Eldredge, Christina

The Health Level 7 (HL7) organization introduced the Information Sensitivity Policy Value Set with 45 sensitive data categories to facilitate the implementation of granular electronic consent technology. The goal is to allow patients to have control over the sharing of their sensitive medical records. This study represents the first attempt to explore physicians’ viewpoints on these categories. Twelve physicians participated in a survey, leading to revisions in 21 HL7 categories. They later classified 600 clinical data items through a second survey using the updated categories. Participants’ perspectives were documented, and data analysis included descriptive measures and heat maps. In the first survey, six participants suggested adding 19 new categories (e.g., personality disorder), and modifying 25 category definitions. Two new categories and sixteen revised category definitions were incorporated to support more patient-friendly content and inclusive language. Fifteen new category recommendations were addressed through a revision of category definitions (e.g., personality disorder described as a behavioral health condition). In the second survey, data categorizations led to recommendations for more categories from ten participants. Future revisions of the HL7 categories should incorporate physicians’ viewpoints, validate the categories using patient data or/and include patients’ perspectives, and develop patient-centric category specifications.

Physician categorizations of electronic health record (EHR) data (e.g., depression) into sensitive data categories (e.g., Mental Health) and their perspectives on the adequacy of the categories to classify medical record data were assessed. One thousand data items from patient EHR were classified by 20 physicians (10 psychiatrists paired with ten non-psychiatrist physicians) into data categories via a survey. Cluster-adjusted chi square tests and mixed models were used for analysis. 10 items were selected per each physician pair (100 items in total) for discussion during 20 follow-up interviews. Interviews were thematically analyzed. Survey item categorization yielded 500 (50.0%) agreements, 175 (17.5%) disagreements, 325 (32.5%) partial agreements. Categorization disagreements were associated with physician specialty and implied patient history. Non-psychiatrists selected significantly ( p = .016) more data categories than psychiatrists when classifying data items. The endorsement of Mental Health and Substance Use categories were significantly ( p = .001) related for both provider types. During thematic analysis, Encounter Diagnosis (100%), Problems (95%), Health Concerns (90%), and Medications (85%) were discussed the most when deciding the sensitivity of medical information. Most (90.0%) interview participants suggested adding additional data categories. Study findings may guide the evolution of digital patient-controlled granular data sharing technology and processes.

AbstractIntroductionComputable biomedical knowledge artifacts (CBKs) are digital objects conveying biomedical knowledge in machine‐interpretable structures. As more CBKs are produced and their complexity increases, the value obtained from sharing CBKs grows. Mobilizing CBKs and sharing them widely can only be achieved if the CBKs are findable, accessible, interoperable, reusable, and trustable (FAIR+T). To help mobilize CBKs, we describe our efforts to outline metadata categories to make CBKs FAIR+T.MethodsWe examined the literature regarding metadata with the potential to make digital artifacts FAIR+T. We also examined metadata available online today for actual CBKs of 12 different types. With iterative refinement, we came to a consensus on key categories of metadata that, when taken together, can make CBKs FAIR+T. We use subject‐predicate‐object triples to more clearly differentiate metadata categories.ResultsWe defined 13 categories of CBK metadata most relevant to making CBKs FAIR+T. Eleven of these categories (type, domain, purpose, identification, location, CBK‐to‐CBK relationships, technical, authorization and rights management, provenance, evidential basis, and evidence from use metadata) are evident today where CBKs are stored online. Two additional categories (preservation and integrity metadata) were not evident in our examples. We provide a research agenda to guide further study and development of these and other metadata categories.ConclusionA wide variety of metadata elements in various categories is needed to make CBKs FAIR+T. More work is needed to develop a common framework for CBK metadata that can make CBKs FAIR+T for all stakeholders.