By Ogwal Alex Gwom and Acheka Edmonton Medium-Term Fellows November, 2013 Improving Data Completeness, Accuracy and Timeliness I

IMPROVING DATA COMPLETENESS, ACCURACY

HEALTH DEPARTMENT

OGWAL ALEX GWOM AND ACHEKA EDMONTON

MEDIUM-TERM FELLOWS

NOVEMBER, 2013

Table of Contents

Declaration...... iii Acknowledgements ...... v Acronyms ...... vi Operational Definitions ...... vii Executive Summary ...... viii 1.0 Introduction & Background ...... 1 1.2 Background ...... 1 2.0 Statement of the problem, conceptual framework and project justification ...... 2 2.1 Statement of the problem ...... 2 2.2 Justification for the project ...... 2 2.3 Conceptual framework...... 3 3.0 General and Specific Objectives ...... 4 3.1 General Objective ...... 4 3.2 Specific Objectives ...... 4 4.0 Methodology ...... 4 4.1 Capacity building ...... 4 4.2 Mentoring and Coaching ...... 5 4.3 Timely submission of reports ...... 6 4.4 Increase in budget allocations ...... 6 4.5 Meetings held ...... 6 5.7 Storage of Information ...... 7 5.0 Project Outcomes ...... 8 6.0 Lessons learned ...... 9 7.0 Challenges and how they were overcome ...... 9 8.0 Summary, Conclusions and Recommendations ...... 10 8.2 Conclusions ...... 10 References ...... 11

Declaration

I Ogwal Alex Gwom and Acheka Edmonton do here by declare that this end of project report entitled Improving data completeness, accuracy and timely reporting in Amolatar District health department has been prepared and submitted in fulfillment of the requirements of mid- term fellowship program at Makerere University School of Public Health and has been submitted not for any academic or nonacademic qualification

Signed………………………………………….Data…………………………………. Ogwal Alex Gwom (Medium-term fellow)

Signed………………………………………….Date………………………………… Acheka Edmonton (Medium-term fellow)

Signed………………………………………….Date………………………………….. Dr Okello Quinto (Institutional Supervisor)

Signed………………………………………….Date………………………………….. Dr Sylvester Kogonza (Academic Supervisor)

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Fellow’s roles

Ogwal Alex Gwom was responsible for project identification and development of the proposal, including the budget. He conducted sensitization for district stakeholders and advocated for budget allocation on the project. In addition, Alex was responsible for coordinating the project activities

On the other hand, Acheka Edmonton participated in project identification, development of the proposal and budget as well as identification of project team members. He was particularly responsible for arranging for the dissemination of project outcomes to stakeholders at district level, supported advocacy efforts for budget allocation and coordinated the process for the training of team members.

Acknowledgements

The successful completion of this project is owed to the assistance we received from a number of individuals and Organizations. We would like to specifically express our gratitude to Makerere University School of Public Health-CDC Fellowship Program for offering us this very important and valuable fellowship program and all technical guidance through face to face and supervision.

We are also very thankful to our Institutional and Academic Supervisors, who show keen interest from the time of project identification up to the final completion of this Project.

We are also quite indebted to Amolatar District Health Team for sparing their time and work throughout the period of this project.

Finally we appreciate the efforts made by M&E Team for their tireless efforts and participation in the active management of data in the entire respective health units to improve date accuracy, completeness and timely reporting in the District. Our sincere honor goes to all the in charges of Health facilities for the maximum cooperation employed during this project implementation.

Acronyms

HMIS Health Management Information Systems

DHIS-2 District Health Information Systems two.

