[{"id":384,"title":"Apple and orange: comparing patient safety, health data and the airline industry ","sha":"0c68c30683be70fb7fff96032e13bf56","user_id":null,"state":"published","body":"Over the decades, the airline industry which was already very safe, has made further strides to improve safety. The current trend in patient safety and simulation conferences is to repeatedly draw parallel conclusions, decrying those in healthcare for not emulating the airline industry's carefully regulated practices. \r\n\r\nThis comparison only applies in limited areas of healthcare. We have made advances by adopting CRM principles in acute resuscitation. Checklists aid some surgical procedures. But running an airline is orders of magnitude simpler than healthcare. The physics of flight is indeed complex but can now be fully simulated. In contrast, we still struggle to simulate the physiome of single cells. Airline business logistics are also simpler. But imagine saying to 200 patients: the appendectomy flight is departing at 1530 - please recline your tables. \r\n\r\nIt is odd how poor we are at estimating risk. Many fear taking a flight (0.5 micromorts) much more than a general anesthetic (6 micromorts). We are pleased that both are much safer than they were, and yes, there are lessons to be learned from analysis of systems errors. \r\n\r\nBut let's not go marching blithely down to the orange grove of tightly regulated practices. The comparison has run out of juice. ","created_at":"2017-05-13T04:03:49.745Z","updated_at":"2017-05-14T06:00:40.393Z","zenodo_id":579641,"doi":"https://doi.org/10.5281/zenodo.579641","subject":null,"tags":["patient safety","simulation"],"vote_count":0,"view_count":1,"score":0.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null},{"id":389,"title":"Axiology: is a learning intervention worth the effort?","sha":"528154386218df84565b16f18517be08","user_id":null,"state":"published","body":"Many medical education studies pursue a measurement approach to demonstrate the efficacy of a learning intervention. Researchers, steeped in the belief system that positions randomized controlled trials as the ultimate form of inquiry, try to apply this methodology in the confounded world of education research. As Cook et al have repeatedly shown, many compare their educational intervention with a control. We already know that something is better than nothing for promoting learning. \r\n \r\nWe often focus excessively on ontology, epistemology or methodology, yet forget to assess the axiology of a study? More specifically, is it worth doing and what is the value of doing it? In this, we run into the classic challenge in cost-benefit analysis: it is easy to count costs but hard to assess benefit. \r\n\r\nConsider this clinical research comparison example: antidepressant studies, which commonly compare new agents with amitriptyline, showing at least as good an effect, but with improved safety and side effects. The relative effect, which is hard to measure, is still open to comparison. \r\n \r\nWhen assessing real world effectiveness, we should consider the economics of the intervention, while comparing learning designs that show equivalent outcomes. Is there less total cost or greater scalability and sustainability?","created_at":"2017-05-29T22:54:41.863Z","updated_at":"2017-06-01T06:00:27.491Z","zenodo_id":801608,"doi":"https://doi.org/10.5281/zenodo.801608","subject":null,"tags":["methodology","economics"],"vote_count":0,"view_count":1,"score":0.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null},{"id":426,"title":"METRICS: a pattern language for education scholarship","sha":"36babba73a054768d1dc738f7392b53e","user_id":null,"state":"published","body":"Scholarly activities in health professions education have been growing but despite the interest, what is considered as scholarship in (medical) education has remained vague. Boyer’s classes of scholarly activity (Boyer 1990) and Glassick’s criteria required of an artefact to render it scholarly (Glassick et al. 1997) have been widely discussed. While the Glassick model helps to define what scholarly activity should be, we have found the Boyer model of what kinds of activity count as scholarship is lacking. We developed the METRICS pattern language of scholarship in (medical) education - this maps more directly to scholarly activities. \r\n\r\nMetascholarship - activities that reflect on the nature of scholarship\r\nEvaluation - activities that measure value or axiology\r\nTranslation - activities that move findings