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Applying Kane's validity framework to a simulation based assessment of clinical competence

机译:将Kane的有效性框架应用于基于模拟的临床能力评估

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摘要

Assessment of clinical competence is complex and inference based. Trustworthy and defensible assessment processes must have favourable evidence of validity, particularly where decisions are considered high stakes. We aimed to organize, collect and interpret validity evidence for a high stakes simulation based assessment strategy for certifying paramedics, using Kane's validity framework, which some report as challenging to implement. We describe our experience using the framework, identifying challenges, decisions points, interpretations and lessons learned. We considered data related to four inferences (scoring, generalization, extrapolation, implications) occurring during assessment and treated validity as a series of assumptions we must evaluate, resulting in several hypotheses and proposed analyses. We then interpreted our findings across the four inferences, judging if the evidence supported or refuted our proposed uses of the assessment data. Data evaluating "Scoring" included: (a) desirable tool characteristics, with acceptable inter-item correlations (b) strong item-total correlations (c) low error variance for items and raters, and (d) strong inter-rater reliability. Data evaluating "Generalizability" included: (a) a robust sampling strategy capturing the majority of relevant medical directives, skills and national competencies, and good overall and inter-station reliability. Data evaluating "Extrapolation" included: low correlations between assessment scores by dimension and clinical errors in practice. Data evaluating "Implications" included low error rates in practice. Interpreting our findings according to Kane's framework, we suggest the evidence for scoring, generalization and implications supports use of our simulation-based paramedic assessment strategy as a certifying exam; however, the extrapolation evidence was weak, suggesting exam scores did not predict clinical error rates. Our analysis represents a worked example others can follow when using Kane's validity framework to evaluate, and iteratively develop and refine assessment strategies.
机译:临床能力的评估是基于复杂和推理的。值得信赖性和可靠的评估过程必须具有有利的有效证据,特别是在决策被认为是高赌注的地方。我们的旨在通过Kane的有效性框架来组织,收集和解释基于高赌注模拟的评估策略的高赌注模拟评估策略,这些框架有些报告挑战实施。我们描述了我们使用该框架的经验,确定挑战,决定点,解释和经验教训。我们认为与在评估和处理的有效期内发生的四次推论(评分,泛化,外推,含义)相关的数据,作为我们必须评估的一系列假设,导致几个假设和建议分析。然后,我们在四次推论中解释了我们的调查结果,如果支持或驳斥我们的拟议使用评估数据的证据,则判断。评估“得分”的数据包括:(a)所需的工具特性,具有可接受的项目间相关性(b)强的项目 - 总相关性(c)物品和评估者的低误差方差,以及(d)强烈的帧间间可靠性。评估“概括性”的数据包括:(a)一种强大的抽样策略,捕获了大多数相关的医学指令,技能和国家能力,以及良好的整体和站点可靠性。评估“推断”的数据包括:在实践中尺寸和临床误差评估分数之间的低关。数据评估“含义”包括实践中的低误差率。根据Kane的框架来解释我们的调查结果,我们建议获得评分,泛化和影响的证据支持使用我们的模拟的护理评估策略作为认证考试;但是,外推证据薄弱,建议考试得分未预测临床误差率。我们的分析代表了一个有效的例子,其他人可以在使用Kane的有效性框架时遵循,以评估,并迭代地发展和精确评估策略。

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