ArticleJournal of the American Medical Directors Association2019
Risk of 30-Day Hospital Readmission Among Patients Discharged to Skilled Nursing Facilities: Development and Validation of a Risk-Prediction Model.
Article in Journal of the American Medical Directors Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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
10 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
- A new simplified minimum data set better predicts outcomes for individuals admitted to intermediate care functional recovery units in catalonia.The Journal of frailty & aging · 2026Article
- A Multi-Outcome Prognostic Model for Community-Dwelling Older Adults Admitted to Skilled Nursing Facilities for Post-Acute Care.Journal of the American Medical Directors Association · 2025Article
- Postoperative Discharge Destination Impacts 30-Day Outcomes: A National Surgical Quality Improvement Program Multi-Specialty Surgical Cohort Analysis.Journal of clinical medicine · 2023Article
- Dementia Care in the Last Year of Life: Experiences in a Community Practice and in Skilled Nursing Facilities.Journal of palliative care · 2023Article
- Risk Prediction Model for 6-Month Mortality for Patients Discharged to Skilled Nursing Facilities.Journal of the American Medical Directors Association · 2022Article
- Telehealth Use and Hospital Readmission Rates in Long-term Care Facilities in Southeastern Minnesota During the COVID-19 Pandemic.Mayo Clinic proceedings. Innovations, quality & outcomes · 2022Article
- Outcomes of a Nursing Home-to-Community Care Transition Program.Journal of the American Medical Directors Association · 2021Article
- Current Trends in Readmission Prediction: An Overview of Approaches.Arabian journal for science and engineering · 2021Article
- Application of machine learning in predicting hospital readmissions: a scoping review of the literature.BMC medical research methodology · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectivesPatients discharged to a skilled nursing facility (SNF) for post-acute care have a high risk of hospital readmission. We aimed to develop and validate a risk-prediction model to prospectively quantify the risk of 30-day hospital readmission at the time of discharge to a SNF.
designRetrospective cohort study.
settingTen independent SNFs affiliated with the post-acute care practice of an integrated health care delivery system.
participantsWe evaluated 6032 patients who were discharged to SNFs for post-acute care after hospitalization. MEASUREMENTS: The primary outcome was all-cause 30-day hospital readmission. Patient demographics, medical comorbidity, prior use of health care, and clinical parameters during the index hospitalization were analyzed by using gradient boosting machine multivariable analysis to build a predictive model for 30-day hospital readmission. Area under the receiver operating characteristic curve (AUC) was assessed on out-of-sample observations under 10-fold cross-validation.
resultsAmong 8616 discharges to SNFs from January 1, 2009, through June 30, 2014, a total of 1568 (18.2%) were readmitted to the hospital within 30 days. The 30-day hospital readmission prediction model had an AUC of 0.69, a 16% improvement over risk assessment using the Charlson Comorbidity Index alone. The final model included length of stay, abnormal laboratory parameters, and need for intensive care during the index hospitalization; comorbid status; and number of emergency department and hospital visits within the preceding 6 months. CONCLUSIONS AND IMPLICATIONS: We developed and validated a risk-prediction model for 30-day hospital readmission in patients discharged to a SNF for post-acute care. This prediction tool can be used to risk stratify the complex population of hospitalized patients who are discharged to SNFs to prioritize interventions and potentially improve the quality, safety, and cost-effectiveness of care.
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