James D Park1, Edward Kim2,3, Rachel M Werner4,5,6. 1. Division of General Internal Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA. james.d.park@rutgers.edu. 2. Department of Computer Science, The College of New Jersey, Ewing, NJ, USA. 3. Department of Computing Sciences, Villanova University, Villanova, PA, USA. 4. Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, USA. 5. Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center, Philadelphia, PA, USA. 6. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
Abstract
BACKGROUND: The range of hospital charges for similar diagnoses show tremendous variability across U.S. hospitals. This charge variability remains unexplained. OBJECTIVE: We aimed to describe hospital charge variability in the U.S. and examine its relationship to local health factors. DESIGN: This was a descriptive study of the 2011 Medicare Inpatient Charge data summarizing inpatient hospital charges billed to Medicare. This data was evaluated using 29 county-level measures of health status, health behavior, clinical access and quality, built environment, and socioeconomic status in a clustered, multivariate linear regression. PARTICIPANTS: 2871 U.S. hospitals registered with Medicare and with at least ten discharges for diagnosis-related groups (DRGs) of six common inpatient conditions. MAIN MEASURE: Inpatient hospital charges were assessed. KEY RESULTS: No community health measures were associated with hospital charges. The one notable exception associated with higher charges was higher rates of uninsured status ($344.84 higher charges for every one-percentage point increase in prevalence (p < 0.001)). One variable was associated with lower hospital charges: the percentage of children living in poverty [$309.30 lower charges for every one-percentage point increase in prevalence (p < 0.001)]. CONCLUSIONS: Overall, hospital charges lacked an association with population health measures, and their variability remains largely unexplained. However, the association of higher charges with uninsured status raises concerns about hospitals' price-setting strategies, such as price discrimination and cost-shifting strategies that expose vulnerable populations to great financial risks.
BACKGROUND: The range of hospital charges for similar diagnoses show tremendous variability across U.S. hospitals. This charge variability remains unexplained. OBJECTIVE: We aimed to describe hospital charge variability in the U.S. and examine its relationship to local health factors. DESIGN: This was a descriptive study of the 2011 Medicare Inpatient Charge data summarizing inpatient hospital charges billed to Medicare. This data was evaluated using 29 county-level measures of health status, health behavior, clinical access and quality, built environment, and socioeconomic status in a clustered, multivariate linear regression. PARTICIPANTS: 2871 U.S. hospitals registered with Medicare and with at least ten discharges for diagnosis-related groups (DRGs) of six common inpatient conditions. MAIN MEASURE: Inpatient hospital charges were assessed. KEY RESULTS: No community health measures were associated with hospital charges. The one notable exception associated with higher charges was higher rates of uninsured status ($344.84 higher charges for every one-percentage point increase in prevalence (p < 0.001)). One variable was associated with lower hospital charges: the percentage of children living in poverty [$309.30 lower charges for every one-percentage point increase in prevalence (p < 0.001)]. CONCLUSIONS: Overall, hospital charges lacked an association with population health measures, and their variability remains largely unexplained. However, the association of higher charges with uninsured status raises concerns about hospitals' price-setting strategies, such as price discrimination and cost-shifting strategies that expose vulnerable populations to great financial risks.
Authors: Christopher A Makarewich; Alan K Stotts; Minkyoung Yoo; Richard E Nelson; David L Rothberg Journal: J Pediatr Orthop Date: 2020 May/Jun Impact factor: 2.324
Authors: Michael Urbich; Gary Globe; Krystallia Pantiri; Marieke Heisen; Craig Bennison; Heidi S Wirtz; Gian Luca Di Tanna Journal: Pharmacoeconomics Date: 2020-11 Impact factor: 4.981