Improving Quality of postoperative pain care through innovative use of electronic health records

通过电子健康记录的创新使用提高术后疼痛护理的质量

• 批准号: 8943308
• 负责人: Tina Hernandez-Boussard
• 金额: $ 23.14万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8943308
• 关键词: Improving; Quality; postoperative; pain; care

 DESCRIPTION (provided by applicant): Millions of Americans undergo surgery every year, and postoperative pain is common and too often poorly managed. Poorly managed postoperative pain may cause severe functional impairment, adverse events, impaired care of the underlying diseases, transition to chronic pain, and decreased quality of life. Many controlled studies have demonstrated a variety of interventions that benefit postoperative pain, yet their application in a large and more diverse population is unknown, and a nationally endorsed, concise quality process metric for postoperative pain management does not exist. One roadblock is that postoperative pain and its related outcomes are complex. The gathering of evidence from electronic health data, which draw from and inform real-world practice, could bypass this roadblock and inform decisions leading to more effective and efficient postoperative pain management. This project seeks to measure quality of various care processes for postoperative pain, assess proposed evidence-based interventions from randomized controlled trials, lay the ground work for systematic pain-related research using EMRs, and produce population-based evidence for a nationally-endorsed postoperative pain management quality metric. To achieve these objectives, this project has three specific aims: (1) to develop standardized electronic definitions of pain-related care processes and outcomes (e.g. prolonged opioid use, readmission for pain, etc.); (2) to extract clinically meaningful data from both structured data and free text in electronic medical records (EMR) and examine the relationship between recommended care processes and outcomes for postoperative pain using EMRs; (3) to validate pain-related process-outcome relationships at a national level and to develop a National Quality Forum submission and evaluation form for a postoperative pain quality metric(s). This project will achieve these aims by developing data capture algorithms on Palo Alto Veterans Administration (VA) Healthcare data, refining algorithms at a tertiary academic hospital, and validating algorithms on the National VA healthcare system. Data will be identified and extracted from the EMR using an extended version of our validated data-mining workflow. Our established experience with quality metric development and NQF endorsement will facilitate the dissemination of this work. These approaches are the basis of a learning healthcare system, and the proposed research directly aligns with AHRQ's mission and goals to improve healthcare quality through health information technology and data resources.

 描述（由申请人提供）：每年有数百万美国人接受手术，术后疼痛很常见，而且往往管理不善。术后疼痛管理不善可能导致严重的功能障碍、不良事件、基础疾病护理受损、转变为慢性疼痛和生活质量下降。许多控制 研究已经证明了多种干预措施对术后疼痛有益，但是它们在更大和更多样化的人群中的应用是未知的，并且不存在用于术后疼痛管理的全国认可的简明质量过程度量。其中一个障碍是术后疼痛及其相关结果是复杂的。从电子健康数据中收集证据，这些数据来自现实世界的实践并为之提供信息，可以绕过这一障碍，并为决策提供信息，从而实现更有效和更高效的术后疼痛管理。该项目旨在衡量术后疼痛的各种护理过程的质量，评估随机对照试验中提出的循证干预措施，为使用EMR进行系统性疼痛相关研究奠定基础，并为全国认可的术后疼痛管理质量指标提供基于人群的证据。为实现这些目标，该项目有三个具体目标：（1）制定与疼痛相关的护理过程和结果的标准化电子定义（例如，长期使用阿片类药物，因疼痛再次入院等）; (2)从电子病历（EMR）中的结构化数据和自由文本中提取有临床意义的数据，并使用EMR检查术后疼痛的推荐护理过程和结果之间的关系;（3）在国家层面验证疼痛相关过程-结果关系，并制定国家质量论坛提交和评估表，用于术后疼痛质量度量。该项目将通过在帕洛阿尔托退伍军人管理局（VA）医疗保健数据上开发数据捕获算法，在三级学术医院改进算法，并在国家VA医疗保健系统上验证算法来实现这些目标。数据将被识别，并使用我们的验证数据挖掘工作流程的扩展版本从电子病历中提取。我们在质量指标开发和NQF认可方面的既定经验将促进这项工作的传播。这些方法是学习型医疗保健系统的基础，拟议的研究直接与AHRQ通过健康信息技术和数据资源提高医疗保健质量的使命和目标相一致。