Banerjee Ipsha, Syed Kazi, Potturu Aishwarya, Pragada Venkata Svs, Sharma Rishika S, Murcko Anita, Chern Darwyn, Todd Michael, Aking Padma, Al-Yaqoobi Ali, Bayless Patricia, Belmonte Winona, Cuadra Teresa, Dockins Trudy, Eldredge Christina, El-Kareh Robert, Gale Gregory, Gentile Edward, Kalpas Edward, Morris Meghan, Mueller Laurel, Piekut Dorothy, Ross Mindy K, Sarris John, Singh Gagandeep, Tharani Shalini, Wallace Mark, Grando Maria Adela
Arizona State University, Scottsdale, AZ, US.
Copa Health, Phoenix, AZ, US.
Health Informatics J. 2023 Jul-Sep;29(3):14604582231193519. doi: 10.1177/14604582231193519.
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 ( = .016) more data categories than psychiatrists when classifying data items. The endorsement of Mental Health and Substance Use categories were significantly ( = .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.
评估了医生将电子健康记录（EHR）数据（如抑郁症）归类为敏感数据类别（如心理健康）的情况，以及他们对这些类别对病历数据分类充分性的看法。20名医生（10名精神科医生与10名非精神科医生配对）通过一项调查将来自患者电子健康记录的1000个数据项分类到数据类别中。采用聚类调整卡方检验和混合模型进行分析。在20次后续访谈中，为每对医生选择10个项目（共100个项目）进行讨论。对访谈进行了主题分析。调查项目分类产生了500项（50.0%）一致、175项（17.5%）不一致、325项（32.5%）部分一致。分类不一致与医生专业和隐含的患者病史有关。在对数据项进行分类时，非精神科医生选择的数据类别显著多于精神科医生（P = 0.016）。对于两种类型的提供者，心理健康和物质使用类别的认可显著相关（P = 0.001）。在主题分析中，在确定医疗信息的敏感性时，会诊诊断（100%）、问题（95%）、健康问题（90%）和药物（85%）讨论得最多。大多数（90.0%）访谈参与者建议增加额外的数据类别。研究结果可能会指导数字患者控制的细粒度数据共享技术和流程的发展。
