ASCEND: ApproacheS to CHC ImplEmeNtation of SDH Data Collection and Action

ASCEND：CHC 实施 SDH 数据收集和行动的方法

• 批准号: 9552061
• 负责人: RACHEL GOLD
• 金额: $ 73万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-25 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9552061
• 关键词: Address; Adopted; Adoption; Adult; Affect; Baseline Surveys; Blood Pressure; Caring; Child Health; Clinic; Clinical; Cluster randomized trial; Communities; Community Health Centers; Data; Data Collection; Diabetes Mellitus; Disease; Electronic Health Record; Evaluation; Funding; General Population; Glycosylated hemoglobin A; Guidelines; Health; Health Insurance; Health Personnel; Health Planning Organizations; Impact evaluation; Informatics; Institute of Medicine (U.S.); Intervention; Knowledge; Lipids; Measures; Medical; Medicare; Methods; National Institute of Diabetes and Digestive and Kidney Diseases; Obesity; Outcome; Patients; Pattern; Pilot Projects; Positioning Attribute; Prevalence; Prevention; Preventive care; Primary Health Care; Process; Provider; Public Health; Quality of Care; Randomized; Recommendation; Reporting; Research; Resources; Risk; Risk Management; Social Work; Standardization; Testing; Training; United States Centers for Medicare and Medicaid Services; Variant; Work; base; care providers; clinical practice; community health study; community intervention; data management; design; diabetes risk; electronic structure; formative assessment; health data; health information technology; implementation science; implementation strategy; improved; multidisciplinary; obesity prevention; obesity risk; programs; recruit; safety net; screening; social health determinants; social integration; standard care; tool; treatment planning; uptake

PROJECT SUMMARY/ABSTRACT: Health risks, outcomes, and care quality for people with / at risk for diabetes mellitus (DM) are profoundly affected by non-clinical factors called ‘social determinants of health’ (SDH). Diverse public health leaders and initiatives – including the Institute of Medicine, the Office of the National Coordinator for Health Information Technology, the Medicare Access & CHIP Reauthorization Act of 2015, and the Centers for Medicare & Medicaid Services 2016 Quality Strategy – emphasize the importance of documenting patients’ SDH data in electronic health records (EHRs), and using this data to inform care. However, little is known about how to help primary care teams routinely collect and act on SDH data using EHR-based tools. This knowledge gap is particularly problematic for the community health centers (CHCs) serving our nation’s most vulnerable patients, whose DM prevalence and risk (notably, obesity rates) are higher than the general population’s, and whose health is particularly impacted by SDH. The proposed trial builds on an NIDDK-funded pilot study in which we developed a suite of EHR-based SDH data management tools for primary care CHCs. In June 2016, these tools went live in 440 CHCs that are located in 19 states, but share a centrally-managed EHR. Having demonstrated that ‘SDH data tools’ can be built for CHCs, we now propose to assess: whether and how pragmatic implementation strategies that support other types of practice change will also help CHC teams systematically identify and take action on the SDH-related needs of adult patients with / at risk for DM; and, the impact of doing so on DM risk management. We will do this as follows. Step 1: Evaluate current EHR-based SDH data collection in 440 CHCs; use those formative results to hone a set of approaches for helping CHCs routinely collect SDH data and integrate it into care plans. Step 2: Conduct a pragmatic, stepped-wedge, cluster-randomized trial. Thirty CHCs will be randomized to one of five 6-month wedges, with staggered timing for receiving the intervention: a scalable implementation support package including technical assistance, training, and six months of access to an ‘SDH Implementation Team’ that will tailor support to meet each CHC’s needs. Step 3: Conduct a realist evaluation of how the impact on: (i) integration of SDH data collection into workflows; (ii) integration of SDH data into care; and (iii) DM risk management (controlled BP, HbA1c, BMI, lipids, etc.; up- to-date recommended care). Per PAR-15-157, we will test implementation strategies that are pragmatic, replicable, delivered under routine conditions, use existing resources, and target standard care processes. Our multidisciplinary team includes experts in SDH, implementation science, informatics, and primary care transformation. Study deliverables will include scalable strategies; results will inform SDH data collection and action implementation guidelines and materials for use by CHCs and primary care providers nationwide.

项目总结/摘要：患有/有风险的人的健康风险、结局和护理质量 糖尿病（DM）受到称为“健康的社会决定因素”的非临床因素的深刻影响 （SDH）。不同的公共卫生领导人和倡议-包括医学研究所， 国家卫生信息技术协调员，医疗保险访问和芯片再授权法案 2015年，以及医疗保险和医疗补助服务中心2016年质量战略-强调了 在电子健康记录（EHR）中记录患者的SDH数据，并使用这些数据为护理提供信息。 然而，关于如何帮助初级保健团队定期收集SDH数据并对其采取行动， 基于EHR的工具这种知识差距对于社区卫生中心（CHCs）来说尤其成问题 服务于我们国家最脆弱的患者，他们的糖尿病患病率和风险（特别是肥胖率）是 这些人的健康尤其受到SDH的影响。拟定试验 建立在NIDDK资助的试点研究的基础上，在该研究中，我们开发了一套基于EHR的SDH数据管理 初级保健中心的工具。2016年6月，这些工具在19个州的440个社区卫生中心投入使用， 但是共享一个集中管理的EHR。在证明了可以为CHC构建“SDH数据工具”之后，我们 现在建议评估：是否以及如何采取务实的执行战略， 实践改变的类型也将帮助CHC团队系统地识别并采取行动， 患有DM/有DM风险的成年患者的SDH相关需求;以及这样做对DM风险的影响 管理我们将按照以下步骤进行。步骤1：评估440中当前基于EHR的SDH数据收集 CHC;使用这些形成性结果来完善一套方法，以帮助CHC定期收集SDH数据 并将其纳入护理计划。第二步：进行一项实用的、阶梯式的随机分组试验。 30名CHC将随机分配至5个6个月楔形块中的一个，接受 干预措施：一个可扩展的执行支助一揽子计划，包括技术援助、培训和六个 一个“SDH实施团队”将提供为期数月的支持，以满足每个CHC的需求。步骤 3：对以下方面的影响进行现实的评估：㈠将SDH数据收集纳入工作流程; ㈡ 将SDH数据整合到护理中;以及（iii）DM风险管理（控制BP、HbA 1c、BMI、血脂等）;向上- 最新推荐护理）。根据PAR-15-157，我们将测试实用的实施策略， 可复制的，在常规条件下提供的，使用现有资源，并针对标准护理过程。 我们的多学科团队包括SDH、实施科学、信息学和初级保健方面的专家 转型研究成果将包括可扩展的战略;结果将为SDH数据收集提供信息， 供全国社区卫生中心和初级保健提供者使用的行动执行准则和材料。