Workload Indicators of Staffing Need (WISN) Method for Midwives Planning and Estimation at Asrade Zewude Memorial Primary Hospital, North west Ethiopia

Background: Workforce is a crucial component of the health service delivery system. Ethiopia faces health workforce challenges when it comes to evidence based health workforce planning.Workforce planning was initially determined by comparing the health worker ratio to the general population number. Later, it was determined by standard staffing schedules for each health facility level. However, neither of these methods addressed the evidence based workload variation issue among the same level facilities all around the country. A workload indicator of staff needs (WISN) method can address these variations. Therefore this research was carried on to determine workload pressure excess or gap in midwives, thereby to promote the WISN use in health facilities, based on WISN results of midwives at Asrade Zewude memorial Hospital. Methods: A cross sectional study using WISN model was used to determine the workload excess and gap pressure in midwives at Asrade Zewude Memorial primary hospital, North West Ethiopia. Midwives were selected based on a priority point scale as outlined in the WISN method. Results: According to the data obtained, midwives worked five days a week and 1030 h per year. This working time was spent on health service activities (58.4%), additional activities (36.6%) and support activities (5%). WISN calculations demonstrated a shortage of five midwives with WISN ratio of 0.8 at Asrade Zewude Memorial primary hospital North West Ethiopia. Conclusion: Midwives at the study area were carrying on their routine tasks even though there was a staff gap of 5: thus, the midwives had a workload excess of 20%. Under these conditions, it may be hard for the facility to achieve universal health service goals. Therefore the hospital should institutionalize WISN method planning to objectively employ midwifery professionals. This study had limitations too as it used retrospective annual service statistics and small sample size which affects generalization of the results to other health facilities and other health worker cadres within the study hospital.