The health workforce: a recent priority for investment

The health workforce: a recent priority for investment

• 2006 – 2015: Health workforce decade

• World Health Report 2006: Working together for health

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Demand for information –What do we want to know?

Demand for information –What do we want to know?

• Active workforce -- stocks of various types of health professionals in the public or private sectors

(disaggregated by age, sex and geographic location)

• Entry -- annual numbers graduating from training institutions

• Exit – annual numbers departing from service due to movement to private sector, emigration, change of occupation, retirement or death

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Demand for information –What do we want to know?

Demand for information –What do we want to know?

• Performance -- the outputs of health workers (e.g. outpatient attendance per capita; hospitalizations per capita)

• Costs -- expenditures on remuneration (including benefits) as well as on pre-service training

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Key health workforce metrics for a health system dashboardKey health workforce metrics for a health system dashboard

Health worker densities

• by type of health worker

• by sector

South African health worker densities per 100,000

Sources: HST, HSRC, NDoH, HPCSA, SANC, StatsSA

Total active workforce

Public sector

Private sector

Physicians (2002)

51.2 19.3 31.9

Nurses (2001)

392 245 146

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Key health workforce metrics if there is room on the

dashboard

Key health workforce metrics if there is room on the

dashboard

Health worker densities

• by type of health worker

• by sector

• by geographic location for the public sector

South African health worker densities per 100,000

Sources: HST, HSRC, NDoH, HPCSA, SANC, StatsSA

Total Public Private Public in most advantaged province

Public in least advantaged province

Physicians (2002)

51.2 19.3 31.9 33.1 9.1

Nurses (2001)

392 245 146 267 1815

Supply – What data sources exist?

Supply – What data sources exist?

Sources of data

for monitoring the health workforce

(see handout) :

– National population census

– Labour force survey

– Health facility census

– Professional registration database

– Civil service payroll database

– Staffing reports from each health facility 6

Population censusPopulation census

• Strengths 

• ·     counts all workers:

– - private and public – - health professionals workers working in non-health sectors– - management and support staff working in the health industry

• ·     geographical disaggregation to lowest level

• ·     rigorous collection and management of data

 

• Limitations 

• ·      once each ten years

• ·      occupational data often not coded with sufficient precision

• ·      census authorities may be reluctant to release the micro-data

      provide little information on entry into and exit from the workforce7

Labour force surveyLabour force survey

• Strengths• ·      Counts all occupations (including management & support staff)

• ·    Counts both public and private

• ·    Counts unemployed and part-time workers

• ·    Can provide information salaries & wages

• ·    Rigorous data collection and data management. 

• Limitations• ·      Often only once each 5 years;

• ·    Small sample size – Very wide confidence intervals for countries with few health

workers – Geographic disaggregation often not advisable

• ·    Occupation is often not coded with sufficient precision

• ·    Cross-sectional: can't track entry and exit8

Health facility censusHealth facility census

• Strengths• ·     counts all health facility staff including management & support staff

• ·   allows geographical disaggregation

• ·   can be used to track in-service training/skills and productivity

• ·   (often) rigorous data collection and data management.

• ·   relatively less costly 

• Limitations• ·     no data on entry and exit

• ·   double counts dually employed workers  

• ·   may omit some private facilities, community workers, unemployed

• ·   (historically) conducted ad hoc and infrequently

• ·   usually don't provide data on remuneration 9

Professional registration databaseProfessional registration database

• Strengths• ·      Counts registered health professionals (private as well as public)

• ·    Using a unique identifier the database could track entry and exit 

• Limitations• ·      Requires developing the capacity of regulatory authorities

• ·    Accurate updating depends upon incentives and/or enforcement

• ·    Difficult to track non-professional health workers and support staff

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Multiple data sources validation and interpolationMultiple data sources validation and interpolation

Data on nurses in South Africa

Source: HSRC, SANC, StatsSA, NDoH

1. Total registered with SANC (2001)

2. Active workforce from LFS (2001)

3. Public sector nurses (NDoH, 2001)

4. Private sector nurses (#2 – #3)

190,449 155,484 97,423 58,061

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The gap between Supply & DemandThe gap between Supply & Demand