DHO District Health Officer

DHT District Health Team

DHMT District Health Management Team

MakSPH Makerere University School of Public Health

CDC Center of Disease Control

Bsc HSM Bachelor of Science in Health services Management

BScN Bachelor of Science in Nursing

PMMP Performance measurement and monitoring Plan

HSSIP Health Sector Strategic Investment Plan

NDP National Development Plan

IEC Information Education and Communication

BCC Behavioral Change Communication

PMTCT Prevention of Mother to Child Transmission

ART Antiretroviral Therapy

SMC Safe Male Circumcision

CBO Community Base Organization

MoH Ministry Of Health

M& E Monitoring and Evaluation

MTrack: Machine tracking

Operational Definitions

Data in reference to these documents means crude health information generated directly from the source at health units and CBOs

District Health Department is a unit which handles all health matters in conjunction with other stakeholders at the district

Completeness refers to all health indicators in the HMIS reporting tools properly filled

Timeliness refers to submission of monthly HMIS reports to the required service point within the designated timeframe

M&E team refers to a group of health workers identified to handle health information/data (Comprising all health units in charges and medical record assistants) Accuracy refers to consistency of data being from one level to the next level

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Executive Summary

Background: Amolatar District Health Department had poor data management and reporting systems which is evidenced by: In complete reporting at 68.8%for Health Management Information System 105 and 31.3% for HMIS 108, late reporting at 68.8%, inaccurate data recording in the HMIS tools, and poor data storage. This resulted in poor ranking of the district in the national league table (107) last financial year. Follow up of timeliness and completeness is not practiced at all levels, Data presentation, analysis, validation is done singly by the Biostatistician and dissemination is not given the due consideration it deserves. These had resulted to low demand for data use by the stake holders and low utilization of data to influence decision making for effective planning to improve service delivery at the district. The District in conjunction with Makerere School of Public Health implemented an eight months’ project aimed at improving data completeness for outpatient reporting from 68.8% (HMIS 105) to 100% and for inpatient reporting from 31.3%(HMIS 108) to 100% over a period of six months. The project also aimed at improving accuracy of data collected from 50% to 100% and timely reporting from 68.8% to 100% in health department. This was anticipated to result in an improvement in district ranking on the national district league table from number 107 in FY 2011/12 to at least below 50 in FY 2012/13.

Implementation approach: In order to avert the situation, we trained six (6) records assistants and nineteen (19) health facility in charges in data collection using MoH data collection tools, conducted monthly on job mentoring and supervision in the twelve (12) health facilities/units in the district, facilitated Records Assistants to submit timely data, designed timeliness and completeness tracking tools at the Health sub-District (HSD) and the district. In addition, we held two stakeholders’ dissemination meetings to review project progress, conducted two (2) review meetings with the health facility in-charges and Records Assistants to track performance and data utilization in all the health units, provided three (3) bookshelves to Kyoga HSD, Amolatar HCIV, and District Health Office to Biostatistician for proper storage of HMIS forms and advocated for a small budget to support project sustainability. The M&E team was inspired to support and have equal rights and responsibilities to ensure completeness, accuracy, timeliness of reporting and data use at all levels.

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Achievements: As a result of the project, data completeness improved from 68.8% to 92% for outpatient reporting and 31.3% to 100% for inpatient reporting. In addition, data accuracy improved from 50% to 100%. Timeliness of reporting improved from 68.8% to 90%. As a result of these efforts, the rating of the district in the national league table improved from 107 to 25 within a period of 6 months.

Challenges: There was delayed receipt of funds which in turn delayed our implementation. In addition, the transfer of the Biostatistician from the Health Department to the Planning Unit affected timely implementation of the project. However, we overcame this problem by mentoring the HMIS focal person to take charge until a new biostatistician is recruited.

Lessons learned: During the implementation of this project it was noted that diversity of inputs is imperative for the successful competition and continuous dialogue with both institutional and academic mentors is key in the production of results while engagement of top management stimulates buy in and promotes sustainability of all projects ,on the other hand external technical support motivates stakeholders’ involvement in the implementation

Conclusion and recommendations: In conclusion, the project resulted in improved completeness, accuracy and timeliness of reporting. This eventually improving Amolatar’s rating on the national league table (the district improved by 57 positions, from 107 to 25 in 8 months). This calls for a need to joint effort to maintain data management and quality at all levels while prompt submission of monthly HMIS reports from lower health facilities to HSD and District should be greatly encouraged

