Literature DB >> 21156879

Who has higher readmission rates for heart failure, and why? Implications for efforts to improve care using financial incentives.

Karen E Joynt1, Ashish K Jha.   

Abstract

BACKGROUND: Reducing readmissions for heart failure is an important goal for policymakers. Current national policies financially penalize hospitals with high readmission rates, which may have unintended consequences if these institutions are resource-poor, either financially or clinically. METHODS AND
RESULTS: We analyzed national claims data for Medicare patients with heart failure discharged from US hospitals in 2006 to 2007. We used multivariable models to examine hospital characteristics, 30-day all-cause readmission rates, and likelihood of performing in the worst quartile of readmission rates nationally. Among 905 764 discharges in our sample, patients discharged from public hospitals (27.9%) had higher readmission rates than nonprofit hospitals (25.7%, P<0.001), as did patients discharged from hospitals in counties with low median income (29.4%) compared with counties with high median income (25.7%, P<0.001). Patients discharged from hospitals without cardiac services (27.2%) had higher readmission rates than those from hospitals with full cardiac services (25.1%, P<0.001); patients discharged from hospitals in the lowest quartile of nurse staffing (28.5%) had higher readmission rates than those from hospitals in the highest quartile (25.4%, P<0.001). Patients discharged from small hospitals (28.4%) had higher readmission rates than those discharged from large hospitals (25.2%, P<0.001). These same characteristics identified hospitals that were likely to perform in the worst quartile nationally.
CONCLUSIONS: Given that many poor-performing hospitals also have fewer resources, they may suffer disproportionately from financial penalties for high readmission rates. As we seek to improve care for patients with heart failure, we should ensure that penalties for poor performance do not worsen disparities in quality of care.

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Year:  2010        PMID: 21156879      PMCID: PMC3050549          DOI: 10.1161/CIRCOUTCOMES.110.950964

Source DB:  PubMed          Journal:  Circ Cardiovasc Qual Outcomes        ISSN: 1941-7713


  28 in total

1.  Comparison of the Elixhauser and Charlson/Deyo methods of comorbidity measurement in administrative data.

Authors:  Danielle A Southern; Hude Quan; William A Ghali
Journal:  Med Care       Date:  2004-04       Impact factor: 2.983

2.  Public hospitals and health care reform: choices and challenges.

Authors:  D P Andrulis; K L Acuff; K B Weiss; R J Anderson
Journal:  Am J Public Health       Date:  1996-02       Impact factor: 9.308

3.  Comorbidity measures for use with administrative data.

Authors:  A Elixhauser; C Steiner; D R Harris; R M Coffey
Journal:  Med Care       Date:  1998-01       Impact factor: 2.983

4.  Predictors of readmission among elderly survivors of admission with heart failure.

Authors:  H M Krumholz; Y T Chen; Y Wang; V Vaccarino; M J Radford; R I Horwitz
Journal:  Am Heart J       Date:  2000-01       Impact factor: 4.749

5.  Prediction of hospital readmission for heart failure: development of a simple risk score based on administrative data.

Authors:  E F Philbin; T G DiSalvo
Journal:  J Am Coll Cardiol       Date:  1999-05       Impact factor: 24.094

6.  Socioeconomic status as an independent risk factor for hospital readmission for heart failure.

Authors:  E F Philbin; G W Dec; P L Jenkins; T G DiSalvo
Journal:  Am J Cardiol       Date:  2001-06-15       Impact factor: 2.778

7.  Treatment and outcome of myocardial infarction in hospitals with and without invasive capability. Investigators in the National Registry of Myocardial Infarction.

