Forecasting nursing workforce requirements in tertiary general hospitals under population aging and changing healthcare utilization: A system dynamics simulation.

BACKGROUND: Nurse workforce planning has become increasingly complex in tertiary general hospitals because population aging, changes in healthcare utilization, increasing patient acuity, and nurse turnover interact over time. In South Korea, expansion of the licensed nurse supply has not translated into proportional growth in the clinically employed workforce, particularly in high-acuity hospital settings. OBJECTIVE: To develop and validate a system dynamics model for nurse workforce planning in tertiary general hospitals and to examine the long-term effects of population aging, healthcare utilization change, and structural transformation policy on workforce demand, supply, and turnover. DESIGN: System dynamics simulation study. METHODS: A stock-and-flow simulation model was developed to represent projected nursing workforce requirements, employed nurses, and turnover among newly licensed and experienced nurses from 2015 to 2050. Model inputs were parameterized using publicly available national secondary data. Internal validation included dimensional consistency checks, time-step sensitivity testing, and simplified test runs. External validation was performed by comparing model-simulated projections with observed staffing data to verify predictive accuracy against prior studies. Scenario simulation was conducted to assess the effects of severe-case-centered structural transformation in tertiary hospitals. RESULTS: Projected nursing workforce requirements in tertiary general hospitals were estimated to increase from 44,758 in 2015 to 138,270 in 2050, while employed nurses were projected to increase from 36,473 to 112,157 over the same period. Consequently, the workforce gap widened from 8285 to 26,113. The model showed closer agreement with observed staffing values than prior projection studies, with an absolute percentage error of 5.06% in 2020 and 0.67% in 2025, and a mean absolute percentage error of 2.85%. Policy simulation suggested that severe-case-centered restructuring may reduce demand in the short term through bed adjustment, but was also associated with lower employed nurse numbers and higher turnover over time. Differences by implementation pace were limited. CONCLUSIONS: Nurse workforce planning in tertiary general hospitals is shaped by the dynamic interaction of demographic change, healthcare utilization, patient acuity, turnover, and policy intervention. Policies focused solely on supply expansion or structural reorganization are unlikely to ensure long-term workforce stability. Sustainable workforce planning requires integrated strategies that manage workload growth, strengthen retention, and coordinate care across hospital, outpatient, community-based, and long-term care settings.