Observational studyBMJ open quality2019
Development of a prediction model for 30-day acute readmissions among older medical patients: the influence of social factors along with other patient-specific and organisational factors.
Observational study in BMJ open quality, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk Factors for Early Hospital Readmission in Geriatric Patients: A Systematic Review.International journal of environmental research and public health · 2023Pooled it
- Trial
- Cognitive impairment and hospital admission risk among community-dwelling adults in the MAUCO cohort.Annals of medicine · 2026Article
- The C-Reactive Protein/Albumin Ratio Predicts In-Hospital Mortality Across Age Groups.Nutrients · 2026Article
- Risk factors for frequent unplanned hospital visits in older multimorbid patients after an emergency department visit: a retrospective cohort study.Aging clinical and experimental research · 2025Article
- Predictors of Functional Improvement, Length of Stay, and Discharge Destination in the Context of an Assess and Restore Program in Hospitalized Older Adults.Geriatrics (Basel, Switzerland) · 2022Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Readmission rate is one way to measure quality of care for older patients. Knowledge is sparse on how different social factors can contribute to predict readmission. We aimed to develop and internally validate a comprehensive model for prediction of acute 30-day readmission among older medical patients using various social factors along with demographic, organisational and health-related factors. Methods: We performed an observational prospective study based on a group of 770 medical patients aged 65 years or older, who were consecutively screened for readmission risk factors at an acute care university hospital during the period from February to September 2012. Data on outcome and candidate predictors were obtained from clinical screening and administrative registers. We used multiple logistic regression analyses with backward selection of predictors. Measures of model performance and performed internal validation were calculated. Results: Twenty percent of patients were readmitted within 30 days from index discharge. The final model showed that low educational level, along with male gender, contact with emergency doctor, specific diagnosis, higher Charlson Comorbidity Index score, longer hospital stay, cognitive problems, and medical treatment for thyroid disease, acid-related disorders, and glaucoma, predicted acute 30-day readmission. Area under the receiver operating characteristic curve (0.70) indicated acceptable discriminative ability of the model. Calibration slope was 0.98 and calibration intercept was 0.01. In internal validation analysis, both discrimination and calibration measures were stable. Conclusions: We developed a model for prediction of readmission among older medical patients. The model showed that social factors in the form of educational level along with demographic, organisational and health-related factors contributed to prediction of acute 30-day readmissions among older medical patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.