Multi-institutional Consortium for CER in Diabetes Treatment and Prevention

CER 在糖尿病治疗和预防中的多机构联盟

• 批准号: 8033060
• 负责人: JOHN F STEINER
• 金额: $ 892.01万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2013-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8033060
• 关键词: Multi; institutional; Consortium; CER; Diabetes

DESCRIPTION (provided by applicant): Project Summary /Abstract: The HMO Research Network's (HMORN) Diabetes Multi-Center Research Consortium (DMCRC) Coordinating Center proposes to build a national research network and a multi-system distributed database for conducting comparative effectiveness research (CER) in the treatment and prevention of diabetes mellitus. The network is comprised of 31 investigators from 12 integrated healthcare delivery systems and academic institutions who study diabetes mellitus, gestational diabetes mellitus, childhood and adult obesity, weight management, medical informatics and biostatistics. The network has broad experience conducting system-based interventions to improve treatment of diabetes or to support lifestyle changes to prevent diabetes, as well as broad experience conducting CER. The 12-system database will capture and standardize detailed demographic and longitudinal electronic health record (EHR)-derived clinical data on more than 750,000 persons with diabetes and a much larger membership without diabetes. Once constructed, the database will be used to conduct and publish surveillance data on trends (2005- 2012) in the incidence, prevalence, treatment and outcomes of diabetes in this population. It will also be used to conduct two CER studies. The first is a cluster randomized, multi-system intervention that will rapidly identify diabetes patients with "early nonadherence" to newly prescribed anti-diabetic, antihypertensive, and lipid-lowering medications. Early nonadherence refers to patient failure to fill either the first prescription of a new medication or the first refill, and has been shown to be more frequent than "ongoing" nonadherence. This information will be provided to population management outreach teams in 3-5 health systems via the EHR or other electronic database, along with training in counseling patients on adherence problems. Study outcomes of subsequent risk factor change and adherence to the new medication will be compared within each system to those for patients on teams that do not receive the new information. The second CER study is an observational evaluation of various communication, counseling and referral strategies as provided to women who have had an abnormal glucose test (fasting glucose or oral glucose tolerance test) in the first 6 months after a pregnancy complicated by gestational diabetes mellitus (GDM) and who are therefore at very high risk for developing Type 2 diabetes. Study outcomes include weight change over one year and self-reported physical activity four months after the abnormal test. In each study, we will collect process of care data by applying natural language processing (NLP) to clinical text in EHRs and survey patients for information on demographic, clinical, and behavioral variables. These NLP-derived and patient-reported variables will be studied as possible mediators of treatment effectiveness or as potential modifiers of effectiveness (i.e. variables that identify patient subgroups that benefit less from usual interventions. Variables that prove to be important as mediators or modifiers may be good candidates for routine collection and incorporation into EHR's and/or future diabetes registries. PUBLIC HEALTH RELEVANCE: A network of 32 health services and intervention scientists affiliated with the HMO Research Network propose to build a national database for conducting comparative effectiveness research on treatment and on approaches to preventing diabetes mellitus. The database will include information on more than 750,000 persons with diabetes. It will be used to generate ongoing information on the occurrence, treatments and outcomes of diabetes and to conduct 2 studies of approaches to treating and preventing this condition.

描述（由申请人提供）：项目摘要/摘要：HMO研究网络（HMORN）糖尿病多中心研究联盟（DMCRC）协调中心建议建立一个国家研究网络和一个多系统分布式数据库，用于进行糖尿病治疗和预防的比较有效性研究（CER）。该网络由来自12个综合保健提供系统和学术机构的31名研究人员组成，他们研究糖尿病、妊娠糖尿病、儿童和成人肥胖、体重管理、医学信息学和生物统计学。该网络在进行基于系统的干预以改善糖尿病治疗或支持改变生活方式以预防糖尿病方面拥有广泛的经验，并且在进行CER方面拥有广泛的经验。这个由12个系统组成的数据库将收集75万多名糖尿病患者和更多非糖尿病患者的详细人口统计和纵向电子健康记录（EHR）临床数据，并将其标准化。一旦建立，该数据库将被用来进行和发布关于该人群糖尿病发病率、患病率、治疗和结果趋势（2005- 2012年）的监测数据。它还将用于进行两项CER研究。第一个是一个集群随机，多系统的干预，将迅速识别糖尿病患者的“早期不遵守”新规定的抗糖尿病，抗高血压和降脂药物。早期不依从是指患者未能填写新药的第一个处方或第一次续药，并且已被证明比“持续”不依从更频繁。这些信息将通过EHR或其他电子数据库提供给3-5个卫生系统的人口管理外展团队，同时沿着就依从性问题向患者提供咨询的培训。随后的风险因素变化和对新药物的依从性的研究结果将在每个系统内与未收到新信息的团队中的患者进行比较。第二项CER研究是一项观察性评价，评估了为妊娠合并妊娠糖尿病（GDM）后前6个月内血糖检测（空腹血糖或口服葡萄糖耐量试验）异常的女性提供的各种沟通、咨询和转诊策略，因此这些女性患2型糖尿病的风险非常高。研究结果包括一年内的体重变化和异常测试后四个月自我报告的身体活动。在每项研究中，我们将通过将自然语言处理（NLP）应用于EHR中的临床文本来收集护理数据的过程，并调查患者的人口统计学，临床和行为变量信息。这些NLP衍生和患者报告的变量将作为治疗有效性的可能介质或有效性的潜在修饰因子（即，识别从常规干预中获益较少的患者亚组的变量）进行研究。被证明是重要的介质或修饰的变量可能是很好的候选人，为常规收集和纳入EHR的和/或未来的糖尿病登记。 公共卫生相关性：隶属于HMO研究网络的32名卫生服务和干预科学家组成的网络提议建立一个国家数据库，对治疗和预防糖尿病的方法进行比较有效性研究。该数据库将包括75万多名糖尿病患者的信息。它将用于生成有关糖尿病发生、治疗和结局的持续信息，并进行2项治疗和预防这种疾病的方法研究。

