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PURPOSE: To assess the expected impact of the 2024 medical imaging literature on the workload of diagnostic radiologists. METHODS: A random sample of 416 articles on diagnostic imaging that was published in 2024 was reviewed by one radiologist working in an academic tertiary care center and another radiologist working in a non-academic general teaching hospital. RESULTS: In the academic tertiary care hospital setting, 56.5 % (235/416) of articles had the potential to directly impact patient care, of which 48.9 % (115/235) would increase workload, 48.1 % (113/235) would not change workload, 0.4 % (1/235) would decrease workload, and 2.6 % (6/235) had an unclear effect on workload. Studies with Artificial Intelligence (AI) as primary research area were significantly (P < 0.001) more likely to increase workload compared to studies with another primary research area, with an Odds Ratio (OR) of 14.3 (95 % confidence interval CI: 4.2 to 48.2). In the non-academic general teaching hospital setting, 56.5 % (231/416) of articles had the potential to directly impact patient care, of which 48.9 % (113/231) would increase workload, 48.1 % (111/231) would not change workload, 0.4 % (1/231) would decrease workload, and 2.6 % (6/231) had an unclear effect on workload. Studies with AI as primary research area were significantly (P < 0.001) more likely to increase workload compared to studies with another primary research area, with an OR of 13.7 (95 % CI: 4.1 to 46.5). CONCLUSION: The workload of diagnostic radiologists is expected to increase based on recent (2024) scientific literature, and AI applications generally seem to have an aggravating effect on workload.
Kwee et al. (Tue,) studied this question.