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HUMAN RESOURCES FOR HEALTH AUDIT REPORT 39

MINISTRY OF HEALTH

HUMAN RESOURCES FOR HEALTH AUDIT REPORT

2017/18

“Improving HRH Evidence for Decision Making”

HUMAN RESOURCES FOR HEALTH AUDIT REPORT i

THE REPUBLIC OF UGANDA

Ministry of Health

HUMAN RESOURCES FOR HEALTH AUDIT REPORT

2017/18

“Improving HRH Evidence for Decision Making”

Nov. 2018

HUMAN RESOURCES FOR HEALTH AUDIT REPORTii

Table of Contents

List of Tables:...........................................................................................................................................................................ivList of Figures..........................................................................................................................................................................ivForeword....................................................................................................................................................................................vAcronyms..................................................................................................................................................................................viExecutive Summary.............................................................................................................................................................viii1.0 Introduction..............................................................................................................................1 1.1 Background................................................................................................................................................................1 1.2 Utilization of the Data obtained from the HRH Audit ..............................................................................1 1.3 The Structure of the HRH Audit Report 2017/2018...................................................................................1 1.4 The Purpose of the HRH Audit............................................................................................................................2 1.5 The Specific Objectives of the HRH Audit.....................................................................................................2 1.6 Methodology.............................................................................................................................................................2 1.6.1 The Central Level...........................................................................................................................................2 1.6.2 The Local Government (District) Level..................................................................................................3 1.6.3 The PNFP and PFP Health Sub-sector...................................................................................................3 1.6.4 Other Government Ministries, Parastatal, Departments or Agencies.......................................3 1.6.5 Definition of Excess Staffing and Clarification of Coexistence with Vacancies.....................42.0 Keyfindings/auditsummaries................................................................................................5 2.1 Overall National HRH Staffing level..................................................................................................................5 2.1.1: Trends of Public staffing at National Level for over 9 years (2009/10 – 2017/18).............5 2.1.2: Staffing by Region.......................................................................................................................................6 2.1.3 Other Government Ministries with Health Facilities........................................................................7 2.1.4 Staffing for Selected Cadres in the Public Health Sector..............................................................7 2.1.5 Gender Composition of the Health Workers in Public Health Facilities...................................8 2.2 Central Level Staffing.............................................................................................................................................8 2.2.1 Ministry of Health Headquarters.............................................................................................................9 2.2.2 Mulago and Butabika National Referral Hospital..........................................................................10 2.2.3 Regional Referral Hospitals.....................................................................................................................11 2.2.4 Staffing at MOH National Institutions................................................................................................12 2.3 Staffing at District Level.......................................................................................................................................12 2.3.1 The Staffing Trend at the District Level Over 9 Years....................................................................12 2.3.2 The Staffing Trend at the Lower Level Health Facilities 2009-2018........................................13 2.3.3 Public General Hospitals .........................................................................................................................14 2.3.4 Public Health Centre IV Level.................................................................................................................15 2.3.5 Public Health Centre III Staffing............................................................................................................15 2.3.6 Public Health Centre II Staffing...........................................................................................................16 2.4 Private Not for Profit Health Sub-Sector Staffing.....................................................................................16 2.5 Private for Profit (PFP).........................................................................................................................................17

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3.0ConclusionandRecommendations...........................................................................................18 3.1 Conclusion...............................................................................................................................................................18 3.2 Recommendations................................................................................................................................................194.0InstructionsonaccessingOnlineHRHauditreportdatafromHRIS....................................205.0ANNEXES......................................................................................................................................23 ANNEX 1. Staffing of RRHs as at June-2018......................................................................................................23 ANNEX 2: Summary of the HRH Staffing Levels in each of the 128 Districts - In Alphabetical Order.................................................................................................................................................................................23 ANNEX 3: Summary of the staffing Levels at the District Health Officers’ Offices in 128 Districts .............................................................................................................................................................................................26 ANNEX 4: Summary of the HRH Staffing Levels in each of the 179 Health Centre IVs - In District alphabetic Order...........................................................................................................................................................29 ANNEX 5: Summary of the HRH Staffing levels Health Centre III Level in 128 districts- In Alphabetic Order by District.....................................................................................................................................31 ANNEX 6: Summary of the HRH Staffing Levels in each of the 1,712 Health Centre IIs - In alphabetic order by District......................................................................................................................................34

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List of Tables:

Table 1: Number of facilities per bureau……………………………………………………………….......................................3Table 2: Number of facilities in Government Departments………………………………………..…............................4Table 3: Public and PNFP sector national staffing level -June 2018……………………………………………...…….5Table 4: Average staffing by region……………………………………………………………………………………………........…6Table 5: Staffing level- Prisons and Police Health facilities -June 2018…………………………………….…....…..7Table 6: Staffing Level for Critical Cadres in Public sector-June 2018………………………………………..….……8Table 7: Summary of Central Level staffing- June 2018…………………………………………………...………..…….…9Table 8: MOH HQ staffing for FY 2016/17 and 2017/18 using different Scenarios………………………....…9Table 9: Staffing trends in the 14 RRHs over 9 years – 2009/10 to 2017/18…………………………………..…11Table 10: Summary of staffing at DHOs’ offices focusing on substantially appointed staff-June 2018.......................………………………………………………..……………………………………………….........................13Table 11: Summary of overall staffing in 45 General Hospitals by order of merit………………….…..…….14Table 12: PNFP staffing by Bureau and level of care -June 2018………………………………………………………16

List of Figures

Figure 1: National staffing trends for the last 9 years -2009/10-2017/18………………...................................6Figure 2: Staffing trends at Mulago and Butabika NRHs -2009/10-2017/18…………….....................…..….10Figure 3: Regional referral Hospital staffing level-June 2018………………………………….................................11Figure4: Staffing trends at district level over 9years -2009/10 -2017/18…………….......................…..…….12Figure 5: District Staffing trends by level – 2009/10 – 2017/18…………………………........................…. . ...….13

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Foreword

This 2017/2018 Annual Human Resources for Health (HRH) Audit report is the 9th in series and was compiled by the Ministry of Health (Department of Human Resource Management) with support from USAID-funded Strengthening Human Resource for Health (SHRH) Activity that is implemented by IntraHealth International. The report provides an analysis of staffing levels based on the staffing norms at the different levels of health service delivery.The purpose of the audit is to update the available HRH information, provide analysis of the Human Resources for Health data to establish current staffing levels, gender composition and share with all stakeholders for planning, decision making and resource allocation in both public and Private Not-For Profit (PNFP) health facilities.

The data obtained from the audits is for making evidence-based decisions. It is also a tool for monitoring staffing levels, planning and budgeting for salaries, attraction, retention, training and development of health workers. The data equally informs policy, facilitates gender responsiveness, improved quality of health care service delivery, and equity in health workforce. I therefore urge all health managers to use the information in the Audit Report to plan for Human Resources for Health in their respective facilities.

I commend the MOH Department of Human Resource Management for putting together this report and all key stakeholders that included; line ministries, District Local Governments (DLGs), departments and agencies, particularly ministries of Public Service and Local Government, Health Professional Councils (HPCs), Health Service Commission and Religious Medical Bureaus for providing the relevant information for this report.

Finally, the Ministry extends its appreciation and gratitude to Dr. Vincent Oketcho, Chief of Party, Dr. Susan Wandera, Deputy Chief of Party, Dr. Haruna Lule, Senior Advisor Human Resource Management, Mr. Ismail Wadembere and all staff of IntraHealth International for the support given to produce this report.

Dr. Diana AtwinePermanentSecretaryMinistry of Health

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Acronyms

ACHRM : Assistant Commissioner Human Resources Management ADHO MN : Assistant District Health Officer Maternal Child ADHO EN : Assistant District Health Officer EnvironmentAPPOVD : ApprovedBIO-S : Bio-StatisticianBTCs : Big Town CouncilsCCT : Cold Chain TechnicianCO : Clinical OfficerDD : District DataDHOs : District Health Officers/OfficesDLGs : District Local GovernmentsDRIV : DriverDT : District TotalE.M : Enrolled MidwifeE. N : Enrolled NurseENT : Ear, Nose ThroatEXC/E : ExcessFLD/F : FilledGHs : General HospitalsH. ASST : Health AssistantH. INF ASST : Health Information AssistantHC : Health Centre HMDC : Health Manpower Development CentreHMIS : Health Management Information SystemHNA : Health Nursing AssistantHRH : Human Resource for HealthHRIS : Human Resources Information SystemHRM : Human Resource ManagementHSSP 1 : Health Sector Strategic Plan 1HSSIP : Health Sector Strategic Investment PlanHWF : Health WorkforceHWs : Health WorkersiHRIS : Integrated Human Resource Management SystemMCs : Municipal CouncilsMO SG : Medical Officer Special GradeMO : Medical OfficerMOFPED : Ministry of Finance, Planning and Economic DevelopmentMOH : Ministry of HealthMOPS : Ministry of Public ServiceN : NormsN. ASST : Nursing AssistantNCR1 : Natural Chemotherapeutics Research InstituteNHF : National Health FacilityNO (N) : Nursing Officer (Nursing)NRH : National Referral HospitalOFF.AT : Office AttendantPNFP : Private not for ProfitPO : Personnel Officer

HUMAN RESOURCES FOR HEALTH AUDIT REPORT vii

PPO : Principal Personnel OfficerRHRM : Regional Human Resource ManagementRRHs : Regional Referral HospitalsSCO : Senior Clinical OfficerSEHO : Senior Environment Health OfficerSHE : Senior Health EducatorSPO : Senior Personnel OfficerST. ASST : Stores AssistantSTCs : Small Town CouncilsSTD : Sexually Transmitted DiseaseSTENO S : Stenographer SecretarySHRH : Strengthening Human Resources for HealthTB : Tuberculosis TOR : Terms of referenceUBTS : Uganda Blood Transfusion ServicesUCI : Uganda Cancer InstituteUCMB : Uganda Catholic Medical BureauUCP : Uganda Capacity ProgrammeUHI : Uganda Heart InstituteUMMB : Uganda Muslim Medical BureauUPMB : Uganda Protestant Medical BureauUSAID : United States Agency for International DevelopmentUVRI : Uganda Virus Research InstituteVACA/V : Vacant/Vacancy

HUMAN RESOURCES FOR HEALTH AUDIT REPORTviii

Executive Summary

ContextandBackground

In pursuit of UgandaVision2040, the health sector is expected to ensure a healthy and productive population that effectively contributes to socio-economic growth achievable through provision of accessible and quality health care to all people in Uganda by competent and motivated health workers. It is also known that the country needs an adequate and well-skilled health workforce to achieve especially the third Sustainable Development Goal which is meant to “Ensure healthy lives and promote well-being for all at all ages”.

The MOH therefore monitors progress towards achievement of the desired health workforce goals principally through conducting annual HRH audits. Using these HRH Audits, the MOH monitors the staffing levels of the health facilities and plan interventions for improvement accordingly. This evidence-based planning has helped MOH and Districts recruit health workers according to need and resulted in the upward trends of overall public staffing levels over the last 8 years from 53% (2009/10) to 76% (2017/18) observed over the last 9 years.

This 2017/2018 Annual HRH Audit report is the 9th in series and was compiled with support from USAID-funded Strengthening Human Resource for Health (SHRH) Activity, implemented by IntraHealth International working in collaboration with MOH. The report provides the staffing norms and the filling rate of the staffing norms at the different levels of the sector. Purpose

The purpose of the audit is to update the available HRH information, conduct analysis of the HRH data to establish current staffing levels, and share with all stakeholders for planning, decision making and resource allocation in both public and PNFP health facilities. The Audit also establishes the gender composition of the entire health workforce in Uganda.

Specificobjectives The specific objectives of this audit were to update the HRH data for the year 2017/18 from the previous staff audit; establish the proportion of the approved positions filled by appropriately trained health workers; and to identify staff and skills shortages; assess equity in the distribution of health workforce; provide HRH information that could be used for planning, budgeting and informed decision-making by all the stakeholders; and identify and report any data gaps in the HRH database that need to be addressed. Methodology

The main source of data for this HRH Audit was the Human Resources for Health Information System (HRIS). The HRIS reports were updated to include tables that were critical to produce a comprehensive audit report that provides adequate evidence for decision-making. To improve quality and accuracy of HRIS data, MOH directed all central health institutions and districts to update and clean the HRIS data. A joint team from Ministry of Health and SHRH worked alongside a consultant to incorporate the HRH audit report template into the HRIS and validated all staff data from institutions and districts for consistence, completeness and accuracy. Secondary data analysis was conducted and interpreted accordingly by the Joint MOH/SHRH team.

FindingsThe HRH analysis for the 2017/18 audit report covered 3,300 public and 468 PNFP health facilities. The public health facilities had a total of 62,942 established norms of which 47,661 were filled

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constituting 76% of available positions filled. This maintained the upward trend of public staffing levels observed over the last 9 years. Although this was a positive trend, it was still below the Health Sector Development Plan (HSDP) target of 80% by 2019.

53% 56% 58% 58% 61%69% 70% 71% 73% 76%

80%

0%10%20%30%40%50%60%70%80%90%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

% Staffing Target

The PNFP facilities had a total of 17,629 staffing norms as per the public staffing norm framework and 14,784 were filled constituting 84%. A National combined public and PNFP staffing level was at 77.5%.

Despite continuous improvement in the overall national staffing level over time, there is persistent critical shortage of some health cadres like anaesthetic officers, dispensers, pharmacists, theatre assistants and public health nurses. There was however relative overstaffing for some cadres like Clinical Officers (104%) and Laboratory staff (102%).

Marked improvement in staffing levels was realized for the doctors from 57% (2017) to 63% 2018), midwives from 78% (2018) to 94% (2018).

