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Efficiency, Paths, Goals, and Frontiers in Graduate Education: New Uses for Old Concepts.

describe the application of data envelopment analysis (DEA) to assess the performance of a retrospective cohort of learners in a critical care fellowship program. The inputs to the DEA model included a measure of clinical workload—the clinical workload index—estimated by dividing the number of individual self-reported duty hours by the clinical and procedural production accomplished during that time frame; and a measure of fellows’ commitment to continued education estimated as the inverse percentage of conference attendance. The outputs included scores of the Society of Critical Care Medicine’s Multidisciplinary Critical Care Knowledge Assessment Program (MCCKAP) and midterm faculty evaluations. DEA was used to estimate the relative efficiency of each individual in the sample relative to the most technically efficient fellows—individuals who had attained the best results with fewer inputs. The efficiency of these individuals delimited the efficient frontier, against which the technically inefficient fellows were compared. The resulting DEA model quantified the efforts—as the amount of each output—that would be necessary from each individual to reach the efficient frontier (Table, Figure). In so doing, the DEA model provided paths and goals to improve the efficiency of each fellow. It has been theorized that effective teachers exert their educational leadership by clarifying paths, removing obstacles, and setting goals to improve learners’ performance.2,3 DEA may provide information to help students and teachers in these endeavors. DEA explains different levels of efficiency among peers.4 Recent research on assessment in medical education has been focusing beyond outcomes and includes mechanisms and theories that underlie processes and results.5 There is a need for explanations regarding how and why learners achieve outcomes. By relating the use of educational resources to educational outcomes, DEA is an attractive technique to fulfill the emerging needs of educational research. Accordingly, Tiwari and Kumar1 were able to mathematically explain the differing efficiency levels of fellows sharing the same learning environment, resources, and opportunities. DEA may increase the efficiency of feedback based on relative-to-peers evaluations. Feedback based on relativeto-peers evaluations has been studied in other areas, for example, industry, based on the assumption that by learning about their position relative to that of their peers, workers would be stimulated to improve performance. Research in this area has yielded conflicting results. Higher performers may strive to keep their positions or accommodate and show no further improvement. However, when provided to lower-rank performers, relative-to-peers feedback has consistently been associated with low self-esteem and demotivation.6,7 In this population, relative-to-peers feedback may hinder efforts toward improvement. Similar results have been reported in a study of the effects of relative-to-peers feedback on students’ subsequent performance.8 The estimated effect was strong and positive—improved performance—for students in the highest percentiles; in contrast, low-achieving students performed worse in subsequent tests. The effects were more pronounced among women. Lack of information about the appropriate paths and goals to improve performance may have contributed to the negative results in these studies.7 Motivation is the mechanism behind improvement. According to path-goal theory, 3 elements contribute to the level of intrinsic motivation: