*Result*: Architecting Synergy: Knowledge Graphs for Representing Complex, Multi-Domain Patient Information.

Title:
Architecting Synergy: Knowledge Graphs for Representing Complex, Multi-Domain Patient Information.
Authors:
Keshavjee K; Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.; Omni Health Nexus, Toronto, Canada.
Source:
Studies in health technology and informatics [Stud Health Technol Inform] 2026 Feb 12; Vol. 334, pp. 93-97.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform Subsets: MEDLINE
Imprint Name(s):
Original Publication: Amsterdam ; Washington, DC : IOS Press, 1991-
Contributed Indexing:
Keywords: Knowledge graph; artificial intelligence; information architecture; information management; knowledge representation; ontology; vector database
Entry Date(s):
Date Created: 20260213 Date Completed: 20260213 Latest Revision: 20260213
Update Code:
20260213
DOI:
10.3233/SHTI260023
PMID:
41685480
Database:
MEDLINE

*Further Information*

*Healthcare systems exchange more data than ever, yet gaps in care persist: missed referrals, unsafe polypharmacy, and loss of continuity. This paper asks: what information architecture supports representing care as a dynamic, multi-domain, intent-driven process? Drawing on empirical failure modes (appointment scheduling, referrals, labs, medication processes) identified in primary care in Canada, along with other care failures (e.g. guideline misapplication, discharge lapses), we derive functional and technical requirements. We evaluate four candidate architectures against these requirements. We find that only knowledge graphs satisfy the combination of semantic linkage, schema flexibility, state tracking, longitudinal reasoning, and explainability. We then discuss regulatory, governance, and vendor implications. Knowledge graphs offer a promising path forward toward truly interoperable, safe, and patient-centered care.*