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Background <p>The health workforce or human resources for health (HRH) is the bedrock of an efficient healthcare system, and the consequences of HRH shortage are evident in poor health service delivery. Many low- and middle-income countries (LMICs) have a suboptimal HRH density, far from the Sustainable Development Goals (SDG) target of 4.45 doctors, nurses, and midwives per 1000 population. Despite income levels influencing HRH density, variations in the number of health workers per capita and their performance highlight the need to optimize HRH within any economic context. This study presents a practical framework for optimizing the health workforce in LMICs, using Nigeria as a case study.</p> Methods <p>This research introduces a comprehensive HRH optimization framework derived from a strategic blend of existing frameworks, mainly the International HRH Action Framework, the WHO HRH Assessment Guidelines, and the WHO Health System Governance Action Plan for UHC. The study used a qualitative approach to apply this framework in assessing the HRH challenges and potential optimization strategies in Nigeria using data from a review of relevant documents and key informant interviews at the national and state levels.</p> Results <p>The study reveals a complex HRH landscape in Nigeria, where policies such as Task Shifting and National HRH Policy coexist with challenges in implementation, funding, and political interference. Institutional arrangements show potential for HRH optimization in states such as Gombe and Kaduna but face staffing and funding limitations. Data utilization for HRH decision-making is hindered by integration issues, while political dynamics influence policies and practices, leading to disparities in healthcare access. Challenges in workforce planning, recruitment, administration, and motivation underscore the need for targeted interventions and systemic reforms to optimize HRH density, distribution, skill mix, performance, service coverage, quality of care, and equity of access, crucial for improving healthcare delivery and ensuring equity nationwide.</p> Conclusion <p>As demonstrated in Nigeria, the HRH optimization framework effectively assesses and plans HRH optimization strategies. LMICs facing HRH shortages can use this framework to identify HRH optimization opportunities within their health systems, leading to improved health service.</p>

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Optimizing the health workforce for Universal Health Coverage: a framework for analysis and action

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月11日

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  • Gafar B. Alawode,
  • Abdul-Rahman A. Ajibola,
  • Morohunranti S. Sanusi,
  • Ayomide B. Adewoyin,
  • Kafayat A. Alawode

摘要

Background

The health workforce or human resources for health (HRH) is the bedrock of an efficient healthcare system, and the consequences of HRH shortage are evident in poor health service delivery. Many low- and middle-income countries (LMICs) have a suboptimal HRH density, far from the Sustainable Development Goals (SDG) target of 4.45 doctors, nurses, and midwives per 1000 population. Despite income levels influencing HRH density, variations in the number of health workers per capita and their performance highlight the need to optimize HRH within any economic context. This study presents a practical framework for optimizing the health workforce in LMICs, using Nigeria as a case study.

Methods

This research introduces a comprehensive HRH optimization framework derived from a strategic blend of existing frameworks, mainly the International HRH Action Framework, the WHO HRH Assessment Guidelines, and the WHO Health System Governance Action Plan for UHC. The study used a qualitative approach to apply this framework in assessing the HRH challenges and potential optimization strategies in Nigeria using data from a review of relevant documents and key informant interviews at the national and state levels.

Results

The study reveals a complex HRH landscape in Nigeria, where policies such as Task Shifting and National HRH Policy coexist with challenges in implementation, funding, and political interference. Institutional arrangements show potential for HRH optimization in states such as Gombe and Kaduna but face staffing and funding limitations. Data utilization for HRH decision-making is hindered by integration issues, while political dynamics influence policies and practices, leading to disparities in healthcare access. Challenges in workforce planning, recruitment, administration, and motivation underscore the need for targeted interventions and systemic reforms to optimize HRH density, distribution, skill mix, performance, service coverage, quality of care, and equity of access, crucial for improving healthcare delivery and ensuring equity nationwide.

Conclusion

As demonstrated in Nigeria, the HRH optimization framework effectively assesses and plans HRH optimization strategies. LMICs facing HRH shortages can use this framework to identify HRH optimization opportunities within their health systems, leading to improved health service.