ArticleArtificial intelligence in medicine2009
An ontology-based approach to enhance querying capabilities of general practice medicine for better management of hypertension.
Article in Artificial intelligence in medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Towards a knowledge-based decision support system to foster the return to work of wheelchair users.Computational and structural biotechnology journal · 2024Article
- Integrating terminologies into standard SQL: a new approach for research on routine data.Journal of biomedical semantics · 2019Article
- A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.Journal of medical systems · 2017Article
- Graphical representation of quality indicators based on medical service ontology.SpringerPlus · 2013Article
- A web-based data-querying tool based on ontology-driven methodology and flowchart-based model.JMIR medical informatics · 2013Article
- Development of an obesity management ontology based on the nursing process for the mobile-device domain.Journal of medical Internet research · 2013Article
- Synonym, topic model and predicate-based query expansion for retrieving clinical documents.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2012Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundHypertension is one of the most prevalent chronic conditions and is directly correlated to deadly risks; yet, despite the availability of effective treatment, there is still clear room for improving patient outcomes. Use of relational databases is widespread for storing patient data, but formulating queries to identify patients whose clinical management can be improved is challenging due to the temporal nature of chronic illness and the mismatch in levels of abstraction between key management concepts and coded clinical data.
objectiveThe objective of this work is to develop a sharable and extensible analysis tool that can be used to identify hypertensive patients who satisfy any of a set of evidence-based criteria for quality improvement potential.
methodsWe developed an ontology driven framework to enhance and facilitate some important temporal querying requirements in general practice medicine, focusing on prescribing for hypertension. The Web Ontology Language has been used to develop the ontology and the specific queries have been written in Semantic Query-enhanced Web Rule Language. We have used production electronic medical record (EMR) data from a General Medical Practice in New Zealand to populate the ontology.
resultsA unified patient management ontology consisting of a disease management ontology, a patient data ontology, and a plan violation taxonomy has been created and populated with EMR data. We have queried this ontology to determine patient cohorts that satisfy any of eight quality audit criteria, thereby identifying patients whose clinical management can be improved. A prescription timeline visualisation tool has also been developed to aid a clinician in understanding a patient's antihypertensive prescribing patterns, as well as visually validating the query results.
conclusionsThe presented framework shows potential to provide answers to clinically relevant queries with complex temporal relationships. The framework can be used to successfully identify hypertensive patients who need to be followed-up/recalled.
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