项目成果

Intensification of antihyperglycemic therapy among patients with incident diabetes: a Surveillance Prevention and Management of Diabetes Mellitus (SUPREME-DM) study.

糖尿病患者强化抗高血糖治疗：糖尿病监测预防和管理 (SUPREME-DM) 研究。

• DOI: 10.1002/pds.3610
• 发表时间: 2014
• 期刊: Pharmacoepidemiology and drug safety
• 影响因子: 2.6
• 作者: Raebel,MarshaA;Ellis,JenniferL;Schroeder,EmilyB;Xu,Stanley;O'Connor,PatrickJ;Segal,JodiB;Butler,MelissaG;Schmittdiel,JulieA;Kirchner,HLester;Goodrich,GlennK;Lawrence,JeanM;Nichols,GregoryA;Newton,KatherineM;Pathak,Ra
• 通讯作者: Pathak,Ra

Add-On Antihypertensive Medications to Angiotensin-Aldosterone System Blockers in Diabetes: A Comparative Effectiveness Study.

糖尿病血管紧张素-醛固酮系统阻滞剂的附加抗高血压药物：比较有效性研究。

• DOI: 10.2215/cjn.09510817
• 发表时间: 2018
• 期刊: Clinical journal of the American Society of Nephrology : CJASN
• 作者: Schroeder,EmilyB;Chonchol,Michel;Shetterly,SusanM;Powers,JDavid;Adams,JohnL;Schmittdiel,JulieA;Nichols,GregoryA;O'Connor,PatrickJ;Steiner,JohnF
• 通讯作者: Steiner,JohnF

Predictors of Hyperkalemia and Hypokalemia in Individuals with Diabetes: a Classification and Regression Tree Analysis.

糖尿病患者高钾血症和低钾血症的预测因子：分类和回归树分析。

• DOI: 10.1007/s11606-020-05799-x
• 发表时间: 2020
• 期刊: Journal of general internal medicine
• 影响因子: 5.7
• 作者: Schroeder,EmilyB;Adams,JohnL;Chonchol,Michel;Nichols,GregoryA;O'Connor,PatrickJ;Powers,JDavid;Schmittdiel,JulieA;Shetterly,SusanM;Steiner,JohnF
• 通讯作者: Steiner,JohnF

Initial antihyperglycemic drug therapy among 241 327 adults with newly identified diabetes from 2005 through 2010: a surveillance, prevention, and management of diabetes mellitus (SUPREME-DM) study.

2005 年至 2010 年期间，对 241 327 名新发现糖尿病的成年人进行了初步抗高血糖药物治疗：糖尿病的监测、预防和管理 (SUPREME-DM) 研究。

• DOI: 10.1177/1060028013503624
• 发表时间: 2013
• 期刊: The Annals of pharmacotherapy
• 作者: Raebel,MarshaA;Xu,Stanley;Goodrich,GlennK;Schroeder,EmilyB;Schmittdiel,JulieA;Segal,JodiB;O'Connor,PatrickJ;Nichols,GregoryA;Lawrence,JeanM;Kirchner,HLester;ElstonLafata,Jennifer;Butler,Melissa;Newton,KatherineM;Steine
• 通讯作者: Steine

Construction of a multisite DataLink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus: the SUPREME-DM project.

• DOI: 10.5888/pcd9.110311
• 发表时间: 2012
• 期刊: Preventing chronic disease
• 影响因子: 5.5
• 作者: Nichols GA;Desai J;Elston Lafata J;Lawrence JM;O'Connor PJ;Pathak RD;Raebel MA;Reid RJ;Selby JV;Silverman BG;Steiner JF;Stewart WF;Vupputuri S;Waitzfelder B;SUPREME-DM Study Group
• 通讯作者: SUPREME-DM Study Group