Xiao Xu1, Shu-Xia Li, Haiqun Lin, Sharon-Lise T Normand, Tara Lagu, Nihar Desai, Michael Duan, Eugene A Kroch, Harlan M Krumholz. 1. *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.
Abstract
OBJECTIVES: 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). RESEARCH DESIGN: 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. RESULTS: 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. CONCLUSIONS: 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.
OBJECTIVES: 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). RESEARCH DESIGN: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Elizabeth H Bradley; Jeph Herrin; Leslie Curry; Emily J Cherlin; Yongfei Wang; Tashonna R Webster; Elizabeth E Drye; Sharon-Lise T Normand; Harlan M Krumholz Journal: Am J Cardiol Date: 2010-10-15 Impact factor: 2.778
Authors: Xiao Xu; Shu-Xia Li; Haiqun Lin; Sharon-Lise T Normand; Nancy Kim; Lesli S Ott; Tara Lagu; Michael Duan; Eugene A Kroch; Harlan M Krumholz Journal: Health Serv Res Date: 2014-06-28 Impact factor: 3.402
Authors: E Guadagnoli; M B Landrum; S L Normand; J Z Ayanian; P Garg; P J Hauptman; T J Ryan; B J McNeil Journal: Med Care Date: 2001-05 Impact factor: 2.983
Authors: Pushkal P Garg; Mary Beth Landrum; Sharon-Lise T Normand; John Z Ayanian; Paul J Hauptman; Thomas J Ryan; Barbara J McNeil; Edward Guadagnoli Journal: Med Care Date: 2002-07 Impact factor: 2.983