Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania 15213, USA.
J Am Coll Radiol. 2010 Jun;7(6):431-8. doi: 10.1016/j.jacr.2010.02.001.
Peer review is an essential process for physicians because it facilitates improved quality of patient care and continuing physician learning and improvement. However, peer review often is not well received by radiologists who note that it is time intensive, is subjective, and lacks a demonstrable impact on patient care. Current advances in peer review include the RADPEER() system, with its standardization of discrepancies and incorporation of the peer-review process into the PACS itself. The purpose of this study was to build on RADPEER and similar systems by using a mathematical model to optimally select the types of cases to be reviewed, for each radiologist undergoing review, on the basis of the past frequency of interpretive error, the likelihood of morbidity from an error, the financial cost of an error, and the time required for the reviewing radiologist to interpret the study.
The investigators compiled 612,890 preliminary radiology reports authored by residents and attending radiologists at a large tertiary care medical center from 1999 to 2004. Discrepancies between preliminary and final interpretations were classified by severity and validated by repeat review of major discrepancies. A mathematical model was then used to calculate, for each author of a preliminary report, the combined morbidity and financial costs of expected errors across 3 modalities (MRI, CT, and conventional radiography) and 4 departmental divisions (neuroradiology, abdominal imaging, musculoskeletal imaging, and thoracic imaging).
A customized report was generated for each on-call radiologist that determined the category (modality and body part) with the highest total cost function. A universal total cost based on probability data from all radiologists was also compiled.
The use of mathematical models to guide case selection could optimize the efficiency and effectiveness of physician time spent on peer review and produce more concrete and meaningful feedback to radiologists undergoing peer review.
同行评议对于医生来说是一个至关重要的过程，因为它可以提高患者护理质量和医生的持续学习和改进。然而，放射科医生往往对同行评议不太满意，他们指出同行评议既耗时，又主观，而且缺乏对患者护理的明显影响。目前，同行评议的进展包括 RADPEER()系统，该系统标准化了差异，并将同行评议过程纳入 PACS 本身。本研究的目的是在 RADPEER 和类似系统的基础上，使用数学模型根据过去的解释错误频率、错误导致发病的可能性、错误的财务成本以及审阅放射科医生解释研究所需的时间，为每位接受审查的放射科医生优化选择要审查的病例类型。
研究人员从 1999 年至 2004 年，汇编了一家大型三级保健医疗中心的住院医师和主治放射科医生撰写的 612,890 份初步放射学报告。初步和最终解释之间的差异按严重程度分类，并通过对主要差异的重复审查进行验证。然后使用数学模型为每位初步报告的作者计算了在 3 种模态（MRI、CT 和常规放射摄影）和 4 个科室（神经放射科、腹部成像、肌肉骨骼成像和胸部成像）中预计错误的综合发病和财务成本。
为每位值班放射科医生生成了一份定制报告，该报告确定了总费用函数最高的类别（模态和身体部位）。还汇编了基于所有放射科医生概率数据的通用总费用。
使用数学模型来指导病例选择可以优化放射科医生在同行评议上花费的时间效率和效果，并为接受同行评议的放射科医生提供更具体和有意义的反馈。