Overall, the health workforce employs more women than men at all levels of service delivery (at 54% females and 46% males). Nursing, midwifery and theatre staff cadres were dominated by women while men dominated the higher-level and administrative positions such as senior consultants (over 85% male), directors (over 90% male) and District health officers (over 95% males).

MOH Headquarters had 884 staff occupying positions but only 408 were appointed as per the establishment in the New structure (of 634 norms) constituting 64% filled positions. Of the 884 staff in positions at the HQs, 476 were either staff hired by MOH Development Partners or were in acting positions.

The staffing levels for Mulago and Butabika NRHs stood at 79% and 101% respectively. The staffing at Butabika may be elusive since it is based on old staffing norms which is no longer commensurate with the current work load.

There was a marked decline in staffing levels at Mulago NRH in 2017/18 which was probably caused by the opening of Kiruddu and Kawempe hospitals that shared part of the workforce for Mulago NRH and with no corresponding replacement.

Analysis of average staffing level per region focusing on staffing of districts in a given region indicated that West Nile region had the highest overall staffing levels followed by Northern region. While

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Karamoja and South West (Ankole) region ranked the lowest. Generally, the country has started recording improvements in equitable distribution of health workers because many upcountry/ rural districts compared favorably with the traditional central districts that previously outweighed the former because of their favorable locations.

The overall proportion of the approved positions filled in the 14 RRHs was 75%. This indicated a decline of 5% from the previous financial year 2016/17. This decline was largely due to retirement of many very senior specialists. Despite their small number, there was no immediate replacement since the people to replace them are very few or even not available on market yet. For example, senior consultant surgeon and physician in Jinja RRH and one senior consultant surgeon in Soroti RRH had retired during the year under review but were still not replaced. Overall staffing at the district level of positions filled by appropriately appointed and qualified health workers was at 75% for all the 128 districts (KCCA inclusive) showing a 4% increase over the previous year (MOH HRH audit report, 2016/17).

There was a total of 3,279 health facilities compared to 3,135 in 2016/17 from all the districts. Therefore, in the year 2017/18,144 additional health facilities were included on the previous year’s list for analysis. The 144 health facilities included new facilities opened during the year and those facilities that existed but had not been included in HRIS. The 3,279 health facilities had a total norm of 53,072 posts and 39,588 staff in post constituting 75% of positions which was an improvement from 71% in 2016/17.

Following the downsizing of the staff establishment at the DHOs’ office from 11 to 8 (See table 10), in 2014/15, there was an apparent decline in staffing at this level since the three of the staff cadres (secretary, drivers, accounts assistant) that used to be counted at the DHO’s office were now under the district administration pool staff. The overall staffing at the DHOs’ office was at 46% compared to about 56% in the previous year. The results show Assistant DHOs (MCH and Environment), Senior Health educators, Senior Environmental Health officers, Assistant Inventory Management Officers and Cold Chain Technicians were varyingly few at this level.

The staffing level of approved positions filled by appropriately trained and qualified health workers in the analyzed 45 public general hospitals was at 76% reflecting an improvement from 68% in 2016/17. At HCIV level with 8,592 positions available according to norms, 7,454 were filled giving an overall staffing of 87% hence an increase from 84% in 2016/17. In the same year, overall staffing at HC III level was 80%. while staffing at HCII was 55% - an improvement of 2% from the previous year. HCIIs are the most poorly staffed in the system. It should be noted that the staffing norms are old and therefore don’t necessarily respond to the workload in the district Health facilities

The overall staffing level for all the PNFP health facilities was 84% - higher than the public subsector staffing of 75.7%. UCMB has the most facilities out of the 4 bureaus and the highest staffing level. UOMB is relatively new compared to the others and has the fewest facilities. UMMB has the lowest staffing at 46%.

Conclusion

The overall national HRH staffing levels maintained a general upward trend observed over the last 8 years and public health workforce employs more women than men at all levels (at 46% males and 54% females). Despite continuous improvement in the national staffing level over time, health workforce shortages persisted with cadres like Anaesthetic officers still very few. This may slow efforts for the country to achieving the NPDII and SDG targets.

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The staffing levels in public facilities in many circumstances are elusive because old staffing norms are no longer commensurate with the existing workload changes that have taken place over time following population growth, changes in disease burden and demand in health services. This calls for urgent actions to review the structures and also encourage the use of tools like WISN that promote deployment according to workload and need. HCIIs were poorly staffed compared to other levels of health service delivery and therefore provided substandard services. This situation can be averted by implementing the new health reform of upgrading all health centres IIs to HCIII. Although the PNFP subsector staffing level were higher (84%) compared to public (76%), this was likely to be very subtle since PNFP facilities were subjected to the Public staffing norm framework that under or over scored some facilities giving a deceptive impression contrary to the reality on the ground. This therefore calls for development of standard PNFP staffing norms independent of the public.

Recommendations

1. PNFPs need to be supported to develop staffing norms for their different levels of service delivery for better comparability.

2. There is a need to fast track the review of staffing structures in public sub-sector to accommodate the many health workers who occupy positions beyond the established norms due to the sector need so that they handle workload at respective workstations.

3. Support is needed for Karamoja Region particularly Amudat and Moroto districts to improve their health worker attraction and retention packages to improve their staffing that has persistently remained low.

4. Government should develop strategies to train and deploy more anaesthetic officers who are still few on market and therefore very difficult to attract and retain.

5. The government should actualize the decision to upgrade health center IIs to IIIs in the country or plan to increase staffing at this level in the short term to improve service delivery.

6. Prioritize filling of vacant positions at DHOs’ office in the country to improve staffing at this level in order to improve leadership and governance of district health service directorates for better health service delivery.


1.0 Introduction

1.1Background

In pursuit of UgandaVision2040, the health sector aims at producing a healthy and productive population that effectively contributes to socio-economic growth achievable through provision of accessible and quality health care to all people in Uganda. Therefore, the roles and contributions of all health care players and providers(healthworkers) remain pertinent in the implementation of the Second National Development II (NDPII). It is also known that the country needs an adequate and well-skilled health workforce to achieve the Sustainable Development Goals (SDG) especially the SDG Goal 3 which is meant to “Ensure healthy lives and promote well-being for all at all ages”.

The goal of Uganda’s Ministry of Health Human Resource Strategic Plan (2005 – 2020) is “To supply and maintain an adequately sized, equitably distributed appropriately skilled, motivated and productive workforce matched to the changing population needs and demands, health care technology and financing.” (MoH, June 2007). This plan responds to the Health Sector Development Plan (HSDP) 2015/16 - 2019/20 and operationalizes the Human Resource for Health Policy. The Human Resource for Health Policy (MoH, April 2006), and therefore the Human Resource Strategic Plan, were developed in the context of achieving a reduction in the burden of disease and a subdued population growth rate. The HRH strategic plan foresees a national reduction in population growth (from 2.5% to1.7 %), HIV infection rate (2.5% to 0.5%), Infant Mortality Rate of only 10 per 1,000 live births and a maternal Mortality Rate of 200 per 100, 000 live births and total fertility rate of 3.4 children (from 6.9). It also foresees Ugandans having 5,000 persons per doctor (from 18,600) and 1,000 persons per nurse (from 7,700).

To achieve these health targets, Uganda needs an adequately sized and equitably distributed health workforce that is appropriately skilled, motivated and productive. The Ministry of Health is therefore mandated to monitor progress towards achievement of such a workforce – principally through this annual HRH audit. Through annual HRH Audits, MOH has been able to monitor the staffing levels of the health workers and plan accordingly. This evidence-based planning has helped MOH and Districts recruit health workers according to need and is attributable to the upward trends of staffing levels observed at all levels of health care facilities in the last 8 years.

This 2017/2018 Annual Human Resources for Health Audit report is the 9th in series. The process of compiling this report was supported by USAID funding through the Strengthening Human Resource for Health (SHRH) Activity implemented by IntraHealth International working in collaboration with MOH.

1.2UtilizationoftheDataObtainedfromtheHRHAudit

The HRH data obtained from the audits is needed by all the stakeholders for making evidence-based decisions. It’s a tool for monitoring staffing levels, planning and budgeting for salaries, attraction, retention, training and development of HWs. The data equally informs policy; facilitate gender responsiveness, improved quality of health care service delivery, and equity in health workforce.

1.3TheStructureoftheHRHAuditReport2017/2018

The report gives background information, the purpose and specific objectives of the report and explains the processes followed in collecting, capturing and analyzing the data. The report also provides the staffing norms and proportion of approved norm filled in each institution, district and other levels of health care, or the individual health facilities.

HUMAN RESOURCES FOR HEALTH AUDIT REPORT2

The order of presentation of report findings is as follows:1. National level including Ministry of Health, National Referral Hospitals (NRHs), Regional

Referral Hospitals (RRHs) and institutions2. District level covering General Hospitals, DHO’s Office, Health Centres IVs, IIIs and IIs,

municipal council health offices and town council health offices as well as single health units within the DLGs

3. Private not-for profit (PNFP) health facilities under the four faith-based medical bureaus

The report presents key findings and their interpretation in the context of findings of previous audit reports. Finally, the report gives instructions to the reader on how to access Audit report detailed data from the online Human Resource Information System (HRIS).

1.4ThePurposeoftheHRHAuditThe purpose of the audit is to update the available HRH information, conduct analysis of the HRH staff data to obtain HRH information on staffing levels and available skills to be shared with all stakeholders for planning, decision making and resource allocation in both public and PNFP health facilities. The Audit also establishes the gender composition of the entire health workforce in Uganda.

1.5TheSpecificObjectivesoftheHRHAuditThe specific objectives of the audit are:

1. Collect and update the HRH data for the year 2017/18 from the previous staff audit.2. Establish the proportion of the approved positions filled by appropriately trained health

workers and to identify staff and skills shortages.3. Provide HRH information that could be used for planning, budgeting and informed decision-

making by all the stakeholders.4. To identify and report any data gaps in the available databases that needed to be addressed.5. Add an objective on equitable deployment and skills mix

1.6Methodology

The Human Resources Information System (HRIS) has been updated to include key audit tables so that the data is easy to access and analyze by decision-makers at all levels using this system. Since it was decided that all main HRH audit report data to be generated from HRIS, there was targeted effort by MOH to engage all health institutions and Local governments to update their data in HRIS. A circular by the Permanent Secretary of the MOH was sent to all institutions and DLGs requesting them to update their staff data. Where updates were not forth coming, the MOH call center and SHRH teams were used to follow up with a call or visit institutions/districts. This approach ensured that data in the HRIS was as it was on the ground and therefore more reliable and of desired integrity.

A joint team from MOH and SHRH worked alongside a consultant to incorporate the HRH audit templates into the HRIS and improve as appropriate. This same team also validated all staff data from institutions/DLGs for consistence, completeness and accuracy. All these measures were intended to control the quality of data and the subsequent reports generated. Secondary data analysis was conducted and interpreted accordingly by the Joint MOH/SHRH team. The analyzed data was presented by level as out lined below. 1.6.1TheCentralLevelThe institutions that fall under this level or category included:

1 Ministry of Health Headquarters2 National Referral Hospitals (NRHs) comprising 2 units namely; Mulago Hospital and Butabika

Hospital


3 Regional Referral Hospitals (RRHs) 14 units including; Jinja, Mbale, Mbarara, Fort Portal, Hoima, Kabale, Arua, Gulu, Soroti, Lira. Masaka, Moroto, Mubende and Naguru

4 National institutions namely: Uganda Virus Research Institute (UVRI), Uganda Cancer Institute (UCI), Uganda Heart Institute (UHI), Uganda Blood Transfusion Services (UBTS)

1.6.2TheLocalGovernment(District)Level

The health care facilities at this level or category included: 1. District Health offices in 127 districts and Kampala Capital City Authority (KCCA)2. General (District) Hospitals (GHs) – 45 3. Health Centre IVs (HCIV)- 1794. Health Centre IIIs (HCIII)- 9915. Health Centre IIs (HCII)- 1,7126. Municipal Councils (MCs)- 467. Town Councils (both big and small)- 131

1.6.3ThePNFPandPFPHealthSub-sector

In this sub-sector, the audit covered faith-based health facilities under the four medical bureaus including the Uganda Catholic Medical Bureau (UCMB), Uganda Protestant Medical Bureau (UPMB), Uganda Muslim Medical Bureau (UMMB) and the Uganda Orthodox Medical Bureau (UOMB) which have several accredited health facilities across the country providing not-for-profit Health services. It was not possible however to get the data from the PFP health facilities because they are not captured in the HRIS and there was no time to collect that information from the facilities. Table 1 Below summarizes the number of PNFP facilities at each level per Medical Bureau.

Table 1: Number of facilities per Bureau

S# BUREAU GENERAL HOSPITAL HCIV HCIII HCII Total

1 UCMB 32 8 176 79 2952 UPMB 19 9 27 48 1033 UMMB 5 2 25 20 524 UOMB 1 1 3 12 18

Total 57 20 231 159 468

It should be noted that although Lacor (UCMB), Rubaga (UCMB), Namirembe (UPMB), Nsambya (UCMB) and Kibuli (UMMB) are captured as General Hospitals under their respective bureaus they operate like Regional Referral hospitals.

1.6.4OtherGovernmentMinistries,Parastatal,DepartmentsorAgencies

Apart from the MOH, there are other government ministries, parastatals, departments or agencies tApart from the MOH, there are other government ministries, parastatals, departments or agencies that run health facilities and therefore employ health workers. To give a comprehensive country HRH picture, data from these entities was also collected and analyzed where possible. Government ministries with health facilities are mainly Ministry of Defense (UPDF Health Department) and Ministry of Internal Affairs mostly in Uganda Prison Service and Uganda Police Force (table 2) and to some extent Ministry of Education and Sports, Science and Technology.


