Premium
RETRACTED: Composite reliability of workplace‐based assessment for international medical graduates
Author(s) -
Nair Balakrishnan Kichu R,
Moonenvan Loon Joyce MW,
Parvathy Mulavana S,
Vleuten Cees PM
Publication year - 2016
Publication title -
medical journal of australia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.904
H-Index - 131
eISSN - 1326-5377
pISSN - 0025-729X
DOI - 10.5694/mja16.00069
Subject(s) - reliability (semiconductor) , composite number , reliability engineering , medical education , psychology , computer science , engineering , medicine , physics , power (physics) , quantum mechanics , algorithm
Abstract Objective: The fitness to practise of international medical graduates (IMGs) is usually evaluated with standardised assessment tests. Practising doctors should, however, be assessed on their performance rather than their competency, for which reason workplace‐based assessment (WBA) has gained increasing attention. Our aim was to assess the composite reliability of WBA instruments for assessing the performance of IMGs. Design and setting: Between June 2010 and April 2015, 142 IMGs were assessed by 99 calibrated assessors; each cohort was assessed at their workplace over 6 months. The IMGs completed 970 case‐based discussions (CBDs), 1741 Mini‐Clinical Examination Exercises (mini‐CEX) and 1020 multisource feedback (MSF) sessions. Participants: 103 male and 39 female candidates based in urban and rural hospitals of the Hunter New England Health region, from 28 countries (Africa, Asia, Europe, South America, South Pacific). Main outcome measures: The reliability of the three WBA tools; the composite reliability of the tools as a group. Results: The composite reliability of our WBA toolbox program was good: the composite reliability coefficient for five CBDs and 12 mini‐CEX was 0.895 (standard error of measurement, 0.138). When the six MSF results were included, the composite reliability coefficient was 0.899 (standard error of measurement, 0.125). Conclusions: WBA is a reliable method for assessing IMGs when multiple tools and assessors are used over a period of time. This form of assessment meets the criteria for “good assessment” (reliability ≥ 0.8) and can be applied in other settings.