Human Resource for Health (HRH) Database Linkage and Harmonisation

in UgandaManiple EB, Biesma RG, Byrne E & Brugha R

CHRAIC ProgrammeDep’t of Epidemiology & Public Health Medicine,

Population Health Sciences Division, RCSI

Acknowledgements: MOH Uganda, Uganda Faith-based Medical Bureaux, IntraHealth, IFGH, CHRAIC programme,

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

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

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”

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

Objectives1. 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

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)

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

Findings (II) – Geographical and Skill Mix Distribution

Source: MOH Uganda and IntraHealth, 2010: Human Resources for Health Audit Report 2010

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)

Findings (IV) – Quality of InformationOwner Hospitals Lower

LevelsContent

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

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 levelNational Private Practitioners HRH Database

UMMB HRH Database

Traditional Medicine practitioner

District level National level Traditional Medicine HRH Database

KeyRed /dashed= lacking structure or link

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

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

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

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)

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

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