Using ethnographic methods to classify the human experience in medicine: a case study of the presence ontology - PubMed (original) (raw)
Using ethnographic methods to classify the human experience in medicine: a case study of the presence ontology
Amrapali Maitra et al. J Am Med Inform Assoc. 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.
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 (n = 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.
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.
Conclusion: The Presence Ontology provides a model for using ethnographic approaches to classify interpersonal data.
Keywords: communication; electronic health record; ethnographic methods; interpersonal; ontology.
© 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.
Figures
Figure 1.
Conceptual model for clinical observations to develop Presence relational ethnography. The model depicts the conceptual hierarchy for themes related to the clinical encounter. The model was developed through literature survey and expert review and finalized prior to conducting the relational ethnography. Presence research team members were trained using this model in order to structure fieldnotes for observed patient–physician encounters (n =27) using a rapid ethnography approach. At the core is the clinical ritual, upon which is layered interpersonal interaction (with attention to verbal and nonverbal communication, timing, and silence), then individual identity features of both the clinician and patient, structural and systems-level features such as clinic resources or wait time, and finally the environmental milieu within which encounters occur. Additional elements that mediate the encounter include power dynamics, care team members, the patient’s family and friends, technology, tools, and touch.
Figure 2.
Class diagram of the Presence Ontology elaborating upper-level class hierarchies and object properties. Each colored box indicates an upper-level class (eg, “Factor”), with subsequent inner boxes depicting the hierarchy under the upper-level class (eg, “Patient History” is a subclass of “Factor,” and in turn “Family History” is a subclass of “Patient History”). Different classes are connected using object properties in the Presence Ontology. For example, the object property “performs” associates the class “Person” with the class “Action” (an individual under the class “Person,” whether a “Patient” or a “Provider,” will perform some “Action”); whereas, the object property “hasCharacteristic” associates the class “Person” with the class “Characteristic” (an individual under the class “Person” has at least 1 “Characteristic,” such as “Age,” “Occupation,” “Race,” etc). For simplicity, we have only shown the most relevant classes in this class diagram and refer the reader to explore the Presence Ontology in the BioPortal repository for more information around the class hierarchies and the object properties.
Figure 3.
Concepts from the Presence Ontology that were most commonly identified in the 77 abstracts related to Presence literature. The X-axis in this histogram showcases the 20 most commonly identified concepts from the Presence Ontology in the Presence literature. Each red bar in the histogram indicates the total number of abstracts in which the represented concept is mentioned; whereas, each blue bar indicates the total number of Presence concepts that co-occur with the represented concept in these abstracts. The importance of patient-centric concepts in our approach broadens the focus from providers as drivers of human experience in medicine toward a relational framework for presence, the direct outcome of our ethnographic methods for ontology development.
Figure 4.
Co-occurrence network for the concept of “stress” generated from the identification of Presence concepts in literature. The concept of “stress” from the Presence Ontology generally co-occurs with common concepts of “patient” or “physician” but also with concepts such as “empathy,” “anger,” “trust,” etc. The size and the color of the nodes is indicative of the number of abstracts in which the presence concept is identified, and the thickness of the connecting edges between 2 nodes is indicative of the number of abstracts in which the connected concepts co-occur together.
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