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. 2018 Jan 4;18(1):1.
doi: 10.1186/s12911-017-0580-8.

Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital

Yashar Maali  1 , Oscar Perez-Concha  1   2 , Enrico Coiera  1 , David Roffe  3 , Richard O Day  4   5 , Blanca Gallego  6
Affiliations

Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital

Yashar Maali et al. BMC Med Inform Decis Mak. .

Abstract

Background: The identification of patients at high risk of unplanned readmission is an important component of discharge planning strategies aimed at preventing unwanted returns to hospital. The aim of this study was to investigate the factors associated with unplanned readmission in a Sydney hospital. We developed and compared validated readmission risk scores using routinely collected hospital data to predict 7-day, 30-day and 60-day all-cause unplanned readmission.

Methods: A combination of gradient boosted tree algorithms for variable selection and logistic regression models was used to build and validate readmission risk scores using medical records from 62,235 live discharges from a metropolitan hospital in Sydney, Australia.

Results: The scores had good calibration and fair discriminative performance with c-statistic of 0.71 for 7-day and for 30-day readmission, and 0.74 for 60-day. Previous history of healthcare utilization, urgency of the index admission, old age, comorbidities related to cancer, psychosis, and drug-abuse, abnormal pathology results at discharge, and being unmarried and a public patient were found to be important predictors in all models. Unplanned readmissions beyond 7 days were more strongly associated with longer hospital stays and older patients with higher number of comorbidities and higher use of acute care in the past year.

Conclusions: This study demonstrates similar predictors and performance to previous risk scores of 30-day unplanned readmission. Shorter-term readmissions may have different causal pathways than 30-day readmission, and may, therefore, require different screening tools and interventions. This study also re-iterates the need to include more informative data elements to ensure the appropriateness of these risk scores in clinical practice.

Keywords: Hospital readmission; Readmission risk scores.

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Conflict of interest statement

Ethics approval and consent to participate

Ethics approval was obtained from New South Wales Population and Health Services Research Ethics Committee and the hospital’s Ethics Committee (HREC/13/CIPHS/29). The need for consent from the participants was waived by the ethics committee due to the retrospective nature of the analysis.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Summary of patients discharged and readmitted over three overlapping periods: 7-days, 30-days and 60-days postdischarge
Fig. 2
Fig. 2
Left panel: Number of planned and unplanned readmissions per 1000 live discharges, per day up to 30 days post-discharge. Right panel: Number of unplanned readmissions per 1000 live discharges, per day up to 30 days post-discharge to the same hospital, other hospitals within the same area health services (AHS) and other hospital in other AHS. Here readmission refers only to the first readmission after discharge. Subsequent readmissions by the same patient have been ignored
Fig. 3
Fig. 3
Distribution of selected features characterizing index admissions that are followed by unplanned readmission within 7 days from discharge or unplanned readmission between 8 and 30 days from discharge. Selected features are those for which the difference in proportions is statistically significant. LOS = Length of Stay; CumLOS=Cummulative LOS; ED = Emergency Department; Emergency/Mobile ward refers to Emergency ward or mobile acute treatment units
See this image and copyright information in PMC

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