Literature DB >> 19573630

Assessment, surgeon, and society.

John Norcini1, Jamsheer Talati.   

Abstract

An increasing public demand to monitor and assure the quality of care provided by physicians and surgeons has been accompanied by a deepening appreciation within the profession of the demands of self-regulation and the need for accountability. To respond to these developments, the public and the profession have turned increasingly to assessment, both to establish initial competence and to ensure that it is maintained throughout a career. Fortunately, this comes at a time when there have been significant advances in the breadth and quality of the assessment tools available. This article provides an overview of the drivers of change in assessment which includes the educational outcomes movement, the development of technology, and advances in assessment. It then outlines the factors that are important in selecting assessment devices as well as a system for classifying the methods that are available. Finally, the drivers of change have spawned a number of trends in the assessment of competence as a surgeon. Three of them are of particular note, simulation, workplace-based assessment, and the assessment of new competences, and each is reviewed with a focus on its potential.

Mesh:

Year:  2009        PMID: 19573630     DOI: 10.1016/j.ijsu.2009.06.011

Source DB:  PubMed          Journal:  Int J Surg        ISSN: 1743-9159            Impact factor:   6.071


  4 in total

1.  New tools for systematic evaluation of teaching qualities of medical faculty: results of an ongoing multi-center survey.

Authors:  Onyebuchi A Arah; Joost B L Hoekstra; Albert P Bos; Kiki M J M H Lombarts
Journal:  PLoS One       Date:  2011-10-14       Impact factor: 3.240

2.  An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education.

Authors:  Juan Diego Lemos; Alher Mauricio Hernandez; Georges Soto-Romero
Journal:  Sensors (Basel)       Date:  2017-04-29       Impact factor: 3.576

3.  Perspectives on procedure-based assessments: a thematic analysis of semistructured interviews with 10 UK surgical trainees.

Authors:  Joseph Shalhoub; Dominic C Marshall; Kate Ippolito
Journal:  BMJ Open       Date:  2017-03-24       Impact factor: 2.692

4.  Using machine learning to identify quality-of-care predictors for emergency caesarean sections: a retrospective cohort study.

Authors:  Betina Ristorp Andersen; Ida Ammitzbøll; Jesper Hinrich; Sune Lehmann; Charlotte Vibeke Ringsted; Ellen Christine Leth Løkkegaard; Martin G Tolsgaard
Journal:  BMJ Open       Date:  2022-03-07       Impact factor: 2.692

  4 in total

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