1.0 Introduction & Background

1.1 Introduction Amolatar District was carved out of Lira District in July, 2005 by Parliament of Uganda. It’s located in the Northern-Central part of Uganda and is bordered by Dokolo district in the North, Kaberamido district in the East, Apac district in the North West, Kamuli district in the South and Nakasongola in the West. The District is enclosed almost on all sides by two large water bodies; namely: Lake Kyoga in the east-south-western part and Lake Kwania in the North Western part of the district. The district has a total population of 131,011 people with one administrative county and 9 sub-county and two Town Councils. It has 58 parishes and 435 villages. The District Health Department uses HMIS forms for monitoring and evaluation of health program at all levels.

Amolatar District Local Government in conjunction with Makerere University School of Public Health implemented an eight months’ project aimed at improving data completeness, accuracy and timely reporting in Amolatar District by September 2013. The project was sponsored by the US Centers for Disease Control & Prevention (CDC) through Makerere University School of Public Health.

1.2 Background

Monitoring and Evaluation (M&E) of the health response in the health sector is critical for a well-informed and strategically guided response. In line with this, the health sector is expected to provide most of the data for tracking health indicators in the Health Sector Strategic Investment plan (the national sector plan) as well as the Performance Measurement and Monitoring Plan (PMMP). This is also expected to meet other national and global reporting obligations. This requires an M&E plan aligned to the District Health Information System (DHIS2). Although the national health sector plan has a corresponding Performance Measurement and Monitoring Plan, there is currently no comprehensive M&E Framework and plan for the health sector to monitor and evaluate health interventions, given that the only framework developed during the 1990s is now obsolete. Because of this void, currently, M&E processes and tracking of program indicators in the health sector are based

1 on multiple processes that have not been harmonized into a common program-wide M&E plan and framework. Moreover data elements and indicators are not standardized. On the other hand, tracking of program outputs, processes and coverage is often characterized by multiple vertical data collection systems and tools for some interventions. The proliferation of the multiple data collection systems for specific vertical interventions overburdens health facilities and makes the data management process very expensive, incomplete and untimely. It was against this background that the District Health Department designed an intervention to improve completeness of reporting, data accuracy and timeliness of reporting in Amolatar district.

2.0 Statement of the problem, conceptual framework and project justification

2.1 Statement of the problem

Amolatar District Health Department has poor data management and reporting systems which are evidenced by: In complete reporting, late reporting, inaccurate data recording in the HMIS tools, and poor data storage. Follow up of timeliness and completeness was not practiced at all levels, data presentation, analysis, validation is done singly by the Biostatistician and dissemination is not given the due consideration it deserves. These challenges have resulted in low demand for data by the stakeholders and low utilization of data to influence decision making for effective planning to improve health service delivery in the district.

2.2 Justification for the project

Poor data management and submission affects the following:  Planning of health service deliveries both at the district and Ministry of Health (leads to wrong intervention, wastage of resources).  Ranking of the District in the league table as well as poor reputation  Budget allocation of resources  Lack of trust and interest in our data leading to low demand for data use.  Poor motivation of human resource for health

Therefore the project is justifiable to improve planning, ranking of the District in the league table, resource allocation, motivation of staff and build data demand for use in decision making for better service deliveries.

2.3 Conceptual framework

The conceptual frame work for improving data completeness, accuracy and timeliness was based on the results chain model whereby one objective leads to the next level objective as illustrated in this frame work

Fig: 1: Conceptual framework

Input Processes Output Outcome Impact

District ranking Review of the 25 people Improved data o National improved from existing trained completeness HMIS 107 last financial documents and reporting of policy,DHIS years to 25 this 3 bookshelves HMIS 105 from 2 Designed data financial year procured 68.8% to 92% o M& E team tracking tools and HMIS 108 and resource Data utilization 2 Dissemination from 31.3% to persons Facilitation to to influence meeting 100% o Other HMIS Records decision marking conducted and M&E Assistants for materials timely monthly Timely reporting -power Designed data reporting tracking tools improved from - Dissemination Financial 68.8% to 90 % meeting M& E team support Formed Review meeting.

