The paradox of AI assistance: enhancing quality while hindering efficiency in local hospitals
Year: 2025
Type: article
Abstract: Artificial intelligence (AI) is transforming the medical industry, with AI applications in healthcare expanding across clinical domains. By 2025, medical AI is expected to be adopted in 90% of hospitals to support doctors’ work. Although AI has demonstrated proven capabilities in enhancing medical diagnosis and treatment efficacy, there remains a lack of in-depth research on its impact on doctors’ work, particularly for doctors with average qualifications in small-scale hospitals. Through an analysis of chest CT diagnostic data from a local hospital in China, our analysis reveals that after the introduction of AI assistance, doctors’ work quality improved, as evidenced by a 2.8% increase in the length of report conclusions and a 1.0% increase in the description length. However, work efficiency declined, with the average number of chest CT reports processed daily reduced by 4.3% for the overall department and 2.8% per doctor. Notably, over a six-month period following the adoption of AI, this trade-off became increasingly significant. Understanding the impact of AI assistance on doctors’ work performance is crucial for optimizing healthcare resource allocation and management decisions, ultimately enhancing patient satisfaction and well-being. This study redirects attention from patient perceptions to clinician behaviors, offering actionable insights for AI implementation in small-scale hospitals.
Source: Journal of Digital Management
Authors: Siqi Dai, Zhiyi Xie, Zheshuai Yang, Wei Miao
Institutions: Zhejiang University, University College London
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,060
Award: G1487015978
OpenAlex ID: W4410215949