ArticleInternational journal of telemedicine and applications2013
Assessing hospital readmission risk factors in heart failure patients enrolled in a telemonitoring program.
Article in International journal of telemedicine and applications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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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
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Evaluating risk prediction models for adults with heart failure: A systematic literature review.PloS one · 2020Pooled it
- Utility of models to predict 28-day or 30-day unplanned hospital readmissions: an updated systematic review.BMJ open · 2016Pooled it
- Digitalization of prevention and treatment and the combination of western and Chinese medicine in management of acute heart failure.Frontiers in cardiovascular medicine · 2023Review
- Predictors of readmission in hospitalized heart failure patients.Journal of cardiovascular and thoracic research · 2022Article
- Article
- Digital Health Applications in Heart Failure: a Critical Appraisal of Literature.Current treatment options in cardiovascular medicine · 2021Review
- Impact on Readmission Reduction Among Heart Failure Patients Using Digital Health Monitoring: Feasibility and Adoptability Study.JMIR medical informatics · 2019Article
- "Future Patient" Telerehabilitation for Patients With Heart Failure: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2019Article
- Intercycle Unplanned Hospital Admissions Due to Cisplatin-based Chemotherapy Regimen-induced Adverse Reactions: A Retrospective Analysis.Current drug safety · 2019Article
- Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision.Yearbook of medical informatics · 2016Review
- 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
- An AI-Enabled, Patient-Centred Digital Platform for Integrated Chronic Heart Failure Management: Architecture, Validation and Clinical Insights.Healthcare technology lettersArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on psychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the impact of weight fluctuations and other factors on hospital readmission. Clinical, demographic, and telemonitoring data was collected from 100 patients enrolled in the Partners Connected Cardiac Care Program between July 2008 and November 2011. 38% of study participants were readmitted to the hospital within 30 days. Ten different heart-failure-related symptoms were reported 17,389 times, with the top three contributing approximately 50% of the volume. The psychosocial readmission model yielded an AUC of 0.67, along with sensitivity 0.87, specificity 0.32, positive predictive value 0.44, and negative predictive value 0.8 at a cutoff value of 0.30. In summary, hospital readmission models based on psychosocial characteristics, standardized changes in weight, or patient-reported symptoms can be developed and validated in heart failure patients participating in an institutional telemonitoring program. However, more robust models will need to be developed that use a comprehensive set of factors in order to have a significant impact on population health.
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Registered trials
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