WORKLOAD ANALYSIS FOR HUMAN RESOURCE OPTIMIZATION IN PRIMARY HEALTHCARE CLINIC X - Dina Maria Ulfa; Syihabudhin; Sopiah (Multidiciplinary Output Research For Actual and International Issue (MORFAI), 2025)
This study investigates workload distribution and staffing adequacy as the foundation for optimizing human resources in Primary Healthcare Clinic X. Increasing service demands and diverse job characteristics across clinical and administrative units have highlighted potential imbalances in workforce allocation. Using a descriptive qualitative design supported by quantitative workload-analysis techniques, this research integrates the Full-Time Equivalent (FTE) method and the Workload Indicators of Staffing Need (WISN) approach to provide an evidence-based assessment of staffing requirements. Data was obtained through semi-structured interviews, direct observations of work processes, and analysis of organizational documents, followed by thematic analysis and methodological triangulation to ensure validity and reliability. The results reveal that workload imbalances are not uniform across units. Clinical roles—such as registration staff, nurses, general practitioners, and dentists—experience peak-hour surges and external service demand that justify maintaining existing staffing levels despite numerical surpluses. In contrast, several administrative and support positions, including facilities management, personnel administration, and sterilization, show significant underload and prolonged idle time. FTE and WISN calculations indicate that two positions can be reduced without affecting service quality: one from the sterilization unit and one from the resource subdivision through the consolidation of periodic administrative tasks. The study concludes that human-resource optimization requires a unit-specific approach integrating workload analysis with strategic job redesign and structural alignment. The findings offer practical implications for workforce planning, efficiency improvement, and organizational sustainability in healthcare service settings.