{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T23:56:52Z","timestamp":1781308612171,"version":"3.54.1"},"reference-count":17,"publisher":"Georg Thieme Verlag KG","issue":"03","funder":[{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"crossref","award":["9R01DA056984-06A1"],"award-info":[{"award-number":["9R01DA056984-06A1"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Protecting sensitive health information, particularly substance use data, is essential to preserving patient trust, improving care engagement, and ensuring compliance with federal confidentiality laws such as 42 CFR Part 2. Manual segmentation of sensitive data remains burdensome and error-prone, creating a need for scalable, automated, and patient-centered data segmentation technologies.<\/jats:p>\n                  <jats:p>The objective of this study is to evaluate the technical effectiveness, scalability, and computational performance of SHARES, an open-source data segmentation platform based on HL7 Fast Healthcare Interoperability Resources (FHIR), designed to support patient-directed, granular control over sharing sensitive substance use-related health information.<\/jats:p>\n                  <jats:p>We generated 11,519 synthetic FHIR patient records using Synthea and conducted physician-led classifications of 1,848 unique clinical terms contained in those patient records. These classifications were used to assign code-category-confidence rules applied by the SHARES segmentation engine. We deployed the SHARES platform in simulation environments to label and segment substance use-related data using varying confidentiality thresholds. We benchmarked throughput, scalability, and computational performance across large FHIR datasets, and measured segmentation accuracy via physician manual review.<\/jats:p>\n                  <jats:p>Physicians categorized 232 data items as substance use or \u201cmaybe\u201d substance use data elements. The SHARES segmentation engine processed 197.6 million FHIR resources across 11 confidentiality thresholds. Overall, 17 million data items (8.64%) were flagged as sensitive. SHARES achieved a throughput of 10.36 patient bundles per second, or approximately 18,909 FHIR resources per second, on a commodity laptop. A full segmentation run on 11,519 patients had a cost of under one cent.<\/jats:p>\n                  <jats:p>This study demonstrates the feasibility and scalability of automated, rule-based data segmentation within a FHIR-native architecture, using a physician-derived sensitivity construct for substance use as an applied test case. SHARES offers high-throughput, low-cost classification performance, and supports auditability and deterministic decision-making, which are key strengths for compliance with 42 CFR Part 2. Future enhancements will incorporate clinical quality language (CQL)-based logic to better reflect real-world clinical reasoning and contextual data interpretation.<\/jats:p>","DOI":"10.1055\/a-2863-4129","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T23:45:27Z","timestamp":1781307927000},"page":"423-433","source":"Crossref","is-referenced-by-count":0,"title":["Assessing the Effectiveness and Scalability of Fast Healthcare Interoperability Resource-Based Granular Data Segmentation Technology"],"prefix":"10.1055","volume":"17","author":[{"given":"Preston","family":"Lee","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abhishek Singh","family":"Dhadwal","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martha","family":"Kaiser","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soroush","family":"Dianaty","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"Lott","sequence":"additional","affiliation":[{"name":"Community Bridges, Mesa, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gagandeep","family":"Singh","sequence":"additional","affiliation":[{"name":"Mercy Care, Phoenix, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darwyn","family":"Chern","sequence":"additional","affiliation":[{"name":"Copa Health, Mesa, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason","family":"Walonoski","sequence":"additional","affiliation":[{"name":"The MITRE Corporation, McLean, Virginia, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5769-8556","authenticated-orcid":false,"given":"Adela","family":"Grando","sequence":"additional","affiliation":[{"name":"Biomedical Informatics, College of Health Solutions, Arizona State University, Phoenix, Arizona, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2026,6,12]]},"reference":[{"issue":"04","key":"ref1","first-page":"411","article-title":"Granular patient control of personal health information: federal and state law considerations","volume":"58","author":"M J Saks","year":"2018","journal-title":"Jurimetrics"},{"issue":"04","key":"ref2","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1055\/a-2591-9129","article-title":"Patient-driven sharing of health information: a national effort to advance equitable interoperability","volume":"16","author":"H K Galvin","year":"2025","journal-title":"Appl Clin Inform"},{"issue":"02","key":"ref3","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1177\/1073110517720653","article-title":"A