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Enregistrement W2328725789 · doi:10.1097/01.sih.0000441673.22247.f1

Board 421 - Research Abstract A Systematic Approach to Design Clinical Performance Checklists (Submission #227)

2013· article· en· W2328725789 sur OpenAlexaboutno aff
Jan B. Schmutz, Walter Eppich, Florian Hoffmann, Ellen Heimberg, Tanja Manser

Notice bibliographique

RevueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2013
Typearticle
Langueen
DomaineMedicine
ThématiqueSepsis Diagnosis and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésChecklistTask (project management)Delphi methodSystematic reviewComputer scienceProcess (computing)DelphiProcess managementMedical physicsMEDLINEPsychologyMedicineSystems engineeringEngineeringArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Introduction/Background Assessing performance helps to identify the abilities of clinicians and potential performance gaps, augments debriefings and is essential for scientific studies investigating factors influencing clinical performance.1 Checklists are widespread tools to assess performance. But while the development process of such a performance checklist is essential for its quality, existing studies rarely describe their checklist development in detail. Current methodological recommendations2,3 fail to provide a systematic, step-by-step approach to develop clinical performance checklists. Such a systematic approach would support researchers in evaluating the suitability of the checklists for different contexts, designing performance assessment tools for specific clinical scenarios reflecting precisely the task demands on the clinician and in either adapting existing checklists or generating new ones. Thus, the aim of this study was to provide an overall systematic approach to develop clinical performance checklists. Using the example of a simulated sepsis scenario we illustrate our five development steps. Methods Step 1 - Draft Checklist: Based on the literature and own clinical experience we designed a draft checklist. Step 2 – The Delphi-Review-Rounds: We sent out the draft checklist to five experts for reviewing using an adapted Delphi-Method.4 Step 3 – Design of the final checklist and pilot testing: Every checklist item was then divided into three scoring categories: task not performed (0 points); task performed partially (1 point), and task performed completely (2 points). Then the checklist was tested by rating video clips of simulation trainings and a few adjustments have been made. This step is indispensable; by applying the checklist to a set of different examples, the raters experience the applicability of the items and the usability of the rating scale. Step 4 – Final Delphi-Review-Round: To assure that the changes made after the pilot testing are generally valid the checklist resulted from step three was sent out again to the five experts. Step 5 – Items weighting: In the last step we sent out the checklist to 30 pediatricians and instructed them to rate all actions in terms of their importance for the success of the treatment. The mean importance score serves as a weighting factor for every item. This way we get a more accurate assessment of performance because the checklist differentiates more between essential and less important items. Validity testing – Six videos of septic shock simulation training were independently rated from two raters. Interrater reliability was calculated using Cronbach’s α; criterion validity was tested by investigating the relationship between the checklist score and three external criterion: team experience level, experience level of the leader and a global performance rating (rating from 1-10). Results We successfully applied our five step approach and we developed a performance checklist including 33 items for a simulated paediatric sepsis scenario. Cronbach’s α ranged from acceptable (αα = .6) to very good (α = .9). Criterion validity is given: Significant correlation between the checklist score and i) mean experience level of team (r = .37, p= .05) ii) leader experience level (r = .44, p= .05) iii) global performance rating score (r = .54, p= .05). Conclusion We described a systematic approach to design clinical performance checklists that integrates the published evidence and the knowledge of domain experts. The validity of the checklist has been confirmed. A structured development process is a necessary prerequisite of a valid checklist. Only if a widely recognized standard for developing performance checklists is established we can design appropriate measurement tools and move the field of performance assessment in healthcare forward. References 1. Boulet JR, Murray D. Review article: Assessment in anesthesiology education. Canadian Journal of Anesthesia/Journal canadien d’anesthésie. 2011:1-11. 2. Stufflebeam DL. Guidelines for developing evaluation checklists: the checklists development checklist (CDC). [monograph on the Internet]. 2000; http://www.wmich.edu/evalctr/archive_checklists/guidelines_cdc.pdf. Accessed Dezember 17, 2012. 3. Scriven M. The logic and methodology of checklists. Retrieved on. 2000;11:02-07. 4. Clayton MJ. Delphi: a technique to harness expert opinion for critical decision†making tasks in education. Educational Psychology. 1997;17(4):373-386. Disclosures Salary Support from Center for Medical Simulation to teach on simulation courses none Per dien honoraria from PAEDSIM e.V. to teach on pediatric simulation courses non-profit organization PAEDSIM e.V.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,013
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,297
Score d'incertitude au seuil0,655

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0130,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,419
Tête enseignante GPT0,520
Écart entre enseignants0,102 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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Même revueSimulation in Healthcare The Journal of the Society for Simulation in HealthcareMême sujetSepsis Diagnosis and TreatmentTravaux en français237 207