HRH Databases in UG

1. Human Resource for Health (HRH)
Database Linkage and Harmonisation
in Uganda
Maniple EB, Biesma RG, Byrne E & Brugha R
CHRAIC Programme
Dep’t of Epidemiology & Public Health Medicine,
Population Health Sciences Division, RCSI
Acknowledgements: MOH Uganda, Uganda Faith-based
Medical Bureaux, IntraHealth, IFGH, CHRAIC programme,

2. Uganda
• East Africa
• 34 million people
• 82% in rural areas
• GNI US $350 per capita p.a.
• 0.08 doctors/1000 people
• 4 medical schools, 27 Nurse Training
Schools, 3 Clinical Officer schools
•Health care: Gov’t, PNFP, PHP, TCM

3. Background
• Human Resources for Health (HRH) crisis
– global but developing countries worst affected
– 46 of 57 countries below density of 2.5/1000 population were from Sub-
Saharan Africa
– Uganda had 0.08 doctors/1000 population
• Poor Human Resources Management (HRM) is a key aspect of the HRH
crisis
• Lack of comprehensive and reliable data on HRH negatively affects
planning, deployment, supervision and management of staff
• Staff maldistribution exists between and within countries, with rural
areas worst affected, but no analysis of rural-urban distribution

4. Background (II)
• GHWA’s 2008 Kampala Declaration and Agenda
for Global Action calls for establishment of
workforce information systems
• Uganda
– set up a HR Information System (HRIS)
– conducts periodic audit of health workers to ensure
smooth management of the payroll and reduce on
“ghost workers”

5. Problem Statement & Justification
• Inequitable distribution of health workers negatively
affects right to equitable access to quality health care
• Lack of comprehensive and accurate information on
HRH limits ability to plan improvements in distribution
and management of staff, wastes resources
• Overworked staff are demotivated and dangerous,
hence need to know under-staffed areas and skills
• Fragmented information is a waste of resources, hence
need to integrate HRH information from entire sector

6. Objectives
1. To determine the geographic and skill mix distribution of
qualified health workers in Uganda
2. To identify the current efforts to improve the quality of
available information on the distribution of health
workers
3. To determine the level of integration of data on the
distribution of health workers
4. To identify the successes and challenges of producing
high quality information on the distribution of health
workers

7. Methodology (II)
1. Review of
– Documents:
• HRH Audit Reports (2010, 2009)
• Sector Performance Reports (2011, 2010, 2009)
• Sector Plans: HSSIP, Health Policy
– Existing HRH databases: MOH, UCMB, UPMB, UMMB
2. In-depth Interviews:
– MOH (Personnel Department, Resource Centre)
– 3 Faith-based medical bureaux
– NGO (Capacity Project/IntraHealth)

8. Findings (I) - Geographical and Skill Mix Distribution
• Government:
– 47,173 approved posts but only 56% (24,914) filled with
qualified staff
– Most of the remaining 44% are filled but with unqualified staff
– Central region best and worst staffed (Range: 42% to 123%)
– Worst staffed district in Northwest (19%)
• Other subsystems:
– Private practitioners: No centralised data
– PNFP:
• No comprehensive data on approved positions
• Only 35% of staff are qualified
– TCM: No data, no known qualification, no structure
• Skill-mix distribution: Analysis on-going

9. Findings (II) – Geographical and Skill Mix Distribution
Source: MOH Uganda and IntraHealth, 2010: Human Resources for Health Audit Report 2010

10. Findings (III) – Efforts to Improve Quality of Information
• Establishment of positions of
– Records Assistant at health facility level
– Biostatistician at district level
• Recruiting & training data managers
• Decentralisation of HMIS stationery management
• Supply of computers and internet connection
• Web-enabled report forms (UPMB)
• Regular feedback (UCMB)

11. Findings (IV) – Quality of Information
Owner Hospitals Lower
Levels
Content
MOH √ √ Numbers, qualifications,
vacancies
FBB –
Catholic
√ √ Numbers, qualifications,
vacancies
FBB –
Protestant
√ Some Numbers, qualifications,
vacancies
FBB - Muslim √ Some Numbers, qualifications,
vacancies
•Only MOH database attempts a geographical analysis
•No database analyses health-worker skills

12. Findings (V) – Database Linkage and Integration
Government
health facility
District level MOH HRIS
National HRH
Database
Diocese level
Diocese level
District level
Protestant
health facility
Muslim health
facility
Catholic health
facility
UPMB HRH
Database
UCMB HRH Database
Private health
facility
District level
National Private
Practitioners HRH
Database
UMMB HRH
Database
Traditional
Medicine
practitioner
District level National level Traditional
Medicine HRH Database
Key
Red /dashed= lacking structure or link

13. Findings (VI) – Database Linkage and Integration
• No comprehensive national database covering the
entire health sector
• Parallel databases operated by subsectors
• No linkage of databases at any level
• No common format, hence different levels of detail
• No integration
• Data only shared upon request
• No joint meetings to discuss the issue

14. Findings (VII) – Successes & Opportunities
• All subsystems, except private practitioners
and TCM practitioners, have HRH databases
up to national level
• Presence of web-enabled electronic databases
• Internet access in most parts of the country

15. Findings (VII) – Challenges & Threats
• Lack of a policy compelling all to report
• Lack of communication and formal structures for
communication between subsystems at different
levels
• Multiple formats and software
• Inadequate funding, IT facilities and technical
capacity especially at lower level facilities

16. Findings (VIII) – Challenges & Threats
• High staff turnover especially in PNFP subsector
• Low demand for HRH data (MOH asks only for
clinical outputs)
• Lack of a policy on data governance and security
• Lack of unique staff identifier (no National ID)

17. Discussion
• Regional and rural-urban imbalance in staff distribution
exists in Uganda but is poorly documented
• Lack of relevant supportive policies creates room for low
investment in HRM systems and non-reporting
• Presence of 4 national HRH databases is an opportunity
to be exploited
• Low demand for HRH data provides no incentive for
investment in data linkage, analysis and utilisation

18. Recommendations
• To Ministries of Health and ICT to prepare a
national policy on electronic databases
• To MOH and faith-based Bureaux to harmonise
the formats of minimum data collected on HRH
• To MOH and faith-based Bureaux to analyse and
share HRH data more regularly than is the case