Observational studyJournal of hospital medicine2016
Predicting all-cause readmissions using electronic health record data from the entire hospitalization: Model development and comparison.
Observational study in Journal of hospital medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 78 citations in OpenAlex.
- Use of electronic medical records in development and validation of risk prediction models of hospital readmission: systematic review.BMJ (Clinical research ed.) · 2020Pooled it
- Predicting the Risk of Readmission in Pneumonia. A Systematic Review of Model Performance.Annals of the American Thoracic Society · 2016Pooled it
- A Machine Learning Approach for Predicting 30-Day Hospital Readmission in Patients with Diabetes.Healthcare (Basel, Switzerland) · 2026Article
- Validation of 30-Day Pediatric Hospital Readmission Risk Prediction Models.JAMA network open · 2025Article
- Acquisition of patients' EHR information under ED congestion - an empirical investigation.Health systems (Basingstoke, England) · 2025Review
- Survival models and longitudinal medical events for hospital readmission forecasting.BMC health services research · 2024Article
- Article
- Medications and Patient Factors Associated With Increased Readmission for Alcohol-Related Diagnoses.Mayo Clinic proceedings. Innovations, quality & outcomes · 2022Article
- Applying Hospital Readmissions to Oncology: A Square Peg in a Round Hole?JCO oncology practice · 2022Article
- Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital.Frontiers in pharmacology · 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
- Prior Frequent Emergency Department Use as a Predictor of Emergency Department Visits After a New Cancer Diagnosis.JCO oncology practice · 2021Article
- Man vs. Machine: Comparing Physician vs. Electronic Health Record-Based Model Predictions for 30-Day Hospital Readmissions.Journal of general internal medicine · 2021Article
- Implementing an Individual-Centric Discharge Process across Singapore Public Hospitals.International journal of environmental research and public health · 2021Article
- Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study.International journal of clinical practice · 2021Article
- Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.Medicine · 2020Observational
- Predicting Unplanned Readmissions Following a Hip or Knee Arthroplasty: Retrospective Observational Study.JMIR medical informatics · 2020Article
- Comparative effectiveness of long-term acute care hospital versus skilled nursing facility transfer.BMC health services research · 2020Article
- Can we predict early 7-day readmissions using a standard 30-day hospital readmission risk prediction model?BMC medical informatics and decision making · 2020Article
- Implementation and Continuous Monitoring of an Electronic Health Record Embedded Readmissions Clinical Decision Support Tool.Journal of personalized medicine · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundIncorporating clinical information from the full hospital course may improve prediction of 30-day readmissions.
objectiveTo develop an all-cause readmissions risk-prediction model incorporating electronic health record (EHR) data from the full hospital stay, and to compare "full-stay" model performance to a "first day" and 2 other validated models, LACE (includes Length of stay, Acute [nonelective] admission status, Charlson Comorbidity Index, and Emergency department visits in the past year), and HOSPITAL (includes Hemoglobin at discharge, discharge from Oncology service, Sodium level at discharge, Procedure during index hospitalization, Index hospitalization Type [nonelective], number of Admissions in the past year, and Length of stay).
designObservational cohort study. SUBJECTS: All medicine discharges between November 2009 and October 2010 from 6 hospitals in North Texas, including safety net, teaching, and nonteaching sites. MEASURES: Thirty-day nonelective readmissions were ascertained from 75 regional hospitals.
resultsAmong 32,922 admissions (validation = 16,430), 12.7% were readmitted. In addition to many first-day factors, we identified hospital-acquired Clostridium difficile infection (adjusted odds ratio [AOR]: 2.03, 95% confidence interval [CI]: 1.18-3.48), vital sign instability on discharge (AOR: 1.25, 95% CI: 1.15-1.36), hyponatremia on discharge (AOR: 1.34, 95% CI: 1.18-1.51), and length of stay (AOR: 1.06, 95% CI: 1.04-1.07) as significant predictors. The full-stay model had better discrimination than other models though the improvement was modest (C statistic 0.69 vs 0.64-0.67). It was also modestly better in identifying patients at highest risk for readmission (likelihood ratio +2.4 vs. 1.8-2.1) and in reclassifying individuals (net reclassification index 0.02-0.06).
conclusionsIncorporating clinically granular EHR data from the full hospital stay modestly improves prediction of 30-day readmissions. Given limited improvement in prediction despite incorporation of data on hospital complications, clinical instabilities, and trajectory, our findings suggest that many factors influencing readmissions remain unaccounted for. Further improvements in readmission models will likely require accounting for psychosocial and behavioral factors not currently captured by EHRs. Journal of Hospital Medicine 2016;11:473-480. © 2016 Society of Hospital Medicine.
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Registered trials
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