背景:多学科团队会议根据患者和疾病特征制定基于指南的个人治疗计划,并激发偏差的原因。临床决策树可以支持多学科团队更准确地遵守指南。每个临床决策树都是针对护理路径中的特定决策时刻而定制的,并且由患者和疾病特征组成,从而得出指南建议。
目的:本研究调查了(1)多学科团队建议与临床决策树建议之间的一致性,以及(2)多学科团队会议期间可获得的患者和疾病特征的完整性,以应用临床决策树,从而导致指南建议。
方法:这种前瞻性,多中心,观察性一致性研究评估了17个选定的临床决策树,根据荷兰流行的乳房指南,结直肠癌和前列腺癌。如果有足够的数据,多学科团队和临床决策树建议之间的一致性被归类为一致性,条件一致(多学科团队指定了推荐的先决条件)和不一致.
结果:在8家不同的医院参加了59个多学科小组会议,包括355例。对于296例(83.4%),所有患者数据均可用于提供无条件临床决策树建议.59例(16.6%),没有足够的数据,因此提出了临时临床决策树建议.从296个成功生成的临床决策树建议,在249例(84.1%)病例中,多学科小组的建议是一致的,24例(8.1%)有条件一致,23例(7.8%)有不一致,其中7例(2.4%)中,偏离临床决策树生成的指南建议的原因不是出于动机.
结论:在本研究的多学科团队会议期间,观察到的多学科团队与临床决策树之间的建议一致性以及数据的完整性,表明实施临床决策树以支持多学科团队决策的潜在作用。
BACKGROUND: Multidisciplinary team meetings formulate
guideline-based individual treatment plans based on patient and disease characteristics and motivate reasons for deviation. Clinical decision trees could support multidisciplinary teams to adhere more accurately to
guidelines. Every clinical decision tree is tailored to a specific decision moment in a care pathway and is composed of patient and disease characteristics leading to a
guideline recommendation.
OBJECTIVE: This study investigated (1) the concordance between multidisciplinary team and clinical decision tree recommendations and (2) the completeness of patient and disease characteristics available during multidisciplinary team meetings to apply clinical decision trees such that it results in a guideline recommendation.
METHODS: This prospective, multicenter, observational concordance study evaluated 17 selected clinical decision trees, based on the prevailing Dutch
guidelines for breast, colorectal and prostate cancers. In cases with sufficient data, concordance between multidisciplinary team and clinical decision tree recommendations was classified as concordant, conditional concordant (multidisciplinary team specified a prerequisite for the recommendation) and non-concordant.
RESULTS: Fifty-nine multidisciplinary team meetings were attended in 8 different hospitals, and 355 cases were included. For 296 cases (83.4%), all patient data were available for providing an unconditional clinical decision tree recommendation. In 59 cases (16.6%), insufficient data were available resulting in provisional clinical decision tree recommendations. From the 296 successfully generated clinical decision tree recommendations, the multidisciplinary team recommendations were concordant in 249 (84.1%) cases, conditional concordant in 24 (8.1%) cases and non-concordant in 23 (7.8%) cases of which in 7 (2.4%) cases the reason for deviation from the clinical decision tree generated
guideline recommendation was not motivated.
CONCLUSIONS: The observed concordance of recommendations between multidisciplinary teams and clinical decision trees and data completeness during multidisciplinary team meetings in this study indicate a potential role for implementation of clinical decision trees to support multidisciplinary team decision-making.