Evaluation of Risk-Adjusted Home Time After Hospitalization for Heart Failure as a Potential Hospital Performance Metric

Background: The utility of 30-day risk-standardized readmission rate (RSRR) as a hospital performance metric has been a matter of debate. Home time is a patient-centered outcome measure that accounts for rehospitalization, mortality, and postdischarge care. We aim to characterize risk-adjusted 30-day home time in patients with acute myocardial infarction (AMI) as a hospital-level performance metric and to evaluate associations with 30-day RSRR, 30-day risk-standardized mortality rate (RSMR), and 1-year RSMR. Methods: The study included 984 612 patients with AMI hospitalization across 2379 hospitals between 2009 and 2015 derived from 100% Medicare claims data. Home time was defined as the number of days alive and spent outside of a hospital, skilled nursing facility, or intermediate-/long-term acute care facility 30 days after discharge. Correlations between hospital-level risk-adjusted 30-day home time and 30-day RSRR, 30-day RSMR, and 1-year RSMR were estimated with the Pearson correlation. Reclassification in hospital performance using 30-day home time versus 30-day RSRR and 30-day RSMR was also evaluated. Results: Median hospital-level risk-adjusted 30-day home time was 24.0 days (range, 15.3–29.0 days). Hospitals with higher home time were more commonly academic centers, had available cardiac surgery and rehabilitation services, and had higher AMI volume and percutaneous coronary intervention use during the AMI hospitalization. Of the mean 30-day home time days lost, 58% were to intermediate-/long-term care or skilled nursing facility stays (4.7 days), 30% to death (2.5 days), and 12% to readmission (1.0 days). Hospital-level risk-adjusted 30-day home time was inversely correlated with 30-day RSMR ( r =−0.22, P <0.0001) and 30-day RSRR (r =−0.25, P <0.0001). Patients admitted to hospitals with higher risk-adjusted 30-day home time had lower 30-day readmission (quartile 1 versus 4, 21% versus 17%), 30-day mortality rate (5% versus 3%), and 1-year mortality rate (18% versus 12%). Furthermore, 30-day home time reclassified hospital performance status in ≈30% of hospitals versus 30-day RSRR and 30-day RSMR. Conclusions: Thirty-day home time for patients with AMI can be assessed as a hospital-level performance metric with the use of Medicare claims data. It varies across hospitals, is associated with postdischarge readmission and mortality outcomes, and meaningfully reclassifies hospital performance compared with the 30-day RSRR and 30-day RSMR metrics.

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HOSPITAL PERFORMANCE IS NOT ASSOCIATED WITH THE TIMING OR CAUSES OF 30-DAY READMISSION AFTER HOSPITALIZATION FOR HEART FAILURE OR ACUTE MYOCARDIAL INFARCTION

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(12)61888-9 ◽

2012 ◽

Vol 59 (13) ◽

pp. E1887

Author(s):

Kumar Dharmarajan ◽

Fu-Chi Hsieh ◽

Zhen Qiu Lin ◽

Nancy Kim ◽

Susannah Bernheim ◽

...

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Acute Myocardial Infarction ◽

Hospital Performance

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COMPARISON OF HOSPITAL PERFORMANCE OF ACUTE MYOCARDIAL INFARCTION AND HEART FAILURE QUALITY MEASURES: FINDINGS FROM THE GET WITH THE GUIDELINES REGISTRY

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(10)61339-3 ◽

2010 ◽

Vol 55 (10) ◽

pp. A142.E1338

Author(s):

Tracy Wang ◽

David Dai ◽

Adrian Hernandez ◽

Deepak Bhatt ◽

Paul Heidenreich ◽

...

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Acute Myocardial Infarction ◽

Quality Measures ◽

Hospital Performance ◽

Get With The Guidelines

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Abstract P255: Should Models of Hospital Outcomes Include Race as a Covariate?

Circulation Cardiovascular Quality and Outcomes ◽

10.1161/circoutcomes.4.suppl_1.ap255 ◽

2011 ◽

Vol 4 (suppl_1) ◽

Author(s):

Paul L Hebert ◽

Joseph Ross ◽

Nathan Goldstein ◽

Elizabeth Howell

Keyword(s):

Heart Failure ◽

Hospital Performance ◽

Hospital Quality ◽

Quality Performance ◽

Hospital Outcome ◽

Causal Pathways ◽

Patient Race ◽

Treatment Bias ◽

The Impact ◽

White Patients

Objective: There remains controversy about whether models of hospital performance should account for patient race. We used simulated data to explore the effects on hospital rankings of including or excluding race as a covariate in risk-standardized hospital outcome models, using hospitalizations for heart failure as a case study. Methods We simulated three scenarios by which patient race might affect heart failure hospital outcome: a) a treatment bias simulation in which non-white patients were 20% less likely to receive optimal treatment regardless of hospital quality performance; b) an allocative bias simulation in which non-white patients systematically received care from lower performing hospitals that lower quality care to all patients uniformly; and c) a survival bias simulation in which nonwhite patients were 10% less likely to survive than white patients regardless of hospital quality performance. We evaluated the concordance in estimated hospital rank between models that did and did not include race for a simulation of 100,000 patients hospitalized at 1,000 hospitals. We also present the extent to which each model over- or under-predicted hospital quality for hospitals that treat a high percentage of nonwhite patients. Results When allocation or treatment bias scenarios were simulated, the model results were highly consistent (kappa>0.9) regardless of whether or not patient race was included in risk-standardization models; models were most disparate for the survival bias scenario (kappa =0.689). In both the allocative bias and the treatment bias scenarios, models that include race overestimated the quality of hospital care at hospitals that treat a higher percentage of nonwhite patients (beta =91.9 and 78.9, respectively; p<0.001) while models that excluded race did not (beta=31.5; p=0.184, and 2.5; p=0.916, respectively). In the survival disparity scenario, the model that included race performed well (beta=-36.7 p=0.15), whereas the model that excluded race significantly underestimated quality at highly nonwhite hospitals (beta= -326.6; p<0.001). Conclusion The impact of including race in risk standardization models of hospital performance depends on causal pathways by which race impacts clinical outcomes.

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