Table 2: Number of facilities Government Departments

Ministry/Agency Health Department

General Hospital HCIV HCIII HCII Total

Uganda Prison Services 1 1 1 19 21 43Uganda Police Force (UPF) 1 0 11 15 70 97

Total 2 1 12 34 91 140

Like PNFP facilities, these ministries did not have standardized structures and norms. Nevertheless, their facilities were equated to the mainstream health sector facility levels and categorized accordingly.

It was not however possible to get the numbers of health facilities and health workers under Ministry of Defense and for schools (Primary, Secondary and tertiary institutions) since these are also part of the health workforce in the country.

1.6.5DefinitionofExcessStaffingandClarificationofCoexistencewithVacancies

In the report, some positions or posts were reflected as having excess staff. “Excess staffing” occurs when the number or proportion of the staff filling the approved positions is more than the approved norms for the level/unit of health care. It can occur under any of the following circumstances:

• When the number of staffs in post is more than the approved norm. For example, if there are 10 medical officers in post but the approved norm is 6, 4 of those Medical Officers would be considered “excess”.

• The staffs in post are holding positions which are not in the structure of that particular health facility. These will be described as “excess” for the number allowable by the structure.

It is worth noting that whereas some posts have excess staff who have no room in the structure for a given facility, there may also be other posts in the same facility or institution which have vacancies that require filling by recruitment of more staff of the cadre lacking and needed in the structure to fill the gap. For example, in a given health facility, you may have a staffing norm of 4 enrolled nurses but have 8 in post and on the other hand a norm of 4 midwives but only 2 filled. This facility will have a total norm of 8, with total filled of 10. The 4 nurses are reflected as “Excess” but at the same time have a vacancy of 2 Midwives (Health workers).


2.0 Key findings/audit summaries

This section discusses major findings following the analysis of HRH data from HRIS.

2.1OverallNationalHRHStaffinglevel

The analysis for the 2017/18 audit covered 3,300 public health facilities. These facilities had total norm of 62,942 posts, of which 47,661 (76%) and 15,126 (24%) vacant positions (table 3). The public staffing level of 76% reflected an increase from 73% achieved in last year 2016/17. This increase in staff could be attributable to improvements in the capacity of central institutions and districts to analyze wage and plan for and complete recruitment.

Analysis of PNFP covered 468 facilities of different levels with a total norm of 17,629 using the public staffing level standards since PNFPs do not have one yet. Of the 17,629 positions, 14,784 (84%) were found filled while 2,845 (16%) were vacant, (Table 3). When both staffing norms for public and PNFP covered in this report were combined, the total was 80,571 of 62,445 (77.5%) positions that were filled;

Table 3: Public & PNFP Sectors; National Staffing Level, June 2018

Cost Centre No of Units Total Norms Filled Vacant % Filled %Vac

MOH/Central institutions 21 9870 8073 1797 82% 18%Districts 3,279 53,072 39,588 13,484 75% 25%Total (public sector) 3,300 62,942 47,661 15,281 76% 24%

Cost Centre No of Units Total Norms Filled Vacant % Filled %Vac

PNFPs 468 17,629 14,784 2845 84% 16%Total (Public &PNFPs) 3,768 80,571 62,445 18,126 77.5% 22.5%

At 84% staffing levels, PNFPs looked better staffed than the public at 76%. However, the contrary is true in reality. The high staffing levels exhibited here may be because PNFP sub-sector lack standard staffing norms hence subjected to the public staffing norms framework where some facilities were assessed at levels below the range of services they gave.

For example in this analysis, PNFP hospitals like St.Mary’ Lacor, Lubaga, Mengo, Nsambya and Kibuli were considered as General hospital yet the function like regional referral Hospital with probably bigger staff than recommended for Public general hospitals. Generally, staffing in PNFP is expected to be lower than in Public since they are constrained by funds to hire profession at competitive packages. Their salaries therefore usually tend to be lower compared to public health facilities. For example, a Medical officer in PNFP sector gets an averaged gross monthly salary of about UGX. 2.7m compared to a gross consolidated monthly salary of UGX 3.1m for a medical office in public sector. An enrolled nurse in the public sector earns a consolidated gross monthly salary of UGX 760,000 while the counterpart in PNFP sector earns UGX 450,000.

2.1.1:TrendsofPublicstaffingatNationalLevelforover9years(2009/10–2017/18)

Figure 1 shows the general trends of staffing levels in the country over the last 9 years. This trend gives hope that the public health sector may achieve its HSDP target of 80% staffing by 2018/2019 (fig.1). However, this progress is threatened by the current restrictions on recruitment of new staff in public sector safe for replacement of staff who leave, retire or die.


Fig.1 Public National staffing trends for the last Nine years (2009/10 to 2017/18)

53% 56% 58% 58% 61%69% 70% 71% 73% 76%

80%

0%

20%

40%

60%

80%

100%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018% Staffing Target

Despite continuous improvement in the national staffing level over the time, health workforce shortages still exist in Uganda. This poses a potential threat for the country not to achieve the SDG targets. There are shortages of staff generally, imbalances in skill mix, and inequitable distribution of health workers. The country health workers per 1,000 population (1.82 per 1000 population) is still below the World Health Organization (WHO) recommended standard of 2.3 health workers (doctors, nurses or midwives) per 1,000 people. A major factor contributing to the apparent low progress in this ratio is the high population growth rate in the country without necessarily corresponding increase in the health workforce. Staff attraction and retention particularly in rural locations continues to be a challenge and grossly affect staff performance and health care service delivery in general.

2.1.2:StaffingbyRegion

Analysis of average staffing level per region focusing on staffing of districts in a given region indicated that West Nile region had the highest overall staffing levels followed by Northern region. While Karamoja and South West (Ankole) region ranked the lowest. Table 4. This indicates that the country has started recording improvements in equitable distribution of health workers where upcountry or rural based districts are presumed to have recruited more health workers for their health facilities to fill the vacant posts. One may also assume that the fewer the facilities in a district (which is the case with many upcountry districts particularly the new ones), the easier it may become for such a district to fill its vacant posts and improve its staffing levels.

Many of these districts prioritized recruitment of health workers and have had numbers increase. However, it should be noted that although many districts in Karamoja region have fewer facilities, it has a peculiar problem of attracting and retaining health workers hence keeping the region with low staffing levels. Table 4: Average staffing levels by Region

S# Region Total # of Districts Average%ageFilled1 Central 26 73%2 East Central 11 74%3 Eastern 25 71%4 Karamoja 8 68%5 Northern 17 84%6 South west 17 68%7 West Nile 9 89%8 Western 15 79%

128 76%


Although it is presumed that staffing in the central region should be better than the rest of the regions because it has more opportunities to attract more health workers, the analysis indicated the contrary. One of the explanations could be that, besides having hard-to-reach spots like Buvuma and Kalangala Districts, many central districts have many health facilities of different levels which make it difficult to fill the vacant posts to desired levels budgetary constraints notwithstanding. The other reason could be that the Health worker labour market in the central region is vast given the many private health entities (PFPs, NGO) therein competing with districts for health workers hence creating an unfavorable environment for districts to attract particular cadres of health workers. This is however likely to improve with the enhanced salaries for public sector health workers.

2.1.3OtherGovernmentMinistrieswithHealthFacilities

This year, the audit team was able to asses other government ministries with health facilities. Of main interest were the Ministry of Defense (UPDF Health Department) and Ministry of Internal Affairs (Uganda Prison Service and Uganda Police Force) since their facilities also provide health care to the public. Like PNFP facilities, these ministries do not have standardized structures and norms. It was however not possible to get data from Ministry of Defense despite several attempts. The analysis therefore covered Police and Prisons forces only.

Table 5: Staffing level – Prisons and Police Health Facilities-June 2018

Cost Center

Facility Level

No of Units Total Filled Vac Excess %

Filled% Vac Male Female %

Health Dept. 1 23 10 14 1 43% 61% 7 3 30%Hospitals 1 361 53 308 0 15% 85% 30 23 43%HC IVs 1 48 39 28 19 81% 58% 5 34 87%HC IIIs 19 361 115 259 13 32% 72% 49 66 57%HC IIs 21 189 35 154 0 19% 81% 21 14 40%Subtotal 43 982 252 763 33 26% 78% 112 140 56%Hospitals 0 0 0 0 0 0% 0% 0 0 0%HC IVs 11 528 141 423 36 27% 80% 78 63 45%HC IIIs 15 285 67 231 13 24% 81% 31 36 54%HC IIs 70 630 98 578 46 16% 92% 49 49 50%Subtotal 96 1443 306 1232 95 21% 85% 158 148 48%

Grand Total 139 2425 558 1995 128 23% 82% 270 288 52%

The staffing levels in prisons and police health facilities are far below the staffing levels in public and PNFP facilities. Only 23% of positions are filled compared to 76 % in the public and 84% for PNFP sub-sector. However, this comparison is taken with caution since Prisons and Police did not have standard staffing norms and therefore were subjected to MOH norms since no alternative norms were available for them. These facilities are possibly meant to have a smaller workforce since their areas of responsibility are smaller than other public facilities - only covering forces staff, their families and offenders where appropriate.

2.1.4StaffingforSelectedCadresinthePublicHealthSector

An analysis of critical cadres in the public sector was conducted. Results show that Clinical officers, Laboratory Staff, Nursing Staff, and Midwifery Staff cadres’ positions are better filled at 104%, 102%, 100%, and 94% respectively. The rates for the other cadres are as shown in Table 4 below in descending order by cadre.


Table 6: Staffing Levels for Critical Cadres in the Public Health Sector, 2017/18

No. ESTABLISHMENT DETAILS

Total Norms

Total Filled

Vac. Exc. % Filled

% M F % F

1 Clinical Officers 2,835 2,945 95 205 104% 3% 2,203 742 25%2 Laboratory Staff 2,993 3,038 350 395 102% 12% 2,200 838 28%3 Nursing Staff 13,141 13,164 557 580 100% 4% 4,001 9,163 70%4 Midwifery Staff 6,349 5,970 691 312 94% 11% 364 5,606 94%5 Theatre Staff 527 373 167 13 71% 32% 173 200 54%6 Doctors 2,633 1,648 1,354 369 63% 51% 1,213 435 26%7 Pharmacy Staff 120 60 65 5 50% 54% 45 15 25%8 Dispensers 406 179 229 2 44% 56% 136 43 24%

9 Anaesthetic Officers 786 235 551 - 30% 70% 132 103 44%

Grand Total 29,790 27,612 4,059 1,881 93% 14% 10,467 62%

Marked improvement is seen in the positions of Nursing (100%) and Midwifery (94%) staff compared to 2016/17 analysis where they were at 87% and 80% respectively. The doctors improved from 58% (2016/17) to 63% 2017/18). Anaesthetic officers were still few at 30% (29% in 2016/2017 audit report) as indicated in table 6. For more information check the HRH audit report available on HRIS dashboard at http://hris.health.go.ug/

2.1.5CompositionoftheHealthWorkersinPublicHealthFacilities

The composition of workforce by gender was also analyzed but limited to the public facilities as PNFPs did not provide gender disaggregated data. Overall, the health workforce employs more women than men at all levels (at 46% males and 54% females). Nursing, midwifery and theatre staff cadres were dominated by women. Men continue to dominate the higher-level cadres such as medical doctors, pharmacists, and clinical officers. Administrative and management positions were also still dominated by men except those that required background training of nursing. This shows that despite the larger number of women in the health workforce as compared to men, the latter are disproportionately dominant in higher-level and managerial positions. For example, 100% of Executive directors of National Referral hospitals, 86% of Directors of Regional Referral Hospitals, 92% of DHOs and 95% of Public General Hospitals are males.

Further analysis of staffing at the different levels of the health sector is discussed in detail in the subsequent parts below.

2.2CentralLevelStaffing

The central level analysis (Table 7) covered the MOH, Mulago NRH, Butabika NRH, 14 RRHs and 4 other central institutions - Uganda Virus Research Institute (UVRI), Uganda Cancer Institute (UCI), Uganda Heart Institute (UHI), Uganda Blood Transfusion Services (UBTS).


Table 7: Summary of Central Level staffing -June 2018

Level Units Norms Filled Vacant %Vac % Exc % Filled % Fem.

MOH HQ 1 634 884 226 250 36% 39% 139% 39%MulagoNRH 1 2,621 2,079 542 0 21% 0% 79% 68%ButabikaNRH 1 418 421 0 3 0% 1% 101% 57%RRH 14 5,262 4,020 1,262 0 24% 0% 76% 57%UVRI 1 227 82 154 9 68% 4% 36% 41%UHI 1 190 118 79 6 42% 3% 62% 53%UCI 1 272 147 132 7 49% 3% 54% 51%UBTS 1 246 322 6 82 2% 33% 131% 38%TOTAL 21 9,870 8,073 2,401 357 24% 44% 82% 57%

2.2.1 Ministry of Health Headquarters

At the beginning of the financial year 2017/18, MOH headquarters started implementing the new staffing structure approved by MOPS. This structure reduced the staffing norm for the headquarters from the previous 821 posts to 634. In the 2016/2017 HRH audit, the number of staffs in post including staff paid from donor funds was 771 which placed the Headquarters at a staffing level of 94% basing on the old norm of 821. However, of the 771 staff, 427 were the substantively appointed MOH staff as per the structure giving an actual staffing level of 52% (427/821), leaving a vacancy of 394 positions or 48% for 2016/17. The 344 (difference between 771 and 427) who included the donor funded staff and others were working at the HQs but not accommodated by the structure despite the fact that their expertise was needed. Table 8, scenario 1A and 2A.

