Bibliographic record
Abstract
An innovative new method of teaching medicine at the bedside termed “scientific medicine” was introduced by Dr Guyatt, an internal medicine residency co-ordinator at McMasters University in Ontario, Canada, in 1990. His new approach to teaching medicine was built upon the initiatives of his mentor, Dr David Sackett, in order to use critical appraisal tools at the bedside. After much criticism from his colleagues about the term “scientific medicine”, Guyatt invented the term “evidence based medicine” which first appeared in the 1991 ACP Journal Club editorial. After many years of refinement and continuing improvement of the strategy, the term now most frequently used is “evidence based practice” (EBP) and encompasses a gamut of health disciplines. The term has been initiated to bring more certainty to health care practice instead of practitioners’ reliance on their clinical expertise and judgement.1,2 Over the past two decades, the increased momentum of EBP has expanded our scientific knowledge base. The establishment of the Joanna Briggs Institute (JBI) in December 1996 cemented the importance of EBP by providing the best available evidence to inform clinical decision-making at the point of care in the form of Best Practice Information Sheets (BPIS). These BPISs are based on systematic reviews that evaluate the scientific evidence for a specific intervention from multiple studies, culminating in a composite estimate of health effect. The JBI BPIS was a novel method to overcome the common mantra “too much literature, not enough time”. Critical appraisal of existing literature has become an essential component of the EBP strategy. Several tools and checklists have been developed to teach people how to critically appraise different types of evidence including systematic reviews, randomized controlled trials, qualitative research, economic evaluation studies, cohort studies, case control studies and studies of diagnostic test accuracy.3 The JBI Rapid Assessment Protocol internet database (JBI RAPid) is an online training resource that provides individual practitioners or students with a framework for critical appraisal of publications using established data collection tools and offers the possibility of publishing the appraisal in the form of a refereed report in the RAP Library. Advances in EBP have resulted in the inclusion of evidence obtained from qualitative studies, economic evaluations, diagnostic studies and expert opinion and reports. The JBI has extended its reach by developing a suite of programs under the banner of SUMARI (System for the Unified Management, Assessment and Review of Information) to enable researchers and practitioners to appraise and synthesize evidence for feasibility, appropriateness, meaningfulness and effectiveness, and to conduct economic evaluations of activities and interventions. However, advances in EBP are bounded by the quality, reach and maintenance of implementation into practice. Several frameworks and theories of implementation have evolved to help embed evidence into practice. Each of these frameworks has different characteristics and outcomes.4 A study by Damschroder et al.5 proposed the Consolidated Framework for Implementation Research (CFIR) model. It offers an overarching classification to promote implementation theory development in health services. The model includes substantiation about what works, why they work and the contexts at which they work.5,6 The JBI is at the forefront of implementation research and has developed a suite of software including PACES (Practical Application of Clinical Evidence System) which is a user-friendly online tool that enables health professionals to conduct efficient, timesaving audits in small or large health care settings. Despite our understanding of the different strategies of EBP and implementation frameworks, a significant amount of work is needed to increase our understanding of the concept of sustainability of health interventions. More recently, Dynamic Sustainability Framework has been proposed by Chambers et al.7,8 which involves continued learning and problem solving, ongoing revision of interventions with a primary focus on fit between interventions and multi-level contexts, and prospects for ongoing development as opposed to reducing outcomes over time. An important next step in the evolution of EBP is the development of strategies and frameworks to monitor the implementation and sustainability of EBP at the patient, practitioner and organizational level.7 In keeping with its logo, JBI in the past 20 years has produced a significant ripple effect in evidence based health care among health care professionals researchers and the general community in Australia and globally. This is evidenced by the large number of JBI international collaborating centers, the development of JBI programs of synthesis, transfer and implementation of research evidence and technological innovations to further EBP. Congratulations JBI on the past 20 years and wish you a sustained and productive future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".