Provision of 2 review bookshelves for meeting data storage conducted

Support 6 monthly supervision and supervision & mentorship mentoring

conducted Increased budget allocation for HMIS 3

3.0 General and Specific Objectives

3.1 General Objective To improve data completeness, accuracy and timely reporting in Amolatar District Health Department by September 2013

3.2 Specific Objectives

a) To improve completeness of HMIS 105 reporting from 68.8% to 100% and HMIS 108

from 31.3% to 100% by September 2013 b) To improve timely data reporting from the District to the Ministry of Health from

68.8% to 100% by September 2013 c) To improve data dissemination, and usage from, 0 to 50 % by September 2013

4.0 Methodology

The project was implemented through a series of activities which included among others

4.1 Capacity building

In Amolatar District, there were capacity gaps identified among data managers in lower Health facilities and the District Health Office. This therefore prompted the fellows to have a discussion with the stakeholders to have the district M&E team formed. This team comprises all the health unit in-charges, all medical record assistants and the District Biostatistician

A five days’ training was organized with the support from Makerere University School of Public Health and a total of twenty two (22) team members were trained in M&E (see photo below). The topics covered during the training included, among others, introduction to M&E concepts; data management and use; data collection methods; introduction to the different data collection tools; introduction to effective communication; introduction to logical frame

4 work; developing logical frameworks; data analysis& validation, as well as writing M&E reports.

Figure 2: Photo showing participants attending M&E training

4.2 Mentoring and Coaching Monthly support supervision, mentorship and coaching were conducted in all health facilities to ensure completeness and timeliness of reporting. The purpose of these mentorships was to promote data completeness, timely reporting and ensuring good storage. We promoted monthly and quarterly data analysis & validation. We also promoted the use of data tracking tools at the HSD. In these mentoring and supervision sessions, we also assessed the availability of data collection tools at all levels. Fellow on mentoring session in one of the Health facility

Figure 3: Mentoring session at Biko HC II

4.3 Timely submission of reports

In order to improve the timely submission of reports, data tracking tools were designed to track timeliness and completeness of reporting at the HSD and the district according Ministry of Health timelines. The M&E data managers at lower health facilities were facilitated to ensure timely reporting (see Appendix I for details)

4.4 Increase in budget allocations

Having registered some remarkable results in data management (timely and completeness of reporting) and the results disseminated to the district stakeholders, the district advocated for more resources to be allocated to health management information system and now there is support from Northern Uganda Health Integration to Enhance Services (NU-HITES) to improve data management at all levels

4.5 Meetings held

Two types of meetings were held: dissemination and review meetings, as discussed below: 4.5.1 Dissemination There were two dissemination meetings conducted with the district stakeholders to share the project progress and outcomes. One of these meetings was attended by the supervisors from Makerere University School of Public Health (see photo below).

Figure 4: One of the dissemination sessions with Facilitators from Makerere University School of Public Health

4.5.2 Review Meetings

Two review meetings were conducted to discuss the implementation strategies and to review progress so far noted and charting the way forward in improving data management and use at all levels (see picture below):

Figure 5: One of the sessions during review meeting

5.7 Storage of Information Due to poor data storage noted at all levels, we procured three (3) bookshelves and seventy two (72) box files as a demonstration for proper storage of HMIS information. The seventy two box files were distributed to all health units and District Health Office while three (3) were allocated to the HSD, health centre four (HC IV) and the DHO’s Office.

