Literature DB >> 28986516

Mortality, readmission and length of stay have different relationships using hospital-level versus patient-level data: an example of the ecological fallacy affecting hospital performance indicators.

Stefanie N Hofstede1, Leti van Bodegom-Vos1, Dionne S Kringos2,3, Ewout Steyerberg4,5, Perla J Marang-van de Mheen1.   

Abstract

BACKGROUND: Ecological fallacy refers to an erroneous inference about individuals on the basis of findings for the group to which those individuals belong. Suppose analysis of a large database shows that hospitals with a high proportion of long length of stay (LOS) patients also have higher than average in-hospital mortality. This may prompt efforts to reduce mortality among patients with long LOS. But patients with long LOS may not be the ones at higher risk of death. It may be that hospitals with higher mortality (regardless of LOS) also have more long LOS patients-either because of quality problems on both counts or because of unaccounted differences in case mix. To provide more insight how the ecological fallacy influences the evaluation of hospital performance indicators, we assessed whether hospital-level associations between in-hospital mortality, readmission and long LOS reflect patient-level associations.
METHODS: Patient admissions from the Dutch National Medical Registration (2007-2012) for specific diseases (stroke, colorectal carcinoma, heart failure, acute myocardial infarction and hip/knee replacements in patients with osteoarthritis) were analysed, as well as all admissions. Logistic regression analysis was used to assess patient-level associations. Pearson correlation coefficients were used to quantify hospital-level associations.
RESULTS: Overall, we observed 2.2% in-hospital mortality, 8.1% readmissions and a mean LOS of 5.9 days among 8 478 884 admissions in 95 hospitals. Of the 10 disease-specific associations tested, 2 were reversed at hospital-level, 3 were consistent and 5 were only significant at either hospital-level or patient-level. A reversed association was found for stroke: patients with long LOS had 58% lower in-hospital mortality (OR 0.42 (95% CI 0.40 to 0.44)), whereas the hospital-level association was reversed (r=0.30, p<0.01). Similar negative patient-level associations were found for each hospital, but LOS varied across hospitals, thereby resulting in a positive hospital-level association. A similar effect was found for long LOS and readmission in patients with heart failure.
CONCLUSIONS: Hospital-level associations did not reflect the same patient-level associations in 7 of 10 associations, and were even reversed in 2 associations. Ecological fallacy thus potentially influences interpretation of hospital performance when patient-level associations are not taken into account. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  continuous quality improvement; healthcare quality improvement; mortality (standardized Mortality Ratios); quality measurement

Mesh:

Year:  2017        PMID: 28986516     DOI: 10.1136/bmjqs-2017-006776

Source DB:  PubMed          Journal:  BMJ Qual Saf        ISSN: 2044-5415            Impact factor:   7.035


  7 in total

1.  Evaluation of hospital outcomes: the relation between length-of-stay, readmission, and mortality in a large international administrative database.

Authors:  Hester F Lingsma; Alex Bottle; Steve Middleton; Job Kievit; Ewout W Steyerberg; Perla J Marang-van de Mheen
Journal:  BMC Health Serv Res       Date:  2018-02-14       Impact factor: 2.655

2.  Ranking hospital performance based on individual indicators: can we increase reliability by creating composite indicators?

Authors:  Peter C Austin; Iris E Ceyisakar; Ewout W Steyerberg; Hester F Lingsma; Perla J Marang-van de Mheen
Journal:  BMC Med Res Methodol       Date:  2019-06-26       Impact factor: 4.615

3.  Associations between hospital deaths (HSMR), readmission and length of stay (LOS): a longitudinal assessment of performance results and facility characteristics of teaching and large-sized hospitals in Canada between 2013-2014 and 2017-2018.

Authors:  Omid Fekri; Edgar Manukyan; Niek Klazinga
Journal:  BMJ Open       Date:  2021-02-05       Impact factor: 2.692

4.  Variation in incidence, prevention and treatment of persistent air leak after lung cancer surgery.

Authors:  Fieke Hoeijmakers; Koen J Hartemink; Ad F Verhagen; Willem H Steup; Elske Marra; W F Boudewijn Röell; David J Heineman; Wilhelmina H Schreurs; Rob A E M Tollenaar; Michel W J M Wouters
Journal:  Eur J Cardiothorac Surg       Date:  2021-12-27       Impact factor: 4.191

5.  Machine-learning based prediction of prognostic risk factors in patients with invasive candidiasis infection and bacterial bloodstream infection: a singled centered retrospective study.

Authors:  Yaling Li; Yutong Wu; Yali Gao; Xueli Niu; Jingyi Li; Mingsui Tang; Chang Fu; Ruiqun Qi; Bing Song; Hongduo Chen; Xinghua Gao; Ying Yang; Xiuhao Guan
Journal:  BMC Infect Dis       Date:  2022-02-13       Impact factor: 3.090

6.  Did case-based payment influence surgical readmission rates in France? A retrospective study.

Authors:  Albert Vuagnat; Engin Yilmaz; Adrien Roussot; Victor Rodwin; Maryse Gadreau; Alain Bernard; Catherine Creuzot-Garcher; Catherine Quantin
Journal:  BMJ Open       Date:  2018-02-01       Impact factor: 2.692

7.  The association between outcome-based quality indicators for intensive care units.

Authors:  Ilona W M Verburg; Evert de Jonge; Niels Peek; Nicolette F de Keizer
Journal:  PLoS One       Date:  2018-06-13       Impact factor: 3.240

  7 in total

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