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Predictive risk score for unplanned 30-day rehospitalizations in the French universal health care system based on a medico-administrative database.

Authors :
Pauly, Vanessa
Mendizabal, Hélène
Gentile, Stéphanie
Auquier, Pascal
Boyer, Laurent
Source :
PLoS ONE. 3/12/2019, Vol. 14 Issue 3, p1-17. 17p.
Publication Year :
2019

Abstract

Background: Reducing unplanned rehospitalizations is one of the priorities of health care policies in France and other Western countries. An easy-to-use algorithm for identifying patients at higher risk of rehospitalizations would help clinicians prioritize actions and care concerning discharge transitions. Our objective was to develop a predictive unplanned 30-day all-cause rehospitalization risk score based on the French hospital medico-administrative database. Methods: This was a retrospective cohort study of all 2015 discharges from acute-care inpatient hospitalizations in a tertiary-care university center comprising four hospitals. The study endpoint was unplanned 30-day all-cause rehospitalization via emergency departments, and we collected sociodemographic, clinical, and hospital characteristics based on hospitalization database computed for reimbursement of fees. We derived a predictive rehospitalization risk score using a split-sample design and multivariate logistic regression, and we compared the discriminative properties with the LACE index risk-score. Result: Our analysis included 118,650 hospitalizations, of which 4,127 (3.5%) led to rehospitalizations via emergency departments. Variables independently associated with rehospitalization were age, gender, state-funded medical assistance, as well as disease category and severity, Charlson comorbidity index, hospitalization via emergency departments, length of stay (LOS), and previous hospitalizations 6 months before. The predictive rehospitalization risk score yielded satisfactory discriminant properties (C statistic: 0.74) exceeding the LACE index (0.66). Conclusion: Our findings indicate that the possibility of unplanned rehospitalization remains high for some patient characteristics, indicating that targeted interventions could be beneficial for patients at the greatest risk. We developed an easy-to-use predictive rehospitalization risk-score of unplanned 30-day all-cause rehospitalizations with satisfactory discriminant properties. Future works should, however, explore if other data from electronic medical records and other databases could improve the accuracy of our predictive rehospitalization risk score based on medico-administrative data. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*MEDICAL databases
*MEDICAL care

Details

Language :
English
ISSN :
19326203
Volume :
14
Issue :
3
Database :
Academic Search Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
135249488
Full Text :
https://doi.org/10.1371/journal.pone.0210714