DECODE: Diagnostic Excellence Center on Diagnostic Error

DECODE：诊断错误诊断卓越中心

• 批准号: 10641651
• 负责人: Ramin Khorasani
• 金额: $ 99.29万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2026-09-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10641651
• 关键词: DECODE; Diagnostic; Excellence; Center; Error

Abstract We plan to establish a Diagnostic Center of Excellence that will focus on reducing diagnostic errors related to diagnostic imaging in two ways. We will: 1) implement a highly reliable and resilient system to enhance safety by reducing failures in timely performance of clinically necessary diagnostic imaging examinations and interpretative errors (Safety 2), and 2) improve diagnostic precision by building consensus using available evidence around four common causes of diagnostic errors – findings that may lead to a diagnosis of lung, prostate, pancreas and adrenal cancer. The DCE will build on strong pre-existing research and operational collaboration between a team of safety scientists, biomedical informaticists and health services researchers at the Massachusetts General Brigham (MGB) Health System. MGB is comprised of 2 tertiary academic hospitals, 7 community acute care hospitals, 3 specialty hospitals, multiple ambulatory care and outpatient imaging facilities serving patients in ambulatory, inpatient and ED settings, with a provider network of over 10,000 employed and affiliated primary care and specialty care physicians. Recent integration at MGB has prioritized clinical integration, creating a single Office of the Chief Operating Officer, a single Office of the Chief Medical Officer, and a single Enterprise Radiology governance including for quality and safety. We will enhance a set of pre-existing limited implementation information technology-enabled functions and workflows before MGB-wide expansion to address multiple types of diagnostic errors, including those leading to missed, incorrect, or delayed diagnoses. Enhancements will improve EHR-integration, monitoring and learning capabilities of our Clinical Dashboard to better address health disparities, to help advance an equity-informed resilient system and associated workflows. Another system for Peer Learning will also be implemented to target interpretive errors in diagnostic imaging. Finally, we will convene a multispecialty team of clinicians to build consensus on recommendations for diagnosis and management of findings that may lead to lung, prostate, pancreatic and adrenal cancer based on available evidence using a Modified Delphi process. Evidence that are agreed upon will be embedded in a clinical decision support system that will be integrated with the electronic health record. All specifications for systems and workflow processes, consensus results, and lessons learned will be disseminated broadly through national conferences and meetings, a public website, networks of clinical practice and institutions, and social media.

摘要