Fig. 6(b): Storage at Amolatar HCIV after before implementation Fig 6(a): Before project implementation

5.0 Project Outcomes

5.1 Improved completeness of HMIS 105 Reporting

The district registered a great improvement in data completeness of monthly reporting from 68.8 % to 92% for HMIS 105 and 31.3 to 100% for HMIS 108 and this was as a result of the intervention mentioned above

Figure 7(b): Data completeness after project implementation Fig. 7(a): Data incompleteness at Biko HC II (Before project implementation)

5.2 Improved Timely Data Reporting

Timeliness of reporting improved from 68.8% to 90%.as a result of the introduction of the data tracking tools at the Health sub-District and the District Health Office. This achievement has been clearly demonstrated in the nation league table of 2012/2013 which greatly improved the district ranking at national level from number 107 last financial years 2011/2012 to 25 this financial year 2012/2013.

5.3 Data Dissemination and Usage

As a result of data dissemination to the stakeholder which included data managers at facility levels and top managers the buy in and sustainability ideas were perceived and taken up the stakeholders. The first dissemination meeting was conducted with a backing from the central facilitators to access the progress of implementation and lay strategies in ensuring the

8 successful completion of the project. The second dissemination was conducted after the district had received the annual performance report for the financial year 2012/2013 to evaluate the evaluate the impact of the project

6.0 Lessons learned

During the implementation of this project a number of lessons were learnt which included among others. Good communication right from the inception of this project which improved health workers perception on data management which finally paved way to improved results and impact on this project Diversity of inputs is imperative for the successful completion of project because of various ideas and resources were shared Continuous Dialogue with both institutional and academic mentors is key in the production of results as they are always there to provide guidance and support towards meeting the project objectives Engagement of top management stimulates buy in and promotes sustainability as to date there is budget line created for management of data External technical support motivates stakeholders’ involvement in the implementation because their support added more value hence many are willing to enroll for M&E course

7.0 Challenges and how they were overcome

There was delay in receipt of funds however the project implementation took of immediately on realizing the need for change. With meager resources the fellows were able accomplished the project objectives There were competing activities which also promoted delays in the implementation never the less it of paramount importance that the project has to be prioritized. Transfer of biostatistician to planning unit also affected the implementation but the HMIS focal person was mentored to take charge until the new biostatistician is recruited There has been incomplete and late reporting from some health facilities however the data tracking tool was designed to monitor the trend, support supervision and mentorship to lower health facilities was strengthen

8.0 Summary, Conclusions and Recommendations

8.1 Summary The project objectives were achieved as a result of the intervention such as training and dissemination on data management which enlightened the health workers and other stakeholders about the importance of M&E and therefore M&E has gained popularity at the district There has been great improvement in data management both at the district and facility level since data is now submitted on time, accurate and complete which has greatly improved the performance of the District as reflected in the National league table of 2012/2013.

Finally the district should continue supporting the M&E team to ensure sustainability of these remarkable results. . 8.2 Conclusions

The project registered remarkable results and there was remarkable improvement in the District ranking in the National league table from 107 out of 112(2011/2012) to 25 out of 112 (2012/2013) This project was able to improve the quality of data of Amolatar health department as evidenced by the fact that data is now complete, timely and easily accessible Improvement of health services delivery requires quality data to influence planning and decision making at all levels and therefore there is serious and urgent need for ministry of health to support the districts in training more health managers and planners in monitoring and evaluation.

8.3 Recommendations There should be continuous professional development at levels to address gaps in data management.

The district should continue supporting and budgeting for Health Management Information System such as DHIS2 and m-Track.

With data dissemination to stakeholders it would therefore be important to influence decision making and facilitate advocacy for financial allocation.

8.4 Next steps The M&E team will be meeting monthly to sort out issues affecting data management and use at the district level Currently the district with support from NUHITES has taken up the issues of supporting support supervision, mentorship in data collection & recording and promoting quarterly data validation and dissemination. The fellows will continue with mentorship and supporting the lower health facilities. The district should continue supporting quarterly dissemination program to various stakeholders

References 1-Health care improvement project (2011) the validity of self-assessment data in Ugandan quality improvement program

2-National Heath sector Strategic investment plan and MoH performance measurement and monitoring plan (2010/ 2015). 3-Uganda, ministry of health annual performance reports for financial year 2012/2013 4-WHO (2011) Assessment of health facility data quality in Uganda 5WHO (2003) Improving data quality; a guide for developing countries 6-WHO (2005) the international journal of public health; Improvements to data Systems for the health sector.

