Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA.
Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Implement Sci. 2024 Aug 19;19(1):61. doi: 10.1186/s13012-024-01385-5.
Germline genetic testing is recommended for an increasing number of conditions with underlying genetic etiologies, the results of which impact medical management. However, genetic testing is underutilized in clinics due to system, clinician, and patient level barriers. Behavioral economics provides a framework to create implementation strategies, such as nudges, to address these multi-level barriers and increase the uptake of genetic testing for conditions where the results impact medical management.
Patients meeting eligibility for germline genetic testing for a group of conditions will be identified using electronic phenotyping algorithms. A pragmatic, type 3 hybrid cluster randomization study will test nudges to patients and/or clinicians, or neither. Clinicians who receive nudges will be prompted to either refer their patient to genetics or order genetic testing themselves. We will use rapid cycle approaches informed by clinician and patient experiences, health equity, and behavioral economics to optimize these nudges before trial initiation. The primary implementation outcome is uptake of germline genetic testing for the pre-selected health conditions. Patient data collected through the electronic health record (e.g. demographics, geocoded address) will be examined as moderators of the effect of nudges.
This study will be one of the first randomized trials to examine the effects of patient- and clinician-directed nudges informed by behavioral economics on uptake of genetic testing. The pragmatic design will facilitate a large and diverse patient sample, allow for the assessment of genetic testing uptake, and provide comparison of the effect of different nudge combinations. This trial also involves optimization of patient identification, test selection, ordering, and result reporting in an electronic health record-based infrastructure to further address clinician-level barriers to utilizing genomic medicine. The findings may help determine the impact of low-cost, sustainable implementation strategies that can be integrated into health care systems to improve the use of genomic medicine.
ClinicalTrials.gov. NCT06377033. Registered on March 31, 2024. https://clinicaltrials.gov/study/NCT06377033?term=NCT06377033&rank=1.
由于潜在遗传病因的影响，越来越多的疾病需要进行种系基因检测，检测结果会影响医疗管理。然而，由于系统、临床医生和患者层面的障碍，基因检测在临床实践中的应用并不广泛。行为经济学为制定实施策略提供了一个框架，例如“推动”策略，以解决这些多层面的障碍，并增加对影响医疗管理的疾病进行基因检测的比例。
使用电子表型算法识别符合一组疾病种系基因检测条件的患者。一项实用的、3 型混合集群随机对照研究将测试针对患者和/或临床医生的推动策略，或两者都不测试。接受推动策略的临床医生将被提示转介患者去进行基因检测或自行安排基因检测。我们将使用基于临床医生和患者经验、健康公平和行为经济学的快速循环方法，在试验开始前优化这些推动策略。主要的实施结果是对预先选择的健康状况进行种系基因检测的比例。通过电子健康记录收集的患者数据（例如人口统计学、地理编码地址）将作为推动策略效果的调节剂进行检查。
这将是首次使用行为经济学提供信息的针对患者和临床医生的推动策略的随机对照试验之一，以评估对基因检测接受率的影响。实用的设计将有利于获得大量和多样化的患者样本，允许评估基因检测的接受率，并比较不同推动策略组合的效果。该试验还涉及优化电子健康记录基础架构中的患者识别、测试选择、订单和结果报告，以进一步解决利用基因组医学的临床医生层面的障碍。研究结果可能有助于确定可以整合到医疗保健系统中以提高基因组医学使用的低成本、可持续实施策略的影响。
ClinicalTrials.gov。NCT06377033。于 2024 年 3 月 31 日注册。https://clinicaltrials.gov/study/NCT06377033?term=NCT06377033&rank=1。
