Estimating health care delivery system value for each US state and testing key associations

Joseph L. Dieleman, Alexander S. Kaldjian, Maitreyi Sahu, Carina Chen, Angela Liu, Abby Chapin, Kirstin Woody Scott, Aleksandr Aravkin, Peng Zheng, Ali Mokdad, Christopher J.L. Murray, Kevin Schulman, Arnold Milstein

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value. Data sources: Annual condition-specific death and incidence estimates for each US state from the Global Burden Disease 2019 Study and annual health care spending per person for each state from the National Health Expenditure Accounts. Study design: Using non-linear meta-stochastic frontier analysis, mortality incidence ratios for 136 major treatable illnesses were regressed separately on per capita health care spending and key covariates such as age, obesity, smoking, and educational attainment. State- and year-specific inefficiency estimates were extracted for each health condition and combined to create a single estimate of health care delivery system value for each US state for each year, 1991–2014. The association between changes in health care value and changes in 23 key health care system characteristics and state policies was measured. Data collection/extraction methods: Not applicable. Principal findings: US state with relatively high spending per person or relatively poor health-outcomes were shown to have low health care delivery system value. New Jersey, Maryland, Florida, Arizona, and New York attained the highest value scores in 2014 (81 [95% uncertainty interval 72-88], 80 [72-87], 80 [71-86], 77 [69-84], and 77 [66-85], respectively), after controlling for health care spending, age, obesity, smoking, physical activity, race, and educational attainment. Greater market concentration of hospitals and of insurers were associated with worse health care value (p-value ranging from <0.01 to 0.02). Higher hospital geographic density and use were also associated with worse health care value (p-value ranging from 0.03 to 0.05). Enrollment in Medicare Advantage HMOs was associated with better value, as was more generous Medicaid income eligibility (p-value 0.04 and 0.01). Conclusions: Substantial variation in the value of health care exists across states. Key health system characteristics such as market concentration and provider density were associated with value.

Original languageEnglish (US)
Pages (from-to)557-567
Number of pages11
JournalHealth services research
Volume57
Issue number3
DOIs
StatePublished - Jun 2022

Keywords

  • comparative health systems
  • health care costs
  • state health policies

ASJC Scopus subject areas

  • Health Policy

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