Multi-country case studies on planning RMNCH services using WISN methodology: Bangladesh, Ghana, Kenya, Sultanate of Oman and Papua New Guinea.

BACKGROUND: Globally, many countries are adopting evidence-based workforce planning that facilitates progress towards achieving sustainable development goals for reproductive, maternal newborn and child health. We reviewed case studies on workforce planning for reproductive maternal newborn child health services at primary care level facilities using workload indicators of staffing need in five countries. METHOD: Using available workload indicators for staffing need reports from Bangladesh, Ghana, Kenya, Sultanate of Oman and Papua New Guinea, we generated descriptive statistics to explore comparable workload components and activity standards, health service delivery models with an emphasis on the primary care levels and the specific health occupations offering interventions associated with reproductive maternal, newborn and child health services. RESULTS: The health services delivery models vary from one country to another. The results showed variability in the countries, in the workload components and activity standards of each regardless of facility level or occupational groups involved. All the countries have decentralized health services with emphasis on comprehensive primary care. Reproductive, maternal and new-born child health care services include antenatal, postnatal, immunization, family planning, baby wellness clinics, delivery and management of integrated minor childhood illnesses. Only Sultanate of Oman offers fertility services at primary care. Kenya has expanded interventions in the households and communities. CONCLUSION: Since the health care services models, health services delivery contexts and the health care worker teams vary from one country to another, the study therefore concludes that activity standards cannot be adopted or adapted from one country to another despite having similar workload components. Evidence based workforce planning must be context-specific, and therefore requires that each country develop its own workload components and activity standards aligned to their local contexts.

Health workforce metrics pre- and post-2015: a stimulus to public policy and planning.

BACKGROUND: Evidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the 'Countdown to 2015' initiative as accounting for more than 95% of the world's maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015. METHODS: Using available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies. RESULTS: There are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed. CONCLUSIONS: There is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning.