ArticleJournal of the American Medical Informatics Association : JAMIA2022
Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians.
Article in Journal of the American Medical Informatics Association : JAMIA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- An AI-Enabled Nursing Future With no Documentation Burden: A Vision for a New Reality.Journal of advanced nursing · 2026Article
- From Conversation to Standardized Terminology: An LLM-RAG Approach for Automated Health Problem Identification in Home Healthcare.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
- Adverse Social Determinants of Health and Urinary Incontinence Among Older Adult Women in Home Health Care.Journal of the American Medical Directors Association · 2025Article
- Article
- Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
- Exploring Natural Language Processing through an Exemplar Using YouTube.International journal of environmental research and public health · 2024Article
- Interventional analytics in skilled nursing facilities associated with reduced readmissions.The American journal of managed care · 2024Article
- Natural Language Processing Applied to Clinical Documentation in Post-acute Care Settings: A Scoping Review.Journal of the American Medical Directors Association · 2024Article
- Social Risk Factors are Associated with Risk for Hospitalization in Home Health Care: A Natural Language Processing Study.Journal of the American Medical Directors Association · 2023Article
- Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Machine learning applied to electronic health record data in home healthcare: A scoping review.International journal of medical informatics · 2023Article
- Capturing Concerns about Patient Deterioration in Narrative Documentation in Home Healthcare.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
objectiveTo identify the risk factors home healthcare (HHC) clinicians associate with patient deterioration and understand how clinicians respond to and document these risk factors.
methodsWe interviewed multidisciplinary HHC clinicians from January to March of 2021. Risk factors were mapped to standardized terminologies (eg, Omaha System). We used directed content analysis to identify risk factors for deterioration. We used inductive thematic analysis to understand HHC clinicians' response to risk factors and documentation of risk factors.
resultsFifteen HHC clinicians identified a total of 79 risk factors that were mapped to standardized terminologies. HHC clinicians most frequently responded to risk factors by communicating with the prescribing provider (86.7% of clinicians) or following up with patients and caregivers (86.7%). HHC clinicians stated that a majority of risk factors can be found in clinical notes (ie, care coordination (53.3%) or visit (46.7%)). DISCUSSION: Clinicians acknowledged that social factors play a role in deterioration risk; but these factors are infrequently studied in HHC. While a majority of risk factors were represented in the Omaha System, additional terminologies are needed to comprehensively capture risk. Since most risk factors are documented in clinical notes, methods such as natural language processing are needed to extract them.
conclusionThis study engaged clinicians to understand risk for deterioration during HHC. The results of our study support the development of an early warning system by providing a comprehensive list of risk factors grounded in clinician expertize and mapped to standardized terminologies.
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