Geographic Variation in Quality of Care for Commercially Insured Patients

McKellar, M. Richard; Landrum, Mary Beth; Gibson, Teresa B.; Landon, Bruce E.; Fendrick, A. Mark; Chernew, Michael E.

doi:10.1111/1475-6773.12501

Cited by 15 publications

(12 citation statements)

References 21 publications

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“…Estimates between top and bottom performers varied up to 2-fold, perhaps reflecting general regional differences in quality and safety of care that have been noted in other reports. 44 , 45 , 46 Variation in health care utilization may be a contributing factor as well. Given that surgical and perioperative AEMT is the most common subtype of AEMT, the southeast region’s higher AEMT mortality estimates may be accounted for by the area’s higher-than-average surgical volume, representing more opportunities for harm to occur.…”

Section: Discussionmentioning

confidence: 99%

Association of Adverse Effects of Medical Treatment With Mortality in the United States

et al. 2019

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Key Points Question How has mortality associated with adverse effects of medical treatment in the United States changed over time, by state, age, and sex? Findings In this cohort study, there was a decrease in the national age-standardized mortality rate associated with adverse effects of medical treatment in the United States between 1990 and 2016. Although no differences by sex were observed, increased mortality due to adverse effects of medical treatment was associated with advancing age, and geographic variability was noted. Meaning Global Burden of Disease 2016 results suggest that mortality associated with the adverse effects of medical treatment has decreased modestly over the past 25 years, and although the degree of improvement varies by state, it appears that an increased burden of adverse effects of medical treatment on aging populations continues to affect the US health system.

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Section: Discussionmentioning

confidence: 99%

Association of Adverse Effects of Medical Treatment With Mortality in the United States

et al. 2019

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“…At the population level, there are conflicting findings. Dartmouth Atlas researchers and others reported a negative relationship in the Medicare population, other researchers reported a positive relationship across both Medicare and commercial populations, and still others found no relationship . A meta‐analysis suggests the overall correlation is nearly zero …”

Section: End Goal Of Transformation: Higher Quality And/or Lower Costmentioning

confidence: 98%

“…The inconsistent cost‐to‐quality relationship further suggests their joint pursuit will require multitasking (and “multiknowledge”) by providers to be successful—if someone can discover how to implement such a model, maintain productivity, and avoid the temptation to sacrifice quality for lower cost or higher net revenue. This implies that the strategies needed to address the manifold drivers of cost may differ from those needed to make progress on a large vector of quality measures that may not be correlated with one another . Thus, efforts to score well on one quality measure may not work to score well on others.…”

Section: End Goal Of Transformation: Higher Quality And/or Lower Costmentioning

confidence: 99%

Transformation of the Health Care Industry: Curb Your Enthusiasm?

Burns

Pauly

2018

Milbank Quarterly

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“…[14] Ultimately, the IOM explicitly commented that, "more research on health care outcomes and quality is needed, particularly in commercially insured populations". [14] Recently, analysis of commercially insured populations from 2007–2009 was published by McKellar and colleagues, in which 10 quality measures were examined for variation at the HRR level, including four outcomes measures, and six process measures [49]. …”

Section: Introductionmentioning

confidence: 99%

Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment

Rosenberg¹,

Kellar²,

Labno³

et al. 2016

PLoS ONE

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BackgroundDespite numerous studies of geographic variation in healthcare cost and utilization at the local, regional, and state levels across the U.S., a comprehensive characterization of geographic variation in outcomes has not been published. Our objective was to quantify variation in US health outcomes in an all-payer population before and after risk-adjustment.Methods and FindingsWe used information from 16 independent data sources, including 22 million all-payer inpatient admissions from the Healthcare Cost and Utilization Project (which covers regions where 50% of the U.S. population lives) to analyze 24 inpatient mortality, inpatient safety, and prevention outcomes. We compared outcome variation at state, hospital referral region, hospital service area, county, and hospital levels. Risk-adjusted outcomes were calculated after adjusting for population factors, co-morbidities, and health system factors. Even after risk-adjustment, there exists large geographical variation in outcomes. The variation in healthcare outcomes exceeds the well publicized variation in US healthcare costs. On average, we observed a 2.1-fold difference in risk-adjusted mortality outcomes between top- and bottom-decile hospitals. For example, we observed a 2.3-fold difference for risk-adjusted acute myocardial infarction inpatient mortality. On average a 10.2-fold difference in risk-adjusted patient safety outcomes exists between top and bottom-decile hospitals, including an 18.3-fold difference for risk-adjusted Central Venous Catheter Bloodstream Infection rates. A 3.0-fold difference in prevention outcomes exists between top- and bottom-decile counties on average; including a 2.2-fold difference for risk-adjusted congestive heart failure admission rates. The population, co-morbidity, and health system factors accounted for a range of R2 between 18–64% of variability in mortality outcomes, 3–39% of variability in patient safety outcomes, and 22–70% of variability in prevention outcomes.ConclusionThe amount of variability in health outcomes in the U.S. is large even after accounting for differences in population, co-morbidities, and health system factors. These findings suggest that: 1) additional examination of regional and local variation in risk-adjusted outcomes should be a priority; 2) assumptions of uniform hospital quality that underpin rationale for policy choices (such as narrow insurance networks or antitrust enforcement) should be challenged; and 3) there exists substantial opportunity for outcomes improvement in the US healthcare system.

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Geographic Variation in Quality of Care for Commercially Insured Patients

Abstract: Quality varied across HRRs and there was only a modest geographic "quality footprint."

Cited by 15 publications

References 21 publications

Association of Adverse Effects of Medical Treatment With Mortality in the United States

Association of Adverse Effects of Medical Treatment With Mortality in the United States

Transformation of the Health Care Industry: Curb Your Enthusiasm?

Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment

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