Evidence Based Decision Making: Integrating Clinical Prediction Rules into Electr

基于证据的决策：将临床预测规则集成到 Electr 中

• 批准号: 7938103
• 负责人: THOMAS G MCGINN
• 金额: $ 37.5万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-01-18
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7938103
• 关键词: Evidence; Based; Decision; Making; Integrating

DESCRIPTION (provided by applicant): Clinical prediction rules (CPRs) are frontline decision aids that help physicians make evidence-based, cost effective decisions that benefit their patients. CPRs are proven tools that translate evidence into practice, increase quality while reducing costs, and can be used by physicians in a wide variety of clinical settings, such as primary care offices, emergency rooms, and hospitals. While many CPRs have been developed and validated over the years, health care providers have yet to incorporate them into everyday care. CPRs aid providers in assessing the impact of individual components of a patient's history, physical examination, and basic lab results to estimate probability of disease or potential response to a treatment. Prediction rules use data that is readily available at the time of a patient encounter and often reduce unnecessary treatments and diagnostic testing. CPRs differ from reminder systems or alerts in that CPRs pull in aspects of the history and physical exam and in an evidence based fashion estimate probabilities, prognosis, or make treatment recommendations. The goal of this study is to utilize patient electronic health records to incorporate CPRs into the face-to-face patient encounter. We propose to select certain clinical situations where well-validated CPRs are available and likely to be needed on a frequent basis. We will randomly assign an integrated CPR versus usual care into the point of care and evaluate the impact of this integration on doctor behavior and evidence-based decision making. Mount Sinai's Division of General Internal Medicine (DGIM) has significant experience with all aspects of CPRs, including derivation, validation, implementation, and systematic review. Furthermore, the Division has developed an interactive web library of CPRs for clinical use that is one of the most widely sites of its kind. We propose to collaborate with Epic, one of the nation's largest and most respected electronic medical record (EMR) companies, to integrate validated CPRs into EMRs and assess the impact on provider behavior and patient care.

描述（由申请人提供）：临床预测规则（CPR）是一线决策辅助工具，可帮助医生做出有利于患者的循证、成本效益高的决策。CPR是经过验证的工具，可以将证据转化为实践，提高质量，同时降低成本，并且可以由医生在各种临床环境中使用，例如初级保健办公室，急诊室和医院。虽然多年来已经开发和验证了许多CPR，但卫生保健提供者尚未将其纳入日常护理。CPR帮助提供者评估患者病史、体格检查和基本实验室结果的各个组成部分的影响，以估计疾病的可能性或对治疗的潜在反应。预测规则使用在患者就诊时容易获得的数据，并且通常减少不必要的治疗和诊断测试。CPR与提醒系统或警报的不同之处在于，CPR引入了病史和体检的方面，并且以基于证据的方式估计概率、预后， 或提出治疗建议。 本研究的目的是利用患者电子健康记录，将CPR纳入面对面的患者接触。我们建议选择某些临床情况下，经过充分验证的CPR是可用的，并可能需要频繁的基础上。我们将随机分配一个综合心肺复苏术与常规护理到护理点，并评估这种整合对医生行为和循证决策的影响。Mount Sinai的普通内科（DGIM）部门在CPR的各个方面都有丰富的经验，包括推导，验证，实施和系统评价。此外，该司还开发了一个供临床使用的国家方案建议互动网络图书馆，这是同类网站中使用最广泛的网站之一。我们 建议与Epic合作，Epic是美国最大和最受尊敬的电子医疗记录（EMR）公司之一，将经过验证的CPR整合到EMR中，并评估对提供者行为和患者护理的影响。