Appendix I: Data tracking tools for HMIS timeliness in Amolatar District Health Department

Name of Name of Month Date Yea Status of Reported Responsible Commence the HSD the of of r report by: officer who on health report report receive timeliness Facilities reporting Kyoga May 2013 Amai 15/6 In Ayaa Okello Tom Late Hosp complete John Amolatar 5/6 Complete Atala ‘ On Time H/CIV Eunice Aputi 11/6 Complete Ogili ‘ Late H/C III Etam 12/6 Complete Apio M ‘ Late H/C III Grace Namasale 12/6 Complete Bot ‘ Late H/C III Albino Acii H/C 6/6 Complete Obwogi ‘ On time

II P Biko H/C 6/6 Complete Okwir ‘ On time II Biafra Alyechm 11/6 In Kyagulan ‘ Late eda H/C Complete gi J II Arwotcek 10/6 Complete Okello ‘ Late H/C II Tom Awonang 6/6 In Auma ‘ On time iro H/C II complete Eunice Nakatiti 5/6 Complete Okello ‘ On time H/C II Andrew Alemere 10/6 In Olung R ‘ Late MED complete Aid H/C II Kyoga June 2013 Amai 8/7 In Ayaa J Okello Tom Late Hosp complete Amolatar 3/7 complete Atala E ‘ On time H/CIV Aputi 4/7 complete Ogili ‘ On time H/C III Etam 4/7 complete Apio M ‘ On time H/C III G Namasale 5/7 complete Bot ‘ On time H/C III Albino Acii H/C 5/7 complete Obwogi ‘ On time II P Biko H/C 5/7 complete Okwir B ‘ On time II Alyechm 9/7 In Kyagolan ‘ Late eda H/C complete gi J II Arwotcek 9/7 complete Okello ‘ Late H/C II Tom Awonang 8/7 In Auma E ‘ Late iro H/C II complete Nakatiti 5/7 complete Okello A ‘ On time H/c II Alemere 9/7 In Olung R ‘ Late Med complete H/C II Kyoga July 2013 Okello Tom Amai 8/8 complete Ayaa J ‘’ Late Hosp

Amolatar 5/8 complete Atala E ‘’ On time HCIV Aputi 6/8 complete Ogili ‘’ On time HCIII Etam 6/8 complete Apio M ‘’ On time HCIII G Namasale 7/8 complete Bot ‘’ On time HCIII Albino Acii HC 7/8 complete Obwogi ‘’ On time II P Biko HC 8/8 complete Okwir B ‘’ Late II Alyecme 5/8 In Kyagolan ‘’ On time da HCII complete gi J Arwokce 6/8 complete Okello ‘’ On time k HCII Tom Awonang 8/8 complete Auma E ‘ Late iro HCII Nakatiti 6/8 complete Okello A ‘’ On time HCII Alemere 7/8 In ‘’ On time medical complete AID Kyoga August 2013 Okello Tom Amai 10/9 complete Okello C ‘’ Late Hosp Amolatar 2/9 complete Atala E ‘’ On time HCIV Aputi 5/9 complete Ogili B ‘ On time HCIII Etam 4/9 Complete ‘ On time HCIII Namasale 5/9 complete Bot ‘ On time HCIII Albino Acii 9/9 In Obwogi ‘ Late HCII complete P Biko 6/9 complete Okwir B ‘ On time HCII Ayecmed 5/9 In Kyagolan ‘ On time a HCII complete gi J Arwotcek 5/9 complete Okello ‘ On time HCII Tom Awonang 6/9 complete Auma E ‘ On time iro HCII Nakatiti 4/9 complete Okello A ‘ On time HCII 14

