Applying the workload indicators of staffing need (WISN) method in Namibia: challenges and implications for human resources for health policy

Hum Resour Health. 2013 Dec 10:11:64. doi: 10.1186/1478-4491-11-64.


Introduction: As 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.

Application: The 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.

Challenges: The task force faced two challenges requiring time and effort to solve: WISN software-related challenges and unavailability of some data at the national level.

Findings: WISN 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 implications: The 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Health Policy
  • Health Services Needs and Demand / statistics & numerical data*
  • Humans
  • Medical Staff, Hospital / supply & distribution*
  • Namibia
  • Personnel Staffing and Scheduling / statistics & numerical data*
  • Primary Health Care*
  • Quality Indicators, Health Care*
  • Quality of Health Care
  • Workforce
  • Workload / statistics & numerical data*