Journal article
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, Vol.30(11), pp.1801-1810
11/2023
DOI: 10.1093/jamia/ocad101
PMCID: PMC10586044
PMID: 37339524
Abstract
OBJECTIVE This study aimed to identify temporal risk factor patterns documented in home health care (HHC) clinical notes and examine their association with hospitalizations or emergency department (ED) visits. MATERIALS AND METHODS Data for 73 350 episodes of care from one large HHC organization were analyzed using dynamic time warping and hierarchical clustering analysis to identify the temporal patterns of risk factors documented in clinical notes. The Omaha System nursing terminology represented risk factors. First, clinical characteristics were compared between clusters. Next, multivariate logistic regression was used to examine the association between clusters and risk for hospitalizations or ED visits. Omaha System domains corresponding to risk factors were analyzed and described in each cluster. RESULTS Six temporal clusters emerged, showing different patterns in how risk factors were documented over time. Patients with a steep increase in documented risk factors over time had a 3 times higher likelihood of hospitalization or ED visit than patients with no documented risk factors. Most risk factors belonged to the physiological domain, and only a few were in the environmental domain. DISCUSSION An analysis of risk factor trajectories reflects a patient's evolving health status during a HHC episode. Using standardized nursing terminology, this study provided new insights into the complex temporal dynamics of HHC, which may lead to improved patient outcomes through better treatment and management plans. CONCLUSION Incorporating temporal patterns in documented risk factors and their clusters into early warning systems may activate interventions to prevent hospitalizations or ED visits in HHC.
Details
- Title: Subtitle
- Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care
- Creators
- Jiyoun Song - Columbia UniversitySe Hee Min - Columbia UniversitySena Chae - University of IowaKathryn H Bowles - University of PennsylvaniaMargaret V McDonald - VNS HealthMollie Hobensack - Columbia UniversityYolanda Barrón - VNS HealthSridevi Sridharan - VNS HealthAnahita Davoudi - VNS HealthSungho Oh - University of PennsylvaniaLauren Evans - VNS HealthMaxim Topaz - Columbia University
- Resource Type
- Journal article
- Publication Details
- Journal of the American Medical Informatics Association : JAMIA, Vol.30(11), pp.1801-1810
- DOI
- 10.1093/jamia/ocad101
- PMID
- 37339524
- PMCID
- PMC10586044
- NLM abbreviation
- J Am Med Inform Assoc
- ISSN
- 1067-5027
- eISSN
- 1527-974X
- Grant note
- DOI: 10.13039/100000133, name: Agency for Healthcare Research and Quality, award: R01 HS027742; DOI: 10.13039/100000056, name: National Institute of Nursing Research; name: Reducing Health Disparities through Informatics, award: T32NR007969; DOI: 10.13039/100000056, name: NINR, award: T32NR007969; name: Care for At Risk Older Adults, award: T32NR009356
- Language
- English
- Electronic publication date
- 06/20/2023
- Date published
- 11/2023
- Academic Unit
- Nursing
- Record Identifier
- 9984436279402771
Metrics
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