Alemere 6/9 In Olung R ‘ On time Medical complete AID Kyoga Septemb 2013 Okello Tom er Amai 7/10 complete Okello C ‘ On time Hosp Amolatar 3/10 complete Atala E ‘ On time HCIV Aputi 3/10 complete Ogili B ‘ On time HCIII Etam 4/10 complete Apio M ‘ On time HCIII G Namasale 3/10 complete Bot A ‘ On time HCIII Acii 7/10 complete Obwogi ‘ On time HCII P Biko 4/10 complete Okwir B ‘ On time HCII Alyecme 4/10 complete Kyagolan ‘ On time da HCII gi J Arwotcek 3/10 complete Okello ‘ On time HCII Tom Awonang 3/10 complete Auma E ‘ On time iro HCII Nakatiti 2/10 complete Okello A ‘ On time HCII Alemere 7/10 complete Olung R ‘ On time medical AID Kyoga October 2013 Okello Tom Amai 6/11 complete Okello C ‘ On time Hosp Amolatar 2/11 complete Atala E ‘ On time HCIV Aputi 4/11 complete Ogili B ‘ On time HCIII Etam 4/11 complete Apio M ‘ On time HCIII G Namasale 4/11 complete Bot ‘ On time HCIII Albino Acii 5/11 complete Obwogi ‘ On time HCII P Biko 5/11 complete Okwir B ‘ On time HCII Ayecmed 4/11 complete Kyagolan ‘ On time 15

a HCII gi J Arwotcek 5/11 complete Okello ‘ On time HCII Tom Awonang 4/11 Complete Auma E ‘ On time iro HCII Nakatiti 4/11 complete Okello A ‘ On time HCII Alemere 5/11 complete Okello C ‘ On time medical Dickens AID Kyoga Novemb 2013 er Amai Hosp Amolatar HCIV Aputi HCIII Etam HCIII Namasale HCIII Acii HCII Biko HCII Ayecmed a HCII Arwotcek HCII Awonang iro HCII Nakatiti HCII Alemere medical AID Kyoga Decemb 2013 er Amai Hosp Amolatar HCIV Aputi HCIII Etam 16

HCIII Namasale HCIII Acii HCII Biko HCII Ayecmed a HCII Arwotcek HCII Awonang iro HCII Nakatiti HCII Alemere medical AID

Appendix II: List of (M& E) team trained in Amolatar District

Name Title Qualification Location Apio Mary Grace Medical records Diploma in UDBS Etam HCIII Assistant Bot Albino Medical Records Namasale HCIII Assistant Ogili Bonny Medical records Certificate in Aputi HCII Assistant Medical Records Mundo Okello Tom Medical Records Diploma in Records Amolatar Assistant and Information Mgt HCIV/DHO Awona winfred Reg Midwife Diploma in Amolaotar HCIV Midwifery Okello caeser E/midwife Certificate in Amai Hospital Midwifery Auma Teddy Com Nurse Certificate in Com Namasale HCIII Nurse Awor Anna Bongo E/midwife Certificate in Aputi HCIII midwifery Apio Grace Reg Nurse Diploma in Nursing Amolatar HCIV

Angom Catherine Reg Nurse Dilpoma in Nursing Etam HCIII Muni Odongo Norman Clinical Officer Diploma in Clinical Namasale HCIII medicine Achola Hellen Nursing Assistant Alyecmeda H/C II Odur Alex Clinical Officer Diploma in Clinical Aputi HCIII medicine Acio Roseline Clinical officer Diploma in Clinical Amolatar HCIV Medicine Okori Debula Clinical Officer Diploma Etam H/C III Lango James Nursing Officer Diploma Namasale H/C III Okello Tom E/ Com Nurse Certificate in Arwotcek HCII enrolled Comprehensive Nurse Auma Eunice E/Nurse Certificate in Nursing Awonangiro HCII Okello Andrew E/Nurse Certificate in Nursing Nakatiti HCII Kyagolanyi James E/Nurse Certificate in Nursing Alyecmeda HCII Ogwal Alex ADHO (Env’t DHO’s Office Health) Acheka Edmonton ADHO ( MCH) DHO’s Office