Estimating general practitioner staffing requirements in a regional cardiac emergency center: a WISN-based study in Southeast Iran

Abstract Effective workforce planning is essential for delivering high-quality emergency care, particularly in settings facing increasing service demand and limited human resources. The World Health Organization’s Workload Indicators of Staffing Need (WISN) method provides an evidence-based approach for estimating staffing requirements using actual workload data. This descriptive-analytical cross-sectional study applied the WISN methodology to estimate the required number of general practitioners (GPs) in the emergency department of Shafa Teaching Hospital, a major regional cardiac emergency center in Southeast Iran. Data were collected through direct observation, time-motion studies, document review, and expert consultation. A structured time-motion checklist, developed based on the WHO WISN User’s Manual, was reviewed by experts and pilot-tested before data collection. Available working time (AWT), workload components, activity standards, and allowance factors were calculated according to WHO guidelines. The annual available working time for each GP was 2,392 h. Analysis of workload components showed that core clinical activities, including history taking, physical examination, and prescribing, accounted for the largest proportion of the workload. The final WISN-based staffing requirement was 6.12 GPs, whereas the actual staffing level was six GPs, resulting in a WISN ratio of 0.98. This finding indicates a slight staffing shortage and associated workload pressure that may contribute to increased fatigue, longer waiting times, and reduced service quality. The WISN method proved to be an effective tool for identifying staffing gaps and quantifying workload pressure in a high-acuity emergency setting. Even minor understaffing may adversely affect service efficiency and patient safety. Integrating the WISN methodology into routine workforce planning in Iran could support more accurate staffing decisions, optimize resource allocation, and improve the quality and sustainability of emergency care service.