Orlando Lori A, Buchanan Adam H, Hahn Susan E, Christianson Carol A, Powell Karen P, Skinner Celette Sugg, Chesnut Blair, Blach Colette, Due Barbara, Ginsburg Geoffrey S, Henrich Vincent C
Department of Medicine, Duke University, Durham, North Carolina 27705, USA.
N C Med J. 2013 Jul-Aug;74(4):287-96.
Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care.
We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics.
Stakeholder feedback resulted in changes to MeTree's interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree's strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers' needs.
The tool was validated in a small cohort.
MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines.
家族健康史是疾病风险的有力预测指标。为降低多种慢性病的发病率和死亡率，基于风险分层的循证指南强烈鼓励收集和整合家族健康史，以指导一级预防策略的选择。然而，此类信息的收集和整合在临床实践中并未得到很好的落实。为解决家族健康史收集和使用方面的障碍，基因医学连接组织开发并验证了MeTree，这是一种基于网络、面向患者的家族健康史收集和临床决策支持工具。MeTree旨在作为初级保健基因组医学模式的一部分，整合到初级保健实践中。
我们描述了用于开发MeTree的指导原则、操作特征、算法开发和编码。通过利益相关者认知访谈、遗传咨询试点项目以及在两家社区初级保健诊所开展的临床实践试点项目进行验证。
利益相关者的反馈导致MeTree界面的更改以及临床决策支持文件措辞的更改。试点研究发现并纠正了编码错误，重新格式化了临床决策支持文件。与其他工具相比，MeTree的优势在于它能无缝整合到临床实践中，并根据提供者的需求提供以行动为导向的建议。
该工具在一个小队列中进行了验证。
MeTree可以整合到初级保健实践中，帮助提供者收集和整合患者的家族健康史信息，以提高对基于风险分层的循证指南的依从性。
