ArticleJournal of preventive medicine and public health = Yebang Uihakhoe chi2012
Selecting the best prediction model for readmission.
Article in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Utility of models to predict 28-day or 30-day unplanned hospital readmissions: an updated systematic review.BMJ open · 2016Pooled it
- Article
- Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach.BMC medical informatics and decision making · 2023Article
- Burden and patient characteristics associated with repeat consultation for unscheduled care within 30 days in primary care: a retrospective case control study with implications for aging and public health.Frontiers in public health · 2023Article
- An AI-driven clinical care pathway to reduce 30-day readmission for chronic obstructive pulmonary disease (COPD) patients.Scientific reports · 2022Article
- Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare.Patterns (New York, N.Y.) · 2022Article
- Article
- Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.Applied clinical informatics · 2020Article
- Risk Assessment of Acute, All-Cause 30-Day Readmission in Patients Aged 65+: a Nationwide, Register-Based Cohort Study.Journal of general internal medicine · 2019Article
- Development of a predictive score for potentially avoidable hospital readmissions for general internal medicine patients.PloS one · 2019Observational
- The association between number of doctors per bed and readmission of elderly patients with pneumonia in South Korea.BMC health services research · 2017Article
- Assessing risk of hospital readmissions for improving medical practice.Health care management science · 2016Article
- Emergency Department Non-Urgent Visits and Hospital Readmissions Are Associated with Different Socio-Economic Variables in Italy.PloS one · 2015Article
- A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study.BMC medical informatics and decision making · 2014Article
- Nationwide prospective study on readmission after umbilical or epigastric hernia repair.Hernia : the journal of hernias and abdominal wall surgery · 2013Article
- Data mining application in customer relationship management for hospital inpatients.Healthcare informatics research · 2012Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study aims to determine the risk factors predicting rehospitalization by comparing three models and selecting the most successful model.
methodsIn order to predict the risk of rehospitalization within 28 days after discharge, 11 951 inpatients were recruited into this study between January and December 2009. Predictive models were constructed with three methods, logistic regression analysis, a decision tree, and a neural network, and the models were compared and evaluated in light of their misclassification rate, root asymptotic standard error, lift chart, and receiver operating characteristic curve.
resultsThe decision tree was selected as the final model. The risk of rehospitalization was higher when the length of stay (LOS) was less than 2 days, route of admission was through the out-patient department (OPD), medical department was in internal medicine, 10th revision of the International Classification of Diseases code was neoplasm, LOS was relatively shorter, and the frequency of OPD visit was greater.
conclusionsWhen a patient is to be discharged within 2 days, the appropriateness of discharge should be considered, with special concern of undiscovered complications and co-morbidities. In particular, if the patient is admitted through the OPD, any suspected disease should be appropriately examined and prompt outcomes of tests should be secured. Moreover, for patients of internal medicine practitioners, co-morbidity and complications caused by chronic illness should be given greater attention.
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