The Saudization–density paradox in physician workforce planning: a dual-stock Monte Carlo simulation for Saudi Arabia to 2045

Abstract Background Saudi Arabia must simultaneously achieve 60% Saudization of the physician workforce by 2030 (Vision 2030 mandate) and sustain physician density above the OECD average through 2045, under uncertainty about workforce inflows, attrition, migration, and population growth. Prior studies use deterministic single-stock models that cannot quantify the joint probability of failing both objectives and treat Saudization as an exogenous parameter rather than as an emergent property of sub-stock dynamics. This study calibrates a dual-stock Monte Carlo simulation on eight annual calibration observations (2010–2017), with 2018–2024 reserved for out-of-sample validation; all quantitative outputs should be read as directional scenario findings rather than high-precision point forecasts. Methods We developed a simulation model tracking Saudi and non-Saudi physician numbers separately over 2024–2045, allowing the Saudization percentage to emerge from actual workforce dynamics rather than being set externally. Workforce attrition rates were estimated from observed year-on-year changes in stock counts and validated against 2018–2024 data (prediction error: 1.74 physicians per 10,000). Three policy scenarios were compared: current trends continuing (Business As Usual), substantial domestic training expansion (Vision 2030 Accelerated), and international recruitment collapse (Adverse Disruption Scenario). Each scenario was run 10,000 times with slight parameter variation to produce a probability distribution of outcomes. Factor importance was assessed by testing 1,000 combinations of all eight model parameters simultaneously. Results The calibrated model reveals three core findings. First, under BAU, the 60% Saudization target is not achieved by 2030 (conditional median: 45.4%; shortfall probability: 100%). Second, physician density erodes to 36.9 per 10,000 by 2045 under BAU (shortfall probability: 77.6%). Third, under Adverse Disruption Scenario, Saudization paradoxically rises to 54.8% by 2030 as non-Saudi physicians exit faster than Saudi nationals, while density collapses to 20.0 per 10,000. PRCC identifies population growth as the dominant driver (PRCC = 0.410) and non-Saudi inflow as the strongest modifiable lever (PRCC = − 0.546). Only Vision 2030 Accelerated achieves the benchmark (52.8 per 10,000 by 2045; shortfall probability: 0.0%). Conclusions Saudization and physician density are structurally distinct challenges requiring different timelines and instruments. The Saudization–density paradox argues for dual-metric policy monitoring. Investment decisions made in 2025–2027 strongly influence physician supply in 2032–2034 under the model’s structural assumptions, given the 7-year training pipeline. A time-phased policy decision framework across four intervention windows is presented.