Authors:  W J Rogers; J G Canto; H V Barron; J A Boscarino; D A Shoultz; N R Every
Journal:  J Am Coll Cardiol       Date:  2000-02       Impact factor: 24.094

8.  Readmission after hospitalization for congestive heart failure among Medicare beneficiaries.

Authors:  H M Krumholz; E M Parent; N Tu; V Vaccarino; Y Wang; M J Radford; J Hennen
Journal:  Arch Intern Med       Date:  1997-01-13

9.  The effect of hospital financial characteristics on quality of care.

Authors:  H R Burstin; S R Lipsitz; I S Udvarhelyi; T A Brennan
Journal:  JAMA       Date:  1993-08-18       Impact factor: 56.272

10.  A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure.

Authors:  M W Rich; V Beckham; C Wittenberg; C L Leven; K E Freedland; R M Carney
Journal:  N Engl J Med       Date:  1995-11-02       Impact factor: 91.245

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  80 in total

1.  HerzMobil Tirol network: rationale for and design of a collaborative heart failure disease management program in Austria.

Authors:  Andreas Von der Heidt; Elske Ammenwerth; Karl Bauer; Bettina Fetz; Thomas Fluckinger; Andrea Gassner; Willhelm Grander; Walter Gritsch; Immaculata Haffner; Gudrun Henle-Talirz; Stefan Hoschek; Stephan Huter; Peter Kastner; Susanne Krestan; Peter Kufner; Robert Modre-Osprian; Josef Noebl; Momen Radi; Clemens Raffeiner; Stefan Welte; Andreas Wiseman; Gerhard Poelzl
Journal:  Wien Klin Wochenschr       Date:  2014-11-13       Impact factor: 1.704

2.  The Quality of Surgical and Pneumonia Care in Minority-Serving and Racially Integrated Hospitals.

Authors:  Darrell J Gaskin; Hossein Zare; Adil H Haider; Thomas A LaVeist
Journal:  Health Serv Res       Date:  2015-09-29       Impact factor: 3.402

3.  Effect of Pharmacist Clinic Visits on 30-Day Heart Failure Readmission Rates at a County Hospital.

Authors:  Lucy Hahn; Matthew Belisle; Sarah Nguyen; Kristin Snackey Alvarez; Sandeep Das
Journal:  Hosp Pharm       Date:  2018-09-11

Review 4.  Risk prediction models for hospital readmission: a systematic review.

Authors:  Devan Kansagara; Honora Englander; Amanda Salanitro; David Kagen; Cecelia Theobald; Michele Freeman; Sunil Kripalani
Journal:  JAMA       Date:  2011-10-19       Impact factor: 56.272

Review 5.  Sleep-disordered breathing in hospitalized patients with congestive heart failure: a concise review and proposed algorithm.

Authors:  Ankit Gupta; Stuart F Quan; Olaf Oldenburg; Atul Malhotra; Sunil Sharma
Journal:  Heart Fail Rev       Date:  2018-09       Impact factor: 4.214

6.  Recurrent Acute Decompensated Heart Failure Admissions for Patients With Reduced Versus Preserved Ejection Fraction (from the Atherosclerosis Risk in Communities Study).

Authors:  Melissa C Caughey; Carla A Sueta; Sally C Stearns; Amil M Shah; Wayne D Rosamond; Patricia P Chang
Journal:  Am J Cardiol       Date:  2018-03-28       Impact factor: 2.778

7.  Health Literacy Predicts Morbidity and Mortality in Rural Patients With Heart Failure.

Authors:  Debra K Moser; Susan Robinson; Martha J Biddle; Michele M Pelter; Thomas S Nesbitt; Jeffery Southard; Lawton Cooper; Kathleen Dracup
Journal:  J Card Fail       Date:  2015-04-20       Impact factor: 5.712

8.  Thirty days are inadequate for assessing readmission following complex hepatopancreatobiliary procedures.

Authors:  Maria S Altieri; Jie Yang; Donglei Yin; Konstantinos Spaniolas; Mark Talamini; Aurora Pryor
Journal:  Surg Endosc       Date:  2018-12-10       Impact factor: 4.584

9.  Variation in surgical-readmission rates and quality of hospital care.

Authors:  Thomas C Tsai; Karen E Joynt; E John Orav; Atul A Gawande; Ashish K Jha
Journal:  N Engl J Med       Date:  2013-09-19       Impact factor: 91.245

10.  Predictors of Rehospitalization Among Adults With Congenital Heart Disease Are Lesion Specific.

Authors:  Ari M Cedars; Sara Burns; Eric L Novak; Amit P Amin
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2016-09-13
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