Table 8: MOH Headquarter staffing for FY 2016/17 and 2017/18 using different scenarios

Year Scenario Norm Filled Vacant DonorStaff % Filled %Vacant %DonorStaff2016/17 1A 821 771 394 344 94% 48% 42%

2A 821 427 394 0 52% 48% 0%2017/18 1B 821 884 413 476 108% 50% 58%

2B 821 408 413 0 50% 50% 0%2017/18 1C 634 884 226 250 139% 36% 39%

2C 634 408 226 0 64% 36% 0%

Note: Description of Scenarios 1A to 2C

Scenario 1A Allstaffinpost(includingDonorsupported&anyotherconsideredusingoldstaffingNorminFY2016/17

Scenario 2A OnlyMinistryofhealthstaffproperlyappointedbasingonoldstaffingnorminFY2016/17

Scenario 1B Allstaffinpost(includingDonorsupported&anyotherconsideredusingoldstaffingNorminFY2017/18

Scenario 2B OnlyMinistryofhealthstaffproperlyappointedbasingonoldstaffingnorminFY2017/18

Scenario 1C Allstaffinpost(includingDonorsupported&anyotherconsideredusingNewstaffingNorminFY2017/18

Scenario 2C OnlyMinistryofhealthstaffproperlyappointedbasingonNewstaffingnorminFY2017/18


The year 2017/2018 HRH audit analysis found MOH headquarters with a total staff of 884 in post including the donor supported staff and others. This gave a staffing level of 108% basing on the old staffing norm of 821. The properly appointed staff reduced from 427 (2016/17) to 408 reflecting a 50% staffing level (basing on the old norm of 821), a reduction from 52% in 2016/17. The donor supported and others informally appointed staff working with the HQs were 476 (or 58% of norm) and 413 (50%) posts vacant against the old norm, table 8, Scenarios 1B and 2B.

When the 2017/18 total MOH Head Quarter staffing of 884 was applied against the revised structure of 634 staffing norm (denominator), the staffing level was 139%(table8,scenario1C). However, when that number of staffs accommodated in the new structure (408 staff) was considered, the staffing is at 64% with 226 vacancies or 36% vacancy rate. In absolutes terms, the number of properly appointed staff at the MOH did not increase but the staffing level was just affected by the denominator due to the revised structure. It should be noted that during the writing of this report, the HQ staff were undergoing verification and validation by HSC to find out which ones qualify for the new structure. Completion of this exercise therefore is likely to cause marked changes in staffing levels and vacancy rate at the MOH headquarters.

2.2.2MulagoandButabikaNationalReferralHospital

The staffing levels for Mulago and Butabika NRHs stood at 79% and 101% respectively. The staffing trends for these NRHs over the last 9 years (2009/10 to 2017/18) are shown in Figure 2. There was a marked decline in staffing levels at Mulago NRH in 2017/18 which was probably caused by the opening of Kirudu hospital that shared part of the workforce for the former and there was no corresponding replacement. This similar explanation may be responsible for the sharp decline experienced in 2015/16 when Kawempe Hospital was opened.

On the contrary Butabika recruited more staff specialized in mental health to improve on services delivery. It is worth noting however that the analysis is based on the existing old staffing norm which has been noted to be no longer commensurate with current work load. So, the 101% of Butabika NRH may be elusive.

Figure 2: Staffing Trends at Mulago and Butabika NRH, 2010-2018


2.2.3RegionalReferralHospital

The overall proportion of the approved positions filled in the 14 RRHs was 75%. This showed a decline of 5% from the previous financial year 2016/17. This decline could have been largely due to retirement of very senior specialists and there was immediate replacement because people with similar expertise to replace them are very few or even not available.. For example, senior consultant surgeon and physician in Jinja RRH and one senior consultant surgeon in Soroti RRH had retired during the year under review and before had not yet been replaced.

The bed capacity and staffing level for each of the RRH are summarized in Annex 1. The RRH with the highest staffing level is Jinja RRH (90%) while Moroto RRH has the lowest (58%). Moroto RRH had a slight improvement of 2% compared to 2016/17 where its staffing was at 56%. The staffing levels for the rest of the RRHs are shown in Annex 1.

Figure 3: Regional Referral Hospitals HRH Staffing Levels, June 2018

2.2.3.1TrendofStaffinginRegionalReferralHospitals(RRHs)

The average staffing levels of all the 14 Regional Referral Hospitals (RRHs) over a period of 9 years was 70%, 62%, 72%, 59%, 81%, 78%,56%, 76% and 75%. Table 9 shows the staffing trends for each RRH over the past 9 years.

Table 9: Staffing Trend in the 14 RRHs over 9 Year period, 2009/10 – 2017/18

RRH 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016/17 2017/18Arua 63% 65% 63% 66% 82% 86% 62% 88% 79%F. Portal 74% 56% 74% 61% 67% 96% 65% 71% 80%Gulu 52% 68% 79% 57% 69% 95% 61% 78% 78%Hoima 62% 44% 67% 55% 69% 76% 44% 85% 72%Jinja 98% 74% 79% 71% 83% 89% 65% 89% 90%Kabale 54% 49% 54% 52% 59% 70% 56% 77% 67%Lira 76% 76% 73% 64% 58% 80% 57% 95% 73%Masaka 86% 68% 90% 69% 66% 84% 54% 78% 70%Mbale 64% 75% 73% 78% 69% 89% 69% 88% 85%Mbarara 69% 65% 74% 67% 74% 92% 59% 96% 85%Moroto N/A N/A 46% 28% 32% 41% 34% 56% 42%Mubende N/A N/A 66% 30% 71% 55% 46% 85% 67%Naguru N/A N/A N/A N/A 56% 67% 62% 88% 73%Soroti 70% 60% 81% 62% 69% 74% 55% 58% 86%

Source: HRIS


From table 9, it is observed that there was a general decline of staffing in 2017/18 in many RRH. The conclusive explanation for this could not be established but this could have been as a result of relocations of staff between RRHs or to Kirudu or Kawempe Hospitals from RRHs without replacement, retirement or staff leaving the sector for greener pastures.

2.2.4StaffingatMOHNationalInstitutions

The 4 Central institutions are UVRI, UHI, UCI and UBTS. Their respective staffing levels for year under review were 34%, 63%, 54% and 131% - showing little change from the previous year. UBTS still had excess staff that were not provided for in the structure. UBTS staffing was 98% placing the institution in a better position to execute its mandate of collecting enough blood from the field for the populace.

2.3StaffingatDistrictLevel

At the Local Government/District Level, the analysis covered District Health Officers’ offices, General Hospitals (GH), HCIVs, HCIIIs and HCIIs. Overall staffing at the district level of positions filled by appropriately appointed and qualified health workers was at 75% for all the 128 districts (KCCA inclusive) showing a 4% increase over the previous year (MOH HRH audit report, 2016/17).

There were a total of 3,279 health facilities compared to 3,135 in 2016/17 from all the districts. Therefore, in the year 2017/18,144, additional health facilities were included on the previous year’s list for analysis. The 144 health facilities included new facilities opened during the year and those facilities that existed but had not been included in HRIS. The 3,279 health facilities had a total norm of 53,072 posts and 39,588 staff in post.

The total shortfall of health workers recorded in the previous analysis of 2016/17 therefore reduced from 22,702 to 15,052 health workers. Although the districts did not recruit health professionals to the tune of 7,650 (22,702 minus 15,052) people during the year under review, it is believed that the intensified cleaning and updating of HRIS data conducted towards the Audit analysis exercise that engaged districts to upload and update data to reflect the reality may be responsible for this indication. See Annex 2.

2.3.1TheStaffingTrendattheDistrictLevelOver9Years

Figure 4 shows the overall trends of district staffing levels for the last nine years. It should be noted that staffing levels at the district level have been on the increase. This trend was partly as a response to the creation of new districts in the country that usually comes with creation of new DHOs’ offices and upgrading of some health facilities there in to serve the required services for the district hence calling for new health staff recruitment.

Figure 4: Staffing Trends at District level over 9 years (2009/10 – 2017/18).


2.3.2TheStaffingTrendattheLowerLevelHealthFacilities2009-2018

Districts health facilities also show an increasing trend in staffing levels over the last 9 years (figure 5). It should be noted however that this analysis did not include the year 2015/16 due to data gaps during that year. Following the downsizing of the staff establishment at the DHOs’ office from 11 to 8 (See table 10), in 2014/15, there was an apparent decline in staffing at this level since the three of the staff cadres (secretary, drivers, accounts assistant) that used to be included at the DHO’s office were moved under the district administration pool staff. Figure 5: District staffing Trends by level 2009/10 -2017/18

0%10%20%30%40%50%60%70%80%90%

100%

%ag

e fil

led

DHOs’ office

GHs

HCIVs

HCIII

HCIIs

Many districts, including the newly created ones, had staff occupying positions in acting capacity either because they did not have the necessary qualifications or because the district lacked wage to recruit. The 2017/18 analysis of staffing at the DHOs’ office (table 10) showed that the substantively appointed staff at this level stood at an average 46%. This low staffing levels for qualified staff at the DHOs’ office is a threat to the performance of districts because this team is responsible for planning and supervising health service delivery and if these functions are not well executed, it is a barrier to quality service delivery to the people of Uganda.

The analysis further indicated that the DHTs were predominantly males conforming to the general observation for the sector that administrative positions are dominated by males. For example, of the 59 properly appointed DHOs in the country, only 3 were females. In some DHO offices, the staff composition was 100% males as in the case of Ntungamo, Tororo, Rubirizi and the newly created districts of Bunyangabu, Bugweri, Butebo, Kapelebyong, Kasanda, Kikube, Kyotera and Nabilatuk. See Annex 3.

Table 10: Summary of staffing at DHOs’ offices focusing on substantively appointed staff in post-June 2018

# JobTitle Salary Scale

ApprovedNorms Filled Vacant %

Filled %Female

1 District Health Officer U1E 128 77 51 60% 4%2 Assistant District Health Officer (Environmental

Health) U2 (SC) 128 43 85 34% 19%

3 Assistant District Health Officer - Maternal and Child Health U2 (SC) 128 63 60 49% 72%

4 Senior Health Educator U3(SC) 128 50 78 39% 19%5 Bio-Statistician U4(SC) 128 114 14 89% 21%6 Senior Environmental Health Officer U4(SC) 128 35 93 27% 18%7 Assistant Inventory Management Officer U5L 128 38 90 30% 61%8 Cold Chain Technician U6U 128 56 72 44% 4%

Total 1024 476 548 46% 25%


Table 10 shows an analysis of staffing by cadre at the DHOs’ office. This indicates that Assistant DHOs (MCH and Environment), Senior Health educators, Senior Environmental Health officers, Assistant Inventory Management Officers and Cold Chain Technicians were still varyingly few at this level.

2.3.3PublicGeneralHospitals The staffing level of approved positions filled by appropriately trained and qualified health workers in all the 45 general (public) hospitals was at 76% which reflected an improvement from 68% in 2016/17 (Table 11). It should be noted that Kawempe and Kirudu hospitals were treated as GHs even though they provide a range of specialized services meant for RRHs. Entebbe hospital was the best staffed at 129% followed by Kitgum (110%), Mityana (108%), Adjumani (106%) and Kalisizo (97%). Entebbe and Mityana underwent major renovation and expansion and therefore more staff (including some specialists) were recruited. This may explain the marked improvement in staffing observed at these two facilities compared to previous years. Kirudu and Kawempe hospitals had the lowest staffing levels and yet they are one of the busiest with the highest burden of patients; they are in Kampala and have large catchment populations and in addition attend to referrals from other district hospitals.

Buwenge hospital in Jinja district is regarded here as a GH although it lacked required infrastructure to deliver services for this level. This explains its low staffing status. Most of the in-patient cases are currently being handled by the nearby Buwenge HCIV that has better infrastructure or referred to Jinja RRH. Because of this current situation at this facility, the district authority redeployed some staff meant for the hospital to Buwenge hospital to handle this extra load.

It was observed that the staff in the 45 hospitals were females except for Anaka, Bulisa, Bududa, Bukwo, Kambuga and Yumbe where males were more. It should be noted that there is generally fair distribution of health workers in both rural versus urban-based General hospitals which is an encouraging observation in addressing the problem of inequitable distribution of health workers and Universal Health Coverage.

