Literature DB >> 24823956

Impact of socioeconomic status measures on hospital profiling in New York City.

Alexander B Blum1, Natalia N Egorova2, Eugene A Sosunov2, Annetine C Gelijns2, Erin DuPree2, Alan J Moskowitz2, Alex D Federman2, Deborah D Ascheim2, Salomeh Keyhani2.   

Abstract

BACKGROUND: Current 30-day readmission models used by the Center for Medicare and Medicaid Services for the purpose of hospital-level comparisons lack measures of socioeconomic status (SES). We examined whether the inclusion of an SES measure in 30-day congestive heart failure readmission models changed hospital risk-standardized readmission rates in New York City (NYC) hospitals. METHODS AND
RESULTS: Using a Centers for Medicare & Medicaid Services (CMS)-like model, we estimated 30-day hospital-level risk-standardized readmission rates by adjusting for age, sex, and comorbid conditions. Next, we examined how hospital risk-standardized readmission rates changed relative to the NYC mean with inclusion of the Agency for Healthcare Research and Quality (AHRQ)-validated SES index score. In a secondary analysis, we examined whether inclusion of the AHRQ SES index score in 30-day readmission models disproportionately impacted the risk-standardized readmission rates of minority-serving hospitals. Higher AHRQ SES scores, indicators of higher SES, were associated with lower odds (0.99) of 30-day readmission (P<0.019). The addition of the AHRQ SES index did not change the model's C statistic (0.63). After adjustment for the AHRQ SES index, 1 hospital changed status from worse than the NYC average to no different than the NYC average. After adjustment for the AHRQ SES index, 1 NYC minority-serving hospital was reclassified from worse to no different than average.
CONCLUSIONS: Although patients with higher SES were less likely to be admitted, the impact of SES on readmission was small. In NYC, inclusion of the AHRQ SES score in a CMS-based model did not impact hospital-level profiling based on 30-day readmission.
© 2014 American Heart Association, Inc.

Entities:  

Keywords:  heart failure; patient readmission; social class

Mesh:

Year:  2014        PMID: 24823956      PMCID: PMC4072036          DOI: 10.1161/CIRCOUTCOMES.113.000520

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


  15 in total

1.  Do the poor cost more? A multihospital study of patients' socioeconomic status and use of hospital resources.

Authors:  A M Epstein; R S Stern; J S Weissman
Journal:  N Engl J Med       Date:  1990-04-19       Impact factor: 91.245

2.  Social determinants of health inequalities.

Authors:  Michael Marmot
Journal:  Lancet       Date:  2005 Mar 19-25       Impact factor: 79.321

3.  The income-associated burden of disease in the United States.

Authors:  Peter Muennig; Peter Franks; Haomiao Jia; Erica Lubetkin; Marthe R Gold
Journal:  Soc Sci Med       Date:  2005-11       Impact factor: 4.634

4.  Community variation: disparities in health care quality between Asian and white medicare beneficiaries.

Authors:  Ernest Moy; Linda G Greenberg; Amanda E Borsky
Journal:  Health Aff (Millwood)       Date:  2008 Mar-Apr       Impact factor: 6.301

5.  An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure.

Authors:  Patricia S Keenan; Sharon-Lise T Normand; Zhenqiu Lin; Elizabeth E Drye; Kanchana R Bhat; Joseph S Ross; Jeremiah D Schuur; Brett D Stauffer; Susannah M Bernheim; Andrew J Epstein; Yongfei Wang; Jeph Herrin; Jersey Chen; Jessica J Federer; Jennifer A Mattera; Yun Wang; Harlan M Krumholz
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2008-09

6.  Medicare program; hospital inpatient prospective payment systems for acute care hospitals and the long-term care hospital prospective payment system and FY 2012 rates; hospitals' FTE resident caps for graduate medical education payment. Final rules.

