ArticleApplied clinical informatics2012
Exploring the value of clinical data standards to predict hospitalization of home care patients.
Article in Applied clinical informatics, 2012. 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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Urinary tract infection-related hospitalization among older adults receiving home health care.American journal of infection control · 2019Article
- Transitions From Skilled Nursing Facility to Home: The Relationship of Early Outpatient Care to Hospital Readmission.Journal of the American Medical Directors Association · 2017Article
- Risk Factors for All-Cause Rehospitalization Among Medicare Recipients with Heart Failure Receiving Telehomecare.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2017Article
- Utilizing Home Healthcare Electronic Health Records for Telehomecare Patients With Heart Failure: A Decision Tree Approach to Detect Associations With Rehospitalizations.Computers, informatics, nursing : CIN · 2016Article
- Activities of Daily Living of Home Healthcare Patients.Home healthcare nowArticle
- Detecting Language Associated With Home Healthcare Patient's Risk for Hospitalization and Emergency Department Visit.Nursing researchArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a critical need to reduce hospitalizations for Medicare patients and electronic health record (EHR) home care data provide new opportunities to evaluate risk of hospitalization for patients.
objectivesThe objectives of this study were to 1) develop a measure to predict risk of hospitalization among home care patients, the Hospitalization Risk Score (HRS), and 2) compare it with an existing severity of illness measure, the Charlson Index of Comorbidity (CIC).
methodsA convenience sample of clinical data from 14 home care agencies' EHRs, representing 1,643 home care patient episodes was used for the study. The development of the HRS was based on review of the literature, and expert panel evaluation to construct the HRS. Descriptive statistics and generalized linear models were used for comparative analysis; areas under curve (AUC) values were compared for receiver operating curves (ROC), and cut points predicting hospitalization were evaluated.
resultsThe HRS for this sample ranged from 0 to 5.6, with a median of 1.25. The CIC for this sample ranged from 0 to 9 and with a median of 0. Nearly three fourths of the sample was hospitalized at an HRS of 2, and a CIC of 1. AUC values for ROC were 0.63 for HRS and 0.59 for the CIC. The ROC curves were significantly different (t = -7.59, p <0.003).
conclusionsThis preliminary study demonstrates the potential value of the HRS using Omaha System EHR data. There was a statistically significant difference for predicting hospitalization of home care patients with the HRS versus the CIC; however the AUC values for both were low. Continued research is needed to further refine the HRS, determine whether it is more sensitive for particular subgroups of patients, and combine it with additional risk factors in understanding rehospitalization.
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