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Stanford Biodesign launched its Innovation Fellowship in 2001 as a first-of-its kind postgraduate training experience for teaching biomedical technology innovators a need-driven process for developing medical technologies and delivering them to patients. Since then, many design-oriented educational programs have been initiated, yet the impact of this type of training remains poorly understood. This study measures the career focus, leadership trajectory, and productivity of 114 Biodesign Innovation Fellowship alumni based on survey data and public career information. It also compares alumni on certain publicly available metrics to finalists interviewed but not selected. Overall, 60% of alumni are employed in health technology in contrast to 35% of finalists interviewed but not selected. On leadership, 72% of alumni hold managerial or higher positions compared to 48% of the finalist group. A total of 67% of alumni reported that the fellowship had been “extremely beneficial” on their careers. As a measure of technology translation, more than 440,000 patients have been reached with technologies developed directly out of the Biodesign Innovation Fellowship, with another 1,000,000+ aided by solutions initiated by alumni after their training. This study suggests a positive impact of the fellowship program on the career focus, leadership, and productivity of its alumni.

Self-appraisal has repeatedly been shown to be inadequate as a mechanism for performance improvement. This has placed greater emphasis on understanding the processes through which self-perception and external feedback interact to influence professional development. As feedback is inevitably interpreted through the lens of one’s self-perceptions it is important to understand how learners interpret, accept, and use feedback (or not) and the factors that influence those interpretations. 134 participants from 8 health professional training/continuing competence programs were recruited to participate in focus groups. Analyses were designed to (a) elicit understandings of the processes used by learners and physicians to interpret, accept and use (or not) data to inform their perceptions of their clinical performance, and (b) further understand the factors (internal and external) believed to influence interpretation of feedback. Multiple influences appear to impact upon the interpretation and uptake of feedback. These include confidence, experience, and fear of not appearing knowledgeable. Importantly, however, each could have a paradoxical effect of both increasing and decreasing receptivity. Less prevalent but nonetheless important themes suggested mechanisms through which cognitive reasoning processes might impede growth from formative feedback. Many studies have examined the effectiveness of feedback through variable interventions focused on feedback delivery. This study suggests that it is equally important to consider feedback from the perspective of how it is received. The interplay observed between fear, confidence, and reasoning processes reinforces the notion that there is no simple recipe for the delivery of effective feedback. These factors should be taken into account when trying to understand (a) why self-appraisal can be flawed, (b) why appropriate external feedback is vital (yet can be ineffective), and (c) why we may need to disentangle the goals of performance improvement from the goals of improving self-assessment.

This article presents a translational model of curricular design in which findings from investigating learning in university BME research laboratories (in vivo sites) are translated into design principles for educational laboratories (in vitro sites). Using these principles, an undergraduate systems physiology lab class was redesigned and then evaluated in a comparative study. Learning outcomes in a control section that utilized a technique-driven approach were compared to those found in an experimental class that embraced a problem-driven approach. Students in the experimental section demonstrated increased learning gains even when they were tasked with solving complex, ill structured problems on the bench top. The findings suggest the need for the development of new, more authentic models of learning that better approximate practices from industry and academia.

Background User understanding of information technology systems (IT-Systems) is a prerequisite for their use. This study aimed to explore how primary care physician trainees learn, understand and use IT-Systems. Methods A paper-based survey study among 301 primary care physician trainees in Baden-Wuerttemberg, Germany, was performed. The questionnaire included measures of understanding and use of nine specific system features, five possible learning strategies, a validated scale for affinity for technology interaction, and five individual and three practice characteristics. Results The sample comprised 94 respondents (31.6% response rate). Between 3.2 and 59.6% said to know specific systems features well; between 13.8 and 42.6% expressed a wish to know more about specific system features. The predominant strategy for learning system features was explanation by others: 51.7 to 66.7% had applied this strategy to learn the features. Between 18.6 and 41.4% had learned the features by trial and error. A better understanding of system features was associated with the use of a trial and error strategy for learning system features (beta = 0.260, p  = 0.012). The use of a greater variety of learning strategies was associated with higher affinity for technology interaction (beta = 0.215, p  = 0.037). Conclusion The study suggests that many physicians need a better understanding of IT-Systems. The role of manuals, online resources and courses in learning IT-Systems seems limited. The new generation of primary care physicians seem to learn features of IT-Systems through explanation by others and trying in their ambulatory practices. The relevance of IT-Systems in healthcare is high, but physicians need more support in learning to use system features.

It has become axiomatic that assessment impacts powerfully on student learning. However, surprisingly little research has been published emanating from authentic higher education settings about the nature and mechanism of the pre-assessment learning effects of summative assessment. Less still emanates from health sciences education settings. This study explored the pre-assessment learning effects of summative assessment in theoretical modules by exploring the variables at play in a multifaceted assessment system and the relationships between them. Using a grounded theory strategy, in-depth interviews were conducted with individual medical students and analyzed qualitatively. Respondents’ learning was influenced by task demands and system design. Assessment impacted on respondents’ cognitive processing activities and metacognitive regulation activities. Individually, our findings confirm findings from other studies in disparate non-medical settings and identify some new factors at play in this setting. Taken together, findings from this study provide, for the first time, some insight into how a whole assessment system influences student learning over time in a medical education setting. The findings from this authentic and complex setting paint a nuanced picture of how intricate and multifaceted interactions between various factors in an assessment system interact to influence student learning. A model linking the sources, mechanism and consequences of the pre-assessment learning effects of summative assessment is proposed that could help enhance the use of summative assessment as a tool to augment learning.

When an operator manual for a physiological monitor exceeds 800 pages and a manual for a hospital bed includes more than 100 distinct warnings and over 100 unique icons, it's clear that medical equipment has become extraordinarily complex. The exponential growth in health technology brings wonderful innovations,1 many of which may be accompanied by challenges in device mastery for the people who are its prime users. Deploying an array of computers, video systems, digitally driven control systems, and other complex devices for patient care places new demands on clinical users to understand, set up, operate, and troubleshoot both stand-alone medical devices and integrated systems. This article focuses on a narrower set of user-centered issues that also relate to effective use of complex technology: design for usability, training, competency assessment, and procurement activities. At its kickoff meeting in April 2017, the AAMI Foundation's National Coalition to Promote the Safe Use of Complex Healthcare Technology identified these issues, among others, as priorities for patient safety.

Nearly a decade ago, Alberto Vasquez was working at the University of Texas Health Science Center in San Antonio, TX, as a research engineering associate, where he used his ability to solve technical problems during clinical trials. Like many healthcare technology management (HTM) professionals, Vasquez worked alongside a mix of other health professionals, including those in nursing and medical training programs. Vasquez noticed a couple things. The first was that many new HTM professionals needed to work on their communication skills while on the hospital floors, particularly in terms of interactions with other healthcare staff. Upon becoming director of the St. Philip's College biomedical engineering technology program, Vasquez made it a priority to modernize the way in which students learned clinical and communication skills. The success of St. Philip's revamped HTM education program has led to additional resources for the school at a time when many education funds are being cut back.