ArticleInternational journal of medical informatics2020
Pilot evaluation of sensitive data segmentation technology for privacy.
Article in International journal of medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Patient-Driven Sharing of Health Information: A National Effort to Advance Equitable Interoperability.Applied clinical informatics · 2025Article
- FHIR Granular Sensitive Data Segmentation.Applied clinical informatics · 2025Article
- Physicians' Perspectives on HL7 Information Policy Sensitive Value Set: A Validation Study through Health Concept Categorization.Healthcare (Basel, Switzerland) · 2023Article
- Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 2): Focus Group Study.JMIR mental health · 2022Article
- My data choices: Pilot evaluation of patient-controlled medical record sharing technology.Health informatics journalArticle
- Ingredient-based method to create medication lists and support granular data segmentation.Health informatics journalArticle
- A pilot comparison of medical records sensitivity perspectives of patients with behavioral health conditions and healthcare providers.Health informatics journalArticle
- Physicians differ in their perceptions of sensitive medical records: Survey and interview study.Health informatics journalArticle
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundConsent2Share (C2S) is an open source software created by the Office of the National Coordinator Data Segmentation for Privacy initiative to support electronic health record (EHR) granular segmentation. To date, there are no published formal evaluations of Consent2Share.
methodStructured data (e.g. medications) codified using standard clinical terminologies (e.g. RxNorm) was extracted from the EHR of 36 patients with behavioral health conditions from study sites. EHRs were available through a health information exchange and two sites. The EHR data was already classified into data types (e.g. procedures and services). Both Consent2Share and health providers classified EHR data based on value sets (e.g. mental health) and sensitivity (e.g. not sensitive. Descriptive statistics and Chi-square analysis were used to compare differences between data categorizations.
resultsFrom the resulting 1,080 medical records items, 584 were distinct. Significant differences were found between sensitivity classifications by Consent2Share and providers (χ2 (2, N = 584) = 114.74, p = <0.0001). Sensitivity comparisons led to 56.0 % of agreements, 31.2 % disagreements, and 12.8 % partial agreements. Most (97.8 %) disagreements resulted from information classified as not sensitive by Consent2Share, but sensitive by provider (e.g. behavioral health prevention education service). In terms of data types, most disagreements (57.1 %) focused on procedures and services information (e.g. ligation of fallopian tube). When considering value sets, most disagreements focused on genetic data (100.0 %), followed by sexual and reproductive health (88.9 %).
conclusionsThere is a need to further validate Consent2Share before broad use in health care settings. The outcomes from this pilot study will help guide improvements in segmentation logic of tools like Consent2Share and may set the stage for a new generation of personalized consent engines.
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Registered trials
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