Table 11: Summary of Overall Staffing Levels in all the 45 General Hospitals in Order by positions filled – June 2018

No. District General Hospital

Total Units Total Filled Vac %Filled %Vac M F % F

1 Wakiso Entebbe 1 190 245 0 55 129% 0% 79 166 68%2 Kitgum Kitgum 1 190 209 0 19 110% 0% 96 113 54%3 Mityana Mityana 1 190 205 0 15 108% 0% 73 132 64%4 Adjumani Adjumani 1 190 201 0 11 106% 0% 86 115 57%5 Kyotera Kalisizo 1 190 184 6 0 97% 3% 52 132 72%6 Apac Apac 1 190 183 7 0 96% 4% 72 111 61%7 Nakaseke Nakaseke 1 190 183 7 0 96% 4% 47 136 74%8 Nebbi Nebbi 1 190 180 10 0 95% 5% 64 116 64%9 Kamuli Kamuli 1 190 178 12 0 94% 6% 70 108 61%

10 Iganga Iganga 1 190 170 20 0 89% 11% 61 109 64%11 Kapchorwa Kapchorwa 1 190 170 20 0 89% 11% 72 98 58%12 Moyo Moyo 1 190 170 20 0 89% 11% 81 89 52%13 Bugiri Bugiri 1 190 168 22 0 88% 12% 54 114 68%14 Kagadi Kagadi 1 190 163 27 0 86% 14% 52 111 68%15 Bundibugyo Bundibugyo 1 190 157 33 0 83% 17% 64 93 59%16 Tororo Tororo 1 190 158 32 0 83% 17% 58 100 63%17 Buikwe Kawolo 1 190 155 35 0 82% 18% 40 115 74%18 Kiryandongo Kiryandongo 1 190 151 39 0 79% 21% 77 74 49%19 Kisoro Kisoro 1 190 151 39 0 79% 21% 60 91 60%20 Ntungamo Itojo 1 190 150 40 0 79% 21% 64 86 57%21 Kasese Bwera 1 190 149 41 0 78% 22% 60 89 60%22 Kiboga Kiboga 1 190 148 42 0 78% 22% 63 85 57%23 Pallisa Pallisa 1 190 145 45 0 76% 24% 68 77 53%24 Kaabong Kaabong 1 190 143 47 0 75% 25% 68 75 52%25 Lyantonde Lyantonde 1 190 141 49 0 74% 26% 43 98 70%


No. District General Hospital

Total Units Total Filled Vac %Filled %Vac M F % F

26 Abim Abim 1 190 138 52 0 73% 27% 56 82 59%27 Kayunga Kayunga 1 190 138 52 0 73% 27% 44 94 68%28 Bududa Bududa 1 190 134 56 0 71% 29% 71 63 47%29 Kanungu Kambuga 1 190 127 63 0 67% 33% 65 62 49%30 Masindi Masindi 1 190 127 63 0 67% 33% 43 84 66%31 Nwoya Anaka 1 190 128 62 0 67% 33% 66 62 48%32 Butaleja Busolwe 1 190 125 65 0 66% 34% 44 81 65%33 Butambala Gombe 1 190 125 65 0 66% 34% 38 87 70%34 Katakwi Katakwi 1 190 119 71 0 63% 37% 64 55 46%35 Yumbe Yumbe 1 190 117 73 0 62% 38% 70 47 40%36 Rakai Rakai 1 190 115 75 0 61% 39% 41 74 64%37 Kyenjojo Kyenjojo 1 190 114 76 0 60% 40% 41 73 64%38 Kumi Kumi 1 190 112 78 0 59% 41% 39 73 65%39 Sheema kitagata 1 190 102 88 0 54% 46% 40 62 61%40 Busia Masafu 1 190 98 92 0 52% 48% 48 50 51%41 Jinja Buwenge 1 190 96 94 0 51% 49% 38 58 60%42 Bukwo Bukwo 1 190 93 97 0 49% 51% 51 42 45%43 Buliisa Buliisa 1 190 92 98 0 48% 52% 51 41 45%44 Kampala Kawempe 1 190 55 135 0 26% 74% 9 46 84%45 Kampala Kiruddu 1 190 44 146 0 26% 74% 7 37 84% Total 45 8550 6456 2194 100 76% 26% 2550 3906 61%

2.3.4PublicHealthCentreIVLevel

The analysis covered 179 public HCIVs. Out of 8,592 positions available according to norms, 7,454 were filled giving an overall staffing of 87%. This is an increase from 84% in 2016/17 – maintaining a general upward trend at this level over the last 9 years (Table 9).

The districts with the highest staffing levels at HCIVs included Bulambuli (152%), Kampala (151%), Kamwenge (146%), Mpigi (144%) and Kyotera (144%). The districts responsible for these facilities prioritized increasing staffing in these facilities to handle the high workload. In fact, Mpigi HCIV among the 5 was already earmarked for upgrading to a General Hospital level.

The five districts with the lowest staffing levels at HCIVs included Kasese (51%), Namisindwa (54%), Mukono (55%), Mityana (55%) and Bukwo (56%). The explanation for the low staffing at Mukono HCIV could not be established and needs further investigation. Given the location of facility and workload, this facility needed more staff than observed in this analysis.

Out of 179 HCIVs, 127 (71%) had staffing levels of 75% and above and were in 82 districts of the128 (64%). In general, health facilities at this level were relatively well staffed. The gender composition of staff at this level was 50% females and 50% male. There was no big disparity in staffing for urban versus rural health facilities at this level which reaffirms the argument of progressive reduction in inequitable distribution of health workers. See Annex 4 for more detailed information.

2.3.5PublicHealthCentreIIIStaffing

The overall staffing level for the 991 public HC III’s was 80% - the same as last year. The five districts with the highest HCIII staffing levels were Kampala (234%), Oyam (118%), Amuru (117%), Jinja (116%) and Rubirizi (112%). 624 out of 991(63%) health facilities located in 88 out of 128 (69%) districts had staffing levels of 75% and above.

It is not surprising that Kampala and Jinja have high staffing levels because they are predominantly urban presumably with conducive work environment where everyone wishes to work, and retention


of health workers expected to be high. There was however no conclusive explanation of these 3 rural based districts of Oyam, Amuru and Rubirizi.

The five districts with lowest staffing levels at HCIIIs were Amudat (37%), Moroto (49%), Isingiro (52%), Kakumiro (54%) and Kagadi (54%). It should be noted that the majority of least staffed health centre IIIs highlighted here are from Karamoja region where attraction and retention of health workers had been difficult over the years despite the apparent improvements in staffing observed during this assessment. At HCIII level, there were 6,930 (46%) male Health Workers compared to 8225 (56%) females. See Annex 5 for more detailed information.

2.3.6PublicHealthCentreIIStaffing

The analysis at this level covered 1,712 HCIIs compared to 1,690 last year (2016/17). The overall staffing at HCII was 55% - an improvement of 2% from the previous year. HCIIs tend to be the most poorly staffed level in the system. The five districts with highest staffing at HCIIs were Amuru (112%), Kibaale (111%), Kyegegwa (111%), Buliisa (107%) and Kyenjojo (102%). 321 health facilities out of 1712 (19%) from 28 out of 128 (9%) districts had staffing levels of 75% and above. The five districts with the lowest staffing at HCII level were Kampala (22%), Bukedea (22%), Bugiri (23%), Sembabule (24%) and Namutumba (25%). Nursing Assistants, askaris and porters occupied the greatest proportion of the total health workforce at HCIIs. Females constituted 55% of the staffing. See Annex 6 for more details.

2.4PrivateNotforProfitHealthSub-SectorStaffing

The PNFP analysis focused on facilities under the four religious medical bureaus namely: Uganda Catholic Medical Bureau (UCMB), Uganda Protestant Medical Bureau (UPMB), Uganda Muslim Medical Bureau (UMMB) and Uganda Orthodox Medical Bureau (UOMB). Facilities owned by Uganda Adventists church were captured under UPMB.

PNFP health facilities do not have standard staffing norms, but for comparability of results with public facilities, the MOH structure was applied to get an approximation of PNFP staffing levels. It would be meaningful if bureaus were supported to develop their own norms that could be used for assessing their staffing levels in the future, especially because their facilities tend to have certain cadres that are not included in MOH facilities such as religious staff.

The four bureaus combined had 468 health facilities with a total approximated norm of 17,629 (Table 12). Their overall staffing level for all the PNFP health facilities was 84% - higher than the public subsector staffing of 75.7%. The data from PNFPs did not include a gender disaggregation so gender analysis was not possible. Table 10 summarizes the staffing by facility level in PNFPs as of June 2018.

Table 12: PNFP Staffing by Bureau and Level of Care -June 2018

Bureau Level Total Units Total Norms Filled Vacant Excess % Vacant

% Excess

% Filled

UCMB

GH 32 6080 6159 3119 3198 51 53 101

HCIV 8 384 334 209 159 54 41 87

HCIII 176 3344 2554 1551 761 46 23 76

HCII 79 711 700 341 330 48 46 98

295 10,519 9,747 5,220 4,448 50% 42% 93%


UPMB

GH 19 3,610 3077 2303 1770 64 49 85

HCIV 9 432 439 244 251 56 58 102

HCIII 27 513 324 300 111 58 22 63

HCII 48 432 200 329 97 76 22 46

103 4,987 4,040 3,176 2,229 64% 45% 81%

UMMB

GH 5 950 313 741 104 78 11 33

HCIV 2 96 36 65 5 68 5 38

HCIII 25 475 308 274 107 58 23 65

HCII 20 180 128 103 51 57 28 71

52 1,701 785 I, I83 267 70% 16% 46%

UOMB

GH 1 190 107 130 47 58 25 56

HCIV 1 48 10 38 0 79 0 21

HCIII 4 76 36 44 4 58 5 47

HCII 12 108 59 59 10 55 9 55

18 422 212 271 61 64% 14% 50%

TOTAL 468 17,629 14,784 9,850 7005 56% 47% 84%

Out of the 4 bureaus, UCMB has the most health facilities and the highest staffing level. UOMB is relatively new compared to the others and has the fewest facilities. UMMB has the lowest staffing at 46%.

Several bureau facilities offer services beyond what is prescribed by MOH for that level of care. For example, Lacor, Lubaga, Nsambya, Namirembe and Kibuli hospitals are here categorized as GHs yet they function like RRHs. Similarly, many HCIVs function as GHs and HCIIIs as HCIVs

2.5PrivateforProfit(PFP)Private-for-profit (PFP) are health facilities that charge for the services and care with the aim of making profits. They include private hospitals and clinics at levels of Health Centre IV, III and II. Although it was desired that PFP are covered by the HRH audit, annual attempts to gather data from them has been futile.


3.0 Conclusion and Recommendations

3.1 Conclusion

The findings indicate that the overall national HRH staffing levels for public facilities improved from 73% in 2016/17 to 76% this year maintaining an upward trend of staffing levels observed over the last nine years (2009 to 2018). In addition, overall staffing for the PNFP sub-sector was 84% which seemingly was higher than for public (76%) due the fact that PNFPs were subjected to the public staffing norms since they don’t have standardized norms. Some facilities were hence assessed at levels below the range of services they gave and number of staff available. Despite the continuous improvement in the national staffing level over time, critical health workforce shortages persist in Uganda, which may threaten the country’s achievement of the Sustainable Development Goal targets. There are shortages of staff, imbalances in skill mix, and inequitable distribution of health workers.

Results showed that the country still had fewer Anaesthetic officers. Overall public health workforce employs more women than men at all levels (46% males and 54% females) with nursing, midwifery and theatre staff cadres dominated by women while men continued to dominate the higher-level cadres such as medical doctors, pharmacists, and clinical officers as well as administrative and management positions.

The proportions of approved positions properly filled at the MOH headquarters is 64% although at the time of this assessment, Health Service Commission was conducting validation and verification of staff against the new structure. This was likely to change this result. The workforce at MOH headquarters included seconded staff whose wages are paid for by development partners.

Mulago registered a decline in staffing compared to the previous year which. This was as a result of the opening of Kiruddu hospital that shared part of the workforce from Mulago and there was no corresponding replacement.

Regional referral hospitals also registered a decline in staffing from 80% last year to 75%. This decline was largely due to the very senior specialists who retired and yet there was no immediate replacement since the people to replace them are very few or even not available on market.

Overall staffing at the district level improved from 71% last year to 75% however Karamoja region still had the most poorly staffed districts. Analysis of staffing at the DHOs’ office showed that the substantively appointed staff at this level was as low as 46% which was a threat to the performance of districts because this team is responsible for planning and supervising health service delivery and if these functions were not well executed would be a barrier to quality service delivery to the people of Uganda.

Staffing in General hospitals and health center IVs also registered an increase from 68% to 76% and 84% to 87% respectively. The overall staffing at HC III level remained stagnant at 80% - the same as last year. The overall staffing at HCII was 55% - an improvement of 2% from the previous year. HCIIs tend to be the most poorly staffed level in the system. It should be noted that the staffing norms are old and therefore don’t necessarily respond to the workload in the district Health facilities

Overall staffing level for all the PNFP health facilities basing on the public health facility staffing norm was 84% - higher than the public sub-sector staffing of 76%. The high PNFP staffing levels could be a result of subjecting PNFP sub-sector to the public staffing norms framework hence some facilities assessed at levels below the range of services they offer and number of staff available.


For example, PNFP hospitals such as St. Mary’s Lacor, Lubaga, Mengo, Nsambya and Kibuli were considered as General hospitals yet they functioned like regional referral hospitals with probably more staff than recommended for public general hospitals. UCMB had the most facilities out of the 4 bureaus and the highest staffing level. UOMB is relatively new compared to the others and had the fewest facilities while UMMB had the lowest staffing at 46%.

3.2Recommendations

1. PNFPs need to be supported to develop staffing norms for their different levels of service delivery for better comparability.

2. There is a need to fast track the review of staffing structures in public sub-sector to accommodate the many health workers who occupy positions beyond the established norms due to the sector need to have them available to handle workload at respective workstations.

3. Support is needed for Karamoja Region particularly Amudat and Moroto districts to improve their health worker attraction and retention packages and increase their staffing that has persistently remained low.

4. Government should develop strategies to train and deploy more anaesthetic officers who are still few on market and therefore very difficult to attract and retain.

5. The government should actualize the decision to upgrade health center IIs to IIIs in the country or plan to increase staffing at this level in the short term to improve service delivery.

6. Prioritize filling of the vacant positions at DHOs’ office across the country to improve staffing at this level I in order to improve leadership and governance of District health service directorates for better health service delivery.


4.0 Instructions on accessing Online HRH audit report data from HRIS

HRH audit tables are embedded in HRIS. The details for the different statistical tables in the HRH audit report are available on HRIS dashboard at http://hris.health.go.ug/

When the dashboard is accessed through the link given above, you look at the left of the dashboard and click on Audit reports (see figure below).

Clicking on the Audit Reports will give the options as illustrated in diagram below.

Click on any of the options above to view detailed reports


For example, to view the National Level Summary, click on the Facility Level Summary and get a detailed report as illustrated in the diagram below.

NOTEThere are four buttons on the left side of the report, below the heading, in this case “NATIONAL FACILITY LEVEL SUMMARY” i.e. COPY,CSV,PDFandPRINT

• The COPY button allows one to copy the table contents into a Word document.• The CSV button allows one to directly export the table in Excel Format.• The PDF button allows one to format the table contents into PDF.• The PRINT button allows you to print the table directly from the system.

To view data for a specific District/Institution, Type the District/Institution name in the Text box which shows “Select Institution”. You can either Type the name or Select from the drop down of the District/Institution. Then Click on ApplyDistrictLimit as indicated by the arrow below.


