Estimated prospects of demand and supply of urologists in Korea over the next 10 years
- Author:
Young Jae IM
1
;
Kwanjin PARK
;
Youngho OH
;
Jun Hyuk HONG
;
Sang Don LEE
Author Information
- Publication Type:Special Article
- From: Investigative and Clinical Urology 2024;65(4):326-333
- CountryRepublic of Korea
- Language:English
-
Abstract:
Purpose:This study aimed to provide the basic data needed to estimate future urologist supply and demand by applying various statistical models related to healthcare utilization.
Materials and Methods:Data from multiple sources, including the Yearbook of Health and Welfare Statistics, Korean Hospital Association, Korean Medical Association, and the Korean Urological Association, were used for supply estimation. Demand estimation incorporated data on both clinical and non-clinical urologists, along with future population estimates. In-and-out moves and demographic methods were employed for supply estimation, while the Bureau of Health Professions model was utilized for demand estimation. Supply estimation assumptions included fixed resident quotas, age-specific death rates, migration rates, and retirement age considerations. Demand estimation assumptions included combining clinical and nonclinical urologist demands, adjusting population size for age-related healthcare usage variations. Urologist productivity was determined by adjusting productivity levels to 100%, 90%, and 80% of the base year based on actual clinical practice volumes.
Results:Estimations of both demand and supply consistently indicate an oversupply of urologists until 2025, followed by an expected shortage by 2035 owing to increased deaths and retirements attributed to the aging urologist population. This shortage becomes more pronounced when employing more reliable models, such as logit or ARIMA (autoregressive integrated moving average), underscoring the growing need for urologists in the future.
Conclusions:All estimation models estimated an oversupply of urologists until 2025, transitioning to a deficit due to reduced supply thereafter. However, considering potential unaccounted factors, greater effort is needed for accurate predictions and corresponding measures.
