Back to Search Start Over

Utilization of BPM+ Health for the Representation of Clinical Knowledge: A Framework for the Expression and Assessment of Clinical Practice Guidelines (CPG) Utilizing Existing and Emerging Object Management Group (OMG) Standards.

Authors :
Lario R
Hasley S
White SA
Eilbeck K
Soley R
Huff S
Kawamoto K
Source :
AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2021 Jan 25; Vol. 2020, pp. 687-696. Date of Electronic Publication: 2021 Jan 25 (Print Publication: 2020).
Publication Year :
2021

Abstract

Clinical Practice Guidelines (CPG), meant to express best practices in healthcare, are commonly presented as narrative documents communicating care processes, decision making, and clinical case knowledge. However, these narratives in and of themselves lack the specificity and conciseness in their use of language to unambiguously express quality clinical recommendations. This impacts the confidence of clinicians, uptake, and implementation of the guidance. As important as the quality of the clinical knowledge articulated, is the quality of the language(s) and methods used to express the recommendations. In this paper, we propose the BPM+ family of modeling languages as a potential solution to this challenge. We present a formalized process and framework for translating CPGs into a standardized BPM+ model. Further, we discuss the features and characteristics of modeling languages that underpin the quality in expressing clinical recommendations. Using an existing CPG, we defined a systematic series of steps to deconstruct the CPG into knowledge constituents, assign CPG knowledge constituents to BPM+ elements, and re-assemble the parts into a clear, precise, and executable model. Limitations of both the CPG and the current BPM+ languages are discussed.<br /> (©2020 AMIA - All rights reserved.)

Details

Language :
English
ISSN :
1942-597X
Volume :
2020
Database :
MEDLINE
Journal :
AMIA ... Annual Symposium proceedings. AMIA Symposium
Publication Type :
Academic Journal
Accession number :
33936443