Abstract
Overuse of health care is a pervasive threat to patients that requires measurement to inform the development of interventions. To measure low-value health care use within health systems in the US and explore features of the health systems associated with low-value care delivery. In this cross-sectional analysis, we identified occurrences of 17 low-value services in 3745 hospitals and affiliated outpatient sites. Hospitals were linked to 676 health systems in the US using the Agency for Healthcare Research and Quality (AHRQ) Compendium of Health Systems. The participants were 100% of Medicare beneficiaries with claims from 2016 to 2018. We identified occurrences of 17 low-value services in 3839 hospitals and affiliated outpatient sites. Hospitals were linked to health systems using AHRQ's Compendium of Health Systems. Between March and August 2021, we modeled overuse occurrences with a negative binomial regression model including the year-quarter, procedure indicator, and a health system indicator. The model included random effects for hospital and beneficiary age, sex, and comorbidity count specific to each indicator, hospital, and quarter. The beta coefficients associated with the health system term, normalized, reflect the tendency of that system to use low-value services relative to all other systems. With ordinary least squares regression, we explored health system characteristics associated with the Overuse Index (OI), expressed as a standard deviation where the mean across all health systems is 0. There were 676 unique health systems assessed in our study that included from 1 to 163 hospitals (median of 2). The mean age of eligible beneficiaries was 75.5 years and 76% were women. Relative to the lowest tertile, health systems in the upper tertile of medical groups count and bed count had an OI that was higher by 0.38 standard deviations (SD) and 0.44 SD, respectively. Health systems that were primarily investor owned had an OI that was 0.56 SD higher than those that were not investor owned. Relative to the lowest tertile, health systems in the upper tertile of primary care physicians, upper tertile of teaching intensity, and upper quartile of uncompensated care had an OI that was lower by 0.59 SD, 0.45 SD, and 0.47 SD, respectively. In this cross-sectional study of US health systems, higher amounts of overuse among health systems were associated with investor ownership and fewer primary care physicians. The OI is a valuable tool for identifying potentially modifiable drivers of overuse and is adaptable to other levels of investigation, such as the state or region, which might be affected by local policies affecting payment or system consolidation.
Highlights
With ordinary least squares regression, we explored health system characteristics associated with the Overuse Index (OI), expressed as a standard deviation where the mean across all health systems is 0
Relative to the lowest tertile, health systems in the upper tertile of medical groups count and bed count had an OI that was higher by 0.38 standard deviations (SD) and 0.44 SD, respectively
Relative to the lowest tertile, health systems in the upper tertile of primary care physicians, upper tertile of teaching intensity, and upper quartile of uncompensated care had an OI that was lower by 0.59 SD, 0.45 SD, and 0.47 SD, respectively
Summary
The provision of low-value or no-value care, is consistently identified as contributing to high costs in the US health care system.[1,2,3] This wasteful care is physically, psychologically, and financially harmful to patients.[4,5,6] Some interventions that seek to encourage high-value care delivery and limit low-value care are implemented nationally, such as the national coverage determinations of the Medicare program[7] or bundled payment models.[8,9,10] Other interventions are delivered locally, within a clinical unit, and are implemented through practice change initiatives. There is scant quantification regarding low-value health care at the health system level despite the importance of this information for state and federal policy setting.[17]
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