MALPRACtice Insurers' Medical Error Prevention Study

目标。这5项研究的目标是：1)利用医疗事故保险计划作为全国性错误报告系统的潜力；2)确定在集中审查医疗事故索赔文件中发现的错误的最常见因素；3)测试病例对照分析，将其作为一种量化各种促成因素对特定错误发生的作用的方法；4)评估通过索赔文件分析检测到的错误模式和影响因素与其他报告系统中确定的错误模式和影响因素进行比较；5)使用索赔数据促进一系列有针对性的患者安全干预措施的设计和实施。方法：研究方法。将分析来自6家大型医疗事故保险公司的约3,000份索赔文件。(这些保险公司总共覆盖了15个州的大约35,000名医生、60家急诊医院和100多家门诊机构)。使用结构化审查方法，医生审查员将识别错误，描述其后果，并判断各种人为因素的贡献作用，包括环境条件(例如，工作量、技术、干扰)、团队/团体行为(例如，移交不充分、沟通失败、缺乏监督、未能遵守/打破既定的协议)以及个人因素(例如，缺乏经验、技术能力不足)。描述性分析技术将被用来分离在每个临床类别中最常涉及特定错误的因素的组合。两个补充数据来源将支持更深入的分析：1)向5家医院的风险管理人员报告的400个“潜在索赔”的人为因素信息；2)审查720-1280个医疗记录(“对照”)。这些数据将使：(A)将造成潜在索赔错误的因素与实际索赔中发现的因素进行比较；(B)3-4。病例对照分析旨在通过隔离作为具体错误的关键原因的那些因素来帮助确定干预措施。干预措施。研究结果将指导在参与保险公司覆盖的机构中确定和设计一系列干预措施。调查员将通过以下方式促进机构选择、设计和实施干预措施：招募和指导协调小组；招募干预小组；通过安全协作组支持干预小组，其中将包括现场

Goals. The 5 study goals are: 1) to harness the potential of malpractice insurance programs to operate as a nationwide error reporting system; 2) to identify the most frequent factors contributing to errors found in a focused review of malpractice claims files; 3) to test case-control analysis as a method of quantifying the role of various contributing factors to the occurrence of specific errors; 4) to assess how the patterns of errors and contributing factors detected through claims file analysis compare to those identified in other reporting systems; 5) to use claims data to facilitate design and implementation of a series of targeted patient safety interventions. Methods. Approximately 3,000 claims files from 6 large malpractice insurers will be analyzed. (Together, these insurers cover approximately 35,000 physicians, 60 acute care hospitals, and more than 100 outpatient facilities in 15 states). Using structured review methods, physician reviewers will identify errors, describe their consequences, and judge the contributing role of a wide range of human factors, including environmental conditions (e.g. workload, technology, interruptions), team/group behavior (e.g. inadequate hand-off, communication failures, lack of supervision, failure to follow/break established protocols), and individual factors (e.g. inexperience, technical incompetence). Descriptive analytical techniques will be used to isolate the combinations of factors that are most frequently implicated in specific errors within each of the clinical categories. Two supplementary data sources will support more in-depth analyses: 1) human factors information on 400 "potential claims" reported to risk managers at 5 hospitals; 2) reviews of 720-1280 medical records ("controls"). These data will allow: a) comparison of factors that contributing to errors in potential claims with those detected in actual claims; (b) 3-4. case-control analyses to designed to help target interventions by isolating those factors that are the key causes of specific errors. Interventions. Study findings will guide identification and design of a series of interventions at institutions covered by the participating insurers. Investigators will facilitate institutions' choice, design, and implementation of interventions through: recruitment and orientation of Coordinating Teams; recruitment of Intervention Teams; support of Intervention Teams through a Safety Collaborative, which will include site