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Using ethnographic methods to classify the human experience in medicine: a case study of the presence ontology.

Authors :
Maitra A
Kamdar MR
Zulman DM
Haverfield MC
Brown-Johnson C
Schwartz R
Israni ST
Verghese A
Musen MA
Source :
Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2021 Aug 13; Vol. 28 (9), pp. 1900-1909.
Publication Year :
2021

Abstract

Objective: Although social and environmental factors are central to provider-patient interactions, the data that reflect these factors can be incomplete, vague, and subjective. We sought to create a conceptual framework to describe and classify data about presence, the domain of interpersonal connection in medicine.<br />Methods: Our top-down approach for ontology development based on the concept of "relationality" included the following: 1) a broad survey of the social sciences literature and a systematic literature review of >20 000 articles around interpersonal connection in medicine, 2) relational ethnography of clinical encounters (nā€‰=ā€‰5 pilot, 27 full), and 3) interviews about relational work with 40 medical and nonmedical professionals. We formalized the model using the Web Ontology Language in the Protégé ontology editor. We iteratively evaluated and refined the Presence Ontology through manual expert review and automated annotation of literature.<br />Results and Discussion: The Presence Ontology facilitates the naming and classification of concepts that would otherwise be vague. Our model categorizes contributors to healthcare encounters and factors such as communication, emotions, tools, and environment. Ontology evaluation indicated that cognitive models (both patients' explanatory models and providers' caregiving approaches) influenced encounters and were subsequently incorporated. We show how ethnographic methods based in relationality can aid the representation of experiential concepts (eg, empathy, trust). Our ontology could support investigative methods to improve healthcare processes for both patients and healthcare providers, including annotation of videotaped encounters, development of clinical instruments to measure presence, or implementation of electronic health record-based reminders for providers.<br />Conclusion: The Presence Ontology provides a model for using ethnographic approaches to classify interpersonal data.<br /> (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Details

Language :
English
ISSN :
1527-974X
Volume :
28
Issue :
9
Database :
MEDLINE
Journal :
Journal of the American Medical Informatics Association : JAMIA
Publication Type :
Academic Journal
Accession number :
34151988
Full Text :
https://doi.org/10.1093/jamia/ocab091