Literature DB >> 9240795

Geographic distribution of pediatricians in the United States: an analysis of the fifty states and Washington, DC.

R K Chang1, N Halfon.   

Abstract

OBJECTIVES: To determine current geographic distribution of pediatricians in the United States, to assess the changes in the geographic distribution of pediatricians between 1982 and 1992, and to identify factors associated with the distribution of pediatricians among the 50 states.
METHODS: A data set was constructed using several published data sources including the American Medical Association Physician Masterfile as the principal source for physician information. The pediatrician-to-child population ratio (PCPR, the number of pediatricians per 100 000 people under 18 years of age) was calculated to compare the distribution of pediatricians among states and the distributional changes between 1982 and 1992. Lorenz curves and Gini indices were used to describe distributions and to compare distributions across time periods. Linear regression analysis was performed to assess the relationship between PCPR (dependent variable) with 9 predictor variables.
RESULTS: Between 1982 and 1992, there was a 5.4% increase in the United States (US) child population and a 46.1% increase in the number of pediatricians in patient care. During that time period, the PCPR increased by 38.6% from 35.1 per 100 000 to 48.6 per 100 000. There was a more than 4-fold difference in the PCPRs of the highest state (Maryland, 84.3) and the lowest state (Idaho, 18.5) in 1992. The PCPR increased in all 50 states, but varied from a 4.1% increase in Wyoming to a 63.4% increase in Massachusetts. The Lorenz curve showed that pediatricians were less evenly distributed than all physicians, but more evenly distributed than pediatric cardiologists. Between 1982 to 1992 the Gini index decreased 9.8% for all physicians and 10.2% for pediatric cardiologists, but only 1. 9% for pediatricians. Since a decrease in the Gini index signifies better overall distribution, these changes are relatively modest for pediatricians as a whole, especially when compared to other physicians. Regression analysis showed that a higher PCPR was associated with a greater number of residency positions per 100 000 children and with the per capita income of the state (R = .93).
CONCLUSIONS: The distribution of pediatricians does not parallel the distribution of the child population in the US, nor has this distribution changed substantially in spite of a 38.6% increase in the PCPR. Pediatricians tend to concentrate in states with high per capita income and in states with a larger number of residency training positions. The failure of market forces to improve the geographic distribution may require manpower policy changes designed to improve distribution in underrepresented states. The uncertain impact of market changes due to increased use of managed care could affect distributional requirements of pediatricians in the future.

Entities:  

Mesh:

Year:  1997        PMID: 9240795     DOI: 10.1542/peds.100.2.172

Source DB:  PubMed          Journal:  Pediatrics        ISSN: 0031-4005            Impact factor:   7.124


  24 in total

1.  US cardiologist workforce from 1995 to 2007: modest growth, lasting geographic maldistribution especially in rural areas.

Authors:  Sanjay Aneja; Joseph S Ross; Yongfei Wang; Masatoshi Matsumoto; George P Rodgers; Susannah M Bernheim; Saif S Rathore; Harlan M Krumholz
Journal:  Health Aff (Millwood)       Date:  2011-12       Impact factor: 6.301

2.  Geographic representation of the jackson heart study cohort to the African-American population in Jackson, Mississippi.

Authors:  Demarc A Hickson; Lance A Waller; Samson Y Gebreab; Sharon B Wyatt; James Kelly; Donna Antoine-Lavigne; Daniel F Sarpong
Journal:  Am J Epidemiol       Date:  2010-11-12       Impact factor: 4.897

Review 3.  Unwarranted variation in pediatric medical care.

Authors:  David C Goodman
Journal:  Pediatr Clin North Am       Date:  2009-08       Impact factor: 3.278

4.  The association between county-level surgeon density and esophageal and gastric cancer mortality.

Authors:  Maria Y Ho; Jasem Al-Barrak; Renata D Peixoto; Winson Y Cheung
Journal:  J Gastrointest Cancer       Date:  2014-12

5.  Mobile phone technology for children with type 1 and type 2 diabetes: a parent survey.

Authors:  Venessa Pena; Alice J Watson; Joseph C Kvedar; Richard W Grant
Journal:  J Diabetes Sci Technol       Date:  2009-11-01

6.  Global inequality in eye health: country-level analysis from the Global Burden of Disease Study.

Authors:  Koichi Ono; Yoshimune Hiratsuka; Akira Murakami
Journal:  Am J Public Health       Date:  2010-07-15       Impact factor: 9.308

7.  Factors related to receipt of well-child visits in insured children.

Authors:  Amber M Goedken; Julie M Urmie; Linnea A Polgreen
Journal:  Matern Child Health J       Date:  2014-04

8.  Estimating the empirical Lorenz curve and Gini coefficient in the presence of error with nested data.

Authors:  Chaya S Moskowitz; Venkatraman E Seshan; Elyn R Riedel; Colin B Begg
Journal:  Stat Med       Date:  2008-07-20       Impact factor: 2.373

9.  Concomitant Adolescent Vaccination in the U.S., 2007-2012.

Authors:  Jennifer L Moss; Paul L Reiter; Noel T Brewer
Journal:  Am J Prev Med       Date:  2016-06-30       Impact factor: 5.043

10.  Accounting for uncertainty in policy decision making: Improving access to pediatric dental care.

Authors:  Stewart Curry; Nicoleta Serban
Journal:  Health Serv Res       Date:  2021-01-22       Impact factor: 3.402

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.