Artificial Intelligence-Assisted Reduction in Patients’ Waiting Time for Outpatient Procedures: A Matched Case–Control Study

Abstract

Abstract Background: Many studies indicate that patient satisfaction is significantly negatively correlated with waiting time. A well-designed healthcare system should not keep patients waiting too long for appointment and consultation. However, in China, patients spend considerable time waiting, and the actual time spent on diagnosis and treatment in the consulting room is comparatively less. Methods: We developed an artificial intelligence (AI)-assisted module that is embedded in hospital information systems. Through its use, outpatients were automatically recommended an imaging examination or a laboratory test based on their symptoms and chief complaint. Thus, they could get examined or tested before they went to see the doctor. People who saw a doctor in the traditional way were assigned to the conventional group, and those who used the AI-assisted system were assigned to the AI-assisted group. We conducted a 1:1 case–control study that applied propensity score matching to pair the data from patients in a pediatric tertiary hospital between August 1, 2019 and January 31, 2020. Waiting time was defined as the time from registration to preparation for a laboratory test or an imaging examination. The total cost included the registration fee, test fee, examination fee, and drug fee. The Wilcoxon rank-sum test was used to compare the differences in time and cost between the AI-assisted group and the conventional group. The statistical significance level was set at 0.05 for two sides. Results: A total of 12,342 visits were recruited for this study, consisting of 6,171 visits in the conventional group and 6,171 visits in the AI-assisted group. The median waiting time was 0.38 (inter-quartile range: 0.20, 1.33) hours for the AI-assisted group compared with 1.97 (0.76, 3.48) hours for the conventional group (p < 0.05). Conclusions: Using AI can significantly reduce the waiting time of patients for outpatient procedures, and thus, enhance the outpatient process of hospitals.

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