Using Ethnographic Methods to Classify the Human Experience in Medicine: A Case Study of the Presence Ontology

05/15/2021
by   Amrapali Maitra, et al.
0

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 1) broad survey of social sciences literature and systematic literature review of more than 20,000 articles around interpersonal connection in medicine, 3) relational ethnography of clinical encounters (5 pilot, 27 full) and 4) interviews about relational work with 40 medical and nonmedical professionals. We formalized the model using the Web Ontology Language in the Protege 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 (e.g., empathy, trust). Our ontology could support informatics applications to improve healthcare such annotation of videotaped encounters, clinical instruments to measure presence, or EHR based reminders for providers. Conclusion The Presence Ontology provides a model for using ethnographic approaches to classify interpersonal data.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 5

page 7

page 9

09/02/2020

CODO: An Ontology for Collection and Analysis of Covid-19 Data

The COviD-19 Ontology for cases and patient information (CODO) provides ...
09/22/2016

Towards Evidence-Based Ontology for Supporting Systematic Literature Review

[Background]: Systematic Literature Review (SLR) has become an important...
09/23/2021

Models for Narrative Information: A Study

The major objective of this work is to study and report the existing ont...
04/14/2020

Multi-Ontology Refined Embeddings (MORE): A Hybrid Multi-Ontology and Corpus-based Semantic Representation for Biomedical Concepts

Objective: Currently, a major limitation for natural language processing...
01/19/2017

CEVO: Comprehensive EVent Ontology Enhancing Cognitive Annotation

While the general analysis of named entities has received substantial re...
05/09/2016

Machine Learning Techniques with Ontology for Subjective Answer Evaluation

Computerized Evaluation of English Essays is performed using Machine lea...
02/05/2019

CMS Sematrix: A Tool to Aid the Development of Clinical Quality Measures (CQMs)

As part of the effort to improve quality and to reduce national healthca...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.