The Global Atlas of the Health Workforce (http://www.who.int/globalatlas/default.asp )

is now more extensively populated:

• Data on more types of health workers – 2004 -- 5 occupations (physician, nurse, midwife, pharmacist, dentist)

2006 – 13 or more occupations (also clinical officer/medical assistant, radiographer, lab scientist, lab technician, dental technician, pharmaceutical technician, community health worker or TBA, health management and support workers)

• Recent data for more countries –

2004 -- 48% of sub-Saharan African countries

2006 -- 96%

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More data …but some data are now less

comparable

More data …but some data are now less

comparable

Number of physicians reported to the Global Atlas for

select countries of

sub-Saharan Africa 0

1000

2000

3000

4000

5000

Ethiopia 1415 1971 1,936

Ghana 1112 1842 3,240

Madagascar 1519 1428 5,201

Mali 474 529 1,053

Zimbabwe 1631 736 2,086

1994 - 1997 1999 - 2002 2003 - 2004

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More data …but some data are now less

comparable

More data …but some data are now less

comparable

Number of physicians reported to the Global Atlas for Ghana

1112

1842

3,240

0

500

1000

1500

2000

2500

3000

3500

1994 - 1997 1999 - 2002 2003 - 2004

MoH payroll

Physicians registered with Ghana Medical council?

Cumulative number of physicians ever trained in Ghana?

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Significant inconsistencies between data sources are

common

Significant inconsistencies between data sources are

common

MoH payroll records

Professional registration database

Staffing reports from health facilities

Physicians 111 283 179

Nurses 2,837 7,955 4,966

Stocks of health workers in Malawi in 2004 – 2005 according to various data sources

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Priorities for consensus on methodsPriorities for consensus on methods

• Metadata must be improved:

detailed information on– Source of data– Known limitations – e.g. double counting– Classification – Is private sector included?; Are health

professionals working for other Ministries included?

• Classification of health occupations needs further development

– Revision of the ILO's ISCO– Harmonization of MoH systems of classification

• Standards for disaggregation by other key variables

– Sub-national location 16

Standards for disaggregation -- to compare geographic

inequalities

Standards for disaggregation -- to compare geographic

inequalities

Country Nat'l

Most advantaged province

Least advantaged province

Most / Least

Burkina Faso (2001) 4.8 38.4 1.7 23

Ghana (1996) 6.2 20.7 1.2 17

Ethiopia (2001) 2.7 22.2 1.5 15

Malawi (2002) 1.3 3.7 0.0 ∞Mozambique (2003) 3.5 41.0 1.5 27

South Africa (2002) 19.3 33.1 9.1 3.6

For many countries, health workforce statistics are already disaggregated by province:

Physicians per 100,000 population

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Priorities for investment in data sources

Priorities for investment in data sources

1. Capacity

Improving health workforce statistics will require investments to build sustainable capacity of– Ministries of Health– regulatory bodies/professional councils– training institutions

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Priorities for investment in data sources

Priorities for investment in data sources

2. Computerization and linkage of administrative data

(on enrolment, graduation, registration/licensing, hiring, pay, deployment, transfer, promotion)

Linkage possible if each worker has a unique identifier

Can strengthen management as well as strategic

M&E

Success depends upon incentives for accurate and timely collection and reporting

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Priorities for investment in data sources

Priorities for investment in data sources

3. Population census

Can generate statistics on the private sector and health professionals working in non-health industries

Data can be dissaggregated to the lowest level

Requires census authorities to code occupational data with greater precision and grant access to the census micro-data.

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Priorities for investment in data sources

Priorities for investment in data sources

4. Health facility census

Can generate data on not only the human resources but their skills, productivity (volume of services provided), absenteeism, availability of other inputs (drugs, supplies, infrastructure) and quality of services.

Enumeration of private facilities is a challenge

Funding and political commitment needed to repeat these surveys each 2 to 3 years

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Priorities for investment in data sources

Priorities for investment in data sources

Distribution of nurses working in the public sector

by district, Rwanda, SAM, 2004

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