Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians.
Omaha System
electronic health record
home health
natural language processing
nursing informatics
qualitative
Journal
Journal of the American Medical Informatics Association : JAMIA
ISSN: 1527-974X
Titre abrégé: J Am Med Inform Assoc
Pays: England
ID NLM: 9430800
Informations de publication
Date de publication:
13 04 2022
13 04 2022
Historique:
received:
05
10
2021
accepted:
08
02
2022
pubmed:
24
2
2022
medline:
16
4
2022
entrez:
23
2
2022
Statut:
ppublish
Résumé
To identify the risk factors home healthcare (HHC) clinicians associate with patient deterioration and understand how clinicians respond to and document these risk factors. We 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. Fifteen 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%)). 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. This 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.
Identifiants
pubmed: 35196369
pii: 6535163
doi: 10.1093/jamia/ocac023
pmc: PMC9006696
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
805-812Subventions
Organisme : NINR NIH HHS
ID : F31 NR019919
Pays : United States
Organisme : AHRQ HHS
ID : R01 HS027742
Pays : United States
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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