Harlan M Krumholz1, Kun Wang1, Zhenqiu Lin1, Kumar Dharmarajan1, Leora I Horwitz1, Joseph S Ross1, Elizabeth E Drye1, Susannah M Bernheim1, Sharon-Lise T Normand1. 1. From the Sections of Cardiovascular Medicine (H.M.K., K.W., K.D.) and General Internal Medicine (J.S.R., S.M.B.) and the National Clinician Scholars Program (J.S.R., S.M.B.), Department of Internal Medicine, and the Department of Pediatrics (E.E.D.), Yale School of Medicine, the Center for Outcomes Research and Evaluation, Yale-New Haven Hospital (H.M.K., K.W., Z.L., K.D., J.S.R., E.E.D., S.M.B.), and the Department of Health Policy and Management, Yale School of Public Health (H.M.K., J.S.R.) - all in New Haven, CT; Clover Health, Jersey City, NJ (K.D.); the Division of Healthcare Delivery Science, Department of Population Health, and the Division of General Internal Medicine and Clinical Innovation, Department of Medicine, New York University (NYU) School of Medicine, Center for Healthcare Innovation and Delivery Science, NYU Langone Health, New York (L.I.H.); and the Department of Health Care Policy, Harvard Medical School, and the Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston (S.-L.T.N.).
Abstract
BACKGROUND: To isolate hospital effects on risk-standardized hospital-readmission rates, we examined readmission outcomes among patients who had multiple admissions for a similar diagnosis at more than one hospital within a given year. METHODS: We divided the Centers for Medicare and Medicaid Services hospital-wide readmission measure cohort from July 2014 through June 2015 into two random samples. All the patients in the cohort were Medicare recipients who were at least 65 years of age. We used the first sample to calculate the risk-standardized readmission rate within 30 days for each hospital, and we classified hospitals into performance quartiles, with a lower readmission rate indicating better performance (performance-classification sample). The study sample (identified from the second sample) included patients who had two admissions for similar diagnoses at different hospitals that occurred more than 1 month and less than 1 year apart, and we compared the observed readmission rates among patients who had been admitted to hospitals in different performance quartiles. RESULTS: In the performance-classification sample, the median risk-standardized readmission rate was 15.5% (interquartile range, 15.3 to 15.8). The study sample included 37,508 patients who had two admissions for similar diagnoses at a total of 4272 different hospitals. The observed readmission rate was consistently higher among patients admitted to hospitals in a worse-performing quartile than among those admitted to hospitals in a better-performing quartile, but the only significant difference was observed when the patients were admitted to hospitals in which one was in the best-performing quartile and the other was in the worst-performing quartile (absolute difference in readmission rate, 2.0 percentage points; 95% confidence interval, 0.4 to 3.5; P=0.001). CONCLUSIONS: When the same patients were admitted with similar diagnoses to hospitals in the best-performing quartile as compared with the worst-performing quartile of hospital readmission performance, there was a significant difference in rates of readmission within 30 days. The findings suggest that hospital quality contributes in part to readmission rates independent of factors involving patients. (Funded by Yale-New Haven Hospital Center for Outcomes Research and Evaluation and others.).
