Examining Wage Disparities by Race and Ethnicity of Health Care Workers

Med Care. 2021 Oct 1;59(Suppl 5):S471-S478. doi: 10.1097/MLR.0000000000001613.

Abstract

Background: Prior studies demonstrated that wage disparities exist across race and ethnicity within selected health care occupations. Wage disparities may negatively affect the industry's ability to recruit and retain a diverse workforce throughout the career ladder.

Objective: To determine whether wage disparities by race and ethnicity persist across health care occupations and whether disparities vary across the skill spectrum.

Research design: Retrospective analysis of 2011-2018 data from the Current Population Survey using Blinder-Oaxaca decomposition regression methods to identify sources of variation in wage disparities. Separate models were run for 9 health care occupations.

Subjects: Employed individuals 18 and older working in health care occupations, categorized by race/ethnicity.

Measures: Annual wages were predicted as a function of race/ethnicity, age, sex, marital status, having a child under 5 in the household, living in a metro area, highest education attained, and usual hours worked.

Results: Non-Hispanics consistently made more than Hispanic licensed practical/vocational nurses (LPNs/LVNs), aides/assistants, technicians, and community-based workers. Asian/Pacific Islanders consistently made more than Black, American Indian/Alaska Native, and Multiracial individuals across occupations except physicians, advanced practitioners, or therapists. Asian/Pacific Islanders only made significantly less when compared with White physicians, but more than White advanced practitioners, registered nurses, LPNs/LVNs, and aides/assistants. Based on observed attributes, Black registered nurses, LPNs/LVNs, and aides/assistants were predicted to make more than their White peers, but unexplained variation negated these gains.

Conclusions: Many wage gaps remained unexplained based on measured factors warranting further study. Addressing wage disparities is critical to advance in careers and reduce job turnover.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Ethnicity / statistics & numerical data*
  • Health Personnel / economics*
  • Health Workforce / economics*
  • Humans
  • Racial Groups / statistics & numerical data*
  • Retrospective Studies
  • Salaries and Fringe Benefits / statistics & numerical data*
  • United States