ArticleBMC medical informatics and decision making2018
Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital.
Article in BMC medical informatics and decision making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.PloS one · 2024Pooled it
- Digital emergency routing: analysis of feasibility, utilization, and equity implications.Israel journal of health policy research · 2026Article
- A Four-Year Monocenter Epidemiological Analysis of 30-Day Unplanned Readmission Patients.Patient preference and adherence · 2026Article
- Risk factors for rehospitalization after trauma: a follow-up study.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Article
- The Impact of Weight Loss Prior to Hospital Readmission.Journal of clinical medicine · 2023Article
- Novel machine learning model for predicting multiple unplanned hospitalisations.BMJ health & care informatics · 2023Article
- Medical Admission Prediction Score (MAPS); a simple tool to predict medical admissions in the emergency department.PloS one · 2023Article
- Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions.EClinicalMedicine · 2022Article
- [Diagnostic value of sinus CT score combined with serum allergen sIgE for postoperative recurrence in patients with eosinophilic CRSwNP].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2022Article
- Development of Prediction Models for Unplanned Hospital Readmission within 30 Days Based on Common Data Model: A Feasibility Study.Methods of information in medicine · 2021Article
- Current Trends in Readmission Prediction: An Overview of Approaches.Arabian journal for science and engineering · 2021Article
- Can we predict early 7-day readmissions using a standard 30-day hospital readmission risk prediction model?BMC medical informatics and decision making · 2020Article
- A machine learning model for predicting risk of hospital readmission within 30 days of discharge: validated with LACE index and patient at risk of hospital readmission (PARR) model.Medical & biological engineering & computing · 2020Article
- Unplanned Readmission within 28 Days of Hospital Discharge in a Longitudinal Population-Based Cohort of Older Australian Women.International journal of environmental research and public health · 2020Article
- A Gradient Boosting Machine Learning Model for Predicting Early Mortality in the Emergency Department Triage: Devising a Nine-Point Triage Score.Journal of general internal medicine · 2020Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsA 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.
resultsThe 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.
conclusionsThis 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.
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