Rosner Benjamin I, Zwaan Laura, Olson Andrew P J
Division of Hospital Medicine and Center for Clinical Informatics and Improvement Research, University of California, San Francisco, CA, USA.
Institute of Medical Education Research Rotterdam, Erasmus MC, Rotterdam, Netherlands.
Diagnosis (Berl). 2022 Nov 16;10(1):31-37. doi: 10.1515/dx-2022-0055. eCollection 2023 Feb 1.
Diagnostic performance is uniquely challenging to measure, and providing feedback on diagnostic performance to catalyze diagnostic recalibration remains the exception to the rule in healthcare. Diagnostic accuracy, timeliness, and explanation to the patient are essential dimensions of diagnostic performance that each intersect with a variety of technical, contextual, cultural, and policy barriers. Setting aside assumptions about current constraints, we explore the future of diagnostic performance feedback by describing the "minimum viable products" and the "ideal state" solutions that can be envisioned for each of several important barriers. Only through deliberate and iterative approaches to breaking down these barriers can we improve recalibration and continuously drive the healthcare ecosystem towards diagnostic excellence.
诊断性能的衡量极具挑战性,而在医疗保健领域,就诊断性能提供反馈以促进诊断重新校准仍是罕见的例外情况。诊断准确性、及时性以及向患者做出解释,是诊断性能的关键维度,每一个维度都与各种技术、背景、文化和政策障碍相互交织。抛开对当前限制的假设,我们通过描述针对几个重要障碍中每一个障碍可设想的“最小可行产品”和“理想状态”解决方案,来探索诊断性能反馈的未来。只有通过深思熟虑且反复迭代的方法来打破这些障碍,我们才能改进重新校准,并持续推动医疗保健生态系统迈向卓越诊断。