study to elicit behavioral health patients' and providers' opinions on health records consent","volume":"45","author":"M A Grando","year":"2017","journal-title":"J Law Med Ethics"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"103338","DOI":"10.1016\/j.jbi.2019.103338","article-title":"State of the art and a mixed-method personalized approach to assess patient perceptions on medical record sharing and sensitivity","volume":"101","author":"H Soni","year":"2020","journal-title":"J Biomed Inform"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.jsat.2018.11.005","article-title":"Interpretation and integration of the federal substance use privacy protection rule in integrated health systems: a qualitative analysis","volume":"97","author":"A NC Campbell","year":"2019","journal-title":"J Subst Abuse Treat"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"104401","DOI":"10.1016\/j.ijmedinf.2021.104401","article-title":"Do data security measures, privacy regulations, and communication standards impact the interoperability of patient health information? A cross-country investigation","volume":"148","author":"U Shrivastava","year":"2021","journal-title":"Int J Med Inform"},{"issue":"03","key":"ref8","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1055\/s-0043-1769924","article-title":"Shifting into action: from data segmentation to equitable interoperability for adolescents (and everyone else)","volume":"14","author":"C Sarabu","year":"2023","journal-title":"Appl Clin Inform"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"104121","DOI":"10.1016\/j.ijmedinf.2020.104121","article-title":"Pilot evaluation of sensitive data segmentation technology for privacy","volume":"138","author":"A Grando","year":"2020","journal-title":"Int J Med Inform"},{"issue":"01","key":"ref10","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1055\/a-2466-4371","article-title":"FHIR granular sensitive data segmentation","volume":"16","author":"P Lee","year":"2025","journal-title":"Appl Clin Inform"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"105066","DOI":"10.1016\/j.ijmedinf.2023.105066","article-title":"Security, confidentiality, privacy and patient safety in the hospital information systems from the users' perspective: a cross-sectional study","volume":"175","author":"J Alipour","year":"2023","journal-title":"Int J Med Inform"},{"issue":"21","key":"ref12","first-page":"21","article-title":"Physicians' perspectives on HL7 information policy sensitive value set: a validation study through health concept categorization","volume":"11","author":"M Eluru","year":"2023","journal-title":"Healthcare (Basel)"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"105763","DOI":"10.1016\/j.ijmedinf.2024.105763","article-title":"Synthetic data generation in healthcare: a scoping review of reviews on domains, motivations, and future applications","volume":"195","author":"M Rujas","year":"2025","journal-title":"Int J Med Inform"},{"issue":"03","key":"ref14","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1093\/jamia\/ocx079","article-title":"Synthea: an approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record","volume":"25","author":"J Walonoski","year":"2018","journal-title":"J Am Med Inform Assoc"},{"issue":"05","key":"ref15","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1108\/00220410410560582","article-title":"Understanding inverse document frequency: on theoretical arguments for IDF","volume":"60","author":"S Robertson","year":"2004","journal-title":"J Doc"},{"issue":"01","key":"ref16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1108\/eb026526","article-title":"A statistical interpretation of term specificity and its application in retrieval","volume":"28","author":"K Sparck Jones","year":"1972","journal-title":"J Doc"},{"issue":"03","key":"ref17","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1177\/14604582231193519","article-title":"Physicians differ in their perceptions of sensitive medical records: survey and interview study","volume":"29","author":"I Banerjee","year":"2023","journal-title":"Health Informatics J"},{"issue":"01","key":"ref20","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1186\/s12911-019-0793-0","article-title":"The validity of synthetic clinical data: a validation study of a leading synthetic data generator (Synthea) using clinical quality measures","volume":"19","author":"J Chen","year":"2019","journal-title":"BMC Med Inform Decis Mak"}],"container-title":["Applied Clinical Informatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2863-4129.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T23:45:33Z","timestamp":1781307933000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2863-4129"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":17,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2026,5,28]]},"published-print":{"date-parts":[[2026,5]]}},"URL":"https:\/\/doi.org\/10.1055\/a-2863-4129","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["1869-0327"],"issn-type":[{"value":"1869-0327","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5]]}}}