Authors: 
Journal:  Fed Regist       Date:  2011-08-18

7.  Impact of socioeconomic status on hospital use in New York City.

Authors:  J Billings; L Zeitel; J Lukomnik; T S Carey; A E Blank; L Newman
Journal:  Health Aff (Millwood)       Date:  1993       Impact factor: 6.301

8.  Prevalence and mortality rate of congestive heart failure in the United States.

Authors:  D D Schocken; M I Arrieta; P E Leaverton; E A Ross
Journal:  J Am Coll Cardiol       Date:  1992-08       Impact factor: 24.094

9.  Survival after the onset of congestive heart failure in Framingham Heart Study subjects.

Authors:  K K Ho; K M Anderson; W B Kannel; W Grossman; D Levy
Journal:  Circulation       Date:  1993-07       Impact factor: 29.690

10.  Conflicting measures of hospital quality: ratings from "Hospital Compare" versus "Best Hospitals".

Authors:  Lakshmi K Halasyamani; Matthew M Davis
Journal:  J Hosp Med       Date:  2007-05       Impact factor: 2.960

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  23 in total

1.  Geographic Variation in Trends and Disparities in Acute Myocardial Infarction Hospitalization and Mortality by Income Levels, 1999-2013.

Authors:  Erica S Spatz; Adam L Beckman; Yun Wang; Nihar R Desai; Harlan M Krumholz
Journal:  JAMA Cardiol       Date:  2016-06-01       Impact factor: 14.676

2.  Financial toxicity is associated with worse physical and emotional long-term outcomes after traumatic injury.

Authors:  Patrick B Murphy; Sarah Severance; Stephanie Savage; Samilia Obeng-Gyasi; Lava R Timsina; Ben L Zarzaur
Journal:  J Trauma Acute Care Surg       Date:  2019-11       Impact factor: 3.313

3.  Impact of Risk Adjustment for Socioeconomic Status on Risk-adjusted Surgical Readmission Rates.

Authors:  Laurent G Glance; Arthur L Kellermann; Turner M Osler; Yue Li; Wenjun Li; Andrew W Dick
Journal:  Ann Surg       Date:  2016-04       Impact factor: 12.969

4.  Augmenting community-level social determinants of health data with individual-level survey data.

Authors:  Min-Hyung Kim; Yiye Zhang; Jessica S Ancker
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

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

Authors:  Michael P Thompson; Cameron M Kaplan; Yu Cao; Gloria J Bazzoli; Teresa M Waters
Journal:  Health Serv Res       Date:  2016-10-21       Impact factor: 3.402

6.  Development and Validation of a County-Level Social Determinants of Health Risk Assessment Tool for Cardiovascular Disease.

Authors:  Young-Rock Hong; Arch G Mainous
Journal:  Ann Fam Med       Date:  2020-07       Impact factor: 5.166

7.  Utility of socioeconomic status in predicting 30-day outcomes after heart failure hospitalization.

Authors:  Zubin J Eapen; Lisa A McCoy; Gregg C Fonarow; Clyde W Yancy; Marie Lynn Miranda; Eric D Peterson; Robert M Califf; Adrian F Hernandez
Journal:  Circ Heart Fail       Date:  2015-03-06       Impact factor: 8.790

8.  Impact of Socioeconomic Status on Patients Supported With a Left Ventricular Assist Device: An Analysis of the UNOS Database (United Network for Organ Sharing).

Authors:  Kevin J Clerkin; Arthur Reshad Garan; Brian Wayda; Raymond C Givens; Melana Yuzefpolskaya; Shunichi Nakagawa; Koji Takeda; Hiroo Takayama; Yoshifumi Naka; Donna M Mancini; Paolo C Colombo; Veli K Topkara
Journal:  Circ Heart Fail       Date:  2016-10       Impact factor: 8.790

9.  Hospital-Readmission Risk - Isolating Hospital Effects from Patient Effects.

Authors:  Harlan M Krumholz; Kun Wang; Zhenqiu Lin; Kumar Dharmarajan; Leora I Horwitz; Joseph S Ross; Elizabeth E Drye; Susannah M Bernheim; Sharon-Lise T Normand
Journal:  N Engl J Med       Date:  2017-09-14       Impact factor: 91.245

10.  Accounting For Patients' Socioeconomic Status Does Not Change Hospital Readmission Rates.

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

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