Reducing Clinical Inertia in Obesity Management of Diabetes in Primary Care: Cluster-Randomized Trial

减少初级保健中糖尿病肥胖管理的临床惰性：整群随机试验

基本信息

批准号：
10618142
负责人：
PATRICK J O'CONNOR
金额：
$ 65.63万
依托单位：
HEALTHPARTNERS INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-01 至 2026-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10618142
关键词：
Address Adopted Adult Affect Age American Arthritis Behavior Therapy Benefits and Risks Body Weight decreased Body mass index Caring Clinic Clinical Clinical Decision Support Systems Cluster randomized trial Communication Data Reporting Decision Support Model Diabetes Mellitus Disease Effectiveness Electronic Health Record Eligibility Determination Equation Evaluation FDA approved Health Health Information System Hypertension Intervention Investments Life Style Link Metabolic Morbid Obesity Myocardial Infarction Non-Insulin-Dependent Diabetes Mellitus Obesity Online Systems Operative Surgical Procedures Outcome Outpatients Patient Care Patients Performance Pharmaceutical Preparations Pharmacologic Substance Pharmacotherapy Prevalence Primary Care Privatization Randomized Regimen Reporting Sampling Sleep Apnea Syndromes Stroke Suggestion Surveys Time Translating Update Visit Weight Weight maintenance regimen Work adult obesity bariatric surgery blood glucose regulation care delivery clinical care clinical decision support clinical encounter design diabetes management effective therapy electronic medical record system evidence base high risk improved indexing innovation lifestyle intervention neglect obese patients obesity management obesity treatment patient oriented point of care predictive modeling primary care clinic primary care clinician primary outcome randomized trial satisfaction sex shared decision making treatment as usual

项目摘要

Project Summary Obesity has been steadily increasing in prevalence and now affects more than 4 in 10 U.S. adults, leading to many adverse health outcomes including myocardial infarction, stroke, type 2 diabetes (T2DM), hypertension, sleep apnea, arthritis, and others. Effective surgical, pharmaceutical, and behavioral treatments for obesity are available, and the evidence to support the broad use of these treatments for obesity is very well established. However, active management of obesity defined as prescribing or referring adults with obesity for lifestyle, pharmaceutical, or surgical treatment of obesity, is greatly underused. Major underlying reasons for underutilization of effective obesity treatments include: (a) both patients and primary care clinicians (PCCs) frequently underestimate the effectiveness and potential benefits of obesity treatments; and (b) both patients and clinicians typically lack access to evidence-based, patient-specific estimates of the potential benefits and risks of appropriate patient-specific obesity treatment options. To address this problem, we integrate externally validated prediction equations that estimate benefits and risk of various obesity treatment options in adults with T2DM into a widely-used and successful clinical decision support system in order to deliver appropriate patient-specific obesity treatment suggestions at the point of care. We implement a scalable, web-based point-of-care decision-support intervention in a randomized trial in 40 primary care clinics with 15,814 eligible patients, and assess intervention impact on the following primary outcomes: (a) appropriate referral of eligible patients for evaluation for metabolic bariatric surgery (MBS); (b) appropriate initiation of FDA-approved medications for weight loss; (c) weight trajectories; and (d) patient- reported conversations with their PCC about weight loss and intentions to engage in weight loss. In addition, we collect and analyze clinician-reported and patient-reported data to identify factors that may impede or facilitate broad dissemination of this intervention strategy to other care delivery settings. This innovative project will (a) provide state-of-the-art scientific evidence on obesity treatment to large numbers of obese American adults with T2DM and their PCCs at the point of care; (b) help PCCs identify appropriate patient-specific obesity treatment options; (c) implement in primary care a web-based EHR-linked obesity treatment clinical decision support model that uses state-of-the-art HIT standards, is broadly scalable, easy to update as evidence changes, and optimized for clear communication of information to patients and PCCs; and (d) improve the clinical return on ongoing massive private and public investments in outpatient health information systems.

项目概要肥胖症的患病率一直在稳步上升，目前影响超过十分之四的美国成年人，导致许多不良健康后果，包括心肌梗塞、中风、2 型糖尿病 (T2DM)、高血压、睡眠呼吸暂停、关节炎等。肥胖症的有效手术、药物和行为治疗包括现有证据支持广泛使用这些治疗肥胖症的方法。然而，肥胖的积极管理定义为对肥胖成年人进行处方或转介生活方式，肥胖症的药物或手术治疗尚未得到充分利用。主要根本原因有效的肥胖治疗方法未得到充分利用包括：(a) 患者和初级保健临床医生 (PCC) 经常低估肥胖治疗的有效性和潜在益处； (b) 两名患者临床医生通常缺乏对潜在益处和患者具体情况的基于证据的估计适当的患者特异性肥胖治疗方案的风险。为了解决这个问题，我们集成了外部验证的预测方程来估计收益和风险将成人 T2DM 的各种肥胖治疗方案纳入广泛使用且成功的临床决策支持系统，以便在患者出现问题时提供适当的针对特定患者的肥胖治疗建议关心。我们在一项随机试验中实施了可扩展的、基于网络的护理点决策支持干预措施 40 个初级保健诊所有 15,814 名符合资格的患者，并评估干预措施对以下初级保健的影响结果：(a) 适当转诊符合条件的患者进行代谢减肥手术（MBS）评估； (二) 适当开始使用 FDA 批准的减肥药物； (c) 体重轨迹； (d) 病人- 报告了与 PCC 关于减肥和减肥意图的对话。此外，我们收集并分析临床医生报告和患者报告的数据，以确定可能阻碍或促进将该干预策略广泛传播到其他护理服务机构。该创新项目将 (a) 为大量人群提供关于肥胖治疗的最先进的科学证据患有 T2DM 的美国肥胖成年人及其 PCC 在护理点的比例； (b) 帮助 PCC 确定适当的针对患者的肥胖治疗方案； (c) 在初级保健中实施基于网络的电子病历相关肥胖治疗临床决策支持模型采用最先进的 HIT 标准，具有广泛的可扩展性，易于随着证据的变化进行更新，并进行优化，以便向患者和 PCC 清晰地传达信息；和 (d) 提高门诊医疗领域持续大规模私人和公共投资的临床回报信息系统。