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Updated: Jan 24, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A review of current approaches for evaluating impaired performance in around-the-clock medical professionals
Coen R H Huizinga1, Fokkedien H M P Tummers1, Perla J Marang-van de Mheen2
1Centre for Human Drug Research, Leiden, the Netherlands.
Abstract:
The need for data to study the relationship between fatigued healthcare professionals and performance outcomes is evident, however, it is unclear which methodology is most appropriate to provide these insights. To address this issue, we performed a systematic review of relevant articles by searching the MEDLINE, EMBASE, Cochrane, Web of Science, and CINAHL databases. The literature search identified 2960 unique references, of which 82 were identified eligible. The impact on performance was studied on clinical outcomes, medical simulation, neurocognitive performance, sleep quantification and subjective assessment. In general results on performance are conflicting; impairment, no effect, and improvement were found. This review outlines the various methods currently available for assessing fatigue-impaired performance. The contrasting outcomes can be attributed to three main factors: differences in the operationalisation of fatigue, incomplete control data, and the wide variety in the methods used. We recommend the implementation of a clinically applicable tool that can provide uniform data. Until these data become available, caution should be used when developing regulations that can have implications for physicians, education, manpower planning, and ‒ ultimately ‒ patient care.
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