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Background: Nurses are health human resources who have a strategic role and make a major contribution to health services to patients in hospitals. The number of health workers on duty in a hospital greatly influences services. The number of inpatient nurses at Konawe Hospital is 13 people compared to the total population, which is still in the low category with a BOR above 80%, which shows that nurses have a high workload. Objectives: This research aims to determine the analysis of nursing staff needs using the Workload Indicator Staffing Needs (WISN) approach in inpatient services at the Regional General Hospital of Konawe Islands Regency in 2023. Method: The research carried out was a qualitative descriptive study using the work sampling method. The sample for this research was all 13 inpatient nursing staff at the Konawe Islands Regional Hospital. Results: Based on the research results, it is known that the calculation of the need for nursing staff based on workload obtained 16.89 number of nursing staff with a WISN ratio of 0.7. The working days available for the HR category are multiplied by the nurses' working time so the total working time available is 1996.8. The ratio of nurses to the number of beds is 13:25 with the number of patients in 2022 being 683 patients. The workload consists of 16 types of activities, the largest of which is changing IV fluids and installing identification bracelets, namely 57048 times, while the smallest workload activities are wound care, changing dressings, nurses going around patient observation rooms, cleaning beds, taking/moving patients to another place, and received patients from other rooms, namely 11410 times. Conclusion: The current amount of power is smaller than the amount of power needed to run the existing workload. There needs to be an additional 3 people from the existing 13 people to achieve a balanced situation. Therefore, it is necessary to manage nursing staff optimally to achieve quality nursing services, considering the workload of nurses as a reference in determining the need for nursing staff.
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Suhadi et al. (2024) studied this question.
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