Hospital Phenotypes in the Management of Patients Admitted for Acute Myocardial Infarction.
To characterize hospital phenotypes by their combined utilization pattern of percutaneous coronary interventions (PCI), coronary artery bypass grafting (CABG) procedures, and intensive care unit (ICU) admissions for patients hospitalized for acute myocardial infarction (AMI).



Using the Premier Analytical Database, we identified 129,138 hospitalizations for AMI from 246 hospitals with the capacity for performing open-heart surgery during 2010-2013. We calculated year-specific, risk-standardized estimates of PCI procedure rates, CABG procedure rates, and ICU admission rates for each hospital, adjusting for patient clinical characteristics and within-hospital correlation of patients. We used a mixture modeling approach to identify groups of hospitals (ie, hospital phenotypes) that exhibit distinct longitudinal patterns of risk-standardized PCI, CABG, and ICU admission rates.



We identified 3 distinct phenotypes among the 246 hospitals: (1) high PCI-low CABG-high ICU admission (39.2% of the hospitals), (2) high PCI-low CABG-low ICU admission (30.5%), and (3) low PCI-high CABG-moderate ICU admission (30.4%). Hospitals in the high PCI-low CABG-high ICU admission phenotype had significantly higher risk-standardized in-hospital costs and 30-day risk-standardized payment yet similar risk-standardized mortality and readmission rates compared with hospitals in the low PCI-high CABG-moderate ICU admission phenotype. Hospitals in these phenotypes differed by geographic region.



Hospitals differ in how they manage patients hospitalized for AMI. Their distinctive practice patterns suggest that some hospital phenotypes may be more successful in producing good outcomes at lower cost.
*Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine †Center for Outcomes Research and Evaluation, Yale-New Haven Hospital ‡Department of Biostatistics, Yale School of Public Health, New Haven, CT §Department of Health Care Policy, Harvard Medical School ∥Department of Biostatistics, Harvard T.H. Chan School of Public Health ¶Division of General Medicine, Tufts University School of Medicine, Boston #Baystate Medical Center, Springfield, MA **Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT ††Premier Inc., Charlotte, NC ‡‡Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA §§Booz Allen Hamilton Inc., McLean, VA ∥∥Robert Wood Johnson Foundation Clinical Scholars Program, Department of Internal Medicine, Yale School of Medicine ¶¶Department of Health Policy and Management, Yale School of Public Health, New Haven, CT.
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Shu-Xia
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Li
Haiqun
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Lin
Sharon-Lise T
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Normand
Tara
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Lagu
Nihar
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Desai
Michael
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Duan
Eugene A
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Kroch
Harlan M
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Krumholz
D000208:Acute Disease; D000368:Aged; D001026:Coronary Artery Bypass / Q000706:statistics & numerical data; D017721:Hospital Costs / Q000706:statistics & numerical data; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data; D009203:Myocardial Infarction / Q000191:economics / Q000401:mortality / Q000628:therapy*; D062645:Percutaneous Coronary Intervention / Q000706:statistics & numerical data