For example, to view Adjumani district data, type Adjumani in the “Select Institution” box, Click ApplyDistrictLimit. You’ll get the detailed data of Adjumani as indicated in the diagram below.


5.0 ANNEXES

ANNEX 1. Staffing of RRHs as at June-2018

No. RRH Bed Capacity

Total Norms Filled Vac %

Filled %Vac M F % F

1 Arua 270 316 251 65 79% 21% 128 123 49%2 Fort Portal 306 427 342 85 80% 20% 142 200 58%3 Gulu 230 446 347 99 78% 22% 129 218 63%4 Hoima 200 410 297 113 72% 28% 140 157 53%5 Jinja 500 416 375 41 90% 10% 144 231 62%6 Kabale 250 372 250 122 67% 33% 117 133 53%7 Lira 350 414 303 111 73% 27% 136 167 55%8 Masaka 330 350 244 106 70% 30% 90 154 63%9 Mbale 370 450 381 69 85% 15% 175 206 54%

10 Mbarara 350 341 290 51 85% 15% 115 175 60%11 Moroto 100 379 160 219 42% 58% 82 78 49%12 Mubende 230 346 232 114 67% 33% 114 118 51%13 Naguru 100 348 253 95 73% 27% 84 169 67%14 Soroti 250 343 295 48 86% 14% 136 159 54%

Total 3,836 5,358 4,020 1,338 75% 25% 1,732 2,288 57%

ANNEX 2: Summary of the HRH Staffing Levels in each of the 128 Districts - In Alphabetical Order

No District No of Units

Total Norms Fld Vaca Exc %Fld %Vac %Exc % F

1 Abim 22 393 270 124 1 69% 32% 0% 53%2 Adjumani 34 590 582 28 20 99% 5% 3% 46%3 Agago 41 443 422 51 30 95% 12% 7% 48%4 Alebtong 18 234 161 75 2 69% 32% 1% 47%5 Amolatar 14 182 143 41 2 79% 23% 1% 39%6 Amudat 10 94 50 61 17 53% 65% 18% 46%7 Amuria 18 254 203 58 7 80% 23% 3% 50%8 Amuru 28 364 415 2 53 1% 15% 44%9 Apac 19 398 352 50 4 88% 13% 1% 49%

10 Arua 58 861 643 247 29 75% 29% 3% 47%11 Budaka 17 295 212 83 0 72% 28% 0% 51%12 Bududa 16 388 265 123 0 68% 32% 0% 51%13 Bugiri 37 639 396 252 9 62% 39% 1% 64%14 Bugweri 17 225 164 63 2 73% 28% 1% 52%15 Buhweju 15 207 137 73 3 66% 35% 1% 52%16 Buikwe 32 579 383 199 3 66% 34% 1% 66%17 Bukedea 9 163 129 35 1 79% 21% 1% 52%18 Bukomansimbi 9 143 123 23 3 86% 16% 2% 59%19 Bukwo 18 405 258 147 0 64% 36% 0% 45%20 Bulambuli 27 405 287 143 25 71% 35% 6% 57%21 Buliisa 11 352 248 110 6 70% 31% 2% 49%22 Bundibugyo 25 531 428 103 0 81% 19% 0% 48%23 Bunyangabu 19 283 236 53 6 83% 19% 2% 61%24 Bushenyi 23 351 279 80 8 79% 23% 2% 54%25 Busia 31 556 307 253 4 55% 46% 1% 53%26 Butaleja 25 503 347 156 0 69% 31% 0% 60%27 Butambala 16 368 230 138 0 63% 38% 0% 67%




28 Butebo 10 162 111 51 0 69% 31% 0% 51%29 Buvuma 12 200 160 40 0 80% 20% 0% 49%30 Buyende 13 189 132 57 0 70% 30% 0% 52%31 Dokolo 18 234 204 43 13 87% 18% 6% 45%32 Gomba 19 253 161 92 0 64% 36% 0% 58%33 Gulu 28 377 314 63 0 83% 17% 0% 52%34 Hoima 25 354 230 125 1 65% 35% 0% 55%35 Ibanda 27 306 190 119 3 62% 39% 1% 59%36 Iganga 28 558 469 101 12 84% 18% 2% 61%37 Isingiro 58 851 457 399 5 54% 47% 1% 56%38 Jinja 56 959 887 149 77 92% 16% 8% 59%39 Kaabong 34 589 402 196 9 68% 33% 2% 43%40 Kabale 44 579 385 198 4 66% 34% 1% 50%41 Kabarole 30 478 451 51 24 94% 11% 5% 63%42 Kaberamaido 17 265 228 44 7 86% 17% 3% 39%43 Kagadi 21 463 311 153 1 67% 33% 0% 65%44 Kakumiro 16 275 146 129 0 53% 47% 0% 55%45 Kalangala 19 312 237 76 1 76% 24% 0% 58%46 Kaliro 14 198 185 16 3 93% 8% 2% 46%47 Kalungu 14 238 205 33 0 86% 14% 0% 61%48 Kampala 22 715 642 303 230 90% 42% 32% 37%49 Kamuli 37 688 576 114 2 84% 17% 0% 57%50 Kamwenge 30 421 415 52 46 99% 12% 11% 52%51 Kanungu 31 609 475 144 10 78% 24% 2% 49%52 Kapchorwa 22 455 374 86 5 82% 19% 1% 52%53 Kapelebyong 14 178 113 65 0 63% 37% 0% 35%54 Kasanda 20 291 143 148 0 49% 51% 0% 60%55 Kasese 98 1451 1018 529 96 70% 36% 7% 58%56 Katakwi 22 451 297 154 0 66% 34% 0% 52%57 Kayunga 21 521 423 103 5 81% 20% 1% 63%58 Kibaale 7 125 129 3 7 2% 6% 51%59 Kiboga 22 471 333 140 2 71% 30% 0% 54%60 Kibuku 14 228 189 47 8 83% 21% 4% 57%61 Kikuube 22 399 228 171 0 57% 43% 0% 51%62 Kiruhura 40 533 267 266 0 50% 50% 0% 53%63 Kiryandongo 22 413 342 82 11 83% 20% 3% 49%64 Kisoro 41 757 602 178 23 80% 24% 3% 49%65 Kitgum 26 530 501 53 24 95% 10% 5% 51%66 Koboko 18 248 259 57 68 23% 27% 49%67 Kole 12 180 171 12 3 95% 7% 2% 43%68 Kotido 19 266 183 84 1 69% 32% 0% 51%69 Kumi 22 465 270 199 4 58% 43% 1% 65%70 Kwania 16 230 219 33 22 95% 14% 10% 46%71 Kween 27 359 295 72 8 82% 20% 2% 39%72 Kyankwanzi 18 262 183 79 0 70% 30% 0% 53%73 Kyegegwa 15 227 229 13 15 6% 7% 47%74 Kyenjojo 22 473 391 88 6 83% 19% 1% 54%75 Kyotera 37 640 577 85 22 90% 13% 3% 63%76 Lamwo 24 347 205 142 0 59% 41% 0% 55%77 Lira 22 382 326 58 2 85% 15% 1% 47%78 Luuka 29 353 219 144 10 62% 41% 3% 59%79 Luwero 42 648 566 128 46 87% 20% 7% 66%80 Lwengo 19 315 212 103 0 67% 33% 0% 68%81 Lyantonde 18 376 280 96 0 74% 26% 0% 61%82 Manafwa 11 210 170 40 0 81% 19% 0% 58%




83 Maracha 19 236 276 33 73 14% 31% 43%84 Masaka 24 360 253 120 13 70% 33% 4% 67%85 Masindi 33 642 480 163 1 75% 25% 0% 54%86 Mayuge 38 464 380 94 10 82% 20% 2% 48%87 Mbale 41 781 560 223 2 72% 29% 0% 60%88 Mbarara 48 704 370 340 6 53% 48% 1% 65%89 Mitooma 17 245 171 74 0 70% 30% 0% 53%90 Mityana 38 767 529 257 19 69% 34% 2% 63%91 Moroto 15 230 123 109 2 53% 47% 1% 44%92 Moyo 41 702 659 67 24 94% 10% 3% 44%93 Mpigi 22 341 297 85 41 87% 25% 12% 63%94 Mubende 38 408 197 215 4 48% 53% 1% 64%95 Mukono 36 518 394 124 0 76% 24% 0% 56%96 Nabilatuk 9 133 82 51 0 62% 38% 0% 43%97 Nakapiripirit 9 134 108 33 7 81% 25% 5% 54%98 Nakaseke 24 494 420 78 4 85% 16% 1% 69%99 Nakasongola 35 444 384 72 12 86% 16% 3% 49%

100 Namayingo 28 324 189 137 2 58% 42% 1% 54%101 Namisindwa 16 250 185 65 0 74% 26% 0% 47%102 Namutumba 25 307 178 130 1 58% 42% 0% 60%103 Napak 16 188 164 32 8 87% 17% 4% 54%104 Nebbi 23 436 346 98 8 79% 22% 2% 53%105 Ngora 12 200 140 62 2 70% 31% 1% 60%106 Ntoroko 11 149 122 28 1 82% 19% 1% 38%107 Ntungamo 44 820 636 186 2 78% 23% 0% 52%108 Nwoya 15 339 234 106 1 69% 31% 0% 45%109 Omoro 24 298 266 32 0 89% 11% 0% 47%110 Otuke 17 235 150 85 0 64% 36% 0% 35%111 Oyam 27 305 305 28 28 9% 9% 43%112 Pader 38 478 304 175 1 64% 37% 0% 48%113 Pakwach 20 254 163 105 14 64% 41% 6% 41%114 Pallisa 18 426 339 95 8 80% 22% 2% 53%115 Rakai 34 570 354 220 4 62% 39% 1% 55%116 Rubanda 28 373 266 108 1 71% 29% 0% 47%117 Rubirizi 15 197 128 76 7 65% 39% 4% 52%118 Rukiga 25 326 242 84 0 74% 26% 0% 47%119 Rukungiri 56 747 474 283 10 63% 38% 1% 60%120 Serere 18 293 185 111 3 63% 38% 1% 51%121 Sheema 28 502 280 231 9 56% 46% 2% 57%122 Sironko 29 472 346 141 15 73% 30% 3% 46%123 Soroti 24 390 258 132 0 66% 34% 0% 53%124 Ssembabule 26 355 170 185 0 48% 52% 0% 55%125 Tororo 59 1005 604 408 7 60% 41% 1% 57%126 Wakiso 70 1177 929 339 91 79% 29% 8% 68%127 Yumbe 33 602 401 222 21 67% 37% 3% 43%128 Zombo 19 188 190 33 35 18% 19% 51%

Total 3,279 3,072 39,588 15,052 1,568 75% 28% 3% 54%


ANNEX 3: Summary of the staffing Levels at the District Health Officers’ Offices in 128 Districts

No. DHOsOffice TotalNorms Peopleinposition

Properlyappointedinposition

% Filled properlyappointed

% Filled (Peopleinposition)

1 Abim 8 5 4 50% 63%2 Adjumani 8 5 3 38% 63%3 Agago 8 5 5 63% 63%4 Alebtong 8 4 3 38% 50%5 Amolatar 8 4 4 50% 50%6 Amudat 8 3 2 25% 38%7 Amuria 8 6 5 63% 75%8 Amuru 8 6 6 75% 75%9 Apac 8 7 5 63% 88%10 Arua 8 7 6 75% 88%11 Budaka 8 7 3 38% 88%12 Bududa 8 6 4 50% 75%13 Bugiri 8 10 6 75% 125%14 Bugweri 8 1 0 0% 13%15 Buhweju 8 8 3 38% 100%16 Buikwe 8 6 3 38% 75%17 Bukedea 8 9 2 25% 113%18 Bukomansimbi 8 5 3 38% 63%19 Bukwo 8 4 4 50% 50%20 Bulambuli 8 8 4 50% 100%21 Buliisa 8 8 7 88% 100%22 Bundibugyo 8 7 4 50% 88%23 Bunyangabu 8 2 2 25% 25%24 Bushenyi 8 9 5 63% 113%25 Busia 8 5 4 50% 63%26 Butaleja 8 7 4 50% 88%27 Butambala 8 5 3 38% 63%28 Butebo 8 1 1 13% 13%29 Buvuma 8 6 2 25% 75%30 Buyende 8 8 3 38% 100%31 Dokolo 8 9 4 50% 113%32 Gomba 8 6 2 25% 75%33 Gulu 8 8 6 75% 100%34 Hoima 8 9 5 63% 113%35 Ibanda 8 9 5 63% 113%36 Iganga 8 7 7 88% 88%37 Isingiro 8 7 2 25% 88%38 Jinja 8 8 6 75% 100%39 Kaabong 8 6 2 25% 75%40 Kabale 8 8 4 50% 100%41 Kabarole 8 8 3 38% 100%42 Kaberamaido 8 7 3 38% 88%43 Kagadi 8 9 4 50% 113%44 Kakumiro 8 6 1 13% 75%45 Kalangala 8 6 5 63% 75%


