Literature DB >> 23938273

Hospital readmission rates: signal of failure or success?

Mauro Laudicella1, Paolo Li Donni, Peter C Smith.   

Abstract

Hospital readmission rates are increasingly used as signals of hospital performance and a basis for hospital reimbursement. However, their interpretation may be complicated by differential patient survival rates. If patient characteristics are not perfectly observable and hospitals differ in their mortality rates, then hospitals with low mortality rates are likely to have a larger share of un-observably sicker patients at risk of a readmission. Their performance on readmissions will then be underestimated. We examine hospitals' performance relaxing the assumption of independence between mortality and readmissions implicitly adopted in many empirical applications. We use data from the Hospital Episode Statistics on emergency admissions for fractured hip in 290,000 patients aged 65 and over from 2003 to 2008 in England. We find evidence of sample selection bias that affects inference from traditional models. We use a bivariate sample selection model to allow for the selection process and the dichotomous nature of the outcome variables.
Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  C50; Hip fractures; Hospital performance; I18; Mortality rates; Readmission rates; Sample selection

Mesh:

Year:  2013        PMID: 23938273     DOI: 10.1016/j.jhealeco.2013.06.004

Source DB:  PubMed          Journal:  J Health Econ        ISSN: 0167-6296            Impact factor:   3.883


  15 in total

1.  Is mortality readmissions bias a concern for readmission rates under the Hospital Readmissions Reduction Program?

Authors:  Irene Papanicolas; E John Orav; Ashish K Jha
Journal:  Health Serv Res       Date:  2020-01-26       Impact factor: 3.402

2.  Thirty-day hospital readmissions for adults with and without HIV infection.

Authors:  S A Berry; J A Fleishman; R D Moore; K A Gebo
Journal:  HIV Med       Date:  2015-07-14       Impact factor: 3.180

3.  Outcomes and inequalities in diabetes from 2004/2005 to 2011/2012: English longitudinal study.

Authors:  Robert Fleetcroft; Miqdad Asaria; Shehzad Ali; Richard Cookson
Journal:  Br J Gen Pract       Date:  2016-12-05       Impact factor: 5.386

4.  Risk factors for hospital re-presentation among older adults following fragility fractures: protocol for a systematic review.

Authors:  Saira A Mathew; Kristiann C Heesch; Elise Gane; Steven M McPhail
Journal:  Syst Rev       Date:  2015-07-11

5.  National trends in emergency readmission rates: a longitudinal analysis of administrative data for England between 2006 and 2016.

Authors:  Rocco Friebel; Katharina Hauck; Paul Aylin; Adam Steventon
Journal:  BMJ Open       Date:  2018-03-12       Impact factor: 2.692

6.  Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone.

Authors:  Laurent G Glance; Yue Li; Andrew W Dick
Journal:  BMC Health Serv Res       Date:  2017-05-05       Impact factor: 2.655

7.  What is the impact on the readmission ratio of taking into account readmissions to other hospitals? A cross-sectional study.

Authors:  Karin Hekkert; Ine Borghans; Sezgin Cihangir; Gert P Westert; Rudolf B Kool
Journal:  BMJ Open       Date:  2019-04-09       Impact factor: 2.692

8.  Prevalence, Reasons, and Predisposing Factors Associated with 30-day Hospital Readmissions in Poland.

Authors:  Jacek Kryś; Błażej Łyszczarz; Zofia Wyszkowska; Kornelia Kędziora-Kornatowska
Journal:  Int J Environ Res Public Health       Date:  2019-07-02       Impact factor: 3.390

9.  Readmission of older patients after hospital discharge for hip fracture: a multilevel approach.

Authors:  Fátima de Lima Paula; Geraldo Marcelo da Cunha; Iúri da Costa Leite; Rejane Sobrino Pinheiro; Joaquim Gonçalves Valente
Journal:  Rev Saude Publica       Date:  2016-05-03       Impact factor: 2.106

10.  Do Reduced Hospital Mortality Rates Lead to Increased Utilization of Inpatient Emergency Care? A Population-Based Cohort Study.

Authors:  Mauro Laudicella; Stephen Martin; Paolo Li Donni; Peter C Smith
Journal:  Health Serv Res       Date:  2017-09-14       Impact factor: 3.402

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