Utility Of Models To Predict 28-day Or 30-day Unplanned Hospital Readmissions: An Updated Systematic Review

Authors:Huaqiong Zhou,Phillip R Della,Pamela Roberts,Louise Goh, Satvinder S Dhaliwal

Abstract:

Objective

To update previous systematic review of predictive models for 28-day or 30-day unplanned hospital readmissions.

Design

Systematic review.

Setting/data source

CINAHL, Embase, MEDLINE from 2011 to 2015.

Participants

All studies of 28-day and 30-day readmission predictive model.

Outcome measures

Characteristics of the included studies, performance of the identified predictive models and key predictive variables included in the models.

Results  Of 7310 records, a total of 60 studies with 73 unique predictive models met the inclusion criteria. The utilisation outcome of the models included all-cause readmissions, cardiovascular disease including pneumonia, medical conditions, surgical conditions and mental health condition-related readmissions. Overall, a wide-range C-statistic was reported in 56/60 studies (0.21–0.88). 11 of 13 predictive models for medical condition-related readmissions were found to have consistent moderate discrimination ability (C-statistic ≥0.7). Only two models were designed for the potentially preventable/avoidable readmissions and had C-statistic >0.8. The variables ‘comorbidities’, ‘length of stay’ and ‘previous admissions’ were frequently cited across 73 models. The variables ‘laboratory tests’ and ‘medication’ had more weight in the models for cardiovascular disease and medical condition-related readmissions.

Conclusions

The predictive models which focused on general medical condition-related unplanned hospital readmissions reported moderate discriminative ability. Two models for potentially preventable/avoidable readmissions showed high discriminative ability. This updated systematic review, however, found inconsistent performance across the included unique 73 risk predictive models. It is critical to define clearly the utilisation outcomes and the type of accessible data source before the selection of the predictive model. Rigorous validation of the predictive models with moderate-to-high discriminative ability is essential, especially for the two models for the potentially preventable/avoidable readmissions. Given the limited available evidence, the development of a predictive model specifically for paediatric 28-day all-cause, unplanned hospital readmissions is a high priority.

Citation: Huaqiong Zhou,Phillip R Della,Pamela Roberts,Louise Goh, Satvinder S Dhaliwal Utility Of Models To Predict 28-day Or 30-day Unplanned Hospital Readmissions: An Updated Systematic Review
BMJ Open 2016;6:e011060 doi:10.1136/bmjopen-2016-011060

Received 7 January 2016 Revised 17 May 2016 Accepted 23 May 2016 Published 27 June 2016

Copyright : This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.

Contributors

HZ, SD and PD contributed to the design of the review. HZ, SD, PD and LG acquired the data. HZ, SD, PD, PR and LG contributed to analysis. HZ wrote the draft. HZ, SD, PR and PD critically revised the intellectual content of this work.

Funding

This study is funded by a grant from the Australian Research Council—ARC Linkage Grant (Project ID: LP140100563). HZ is also supported by the Academic Research Grant from the Nursing and Midwifery Office, Western Australia Department of Health.

Competing interests

None declared.