Testing a Medication Risk Communication and Surveillance Strategy: The EMC2 Trial
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,005
- 试验地点
- 2
- 主要终点
- Medication Knowledge (0-100)
研究概览
简要总结
This study evaluates the effectiveness of an electronic health record based educational intervention (the EMC2 strategy) to improve patient understanding and use of higher-risk medications. Half of the participants will receive the intervention, while the other half will receive the usual amount of information (usual care).
详细描述
Research has repeatedly demonstrated that individuals lack essential information on how to safely take prescribed (Rx) medications. A risk communication and surveillance strategy is needed in primary care to ensure that patients are adequately informed about medication risks and are taking prescribed regimens safely.
The investigators devised an Electronic health record-based Medication Complete Communication (EMC2) Strategy that leverages electronic health record (EHR) and interactive voice response (IVR) technologies to:
- prompt and guide provider counseling,
- automate the delivery of Medication Guides at prescribing,
- follow patients post-visit to confirm prescription understanding and use, and
- deliver a care alert back to providers to inform them of any potential harms.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- None
入排标准
- 年龄范围
- 21 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •21 and older
- •English or spanish speaking
- •Primarily responsible for administering own medications
- •New prescription of one of 66 study medications on day of recruitment
- •Has a personal mobile or land line phone
排除标准
- •Severe, uncorrectable vision
- •Hearing or cognitive impairments
结局指标
主要结局
Medication Knowledge (0-100)
时间窗: Baseline to 3 Months post baseline
Adjusted Least-square means of Medication Knowledge are calculated based on patient's ability to identify each medication's purpose and side effects, risks, warnings and benefits using general linear mixed models, specifying the identity link (PROC GLIMMIX). Treatment assignment by time is the independent variable of interest and modeled as a fixed effect, and clinic as a random effect, with additional subject statement to model correlations with patient. Confounding variables, such as age, preferred language, race, education, health status, number of chronic diseases, drug class, and health literacy (Newest Vital Sign) are included as fixed effects in the model. Patients are asked 10 questions (a scale developed by our team), and each questions is scored as correct/incorrect, and percentage of correctly answered questions is calculated (0-100 with 100 as best). Results are presented as adjusted least square means with 95% Confidence Intervals
次要结局
- Probability of Prescription Medication Proper Use(1 Month post baseline to 3 Months post baseline)
研究者
Michael S. Wolf
Associate Division Chief - Research Division of General Internal Medicine
Northwestern University