recommendations, Discharge Date, Follow‐up, Discharge status Places to Visit Follow up Date/Time Patient Departs, Destination hospital, Physician Acceptance, Transfer Cause of Dispatch or transport, Diagnosis, Arrival Time, Patient's Symptoms, Referral Practitioner Name, Referral Organization, Discharge Medication Follow up Order Type, Patient Problem Assessed in Follow up, Follow up Outcome Observation, Date/Time of Follow up Medical/Surgical History, Personal and Family History, Immunization, System History and History, Environmental/Food Allergies, Alcohol/Drug Use Indicators, Data review Source Nursing Report, Date of Report, Time of Report, Considerations / Nursing Observations Nurse, Monitoring Vital Signs, Patient Education, Education Subjects,

Consultant Practitioner ID, Date/Time Consult, Date/Time Consult Starts, Consultation Date/Time Consult Stops, Type of Consult, , Request a Consultation to Assess Disease National Code, Sex, Nationality, Occupation, First\ Last Name, Newborn's Death Mother, Mother National Code, Mother Birth Certificate No Anaesthetics, Supportive Therapy (Fluids, Oxygen, etc.), Anaesthesia Start Anaesthesia Time, Anaesthesia completion Time, Type of Anaesthesia, Date of Anaesthesia