or practices from one domain to another\r\nResearch - activities that focus on theory generation or testing (experimental, descriptive or explanatory)\r\nInnovation - activities that focus on creating new ideas, objects and practices\r\nConceptual - activities that explore or develop new models, concepts, and paradigms\r\nSynthesis - activities that focus on the integration of existing knowledge and practice\r\n\r\nHaving built the METRICS model, we now seek to engage others in its implementation. ","created_at":"2017-11-16T10:24:03.145Z","updated_at":"2017-12-04T06:00:30.598Z","zenodo_id":1069730,"doi":"https://doi.org/10.5281/zenodo.1069730","subject":null,"tags":["scholarly communication"],"vote_count":0,"view_count":1,"score":0.1,"deleted":false,"muted":false,"tweeted":false,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null},{"id":430,"title":"Orthogonal versus redundant data in education","sha":"ea895a0b3460d46771cd28573deb0652","user_id":null,"state":"published","body":"Our university was recently hit by malware. It took weeks to restore most data, some lost completely. All backups were affected making a simple restore ineffectual. Why take this redundant approach in data safety? Consider flight data recorders: not all aircraft parameters are recorded or recordable. But critical analysis is afforded by reconstruction from key data such as flap angles. Automotive insurers accurately derive driving habits and risks from brake usage alone: a minimal, easily collectible dataset. Capture data that is orthogonal to, not redundant to, that currently recorded. In education, do we need to track every word written or spoken? Actions speak louder than words. Sentinel behaviours better predict anomalous performers, as learners or teachers. Activity streams, not learning objects, are now a better indicator of what a learner actually does, not what the teacher says they do. But we should beware what activities we monitor. Aside from privacy issues, simple metrics like word counts or time spent are easily spoofed. Fact regurgitation in exams does not prove comprehension. Look at resultant activities ( e.g. rich comment threads in discussions) and emergent properties from existing workflows. We have the tools, and the data. We just need to use them. ","created_at":"2017-12-21T23:50:59.621Z","updated_at":"2018-01-03T06:00:48.333Z","zenodo_id":1134535,"doi":"https://doi.org/10.5281/zenodo.1134535","subject":null,"tags":["activity metrics","data governance"],"vote_count":0,"view_count":1,"score":0.1,"deleted":false,"muted":false,"tweeted":true,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null},{"id":623,"title":"Why do medical schools use learning management systems so little?","sha":"c68bbefdf3fd2d3deb7fccf1c72e4052","user_id":null,"state":"published","body":"In an eLearning workshop, at the 2007 Canadian Conference on Medical Education, there was an informal survey of Canadian medical schools about their use of learning management systems (LMS). All schools had one but their use was very sparse. Despite much interest in eLearning developments, the LMS remains largely unused twelve years later. Group discussions have suggested a number of reasons: the course is the atomic unit on which the LMS architecture is based; med school curricula are rotation-based, not course-based; problem-based learning in small groups rather than large group lectures, with an emphasis on a heutagogical approach; the effects of community-based and distributed medical education; the strong influence of competency-based education; but surprisingly, a recent review showed that this whole area has been little studied. It also relates to some of the unusual assessment methods that are popular in medical education: script concordance testing, situational judgement testing; key feature questions, virtual patients, objective structured clinical exams (OSCEs), most of which are not well accommodated within the LMS structure or design. International collaborations in eLearning suggest that this situation is not unique to Canada but, as noted, there has been little work to assess this. ","created_at":"2019-10-01T04:32:44.950Z","updated_at":"2019-11-21T06:01:01.162Z","zenodo_id":3549040,"doi":"https://doi.org/10.5281/zenodo.3549040","subject":null,"tags":["lms","medical education","assessment"],"vote_count":0,"view_count":1,"score":0.1,"deleted":false,"muted":false,"tweeted":false,"attachment_file_name":null,"attachment_content_type":null,"attachment_file_size":null,"attachment_updated_at":null}]