DOI: 10.1542/peds.2023-063678c ISSN: 0031-4005

Forecasting the Future Supply of Pediatric Subspecialists in the United States: 2020–2040

Erin Fraher, Andy Knapton, Emily McCartha, Laurel K. Leslie
  • Pediatrics, Perinatology and Child Health

Concerns persist about whether the United States has an adequate supply of pediatric subspecialists and whether they are appropriately distributed across the nation to meet children's health needs. This article describes the data and methods used to develop a workforce projection model that estimates the future supply of 14 pediatric subspecialities certified by the American Board of Pediatrics at the national and US census region and division levels from 2020 to 2040. The 14 subspecialties include adolescent medicine, pediatric cardiology, child abuse pediatrics, pediatric critical care medicine, developmental-behavioral pediatrics, pediatric emergency medicine, pediatric endocrinology, pediatric gastroenterology, pediatric hematology-oncology, pediatric infectious diseases, neonatal-perinatal medicine, pediatric nephrology, pediatric pulmonology, and pediatric rheumatology. Hospital medicine was excluded because of the lack of historical data needed for the model. This study addresses the limitations of prior models that grouped adult and pediatric physician subspecialty workforces together and aggregated pediatric subspecialties. The model projects supply at national and subnational levels while accounting for geographic moves that pediatric subspecialists make after training and during their career. Ten “what if” scenarios included in the model simulate the effect of changes in the number of fellows entering training, the rate at which subspecialists leave the workforce, and changes in hours worked in direct and indirect clinical care. All model projections and scenarios are available on a public, interactive Web site. The model’s projections can also be examined with other data to provide insight into the possible future of the pediatric subspecialty workforce and offer data to inform decision-making.

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