46 Kaliro 8 8 4 50% 100%47 Kalungu 8 4 2 25% 50%48 Kampala 8 7 8 100% 88%49 Kamuli 8 6 4 50% 75%50 Kamwenge 8 8 6 75% 100%51 Kanungu 8 6 5 63% 75%52 Kapchorwa 8 5 4 50% 63%53 Kapelebyong 8 1 1 13% 13%54 Kasanda 8 1 1 13% 13%55 Kasese 8 9 2 25% 113%56 Katakwi 8 6 4 50% 75%57 Kayunga 8 7 7 88% 88%58 Kibaale 8 8 7 88% 100%59 Kiboga 8 9 3 38% 113%60 Kibuku 8 6 5 63% 75%61 Kikuube 8 1 1 13% 13%62 Kiruhura 8 5 4 50% 63%63 Kiryandongo 8 7 4 50% 88%64 Kisoro 8 5 4 50% 63%65 Kitgum 8 6 5 63% 75%66 Koboko 8 6 4 50% 75%67 Kole 8 8 7 88% 100%68 Kotido 8 7 5 63% 88%69 Kumi 8 8 6 75% 100%70 Kwania 8 7 2 25% 88%71 Kween 8 5 4 50% 63%72 Kyankwanzi 8 4 2 25% 50%73 Kyegegwa 8 6 5 63% 75%74 Kyenjojo 8 6 3 38% 75%75 Kyotera 8 1 1 13% 13%76 Lamwo 8 2 1 13% 25%77 Lira 8 9 4 50% 113%78 Luuka 8 5 1 13% 63%79 Luwero 8 6 3 38% 75%80 Lwengo 8 6 4 50% 75%81 Lyantonde 8 5 1 13% 63%82 Manafwa 8 8 2 25% 100%83 Maracha 8 9 4 50% 113%84 Masaka 8 7 6 75% 88%85 Masindi 8 9 3 38% 113%86 Mayuge 8 9 5 63% 113%87 Mbale 8 7 3 38% 88%88 Mbarara 8 4 2 25% 50%89 Mitooma 8 4 2 25% 50%90 Mityana 8 9 5 63% 113%91 Moroto 8 5 3 38% 63%92 Moyo 8 9 4 50% 113%93 Mpigi 8 5 5 63% 63%


94 Mubende 8 9 3 38% 113%95 Mukono 8 5 4 50% 63%96 Nabilatuk 8 1 1 13% 13%97 Nakapiripirit 8 5 3 38% 63%98 Nakaseke 8 5 2 25% 63%99 Nakasongola 8 8 5 63% 100%100 Namayingo 8 7 4 50% 88%101 Namisindwa 8 1 0 0% 13%102 Namutumba 8 9 3 38% 113%103 Napak 8 8 3 38% 100%104 Nebbi 8 6 4 50% 75%105 Ngora 8 7 5 63% 88%106 Ntoroko 8 4 2 25% 50%107 Ntungamo 8 9 5 63% 113%108 Nwoya 8 9 4 50% 113%109 Omoro 8 3 2 25% 38%110 Otuke 8 7 3 38% 88%111 Oyam 8 7 7 88% 88%112 Pader 8 9 2 25% 113%113 Pakwach 8 2 1 13% 25%114 Pallisa 8 5 5 63% 63%115 Rakai 8 6 3 38% 75%116 Rubanda 8 9 4 50% 113%117 Rubirizi 8 4 3 38% 50%118 Rukiga 8 5 2 25% 63%119 Rukungiri 8 6 4 50% 75%120 Serere 8 8 7 88% 100%121 Sheema 8 7 6 75% 88%122 Sironko 8 5 2 25% 63%123 Soroti 8 7 6 75% 88%124 Ssembabule 8 7 4 50% 88%125 Tororo 8 7 5 63% 88%126 Wakiso 8 9 6 75% 113%127 Yumbe 8 9 6 75% 113%128 Zombo 8 5 3 38% 63% Total 1024 798 476 46% 78%


ANNEX 4: Summary of the HRH Staffing Levels in each of the 179 Health Centre IVs - In District alphabetic Order

No. District Units Total Norms Fld Vac Exc %Fld %Vac % F

1 Adjumani 1 48 36 12 0 75% 25% 36%2 Alebtong 1 48 50 0 2 104% 0% 44%3 Amolatar 1 48 43 5 0 90% 10% 28%4 Amuria 1 48 55 0 7 115% 0% 56%5 Amuru 1 48 53 0 5 110% 0% 40%6 Arua 4 192 153 39 0 80% 20% 42%7 Budaka 1 48 41 7 0 85% 15% 54%8 Bugiri 1 48 28 20 0 58% 42% 43%9 Bugweri 1 48 50 0 2 104% 0% 60%

10 Buhweju 1 48 39 9 0 81% 19% 44%11 Bukedea 1 48 39 9 0 81% 19% 56%12 Bukomansimbi 1 48 44 4 0 92% 8% 50%13 Bukwo 1 48 27 21 0 56% 44% 56%14 Bulambuli 1 48 73 0 25 152% 0% 49%15 Buliisa 1 48 48 0 0 100% 0% 60%16 Bundibugyo 2 96 84 12 0 88% 13% 44%17 Bunyangabu 1 48 54 0 6 113% 0% 57%18 Bushenyi 2 96 76 20 0 79% 21% 53%19 Busia 1 48 36 12 0 75% 25% 56%20 Butebo 1 48 48 0 0 100% 0% 48%21 Buvuma 1 48 47 1 0 98% 2% 43%22 Buyende 1 48 38 10 0 79% 21% 45%23 Dokolo 1 48 59 0 11 123% 0% 46%24 Gomba 1 48 32 16 0 67% 33% 59%25 Gulu 1 48 42 6 0 88% 13% 45%26 Hoima 1 48 43 5 0 90% 10% 47%27 Ibanda 1 48 46 2 0 96% 4% 52%28 Iganga 1 48 34 14 0 71% 29% 47%29 Isingiro 4 192 121 71 0 63% 37% 50%30 Jinja 5 240 275 0 35 115% 0% 58%31 Kaabong 1 48 41 7 0 85% 15% 37%32 Kabale 3 144 94 50 0 65% 35% 44%33 Kabarole 2 96 88 8 0 92% 8% 63%34 Kaberamaido 1 48 55 0 7 115% 0% 36%35 Kakumiro 2 96 58 38 0 60% 40% 52%36 Kalangala 2 96 85 11 0 89% 11% 54%37 Kaliro 1 48 43 5 0 90% 10% 49%38 Kalungu 1 48 40 8 0 83% 17% 53%39 Kampala 3 144 217 0 73 151% 0% 41%40 Kamuli 2 96 87 9 0 91% 9% 52%41 Kamwenge 2 96 140 0 44 146% 0% 58%42 Kanungu 2 96 103 0 7 107% 0% 54%


43 Kapelebyong 1 48 41 7 0 85% 15% 29%44 Kasanda 2 96 69 27 0 72% 28% 54%45 Kasese 3 144 73 71 0 51% 49% 51%46 Katakwi 1 48 32 16 0 67% 33% 44%47 Kayunga 2 96 93 3 0 97% 3% 59%48 Kibaale 1 48 51 0 3 106% 0% 57%49 Kiboga 1 48 47 1 0 98% 2% 55%50 Kibuku 1 48 56 0 8 117% 0% 41%51 Kikuube 2 96 56 40 0 58% 42% 41%52 Kiruhura 2 96 72 24 0 75% 25% 50%53 Kisoro 3 144 97 47 0 67% 33% 46%54 Kitgum 1 48 50 0 2 104% 0% 32%55 Koboko 1 48 48 0 0 100% 0% 54%56 Kole 1 48 44 4 0 92% 8% 50%57 Kotido 1 48 40 8 0 83% 17% 38%58 Kumi 1 48 35 13 0 73% 27% 63%59 Kwania 1 48 61 0 13 127% 0% 48%60 Kween 1 48 51 0 3 106% 0% 41%61 Kyankwanzi 1 48 45 3 0 94% 6% 47%62 Kyegegwa 1 48 56 0 8 117% 0% 43%63 Kyenjojo 1 48 41 7 0 85% 15% 56%64 Kyotera 1 48 69 0 21 144% 0% 57%65 Lamwo 2 96 77 19 0 80% 20% 40%66 Lira 2 96 85 11 0 89% 11% 49%67 Luuka 1 48 58 0 10 121% 0% 48%68 Luwero 3 144 180 0 36 125% 0% 62%69 Lwengo 3 144 100 44 0 69% 31% 62%70 Manafwa 2 96 78 18 0 81% 19% 54%71 Masaka 2 96 62 34 0 65% 35% 58%72 Masindi 2 96 57 39 0 59% 41% 40%73 Mayuge 2 96 86 10 0 90% 10% 35%74 Mbale 4 192 158 34 0 82% 18% 58%75 Mbarara 4 192 126 66 0 66% 34% 60%76 Mitooma 1 48 41 7 0 85% 15% 51%77 Mityana 4 192 105 87 0 55% 45% 51%78 Moroto 1 48 33 15 0 69% 31% 48%79 Moyo 1 48 57 0 9 119% 0% 39%80 Mpigi 1 48 69 0 21 144% 0% 59%81 Mukono 2 96 53 43 0 55% 45% 43%82 Nabilatuk 1 48 30 18 0 63% 38% 40%83 Nakapiripirit 1 48 43 5 0 90% 10% 51%84 Nakaseke 2 96 86 10 0 90% 10% 71%85 Nakasongola 2 96 100 0 4 104% 0% 44%86 Namayingo 1 48 50 0 2 104% 0% 56%87 Namisindwa 1 48 26 22 0 54% 46% 42%88 Namutumba 1 48 38 10 0 79% 21% 53%


89 Ngora 1 48 30 18 0 63% 38% 50%90 Ntoroko 1 48 45 3 0 94% 6% 44%91 Ntungamo 4 192 160 32 0 83% 17% 53%92 Omoro 1 48 45 3 0 94% 6% 47%93 Otuke 1 48 36 12 0 75% 25% 53%94 Oyam 1 48 61 0 13 127% 0% 46%95 Pader 1 48 44 4 0 92% 8% 36%96 Pakwach 1 48 57 0 9 119% 0% 42%97 Rubanda 2 96 75 21 0 78% 22% 45%98 Rubirizi 1 48 31 17 0 65% 35% 58%99 Rukiga 2 96 78 18 0 81% 19% 41%

100 Rukungiri 4 192 149 43 0 78% 22% 58%101 Serere 2 96 82 14 0 85% 15% 48%102 Sheema 1 48 54 0 6 113% 0% 59%103 Sironko 2 96 107 0 11 111% 0% 45%104 Soroti 2 96 74 22 0 77% 23% 47%105 Ssembabule 2 96 68 28 0 71% 29% 57%106 Tororo 3 144 106 38 0 74% 26% 48%107 Wakiso 5 240 187 53 0 78% 22% 60%108 Yumbe 2 96 75 21 0 78% 22% 55%

Total 179 8592 7454 1541 403 87% 18% 50%

ANNEX 5: Summary of the HRH Staffing levels Health Centre III Level in 128 districts- In Alphabetic Order by District

No. District No of Units

Unit Norm

Total Norms Fld Vac Exc %Fld %Vac % F

1 Abim 3 19 57 47 10 0 82% 18% 47%2 Adjumani 8 19 152 153 0 1 101% 0% 42%3 Agago 9 19 171 190 0 19 111% 0% 46%4 Alebtong 4 19 76 58 18 0 76% 24% 48%5 Amolatar 3 19 57 50 7 0 88% 12% 52%6 Amudat 2 19 38 14 24 0 37% 63% 50%7 Amuria 6 19 114 92 22 0 81% 19% 49%8 Amuru 8 19 152 178 0 26 117% 0% 42%9 Apac 5 19 95 74 21 0 78% 22% 34%

10 Arua 25 19 475 334 141 0 70% 30% 50%11 Budaka 11 19 209 140 69 0 67% 33% 50%12 Bududa 7 19 133 101 32 0 76% 24% 60%13 Bugiri 9 19 171 128 43 0 75% 25% 66%14 Bugweri 4 19 76 62 14 0 82% 18% 47%15 Buhweju 4 19 76 59 17 0 78% 22% 58%16 Buikwe 12 19 228 153 75 0 67% 33% 61%17 Bukedea 5 19 95 78 17 0 82% 18% 56%18 Bukomansimbi 3 19 57 47 10 0 82% 18% 68%19 Bukwo 3 19 57 55 2 0 96% 4% 49%20 Bulambuli 13 19 247 157 90 0 64% 36% 59%


21 Buliisa 4 19 76 66 10 0 87% 13% 50%22 Bundibugyo 6 19 114 93 21 0 82% 18% 45%23 Bunyangabu 8 19 152 126 26 0 83% 17% 60%24 Bushenyi 7 19 133 116 17 0 87% 13% 59%25 Busia 7 19 133 99 34 0 74% 26% 53%26 Butaleja 11 19 209 173 36 0 83% 17% 57%27 Butambala 5 19 95 68 27 0 72% 28% 63%28 Butebo 4 19 76 51 25 0 67% 33% 57%29 Buvuma 6 19 114 89 25 0 78% 22% 51%30 Buyende 4 19 76 60 16 0 79% 21% 53%31 Dokolo 4 19 76 64 12 0 84% 16% 38%32 Gomba 5 19 95 82 13 0 86% 14% 54%33 Gulu 9 19 171 143 28 0 84% 16% 55%34 Hoima 10 19 190 128 62 0 67% 33% 53%35 Ibanda 4 19 76 68 8 0 89% 11% 62%36 Iganga 9 19 171 180 0 9 105% 0% 61%37 Isingiro 18 19 342 179 163 0 52% 48% 58%38 Jinja 11 19 209 242 0 33 116% 0% 63%39 Kaabong 7 19 133 82 51 0 62% 38% 39%40 Kabale 7 19 133 110 23 0 83% 17% 51%41 Kabarole 14 19 266 267 0 1 100% 0% 64%42 Kaberamaido 8 19 152 123 29 0 81% 19% 45%43 Kagadi 10 19 190 103 87 0 54% 46% 64%44 Kakumiro 6 19 114 62 52 0 54% 46% 61%45 Kalangala 7 19 133 95 38 0 71% 29% 55%46 Kaliro 4 19 76 79 0 3 104% 0% 38%47 Kalungu 8 19 152 137 15 0 90% 10% 63%48 Kampala 6 19 114 267 0 234% 0% 37%49 Kamuli 10 19 190 190 0 0 100% 0% 57%50 Kamwenge 8 19 152 148 4 0 97% 3% 51%51 Kanungu 9 19 171 150 21 0 88% 12% 54%52 Kapchorwa 8 19 152 137 15 0 90% 10% 46%53 Kapelebyong 2 19 38 32 6 0 84% 16% 44%54 Kasanda 4 19 76 42 34 0 55% 45% 67%55 Kasese 32 19 608 467 141 0 77% 23% 61%56 Katakwi 4 19 76 61 15 0 80% 20% 59%57 Kayunga 8 19 152 132 20 0 87% 13% 64%58 Kibaale 3 19 57 56 1 0 98% 2% 55%59 Kiboga 6 19 114 88 26 0 77% 23% 50%60 Kibuku 7 19 133 104 29 0 78% 22% 62%61 Kikuube 13 19 247 149 98 0 60% 40% 55%62 Kiruhura 12 19 228 133 95 0 58% 42% 56%63 Kiryandongo 5 19 95 96 0 1 101% 0% 45%64 Kisoro 13 19 247 218 29 0 88% 12% 43%65 Kitgum 8 19 152 146 6 0 96% 4% 53%66 Koboko 6 19 114 93 21 0 82% 18% 42%