BACKGROUND: To isolate hospital effects on risk-standardized hospital-readmission rates, we examined readmission outcomes among patients who had multiple admissions for a similar diagnosis at more than one hospital within a given year. METHODS: We divided the Centers for Medicare and Medicaid Services hospital-wide readmission measure cohort from July 2014 through June 2015 into two random samples. All the patients in the cohort were Medicare recipients who were at least 65 years of age. We used the first sample to calculate the risk-standardized readmission rate within 30 days for each hospital, and we classified hospitals into performance quartiles, with a lower readmission rate indicating better performance (performance-classification sample). The study sample (identified from the second sample) included patients who had two admissions for similar diagnoses at different hospitals that occurred more than 1 month and less than 1 year apart, and we compared the observed readmission rates among patients who had been admitted to hospitals in different performance quartiles. RESULTS: In the performance-classification sample, the median risk-standardized readmission rate was 15.5% (interquartile range, 15.3 to 15.8). The study sample included 37,508 patients who had two admissions for similar diagnoses at a total of 4272 different hospitals. The observed readmission rate was consistently higher among patients admitted to hospitals in a worse-performing quartile than among those admitted to hospitals in a better-performing quartile, but the only significant difference was observed when the patients were admitted to hospitals in which one was in the best-performing quartile and the other was in the worst-performing quartile (absolute difference in readmission rate, 2.0 percentage points; 95% confidence interval, 0.4 to 3.5; P=0.001). CONCLUSIONS: When the same patients were admitted with similar diagnoses to hospitals in the best-performing quartile as compared with the worst-performing quartile of hospital readmission performance, there was a significant difference in rates of readmission within 30 days. The findings suggest that hospital quality contributes in part to readmission rates independent of factors involving patients. (Funded by Yale-New Haven Hospital Center for Outcomes Research and Evaluation and others.).
Authors: Rachael B Zuckerman; Steven H Sheingold; E John Orav; Joel Ruhter; Arnold M Epstein Journal: N Engl J Med Date: 2016-02-24 Impact factor: 91.245
Authors: Leora I Horwitz; Chohreh Partovian; Zhenqiu Lin; Jacqueline N Grady; Jeph Herrin; Mitchell Conover; Julia Montague; Chloe Dillaway; Kathleen Bartczak; Lisa G Suter; Joseph S Ross; Susannah M Bernheim; Harlan M Krumholz; Elizabeth E Drye Journal: Ann Intern Med Date: 2014-11-18 Impact factor: 25.391
Authors: Peter K Lindenauer; Sharon-Lise T Normand; Elizabeth E Drye; Zhenqiu Lin; Katherine Goodrich; Mayur M Desai; Dale W Bratzler; Walter J O'Donnell; Mark L Metersky; Harlan M Krumholz Journal: J Hosp Med Date: 2011-01-05 Impact factor: 2.960
Authors: Harlan M Krumholz; Zhenqiu Lin; Elizabeth E Drye; Mayur M Desai; Lein F Han; Michael T Rapp; Jennifer A Mattera; Sharon-Lise T Normand Journal: Circ Cardiovasc Qual Outcomes Date: 2011-03
Authors: Susannah M Bernheim; Craig S Parzynski; Leora Horwitz; Zhenqiu Lin; Michael J Araas; Joseph S Ross; Elizabeth E Drye; Lisa G Suter; Sharon-Lise T Normand; Harlan M Krumholz Journal: Health Aff (Millwood) Date: 2016-08-01 Impact factor: 6.301
Authors: Alexander B Blum; Natalia N Egorova; Eugene A Sosunov; Annetine C Gelijns; Erin DuPree; Alan J Moskowitz; Alex D Federman; Deborah D Ascheim; Salomeh Keyhani Journal: Circ Cardiovasc Qual Outcomes Date: 2014-05-13
Authors: Rasha A Al-Lami; James E Graham; Rachel R Deer; Jordan Westra; Stephen B Williams; Yong-Fang Kuo; Jacques Baillargeon Journal: Am J Phys Med Rehabil Date: 2019-06 Impact factor: 2.159
Authors: John A Dodson; Alexandra M Hajduk; Terrence E Murphy; Mary Geda; Harlan M Krumholz; Sui Tsang; Michael G Nanna; Mary E Tinetti; David Goldstein; Daniel E Forman; Karen P Alexander; Thomas M Gill; Sarwat I Chaudhry Journal: Circ Cardiovasc Qual Outcomes Date: 2019-05
Authors: Michiel H F Poorthuis; Eelco C Brand; Alison Halliday; Richard Bulbulia; Michiel L Bots; Gert J de Borst Journal: Ann Surg Date: 2019-04 Impact factor: 12.969