Medical University of South Carolina, 171 Ashley Avenue, Charleston, SC 29425, USA.
Transl Behav Med. 2023 Jun 9;13(6):381-387. doi: 10.1093/tbm/ibad006.
In 2021, the Medical University of South Carolina (MUSC) launched In Our DNA SC. This large-scale initiative will screen 100,000 individuals in South Carolina for three preventable hereditary conditions that impact approximately two million people in the USA but often go undetected. In anticipation of inevitable changes to the delivery of this complex initiative, we developed an approach to track and assess the impact of evaluate adaptations made during the pilot phase of program implementation. We used a modified version of the Framework for Reporting Adaptations and Modification-Enhanced (FRAME) and Adaptations to code adaptations made during the 3-month pilot phase of In Our DNA SC. Adaptations were documented in real-time using a REDCap database. We used segmented linear regression models to independently test three hypotheses about the impact of adaptations on program reach (rate of enrollment in the program, rate of messages viewed) and implementation (rate of samples collected) 7 days pre- and post-adaptation. Effectiveness was assessed using qualitative observations. Ten adaptations occurred during the pilot phase of program implementation. Most adaptations (60%) were designed to increase the number and type of patient contacted (reach). Adaptations were primarily made based on knowledge and experience (40%) or from quality improvement data (30%). Of the three adaptations designed to increase reach, shortening the recruitment message potential patients received significantly increased the average rate of invitations viewed by 7.3% (p = 0.0106). There was no effect of adaptations on implementation (number of DNA samples collected). Qualitative findings support improvement in effectiveness of the intervention after shortening the consent form and short-term positive impact on uptake of the intervention as measured by team member's participation. Our approach to tracking adaptations of In Our DNA SC allowed our team to quantify the utility of modifications, make decisions about pursuing the adaptation, and understand consequences of the change. Streamlining tools for tracking and responding to adaptations can help monitor the incremental impact of interventions to support continued learning and problem solving for complex interventions being delivered in health systems based on real-time data.
2021 年,南卡罗来纳医科大学(MUSC)启动了“In Our DNA SC”项目。该大规模计划将对南卡罗来纳州的 10 万人进行三种可预防的遗传性疾病筛查,这些疾病在美国影响约 200 万人,但通常未被发现。为了应对该复杂计划实施过程中不可避免的变化,我们开发了一种方法来跟踪和评估试点阶段所做的调整及其对计划实施的影响。我们使用了修改后的框架报告调整和修改增强版(FRAME)和调整,对“In Our DNA SC”试点阶段的 3 个月期间所做的调整进行编码。使用 REDCap 数据库实时记录调整。我们使用分段线性回归模型,独立检验了三个假设,即调整对计划覆盖率(计划参与率、消息查看率)和实施(样本采集率)的影响。在调整前后的 7 天内进行了测试。使用定性观察来评估有效性。在计划实施的试点阶段共发生了 10 次调整。大多数调整(60%)旨在增加接触到的患者数量和类型(覆盖率)。调整主要基于知识和经验(40%)或质量改进数据(30%)。为了提高覆盖率而设计的三项调整措施中,缩短潜在患者收到的招募信息,将平均邀请查看率提高了 7.3%(p = 0.0106)。调整对实施(收集的 DNA 样本数量)没有影响。定性结果支持在缩短同意书后干预措施的有效性有所提高,并在团队成员参与的情况下,短期内对干预措施的采用产生了积极影响。我们跟踪“In Our DNA SC”调整的方法使我们的团队能够量化修改的效用,对调整做出决策,并了解变更的后果。简化跟踪和响应调整的工具可以帮助监测干预措施的增量影响,从而为基于实时数据在卫生系统中实施的复杂干预措施提供持续学习和解决问题的支持。