67 Kole 4 19 76 71 5 0 93% 7% 41%68 Kotido 6 19 114 88 26 0 77% 23% 53%69 Kumi 6 19 114 81 33 0 71% 29% 68%70 Kwania 6 19 114 98 16 0 86% 14% 53%71 Kween 9 19 171 148 23 0 87% 13% 45%72 Kyankwanzi 8 19 152 109 43 0 72% 28% 56%73 Kyegegwa 6 19 114 102 12 0 89% 11% 52%74 Kyenjojo 8 19 152 154 0 2 101% 0% 49%75 Kyotera 10 19 190 187 3 0 98% 2% 64%76 Lamwo 6 19 114 79 35 0 69% 31% 67%77 Lira 11 19 209 171 38 0 82% 18% 51%78 Luuka 6 19 114 97 17 0 85% 15% 58%79 Luwero 16 19 304 257 47 0 85% 15% 68%80 Lwengo 4 19 76 65 11 0 86% 14% 68%81 Lyantonde 4 19 76 68 8 0 89% 11% 44%82 Manafwa 4 19 76 60 16 0 79% 21% 67%83 Maracha 9 19 171 149 22 0 87% 13% 48%84 Masaka 7 19 133 103 30 0 77% 23% 71%85 Masindi 9 19 171 129 42 0 75% 25% 53%86 Mayuge 6 19 114 113 1 0 99% 1% 54%87 Mbale 26 19 494 325 169 0 66% 34% 60%88 Mbarara 12 19 228 139 89 0 61% 39% 68%89 Mitooma 6 19 114 83 31 0 73% 27% 58%90 Mityana 11 19 209 149 60 0 71% 29% 66%91 Moroto 6 19 114 56 58 0 49% 51% 43%92 Moyo 12 19 228 242 0 14 106% 0% 38%93 Mpigi 12 19 228 172 56 0 75% 25% 66%94 Mubende 7 19 133 99 34 0 74% 26% 72%95 Mukono 12 19 228 196 32 0 86% 14% 63%96 Nabilatuk 2 19 38 27 11 0 71% 29% 52%97 Nakapiripirit 3 19 57 38 19 0 67% 33% 55%98 Nakaseke 5 19 95 97 0 2 102% 0% 59%99 Nakasongola 7 19 133 136 0 3 102% 0% 56%

100 Namayingo 4 19 76 64 12 0 84% 16% 47%101 Namisindwa 8 19 152 143 9 0 94% 6% 49%102 Namutumba 5 19 95 92 3 0 97% 3% 57%103 Napak 6 19 114 94 20 0 82% 18% 51%104 Nebbi 7 19 133 103 30 0 77% 23% 41%105 Ngora 6 19 114 82 32 0 72% 28% 63%106 Ntoroko 3 19 57 40 17 0 70% 30% 33%107 Ntungamo 10 19 190 167 23 0 88% 12% 54%108 Nwoya 3 19 57 49 8 0 86% 14% 49%109 Omoro 5 19 95 89 6 0 94% 6% 47%110 Otuke 5 19 95 61 34 0 64% 36% 33%111 Oyam 3 19 57 67 0 10 118% 0% 43%112 Pader 11 19 209 149 60 0 71% 29% 47%


113 Pakwach 6 19 114 64 50 0 56% 44% 39%114 Pallisa 9 19 171 140 31 0 82% 18% 57%115 Rakai 9 19 171 130 41 0 76% 24% 49%116 Rubanda 5 19 95 73 22 0 77% 23% 42%117 Rubirizi 3 19 57 64 0 7 112% 0% 55%118 Rukiga 3 19 57 53 4 0 93% 7% 43%119 Rukungiri 10 19 190 149 41 0 78% 22% 60%120 Serere 6 19 114 66 48 0 58% 42% 53%121 Sheema 4 19 76 48 28 0 63% 37% 60%122 Sironko 14 19 266 160 106 0 60% 40% 44%123 Soroti 10 19 190 145 45 0 76% 24% 57%124 Ssembabule 5 19 95 57 38 0 60% 40% 47%125 Tororo 18 19 342 232 110 0 68% 32% 57%126 Wakiso 22 19 418 302 116 0 72% 28% 70%127 Yumbe 8 19 152 97 55 0 64% 36% 35%128 Zombo 6 19 114 123 0 9 108% 0% 52%

Total 991 2,432 18,829 80% 21% 54%

ANNEX 6: Summary of the HRH Staffing Levels in each of the 1,712 Health Centre IIs - In alphabetic order by District

N0. District Units Total Norms Fld Vac Exc %Fld %Vac % F

1 Abim 15 135 77 58 0 57% 43% 47%2 Adjumani 21 189 173 16 0 92% 8% 38%3 Agago 29 261 215 46 0 82% 18% 50%4 Alebtong 11 99 47 52 0 47% 53% 49%5 Amolatar 7 63 37 26 0 59% 41% 41%6 Amudat 5 45 15 30 0 33% 67% 60%7 Amuria 9 81 48 33 0 59% 41% 52%8 Amuru 17 153 172 0 19 112% 0% 48%9 Apac 11 99 77 22 0 78% 22% 40%

10 Arua 20 180 113 67 0 63% 37% 48%11 Budaka 3 27 22 5 0 81% 19% 59%12 Bududa 6 54 22 32 0 41% 59% 41%13 Bugiri 24 216 49 167 0 23% 77% 73%14 Bugweri 10 90 50 40 0 56% 44% 54%15 Buhweju 8 72 27 45 0 38% 63% 56%16 Buikwe 16 144 60 84 0 42% 58% 62%17 Bukedea 1 9 2 7 0 22% 78% 0%18 Bukomansimbi 3 27 20 7 0 74% 26% 75%19 Bukwo 11 99 74 25 0 75% 25% 38%20 Bulambuli 11 99 47 52 0 47% 53% 68%21 Buliisa 3 27 29 0 2 107% 0% 55%22 Bundibugyo 13 117 84 33 0 72% 28% 36%23 Bunyangabu 8 72 53 19 0 74% 26% 68%


24 Bushenyi 12 108 68 40 0 63% 37% 59%25 Busia 19 171 58 113 0 34% 66% 67%26 Butaleja 10 90 38 52 0 42% 58% 66%27 Butambala 8 72 29 43 0 40% 60% 66%28 Butebo 3 27 10 17 0 37% 63% 40%29 Buvuma 3 27 17 10 0 63% 37% 65%30 Buyende 6 54 25 29 0 46% 54% 68%31 Dokolo 11 99 68 31 0 69% 31% 54%32 Gomba 11 99 40 59 0 40% 60% 73%33 Gulu 16 144 117 27 0 81% 19% 51%34 Hoima 11 99 45 54 0 45% 55% 73%35 Ibanda 18 162 60 102 0 37% 63% 65%36 Iganga 15 135 71 64 0 53% 47% 68%37 Isingiro 34 306 142 164 0 46% 54% 61%38 Jinja 33 297 249 48 0 84% 16% 56%39 Kaabong 23 207 116 91 0 56% 44% 40%40 Kabale 32 288 163 125 0 57% 43% 56%41 Kabarole 11 99 58 41 0 59% 41% 76%42 Kaberamaido 6 54 41 13 0 76% 24% 29%43 Kagadi 8 72 35 37 0 49% 51% 63%44 Kakumiro 6 54 19 35 0 35% 65% 58%45 Kalangala 8 72 45 27 0 63% 38% 76%46 Kaliro 7 63 54 9 0 86% 14% 57%47 Kalungu 3 27 23 4 0 85% 15% 70%48 Kampala 3 27 6 21 0 22% 78% 67%49 Kamuli 22 198 110 88 0 56% 44% 61%50 Kamwenge 18 162 116 46 0 72% 28% 47%51 Kanungu 15 135 79 56 0 59% 41% 33%52 Kapchorwa 11 99 53 46 0 54% 46% 57%53 Kapelebyong 9 81 38 43 0 47% 53% 37%54 Kasanda 12 108 30 78 0 28% 72% 67%55 Kasese 54 486 215 271 0 44% 56% 52%56 Katakwi 14 126 77 49 0 61% 39% 61%57 Kayunga 8 72 45 27 0 63% 38% 71%58 Kibaale 1 9 10 0 1 111% 0% 30%59 Kiboga 12 108 39 69 0 36% 64% 54%60 Kibuku 4 36 22 14 0 61% 39% 82%61 Kikuube 5 45 21 24 0 47% 53% 52%62 Kiruhura 21 189 52 137 0 28% 72% 54%63 Kiryandongo 13 117 76 41 0 65% 35% 54%64 Kisoro 18 162 104 58 0 64% 36% 50%65 Kitgum 14 126 83 43 0 66% 34% 54%66 Koboko 8 72 43 29 0 60% 40% 49%67 Kole 5 45 44 1 0 98% 2% 43%68 Kotido 10 90 43 47 0 48% 52% 67%69 Kumi 11 99 26 73 0 26% 74% 69%


70 Kwania 6 54 41 13 0 76% 24% 34%71 Kween 14 126 80 46 0 63% 37% 34%72 Kyankwanzi 5 45 21 24 0 47% 53% 62%73 Kyegegwa 6 54 60 0 6 111% 0% 48%74 Kyenjojo 7 63 64 0 1 102% 0% 53%75 Kyotera 22 198 129 69 0 65% 35% 57%76 Lamwo 14 126 46 80 0 37% 63% 59%77 Lira 7 63 54 9 0 86% 14% 37%78 Luuka 20 180 58 122 0 32% 68% 74%79 Luwero 21 189 110 79 0 58% 42% 76%80 Lwengo 9 81 39 42 0 48% 52% 92%81 Lyantonde 11 99 65 34 0 66% 34% 63%82 Manafwa 3 27 22 5 0 81% 19% 68%83 Maracha 6 54 43 11 0 80% 20% 40%84 Masaka 13 117 61 56 0 52% 48% 89%85 Masindi 19 171 155 16 0 91% 9% 51%86 Mayuge 27 243 160 83 0 66% 34% 54%87 Mbale 9 81 63 18 0 78% 22% 68%88 Mbarara 30 270 86 184 0 32% 68% 74%89 Mitooma 8 72 42 30 0 58% 42% 45%90 Mityana 18 162 57 105 0 35% 65% 75%91 Moroto 6 54 19 35 0 35% 65% 42%92 Moyo 25 225 179 46 0 80% 20% 46%93 Mpigi 6 54 25 29 0 46% 54% 60%94 Mubende 29 261 84 177 0 32% 68% 61%95 Mukono 20 180 137 43 0 76% 24% 53%96 Nabilatuk 4 36 23 13 0 64% 36% 39%97 Nakapiripirit 2 18 11 7 0 61% 39% 73%98 Nakaseke 10 90 39 51 0 43% 57% 79%99 Nakasongola 22 198 129 69 0 65% 35% 49%

100 Namayingo 21 189 67 122 0 35% 65% 66%101 Namisindwa 4 36 13 23 0 36% 64% 31%102 Namutumba 17 153 38 115 0 25% 75% 84%103 Napak 7 63 53 10 0 84% 16% 64%104 Nebbi 11 99 46 53 0 46% 54% 48%105 Ngora 3 27 17 10 0 63% 37% 76%106 Ntoroko 3 27 24 3 0 89% 11% 38%107 Ntungamo 26 234 147 87 0 63% 37% 48%108 Nwoya 9 81 47 34 0 58% 42% 36%109 Omoro 16 144 128 16 0 89% 11% 48%110 Otuke 9 81 44 37 0 54% 46% 25%111 Oyam 21 189 161 28 0 85% 15% 41%112 Pader 23 207 99 108 0 48% 52% 56%113 Pakwach 9 81 34 47 0 42% 58% 44%114 Pallisa 6 54 35 19 0 65% 35% 46%115 Rakai 22 198 96 102 0 48% 52% 54%


116 Rubanda 19 171 108 63 0 63% 37% 55%117 Rubirizi 9 81 28 53 0 35% 65% 46%118 Rukiga 18 162 105 57 0 65% 35% 54%119 Rukungiri 39 351 157 194 0 45% 55% 64%120 Serere 8 72 25 47 0 35% 65% 64%121 Sheema 19 171 62 109 0 36% 64% 52%122 Sironko 11 99 65 34 0 66% 34% 52%123 Soroti 10 90 29 61 0 32% 68% 62%124 Ssembabule 17 153 37 116 0 24% 76% 65%125 Tororo 35 315 88 227 0 28% 72% 66%126 Wakiso 33 297 129 168 0 43% 57% 83%127 Yumbe 17 153 81 72 0 53% 47% 44%128 Zombo 7 63 33 30 0 52% 48% 52% 1712 15408 8534 6903 29 55% 45% 55%

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