Documentation of hospitalization risk factors in electronic health records (EHRs): a qualitative study with home healthcare clinicians

• Published in: Journal of the American Medical Informatics Association : JAMIA 2022-04, Vol.29 (5), p.805-812
• Main Authors: Hobensack, Mollie, Ojo, Marietta, Barrón, Yolanda, Bowles, Kathryn H, Cato, Kenrick, Chae, Sena, Kennedy, Erin, McDonald, Margaret V, Rossetti, Sarah Collins, Song, Jiyoun, Sridharan, Sridevi, Topaz, Maxim
• Format: Article
• Language: English
• Subjects: Delivery of Health Care; Documentation; Electronic Health Records; Home Care Services; Hospitalization; Humans; Research and Applications; Risk Factors
• ISSN: 1527-974X; 1067-5027; 1527-974X
• DOI: 10.1093/jamia/ocac023

Abstract Objective To identify the risk factors home healthcare (HHC) clinicians associate with patient deterioration and understand how clinicians respond to and document these risk factors. Methods 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. Results 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%)). 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. Conclusion 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.