Indiana University-Purdue University Indianapolis (IUPUI) / Medication non-adherence is a major healthcare problem that negatively impacts
the health and productivity of individuals and society as a whole. Reasons for medication
non-adherence are multi-faced, with no clear-cut solution. Adherence to medication
remains a difficult area to study, due to inconsistencies in representing medicationadherence
behavior data that poses a challenge to humans and today’s computer
technology related to interpreting and synthesizing such complex information.
Developing a consistent conceptual framework to medication adherence is needed to
facilitate domain understanding, sharing, and communicating, as well as enabling
researchers to formally compare the findings of studies in systematic reviews.
The goal of this research is to create a common language that bridges human and
computer technology by developing a controlled structured vocabulary of medication
adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology)
using breast cancer as a case study to inform and evaluate the proposed ontology and
demonstrating its application to real-world situation. The intention is for MAB-Ontology
to be developed against the background of a philosophical analysis of terms, such as
belief, and desire to be human, computer-understandable, and interoperable with other
systems that support scientific research.
The design process for MAB-Ontology carried out using the METHONTOLOGY
method incorporated with the Basic Formal Ontology (BFO) principles of best practice.
This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including
adherence assessment, adherence determinants, adherence theories, adherence
taxonomies, and tacit knowledge source types. These sources were analyzed using a
systematic approach that involved some questions applied to all source types to guide
data extraction and inform domain conceptualization. A set of intermediate
representations involving tables and graphs was used to allow for domain evaluation
before implementation. The resulting ontology included 629 classes, 529 individuals, 51
object property, and 2 data property.
The intermediate representation was formalized into OWL using Protégé. The
MAB-Ontology was evaluated through competency questions, use-case scenario, face
validity and was found to satisfy the requirement specification. This study provides a
unified method for developing a computerized-based adherence model that can be
applied among various disease groups and different drug categories.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/17767 |
| Date | 02 August 2018 |
| Creators | Sawesi, Suhila |
| Contributors | MacDorman, Karl F., Jones, Josette F., Carpenter, Janet S., Kharrazi, Hadi, Duncan, William D. |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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