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The OSCE is regarded as the gold standard of competence assessment in many healthcare programs, however, there are numerous internal and external sources of variation contributing to checklist marks. There is concern amongst organisers that candidates may be unfairly disadvantaged if they follow an “excellent” preceding candidate. This study assessed if average checklist scores differed depending on who a candidate follows accounted for different sources of variation.

This study examined assessment data from final year MBChB OSCEs at the University of Aberdeen and categorised candidates into three levels dependent on examiner awarded global scores of preceding candidates for each station. Data were modelled using a linear mixed model incorporating fixed and random effects.

A total of 349 candidates sat the OSCEs. The predicted mean (95% CI) score for students following an “excellent” candidate was 21.6 (20.6, 22.6), followed “others” was 21.5 (20.5, 22.4) and followed an “unsatisfactory” student was 22.2 (21.1, 23.3). When accounted for individual, examiner and station levels variabilities, students following an “excellent” candidate did not have different mean scores compared to those who followed “other” (p = 0.829) or “unsatisfactory” candidates (p = 0.162), however, students who followed an “unsatisfactory” student scored slightly higher on average compared to those who followed “other” (p = 0.038).

There was weak evidence that candidate's checklist variations could be attributed to who they followed, particularly those following unsatisfactory students; the difference in predicted mean scores may be of little practical relevance. Further studies with multiple centres may be warranted assuring perceived fairness of the OSCE to candidates and educators.

The purpose of this paper is to create a model that connects drivers between organizational innovation and business model innovation (BMI) to guide empirical research and the design of innovation management strategies.

The model was designed based on the results of a systematic literature review over the past 25 years that provides common predictor variables to build bridges between these two types of innovations.

It is a conceptual relationship between organizational innovation and BMI based on processes, new structures and customer relationship management. Moreover, there are five bridges from common predictors: strategy, top management, exploratory learning, technological innovation and environmental complexity.

The relationships between organizational innovation and BMI have been neglected in the literature. The model fills this gap by proposing hypotheses for empirical research and critical variables and relationships to steer organizational and business model innovation.