Literature DB >> 25732489

Safety-net hospitals more likely than other hospitals to fare poorly under Medicare's value-based purchasing.

Matlin Gilman1, E Kathleen Adams2, Jason M Hockenberry3, Arnold S Milstein4, Ira B Wilson5, Edmund R Becker6.   

Abstract

Medicare's value-based purchasing (VBP) program potentially puts safety-net hospitals at a financial disadvantage compared to other hospitals. In 2014, the second year of the program, patient mortality measures were added to the VBP program's algorithm for assigning penalties and rewards. We examined whether the inclusion of mortality measures in the second year of the program had a disproportionate impact on safety-net hospitals nationally. We found that safety-net hospitals were more likely than other hospitals to be penalized under the VBP program as a result of their poorer performance on process and patient experience scores. In 2014, 63 percent of safety-net hospitals versus 51 percent of all other sample hospitals received payment rate reductions under the program. However, safety-net hospitals' performance on mortality measures was comparable to that of other hospitals, with an average VBP survival score of thirty-two versus thirty-one among other hospitals. Although safety-net hospitals are still more likely than other hospitals to fare poorly under the VBP program, increasing the weight given to mortality in the VBP payment algorithm would reduce this disadvantage. Project HOPE—The People-to-People Health Foundation, Inc.

Entities:  

Keywords:  Financing Health Care; Health Reform; Hospitals; Medicare; Safety-Net Systems

Mesh:

Year:  2015        PMID: 25732489     DOI: 10.1377/hlthaff.2014.1059

Source DB:  PubMed          Journal:  Health Aff (Millwood)        ISSN: 0278-2715            Impact factor:   6.301


  24 in total

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4.  Reliability of 30-Day Readmission Measures Used in the Hospital Readmission Reduction Program.

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Journal:  Health Serv Res       Date:  2016-10-21       Impact factor: 3.402

5.  Hospital uncompensated care and patient experience: An instrumental variable approach.

Authors:  Susan Camilleri; Jeffrey Diebold
Journal:  Health Serv Res       Date:  2019-01-09       Impact factor: 3.402

6.  Hospital Characteristics Associated With Risk-standardized Readmission Rates.

Authors:  Leora I Horwitz; Susannah M Bernheim; Joseph S Ross; Jeph Herrin; Jacqueline N Grady; Harlan M Krumholz; Elizabeth E Drye; Zhenqiu Lin
Journal:  Med Care       Date:  2017-05       Impact factor: 2.983

7.  Association of Patient Social, Cognitive, and Functional Risk Factors with Preventable Hospitalizations: Implications for Physician Value-Based Payment.

Authors:  Kenton J Johnston; Hefei Wen; Mario Schootman; Karen E Joynt Maddox
Journal:  J Gen Intern Med       Date:  2019-04-25       Impact factor: 5.128

8.  Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program.

Authors:  Karen E Joynt Maddox; Mat Reidhead; Jianhui Hu; Amy J H Kind; Alan M Zaslavsky; Elna M Nagasako; David R Nerenz
Journal:  Health Serv Res       Date:  2019-04       Impact factor: 3.402

9.  Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization.

Authors:  Leora I Horwitz; Yongfei Wang; Faseeha K Altaf; Changqin Wang; Zhenqiu Lin; Shuling Liu; Jacqueline Grady; Susannah M Bernheim; Nihar R Desai; Arjun K Venkatesh; Jeph Herrin
Journal:  Med Care       Date:  2018-04       Impact factor: 2.983

10.  Prior Hospitalization Burden and the Relatedness of 30-Day Readmissions in Patients Receiving Hemodialysis.

Authors:  Eugene Lin; Jay Bhattacharya; Glenn M Chertow
Journal:  J Am Soc Nephrol       Date:  2019-01-03       Impact factor: 10.121

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