Saudi Arabia’s Doctor Workforce Faces a Paradox: More Nationalization Could Mean Fewer Doctors

Saudi Arabia is chasing two health policy goals at once, and a new study suggests they may be pulling in opposite directions. The kingdom has pledged, under its Vision 2030 reform program, to raise the share of Saudi national physicians to 60 percent of the medical workforce by 2030. At the same time, it wants to keep the number of doctors per capita above the average of wealthy OECD nations through 2045. According to a dual-stock Monte Carlo simulation published in BMC Health Services Research by Ali Hassan Barnawi of Prince Musaid Bin Abdulrahman University, the country is on track to miss both targets under current trends, and the policies that help one goal can actively undermine the other.

The core insight of the study is what the author calls the Saudization–density paradox. Because the Saudi physician workforce is composed of two distinct stocks—Saudi nationals and non-Saudi expatriate doctors—any shock that removes expatriate physicians mechanically raises the Saudization percentage even as the total number of doctors, and therefore physician density, collapses. Saudization, in other words, is not a dial that policymakers can set directly; it is an emergent property of how the two sub-stocks grow and shrink. Treating it as an exogenous parameter, as earlier deterministic single-stock models did, obscures this dynamic entirely.

To capture it, Barnawi built a simulation that tracks Saudi and non-Saudi physician numbers separately from 2024 to 2045, allowing the Saudization percentage to emerge from the actual dynamics of inflows, attrition, and migration rather than being imposed from outside. Attrition rates were estimated from observed year-on-year changes in workforce stock counts between 2010 and 2017, and the model was then tested against data from 2018 to 2024 that it had never seen. The out-of-sample prediction error came to just 1.74 physicians per 10,000 population, a level of accuracy the author describes as sufficient for directional scenario analysis, though the study is careful to frame all quantitative outputs as scenario findings rather than high-precision forecasts.

The model’s engine is Monte Carlo simulation. Each of three policy scenarios was run 10,000 times with slight random variation in the parameters, producing full probability distributions of outcomes instead of single point estimates. The three scenarios were deliberately contrasting. Business As Usual assumed current trends in training, recruitment, and attrition simply continue. Vision 2030 Accelerated assumed a substantial expansion of domestic medical training. The Adverse Disruption Scenario assumed a collapse in international recruitment, a plausible stress test given global competition for physicians and geopolitical volatility in the regions that supply much of Saudi Arabia’s expatriate medical labor.

The results under Business As Usual are stark. The conditional median Saudization percentage in 2030 is 45.4 percent, far short of the 60 percent mandate, and the model assigns a 100 percent probability to missing the target. Physician density, meanwhile, erodes to 36.9 per 10,000 population by 2045, with a 77.6 percent probability of falling below the OECD average benchmark. In plain terms, if nothing changes, the simulation finds it is essentially certain that the nationalization goal will be missed by 2030, and very likely that the kingdom will have fewer doctors per capita than comparable high-income countries by mid-century.

The Adverse Disruption Scenario delivers the paradox in its purest form. When international recruitment collapses, non-Saudi physicians exit the workforce faster than Saudi nationals can be trained to replace them. The Saudization percentage paradoxically rises, reaching a median of 54.8 percent by 2030, the closest any scenario comes to the nationalization target. Yet physician density collapses to 20.0 per 10,000, a level that would represent a severe shortage by any international standard. A policymaker watching only the Saudization metric would see encouraging progress; one watching only density would see a crisis. Both would be looking at the same workforce.

To understand which levers matter most, the study employed a global sensitivity analysis using Latin Hypercube Sampling and Partial Rank Correlation Coefficients, testing 1,000 combinations of all eight model parameters simultaneously. The analysis identified population growth as the dominant driver of outcomes, with a PRCC of 0.410, reflecting the fact that a rapidly growing population dilutes physician density even when the absolute number of doctors rises. The strongest modifiable lever was the inflow of non-Saudi physicians, with a PRCC of −0.546, meaning that higher expatriate recruitment is strongly associated with lower Saudization but higher density. This single coefficient captures the structural tension at the heart of the paradox: the variable that most improves one metric most degrades the other.

Only the Vision 2030 Accelerated scenario, built around substantial domestic training expansion, achieves the density benchmark. In that scenario, physician density reaches 52.8 per 10,000 by 2045 with a shortfall probability of 0.0 percent. The finding underscores that domestic training is the only instrument that raises density without suppressing Saudization, because it adds Saudi nationals to the workforce directly. But it comes with a built-in delay: medical training pipelines take roughly seven years from matriculation to independent practice, which means investment decisions made in 2025 through 2027 largely determine physician supply in 2032 through 2034. Miss that window, the model implies, and the shortfall of the early 2030s becomes locked in.

The study is transparent about its limitations. It was calibrated on only eight annual observations, and the author notes that the model underestimated the observed Saudization trajectory from 2018 onward, documented in the supplementary year-by-year comparison tables. The validation exercise included rolling-origin checks and comparisons against five baseline models, and the full R analysis code, parameter distributions, and data harmonization tables are published as open supplementary material, allowing independent replication. The author also discloses that large language model assistance was used in manuscript preparation and R code development, while emphasizing that the scientific content, model structure, and interpretation were his own. The research received no external funding.

The practical upshot is a call for dual-metric policy monitoring and a time-phased decision framework spanning four intervention windows. Saudization and physician density, the study concludes, are structurally distinct challenges that require different timelines and different instruments, and conflating them risks celebrating progress on one while the other quietly deteriorates. For Saudi Arabia, the message is that the 2025–2027 window is decisive: expanding domestic training now is the only path the simulation identifies that satisfies both goals, whereas relying on expatriate recruitment preserves density but guarantees failure on nationalization, and losing expatriate physicians delivers the illusion of nationalization success at the cost of a genuine capacity crisis. For workforce planners elsewhere grappling with dependence on migrant doctors, the Saudization–density paradox offers a general lesson: nationalization ratios and service capacity must be modeled and monitored as separate stocks, because a percentage can improve even as the system behind it hollows out.

Subject of Research: Physician workforce planning in Saudi Arabia using dual-stock Monte Carlo simulation

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

Article References: The Saudization–density paradox in physician workforce planning: a dual-stock Monte Carlo simulation for Saudi Arabia to 2045. (n.d.). https://doi.org/10.1186/s12913-026-15836-w

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15836-w

Keywords: Saudization, physician workforce, Monte Carlo simulation, Saudi Arabia, Vision 2030, physician density, health workforce planning, sensitivity analysis, OECD benchmark, workforce projection, density, paradox