IntroductionAs part of ongoing efforts to restructure the health sector and improve health care quality, the Ministry of Health and Social Services (MoHSS) in Namibia sought to update staffing norms for health facilities. To establish an evidence base for the new norms, the MoHSS supported the first-ever national application of the Workload Indicators of Staffing Need (WISN) method, a human resource management tool developed by the World Health Organization.ApplicationThe WISN method calculates the number of health workers per cadre, based on health facility workload. It provides two indicators to assess staffing: (1) the gap/excess between current and required number of staff, and (2) the WISN ratio, a measure of workload pressure. Namibian WISN calculations focused on four cadres (doctors, nurses, pharmacists, pharmacy assistants) and all four levels of public facilities (clinics, health centers, district hospitals, intermediate hospitals). WISN steps included establishing a task force; conducting a regional pilot; holding a national validation workshop; field verifying data; collecting, uploading, processing, and analyzing data; and providing feedback to policy-makers.ChallengesThe task force faced two challenges requiring time and effort to solve: WISN software-related challenges and unavailability of some data at the national level.FindingsWISN findings highlighted health worker shortages and inequities in their distribution. Overall, staff shortages are most profound for doctors and pharmacists. Although the country has an appropriate number of nurses, the nurse workforce is skewed towards hospitals, which are adequately or slightly overstaffed relative to nurses’ workloads. Health centers and, in particular, clinics both have gaps between current and required number of nurses. Inequities in nursing staff also exist between and within regions. Finally, the requirement for nurses varies greatly between less and more busy clinics (range = 1 to 7) and health centers (range = 2 to 57).Policy implicationsThe utility of the WISN health workforce findings has prompted the MoHSS to seek approval for use of WISN in human resources for health policy decisions and practices. The MoHSS will focus on revising staffing norms; improving staffing equity across regions and facility types; ensuring an appropriate skill mix at each level; and estimating workforce requirements for new cadres.

Designers and implementers of decentralization and other reform measures have focused much attention on financial and structural reform measures, but ignored their human resource implications. Concern is mounting about the impact that the reallocation of roles and responsibilities has had on the health workforce and its management, but the experiences and lessons of different countries have not been widely shared. This paper examines evidence from published literature on decentralization's impact on the demand side of the human resource equation, as well as the factors that have contributed to the impact. The elements that make such an impact analysis exceptionally complex are identified. They include the mode of decentralization that a country is implementing, the level of responsibility for the salary budget and pay determination, and the civil service status of transferred health workers.The main body of the paper is devoted to examining decentralization's impact on human resource issues from three different perspectives: that of local health managers, health workers themselves, and national health leaders. These three groups have different concerns in the human resource realm, and consequently, have been differently affected by decentralization processes. The paper concludes with recommendations regarding three key concerns that national authorities and international agencies should give prompt attention to. They are (1) defining the essential human resource policy, planning and management skills for national human resource managers who work in decentralized countries, and developing training programs to equip them with such skills; (2) supporting research that focuses on improving the knowledge base of how different modes of decentralization impact on staffing equity; and (3) identifying factors that most critically influence health worker motivation and performance under decentralization, and documenting the most cost-effective best practices to improve them. Notable experiences from South Africa, Ghana, Indonesia and Mexico are shared in an annex.

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