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This article discusses the importance of developing HRH projection models and reviews different approaches, criteria, and computer-based models for forecasting. It also explores various methods used in HRH projection models, such as needs-based, utilization-based, health worker to population ratio, service target-based, adjusted service target, and facility-based approaches. The article examines forecasting methods including population-based, econometric, and simulation models.
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Overview of Human Resources for Health Projection Models December 13, 2007 Pamela A. McQuide, R.N., Ph.D.
Objectives • To identify strengths and weaknesses of supply and demand approaches • To review methods of analysis for forecasting • To discuss criteria for good projection model • To identify existing computer based projection models
Why is it important to develop a HRH projection model? • Right health worker, with the right knowledge, skills and attitudes, right place at the right time to care for the health needs of the population • MDGs have certain targets for health outcomes (maternal outcomes, HIV, malaria, TB) • Over 60-80% of national health budgets pay for human resources for health
Approaches to estimate HRH requirements (Hall & Mejja (1978); Markham & Birch (1997) and O’Brien-Pallas et al 2001) • Needs-based • Estimates future requirements based on estimated health deficits of population • Assumption: All health needs can and should be met and resources used according to need. • Advantage: Addresses health needs using a mix of HRH and it is independent of utilization • Limitation: Ignores question of efficiency in allocation of resources, requires extensive data and, if technology changes, requires new norms
Utilization-based (demand based) • Estimates future requirements based on current level of service utilization related to future projection of demographic profiles • Assumption: Current level, mix, distribution of health services is appropriate; age and sex requirements constant; population changes are predictable • Advantage: Sets economically feasible targets due to little or no change in population • Limitation: Produces status quo prediction; requires lots of data; overlooks errors from assumptions
Health worker to population Specifies desired health worker to population ratio Assumption: Often based on current best region ratio or reference country with a similar or more developed health sector Advantage: Quick, easy to apply and understand Limitation: No insight into personnel utilization; no interaction between numbers, mix, productivity; base year maldistribution will continue in target year
Service target-based • Sets targets for production and delivery of specific outcome oriented health services; converts targets into HRH requirements for staffing and productivity standards • Assumptions: Assumes standards for each service covered are practicable and can be achieved within timescale and projection • Advantages: Relatively easy and understandable. Can assess interaction between variables • Limitations: Potentially unrealistic assumptions
Adjusted service target approach • Identifies service needs based on epidemiological and demographic profile; identifies tasks and skills required for evidence-based intervention based on functional job analysis; estimates time requirements for each intervention from time-motion or expert opinion and translates information into FTEs. • Assumption: Effective evidence-based interventions can be delivered in all settings and conditions • Advantages: Useful for specific programs and to identify training needs; goes toward competency based training • Limitations: Detailed workflow studies or expert opinion; can only be achieved with infrastructure, supplies & logistics
Facility based – 5 ways to group nurse workforce planning systems (Hurst, 2002) Simple to complex • Professional judgment (Telford approach) • Uses expert health care professional judgment about the size and mix of nursing teams • Nurses per occupied bed (top-down) • Acuity-quality (bottom-up) • Sensitive to the number and mix of patients
Cont.’d • Timed-task/activity approach • Regression analysis
Forecasting methods used • Borrow from demography, epidemiology, economics and industrial engineering. • Future HR requirements are impacted by demography, epidemiology, standards of care and productivity
Several forecasting methods:Population-based • Basic, low, and high projections • Basic assumption is that factors affecting supply would follow current demographic and utilization rates • Many adjustments have been made for attrition by age, part-time/full-time, costs of education, types of procedures…. • Generally assume production and utilization patterns will remain stable Limitations: Changes in supply or demand factors will distort forecast
Econometric models • Complex econometric models take into account factors such as: • Stock, wages • Demand based on vacancies, population and census • Useful for examining relationships between stock, wages, demand and budgets • Limitations: population health needs not taken into account, impact policy, budget pressures, or changes health system
Simulation models • More flexible and able to model real-world system over time, based on mathematical or logical relations. • Model run repeatedly to get an estimate of how the system would behave under different hypotheses related to model parameters • Analyze “what-if” • Costly to implement, detailed data required
Example simulation model China (Song and Rathwell, 1994) • Simulation model consisted of three sub-models • Population projections • Estimation of demand for medical services • Productivity of health services • Produced three estimates based on low and high limits
Why is the type of model important • Canada (Birch et al 1994) compared across several conceptual models in Canada to estimate nurse requirements: • Needs model (70,808) • Utilization /demand (112,000 nurses) Forecasting model can produce highly varied recommendations
Several projection models will be explored • WHO projection/simulation model (Tom Hall/Peter Hornby) • WHO estimates to meet IHTP (cluster working group) • Finland model – long term labor force model
Recommended criteria for good projection model • Clear formulation of objectives and problems to be solved • Issues/problems must be formulated in a quantifiable manner • Data of acceptable quality must be available or collected • Responsible parties must check regularly on projections that they have been used and are updated • Planning horizon timelines must be sufficient to be able to take action to solve identified problems
Considerations • The application of workforce forecasting the policy and training requires projections be for at least 10 years, but that planners should not act on projections beyond 2 or 3 years. (Hall, 1988) • Broad range of factors that need to be considered: population characteristics influence need for health care, ways population uses health care, ways health professionals provide care, others who provide similar or same services, population health (O’Brien-Pallas and Baumann, 2000).