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Eluru M, Mendoza DH, Wong A, Jafari M, Todd M, Bayless P, Chern D, Eldredge C, Fonseca R, Franco-Fuquen P, Garcia-Robledo JE, Gifford BG, Hans R, Moreno-Cortes EF, Perumbeti A, Vargas-Cely FS, Zhao L, Grando MA. Physicians' Perspectives on HL7 Information Policy Sensitive Value Set: A Validation Study through Health Concept Categorization. Healthcare (Basel) 2023; 11:2845. [PMID: 37957990 PMCID: PMC10647660 DOI: 10.3390/healthcare11212845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 10/18/2023] [Accepted: 10/21/2023] [Indexed: 11/15/2023] Open
Abstract
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.
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Affiliation(s)
- Maheswari Eluru
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| | - Daniel Hector Mendoza
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| | - Audrey Wong
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| | - Mohammad Jafari
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
- Health Level Seven International, Ann Arbor, MI 48104, USA
| | - Michael Todd
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ 85004, USA;
| | | | | | - Christina Eldredge
- Morsani College of Medicine, University of South Florida, Tampa, FL 33602, USA
| | | | | | | | | | - Rhea Hans
- Mayo Clinic, Phoenix, AZ 85054, USA; (R.F.); (F.S.V.-C.)
| | | | - Ajay Perumbeti
- College of Medicine, University of Arizona, Phoenix, AZ 85004, USA
- Banner Health Systems, Phoenix, AZ 85006, USA
| | | | - Lin Zhao
- HonorHealth, Phoenix, AZ 85020, USA
| | - Maria Adela Grando
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
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Banerjee I, Syed K, Potturu A, Pragada VS, Sharma RS, Murcko A, Chern D, Todd M, Aking P, Al-Yaqoobi A, Bayless P, Belmonte W, Cuadra T, Dockins T, Eldredge C, El-Kareh R, Gale G, Gentile E, Kalpas E, Morris M, Mueller L, Piekut D, Ross MK, Sarris J, Singh G, Tharani S, Wallace M, Grando MA. Physicians differ in their perceptions of sensitive medical records: Survey and interview study. Health Informatics J 2023; 29:14604582231193519. [PMID: 37544770 DOI: 10.1177/14604582231193519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
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.
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Affiliation(s)
| | - Kazi Syed
- Arizona State University, Scottsdale, AZ, US
| | | | | | | | | | | | | | - Padma Aking
- Trinity Integrated Medicine, Phoenix, AZ, US
| | | | | | | | - Teresa Cuadra
- New York City Zen Center for Contemplative Care, New York, NY, US
| | | | | | | | | | | | - Edward Kalpas
- Arizona State University, Scottsdale, AZ, US
- HonorHealth, Scottsdale, AZ, US
| | - Meghan Morris
- Arizona State University, Scottsdale, AZ, US
- HonorHealth, Scottsdale, AZ, US
| | - Laurel Mueller
- Arizona Osteopathic Medical Association, Phoenix, AZ, US
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Ivanova J, Tang T, Idouraine N, Murcko A, Whitfield MJ, Dye C, Chern D, Grando A. Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 2): Focus Group Study. JMIR Ment Health 2022; 9:e18792. [PMID: 35442213 PMCID: PMC9069296 DOI: 10.2196/18792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 11/30/2020] [Accepted: 09/28/2021] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Patient-directed selection and sharing of health information "granules" is known as granular information sharing. In a previous study, patients with behavioral health conditions categorized their own health information into sensitive categories (eg, mental health) and chose the health professionals (eg, pharmacists) who should have access to those records. Little is known about behavioral health professionals' perspectives of patient-controlled granular information sharing (PC-GIS). OBJECTIVE This study aimed to assess behavioral health professionals' (1) understanding of and opinions about PC-GIS; (2) accuracy in assessing redacted medical information; (3) reactions to patient rationale for health data categorization, assignment of sensitivity, and sharing choices; and (4) recommendations to improve PC-GIS. METHODS Four 2-hour focus groups and pre- and postsurveys were conducted at 2 facilities. During the focus groups, outcomes from a previous study on patients' choices for medical record sharing were discussed. Thematic analysis was applied to focus group transcripts to address study objectives. RESULTS A total of 28 health professionals were recruited. Over half (14/25, 56%) were unaware or provided incorrect definitions of granular information sharing. After PC-GIS was explained, all professionals demonstrated understanding of the terminology and process. Most (26/32 codes, 81%) recognized that key medical data had been redacted from the study case. A majority (41/62 codes, 66%) found the patient rationale for categorization and data sharing choices to be unclear. Finally, education and other approaches to inform and engage patients in granular information sharing were recommended. CONCLUSIONS This study provides detailed insights from behavioral health professionals on granular information sharing. Outcomes will inform the development, deployment, and evaluation of an electronic consent tool for granular health data sharing.
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Affiliation(s)
- Julia Ivanova
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, United States
| | - Tianyu Tang
- College of Medicine, University of Arizona, Tucson, AZ, United States
| | - Nassim Idouraine
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| | - Anita Murcko
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| | | | - Christy Dye
- Partners in Recovery, Phoenix, AZ, United States
| | - Darwyn Chern
- Partners in Recovery, Phoenix, AZ, United States
| | - Adela Grando
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
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