Abstract：
BACKGROUND: Approaches to prevent and manage diabetes at a community population level are hindered because current strategies are not aligned with the structure and function of a community system. We describe a community-driven process based on local data and rapid prototyping as an alternative approach to create diabetes prevention and care management solutions appropriate for each community. We report on the process and provide baseline data for a 3-year case study initiative to improve diabetes outcomes in two rural Nebraska communities.
METHODS: We developed an iterative design process based on the assumption that decentralized decision-making using local data feedback and monitoring will lead to the innovation of local sustainable solutions. Coalitions act as community innovation hubs and meet monthly to work through a facilitated design process. Six core diabetes measures will be tracked over the course of the project using the electronic health record from community clinics as a proxy for the entire community.
RESULTS: Baseline data indicate two-thirds of the population in both communities are at risk for prediabetes based on age and body mass index. However, only a fraction (35% and 12%) of those at risk have been screened. This information led both coalitions to focus on improving screening rates in their communities.
CONCLUSIONS: In order to move a complex system towards an optimal state (e.g., improved diabetes outcomes), stakeholders must have access to continuous feedback of accurate, pertinent information in order to make informed decisions. Conventional approaches of implementing evidence-based interventions do not facilitate this process.
METHODS: We developed an iterative design process based on the assumption that decentralized decision-making using local data feedback and monitoring will lead to the innovation of local sustainable solutions. Coalitions act as community innovation hubs and meet monthly to work through a facilitated design process. Six core diabetes measures will be tracked over the course of the project using the electronic health record from community clinics as a proxy for the entire community.
RESULTS: Baseline data indicate two-thirds of the population in both communities are at risk for prediabetes based on age and body mass index. However, only a fraction (35% and 12%) of those at risk have been screened. This information led both coalitions to focus on improving screening rates in their communities.
CONCLUSIONS: In order to move a complex system towards an optimal state (e.g., improved diabetes outcomes), stakeholders must have access to continuous feedback of accurate, pertinent information in order to make informed decisions. Conventional approaches of implementing evidence-based interventions do not facilitate this process.
摘要：
背景：在社区人群水平上预防和管理糖尿病的方法受到阻碍，因为当前的策略与社区系统的结构和功能不一致。我们描述了基于本地数据和快速原型设计的社区驱动过程，作为创建适合每个社区的糖尿病预防和护理管理解决方案的替代方法。我们报告了该过程，并为一项为期3年的案例研究计划提供了基线数据，以改善内布拉斯加州两个农村社区的糖尿病结局。
方法：我们基于以下假设开发了一个迭代设计过程：使用本地数据反馈和监视的分散决策将导致本地可持续解决方案的创新。联盟充当社区创新中心，每月开会，通过便利的设计过程开展工作。在项目过程中，将使用社区诊所的电子健康记录作为整个社区的代理来跟踪六个核心糖尿病指标。
结果：基线数据表明，根据年龄和体重指数，两个社区中三分之二的人口都有糖尿病前期风险。然而,只有一小部分(35%和12%)的高危人群接受了筛查.这些信息导致两个联盟都专注于提高其社区的筛查率。
结论：为了使复杂系统朝着最佳状态移动（例如，改善糖尿病结局)，利益相关者必须能够获得准确的持续反馈，相关信息，以便做出明智的决定。实施循证干预的传统方法并不能促进这一过程。
方法：我们基于以下假设开发了一个迭代设计过程：使用本地数据反馈和监视的分散决策将导致本地可持续解决方案的创新。联盟充当社区创新中心，每月开会，通过便利的设计过程开展工作。在项目过程中，将使用社区诊所的电子健康记录作为整个社区的代理来跟踪六个核心糖尿病指标。
结果：基线数据表明，根据年龄和体重指数，两个社区中三分之二的人口都有糖尿病前期风险。然而,只有一小部分(35%和12%)的高危人群接受了筛查.这些信息导致两个联盟都专注于提高其社区的筛查率。
结论：为了使复杂系统朝着最佳状态移动（例如，改善糖尿病结局)，利益相关者必须能够获得准确的持续反馈，相关信息，以便做出明智的决定。实施循证干预的传统方法并不能促进这一过程。
