DataSheet2_Environmental scan of family chart linking for genetic cascade screening in a U.S. integrated health system.docx

Background: An alternative to population-based genetic testing, automated cascade genetic testing facilitated by sharing of family health history, has been conceptualized as a more efficient and cost-effective approach to identify hereditary genetic conditions. However, existing software and applications programming interfaces (API) for the practical implementation of this approach in health care settings have not been described. Methods: We reviewed API available for facilitating cascade genetic testing in electronic health records (EHRs). We emphasize any information regarding informed consent as provided for each tool. Using semi-structured key informant interviews, we investigated uptake of and barriers to integrating automated family cascade genetic testing into the EHR. Results: We summarized the functionalities of six tools related to utilizing family health history to facilitate cascade genetic testing. No tools were explicitly capable of facilitating family cascade genetic testing, but few enterprise EHRs supported family health history linkage. We conducted five key informant interviews with four main considerations that emerged including: 1) incentives for interoperability, 2) HIPAA and regulations, 3) mobile-app and alternatives to EHR deployment, 4) fundamental changes to conceptualizing EHRs. Discussion: Despite the capabilities of existing technology, limited bioinformatic support has been developed to automate processes needed for family cascade genetic testing and the main barriers for implementation are nontechnical, including an understanding of regulations, consent, and workflow. As the trade-off between cost and efficiency for population-based and family cascade genetic testing shifts, the additional tools necessary for their implementation should be considered.背景：作为基于人群的基因检测的替代方案，借助家族健康史（family health history）共享实现的自动化级联基因检测（cascade genetic testing）已被构想为一种更高效且具成本效益的遗传性疾病识别方法。然而，目前尚未有针对该方案在医疗场景中实际落地所需的软件及应用程序编程接口（API）的相关报道。 方法：本研究对可用于电子健康记录（EHR）场景下辅助级联基因检测的应用程序编程接口（API）进行了调研。我们重点梳理了各工具相关的知情同意（informed consent）相关信息。通过半结构化关键知情人访谈（key informant interviews），我们探究了将自动化家族级联基因检测（family cascade genetic testing）整合至EHR的应用现状及面临的障碍。 结果：本研究总结了6款用于利用家族健康史辅助级联基因检测的工具的功能特性。目前尚无明确支持家族级联基因检测的工具，且仅有少数企业级EHR支持家族健康史关联功能。我们共完成5次关键知情人访谈，最终归纳出4项核心考量维度：1）互操作性激励措施；2）《健康保险流通与责任法案》（HIPAA）及相关监管要求；3）移动应用及EHR部署替代方案；4）EHR概念框架的根本性变革。 讨论：尽管现有技术已具备一定能力，但针对家族级联基因检测所需自动化流程的生物信息学支持仍较为匮乏，其落地的主要障碍为非技术性因素，包括监管认知、知情同意及工作流程等方面。随着基于人群的基因检测与家族级联基因检测在成本与效率间的权衡关系发生转变，应考虑开发其落地所需的配套工具。