Redesign of a Resident Evaluation Tool Using Exploratory Factor Analysis.

Carly Chappell, Stephen Markowiak, Gang Ren, Laura Wharry, Stephen Stanek, Joseph Sferra
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Abstract

Purpose: Residents at our training program identified timeliness of faculty feedback as an area for improvement, while faculty felt the evaluation tool was time-consuming and redundant. We sought to resolve these issues through stakeholder input and modern data analysis.

Methods: Core faculty and senior residents met to revamp the "Faculty Evaluation of Resident" end of rotation tool. The results of the most recent 5-years of evaluations were analyzed using Exploratory Factor Analysis, a dimension reduction tool provided in the IBM SPSS statistical package, to identify questions which were highly correlated. A new condensed tool was then generated by combining highly correlated questions with committee approval. Spearman's rank order correlation test was used to evaluate each new question versus the eliminated redundant questions. Time to survey completion and frequency of written feedback were compared using t-test. One-way ANOVA was then used to compare scores for each new question versus the eliminated questions that had been grouped together.

Results: 3,268 surveys were completed by 73 attendings regarding 55 resident subjects. Data were blinded by the program coordinator before analysis. Exploratory Factor Analysis indicated the initial 30-question instrument could be reduced to 12-questions, while retaining 96% of the variability in performance. The component matrix indicates that 4 areas accounted for the most variability in resident performance: Overall Performance, Communication, Operative Skill, and Systems Based Practice. Following implementation of the new evaluation form, attending surgeons completed resident evaluations at a median of 36 days after the rotation (IQR 18-59). Faculty left written feedback more frequently (53.4% vs 40.8%, p < 0.0001). For some new questions, the resident performances were statistically different. For example, new question 9 had an average rating of 3.55 out of 5.00, while the questions it replaced averaged 3.76-3.89 (p < 0.001). For other questions, no statistically significant difference was found. For example, new question 12 and the questions it replaced all averaged 3.75 out of 5.00 (p = 0.985). Survey response rates also improved from 35% to 76% at 2 months and 89.3% to 93.5% at 6 months.

Conclusions: Faculty input and advanced statistical analysis shortened a 30-question resident evaluation tool to 12-questions while retaining 96% of the variability in resident performance. The new instrument resulted in improved response rate and increased number of written comments from attendings. Application of Exploratory Factor Analysis to resident education represents novel use of this tool in surgical education.

利用探索性因素分析重新设计住院医师评估工具。
目的:在我们的培训项目中,住院医师认为教师反馈的及时性是一个需要改进的领域,而教师则认为评估工具既耗时又多余。我们试图通过利益相关者的意见和现代数据分析来解决这些问题。方法:核心教师与老年住院医师会面,对“住院医师教师评价”轮转结束工具进行改进。使用IBM SPSS统计软件包中提供的降维工具探索性因子分析(Exploratory Factor Analysis)对最近5年的评估结果进行分析,以识别高度相关的问题。然后,通过将高度相关的问题与委员会的批准相结合,生成了一个新的浓缩工具。使用Spearman秩序相关检验来评估每个新问题与消除的冗余问题。采用t检验比较问卷完成时间和书面反馈频率。然后使用单因素方差分析来比较每个新问题与被分组的被淘汰问题的得分。结果:73名主治医师对55名住院医师完成了3268项调查。数据在分析前由项目协调员进行盲法处理。探索性因素分析表明,最初的30个问题可以减少到12个问题,同时保留96%的性能可变性。成分矩阵表明,住院医生表现中有4个方面的差异最大:整体表现、沟通、操作技能和基于系统的实践。在实施新的评估表后,主治医生在轮转后的中位数36天完成住院医师评估(IQR 18-59)。教师留下书面反馈的频率更高(53.4% vs 40.8%, p < 0.0001)。对于一些新问题,住院医生的表现有统计学差异。例如,新问题9的平均评分为3.55分(满分5.00分),而被它取代的问题的平均评分为3.76-3.89分(p < 0.001)。对于其他问题,没有发现统计学上的显著差异。例如,新问题12和它所取代的问题平均为3.75 (p = 0.985)。调查回应率在2个月时由35%上升至76%,在6个月时由89.3%上升至93.5%。结论:教师输入和先进的统计分析将30个问题的住院医生评估工具缩短到12个问题,同时保留了96%的住院医生表现可变性。新工具提高了回应率,主治医生的书面评论也增加了。探索性因素分析在住院医师教育中的应用代表了这一工具在外科教育中的新应用。
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