Improving the Efficiency of Advanced Life Support Training
Bibliographic record
Abstract
Letters20 November 2012Improving the Efficiency of Advanced Life Support TrainingGavin D. Perkins, MD, Andrew Lockey, MMEd, and Ian Bullock, PhDGavin D. Perkins, MDFrom University of Warwick, Warwick Medical School, Coventry CV4 7AL; Calderdale Royal Hospital, Halifax HX3 0PW; and National Clinical Guideline Centre, Royal College of Physicians, London NW1 4LE, United Kingdom.Search for more papers by this author, Andrew Lockey, MMEdFrom University of Warwick, Warwick Medical School, Coventry CV4 7AL; Calderdale Royal Hospital, Halifax HX3 0PW; and National Clinical Guideline Centre, Royal College of Physicians, London NW1 4LE, United Kingdom.Search for more papers by this author, and Ian Bullock, PhDFrom University of Warwick, Warwick Medical School, Coventry CV4 7AL; Calderdale Royal Hospital, Halifax HX3 0PW; and National Clinical Guideline Centre, Royal College of Physicians, London NW1 4LE, United Kingdom.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-157-10-201211200-00018 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We thank Dr. Wayne and coworkers for their comments on our article. We agree that simulation is central to successful ALS training, which is consistent with international ALS guidelines (1). In our blended learning trial, the number of sessions of cardiac arrest simulation was identical between the 2 groups. Face-to-face content, such as lectures and small-group teaching from the 2-day course, was replaced with e-learning material; skill-focused simulation teaching was not. Improving efficiency and reducing the overall cost of ALS training present an opportunity to save money that can be reinvested in further simulation and deliberate self-practice to ...References1. Soar J, Monsieurs KG, Ballance JH, Barelli A, Biarent D, Greif R, et al. European Resuscitation Council Guidelines for Resuscitation 2010 Section 9. Principles of education in resuscitation. Resuscitation. 2010;81:1434-44. [PMID: 20956044] CrossrefMedlineGoogle Scholar2. Soar J, Mancini ME, Bhanji F, Billi JE, Dennett J, Finn J, et al; Education, Implementation, and Teams Chapter Collaborators. Part 12: Education, implementation, and teams: 2010 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science with Treatment Recommendations. Resuscitation. 2010;81 Suppl 1 288-330. [PMID: 20956038] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From University of Warwick, Warwick Medical School, Coventry CV4 7AL; Calderdale Royal Hospital, Halifax HX3 0PW; and National Clinical Guideline Centre, Royal College of Physicians, London NW1 4LE, United Kingdom.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-3019. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoEffect of Clinical Decision-Support Systems Tiffani J. Bright , Anthony Wong , Ravi Dhurjati , Erin Bristow , Lori Bastian , Remy R. Coeytaux , Gregory Samsa , Vic Hasselblad , John W. Williams , Michael D. Musty , Liz Wing , Amy S. Kendrick , Gillian D. Sanders , and David Lobach Improving the Efficiency of Advanced Life Support Training Diane B. Wayne , Aashish K. Didwania , and William C. McGaghie Metrics 20 November 2012Volume 157, Issue 10Page: 753KeywordsConflicts of interestDisclosureHeartLife expectancy ePublished: 20 November 2012 Issue Published: 20 November 2012 CopyrightCopyright © 2012 by American College of Physicians. All Rights Reserved.PDF DownloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.060 | 0.019 |
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 source (direct Gemma or distilled Codex), 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".