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临床算法疾病分类学:一种比较算法指南的方法。

The clinical algorithm nosology: a method for comparing algorithmic guidelines.

作者信息

Pearson S D, Margolis C Z, Davis S, Schreier L K, Gottlieb L K

机构信息

Clinical Guidelines Program, Harvard Community Health Plan, Brookline, Massachusetts.

出版信息

Med Decis Making. 1992 Apr-Jun;12(2):123-31. doi: 10.1177/0272989X9201200205.

Abstract

Concern regarding the cost and quality of medical care has led to a proliferation of competing clinical practice guidelines. No technique has been described for determining objectively the degree of similarity between alternative guidelines for the same clinical problem. The authors describe the development of the Clinical Algorithm Nosology (CAN), a new method to compare one form of guideline: the clinical algorithm. The CAN measures overall design complexity independent of algorithm content, qualitatively describes the clinical differences between two alternative algorithms, and then scores the degree of similarity between them. CAN algorithm design-complexity scores correlated highly with clinicians' estimates of complexity on an ordinal scale (r = 0.86). Five pairs of clinical algorithms addressing three topics (gallstone lithotripsy, thyroid nodule, and sinusitis) were selected for interrater reliability testing of the CAN clinical-similarity scoring system. Raters categorized the similarity of algorithm pathways in alternative algorithms as "identical," "similar," or "different." Interrater agreement was achieved on 85/109 scores (80%), weighted kappa statistic, k = 0.73. It is concluded that the CAN is a valid method for determining the structural complexity of clinical algorithms, and a reliable method for describing differences and scoring the similarity between algorithms for the same clinical problem. In the future, the CAN may serve to evaluate the reliability of algorithm development programs, and to support providers and purchasers in choosing among alternative clinical guidelines.

摘要

对医疗成本和质量的关注导致了相互竞争的临床实践指南大量涌现。目前尚未有描述用于客观确定针对同一临床问题的替代指南之间相似程度的技术。作者描述了临床算法分类法(CAN)的开发,这是一种比较一种指南形式(即临床算法)的新方法。CAN可测量与算法内容无关的整体设计复杂性,定性描述两种替代算法之间的临床差异,然后对它们之间的相似程度进行评分。CAN算法设计复杂性评分与临床医生按顺序量表对复杂性的估计高度相关(r = 0.86)。选择了针对三个主题(胆结石碎石术、甲状腺结节和鼻窦炎)的五对临床算法进行CAN临床相似性评分系统的评分者间可靠性测试。评分者将替代算法中算法路径的相似性分类为“相同”、“相似”或“不同”。在109个评分中有85个(80%)达成了评分者间的一致性,加权kappa统计量k = 0.73。结论是,CAN是确定临床算法结构复杂性的有效方法,也是描述同一临床问题算法之间差异并对其相似性进行评分的可靠方法。未来,CAN可用于评估算法开发程序的可靠性,并支持提供者和购买者在替代临床指南中进行选择。

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