BACKGROUND Consent2Share (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. METHOD Structured 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. RESULTS From 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 %). CONCLUSIONS There 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.

中文翻译：

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对敏感数据分割技术进行隐私性的初步评估。

背景技术Consent2Share（C2S）是由国家协调员隐私数据分段计划办公室创建的一种开源软件，用于支持电子健康记录（EHR）粒度分段。迄今为止，还没有发布Consent2Share的正式评估。方法从研究地点的36名具有行为健康状况的患者的EHR中提取使用标准临床术语（例如RxNorm）进行整理的结构化数据（例如药物）。通过健康信息交换和两个站点可以获取EHR。EHR数据已经分类为数据类型（例如，程序和服务）。Consent2Share和卫生保健提供者均根据值集（例如精神健康）和敏感性（例如不敏感）对EHR数据进行分类。描述性统计和卡方分析用于比较数据分类之间的差异。结果从产生的1,080份病历中，有584份与众不同。在Consent2Share和提供者的敏感度分类之间发现了显着差异（χ2（2，N = 584）= 114.74，p = <0.0001）。敏感性比较导致56.0％的协议，31.2％的分歧和12.8％的部分协议。大多数（97.8％）的异议是由Consent2Share归类为不敏感但由提供者归类的信息（例如行为健康预防教育服务）引起的。就数据类型而言，大多数分歧（57.1％）集中在程序和服务信息（例如输卵管结扎）上。在考虑价值集时，大多数分歧都集中在遗传数据上（100.0％），其次是性健康和生殖健康（88.9％）。结论在医疗机构广泛使用之前，有必要进一步验证Consent2Share。这项初步研究的结果将有助于指导改进诸如Consent2Share之类的工具的细分逻辑，并可能为新一代个性化同意引擎奠定基础。