Abstract
BACKGROUND: As part of efforts to inform the development of a global human resources for health (HRH) strategy, a comprehensive methodology for estimating HRH supply and requirements was described in a companion paper. The purpose of this paper is to demonstrate the application of that methodology, using data publicly available online, to simulate the supply of and requirements for midwives, nurses, and physicians in the 32 high-income member countries of the Organisation for Economic Co-operation and Development (OECD) up to 2030. METHODS: A model combining a stock-and-flow approach to simulate the future supply of each profession in each country-adjusted according to levels of HRH participation and activity-and a needs-based approach to simulate future HRH requirements was used. Most of the data to populate the model were obtained from the OECD's online indicator database. Other data were obtained from targeted internet searches and documents gathered as part of the companion paper. RESULTS: Relevant recent measures for each model parameter were found for at least one of the included countries. In total, 35% of the desired current data elements were found; assumed values were used for the other current data elements. Multiple scenarios were used to demonstrate the sensitivity of the simulations to different assumed future values of model parameters. Depending on the assumed future values of each model parameter, the simulated HRH gaps across the included countries could range from shortfalls of 74 000 midwives, 3.2 million nurses, and 1.2 million physicians to surpluses of 67 000 midwives, 2.9 million nurses, and 1.0 million physicians by 2030. CONCLUSIONS: Despite important gaps in the data publicly available online and the short time available to implement it, this paper demonstrates the basic feasibility of a more comprehensive, population needs-based approach to estimating HRH supply and requirements than most of those currently being used. HRH planners in individual countries, working with their respective stakeholder groups, would have more direct access to data on the relevant planning parameters and would thus be in an even better position to implement such an approach.