Reducing Errors in the Diagnosis of Melanoma using an Intelligent Tutoring System

使用智能辅导系统减少黑色素瘤的诊断错误

• 批准号: 7236310
• 负责人: DANA MARIE GRZYBICKI
• 金额: $ 27.6万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-30 至 2008-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7236310
• 关键词: clinical research; computer assisted diagnosis; computer simulation; cooperative study; diagnosis design /evaluation; diagnosis quality /standard; health services research tag; human data; human subject; melanoma; neoplasm /cancer diagnosis; patient safety /medical error

DESCRIPTION (PROVIDED BY APPLICANT): Our objective is to improve the diagnostic accuracy of community generalist pathologists for malignant melanoma through the use of a cognitive simulation system. Medical error research and clinical error reduction initiatives to date have primarily focused on therapeutic (e.g. medication) errors rather than on diagnostic errors. The diagnostic error rate in general surgical pathology is generally accepted to be approximately 1 %, although there is evidence that these errors are most likely underreported. Cancer of the skin is the most common of all cancers, and melanoma accounts for about 4% of skin cancer cases but causes a large majority of skin cancer deaths. The American Cancer Society estimates that the number of new melanomas diagnosed in the United States is increasing, and about 7,910 people are expected to die of melanomas during 2006. Since 1973, the mortality rate for melanoma has increased by 50%. False negative diagnostic errors for malignant melanoma are the most frequent diagnostic errors for which patients pursue litigation against pathologists and previous studies have estimated that approximately 10% of all pigmented lesions examined are associated with a clinically significant false negative error related to melanoma resulting in significant harm to patients. Previous studies have also shown that generalist pathologists in community private practices (the majority of pathologists examining pigmented lesions) tend to make more errors than pathologists who have received specialty dermatopathology training. This project represents a logical collaboration between two previously independent, successful, and productive investigators. The first is the proposed project PI; a significant portion of her work has been on a project showing how multi institutional voluntary sharing and root cause analysis of anatomic pathology diagnostic errors (including errors related to melanoma) may lead to successful process changes that reduce errors. The second is one of the proposed co-investigators (Crowley), whose major focus has been on the development, deployment, and evaluation of a highly novel cognitive simulation tool, an intelligent tutoring system, which has been shown to effectively improve diagnostic performance for melanomas and other melanocytic lesions. In order to achieve our objective, we aim to test the effectiveness of the intelligent tutoring system as a performance improvement and error reduction intervention in a prospective case control study, with volunteer community pathologists as study subjects. Pre- and post-interventional performance and error rates will be longitudinally measured and tracked. The result of this project will be a model diagnostic error reduction system for melanoma using cognitive simulation that we plan to use locally for proficiency testing and training and to enhance for use at national educational conferences and for national networking.

描述（由申请人提供）：我们的目标是通过使用认知模拟系统来提高社区通才病理学家对恶性黑色素瘤的诊断准确性。迄今为止，医疗错误研究和减少临床错误的举措主要关注治疗（例如用药）错误，而不是诊断错误。一般外科病理学的诊断错误率被普遍认为约为 1%，尽管有证据表明这些错误很可能被低估。癌症的 皮肤癌是所有癌症中最常见的，黑色素瘤约占皮肤癌病例的 4%，但导致大部分皮肤癌死亡。美国癌症协会估计，美国新诊断出的黑色素瘤数量正在增加，预计2006年约有7,910人死于黑色素瘤。自1973年以来，黑色素瘤的死亡率已增加了50%。恶性黑色素瘤的假阴性诊断错误是最常见的诊断错误，患者因此向病理学家提起诉讼，之前的研究估计，所有检查的色素病变中约有 10% 与黑色素瘤相关的临床显着假阴性错误有关，从而对患者造成重大伤害。先前的研究还表明，全科病理学家 社区私人诊所（大多数病理学家检查色素病变）往往比接受过专业皮肤病理学培训的病理学家犯更多错误。该项目代表了两位先前独立、成功且富有成效的研究人员之间的逻辑合作。第一个是拟定的项目PI；她的工作的很大一部分是在一个项目上，该项目展示了多机构自愿共享和解剖病理学诊断错误（包括与黑色素瘤相关的错误）的根本原因分析如何导致成功的流程变革，从而减少错误。第二个是拟议的联合研究人员之一（克劳利），他的主要重点是开发、部署、 以及对一种高度新颖的认知模拟工具（智能辅导系统）的评估，该工具已被证明可以有效提高黑色素瘤和其他黑色素细胞病变的诊断性能。为了实现我们的目标，我们旨在以社区病理学家志愿者为研究对象，在前瞻性病例对照研究中测试智能辅导系统作为绩效改进和减少错误干预措施的有效性。将纵向测量和跟踪干预前后的表现和错误率。该项目的成果将是使用认知模拟的黑色素瘤诊断错误减少模型系统，我们计划在本地使用该系统进行能力测试和培训，并增强在国家教育会议和国家网络中的使用。