ArticleBMC health services research2021
Artificial intelligence-assisted reduction in patients' waiting time for outpatient process: a retrospective cohort study.
Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- An interdisciplinary mixed-methods systematic review of multidimensional factors shaping the outpatient waiting experience.BMC health services research · 2026Pooled it
- Pediatric Predictive Artificial Intelligence Implemented in Clinical Practice from 2010 to 2021: A Systematic Review.Applied clinical informatics · 2025Pooled it
- How to adjust the expected waiting time to improve patient's satisfaction?BMC health services research · 2023Trial
- Deep learning models for the detection of dental-findings and tooth-types using video data.BMC oral health · 2026Article
- Health information needs of women with gestational diabetes mellitus: a qualitative study.Scientific reports · 2026Article
- Barriers to continuity of outpatient infusion-port maintenance among patients with cancer: a single-center cross-sectional study in China.Frontiers in public health · 2026Observational
- A clinically validated AI framework for kidney cancer detection and characterization.Communications medicine · 2025Article
- The waiting game: determinants and effects of OPD service delays in a Tertiary Health Facility.BMC health services research · 2025Article
- The hope and the hype of artificial intelligence for syncope management.European heart journal. Digital health · 2025Article
- Patient-Centered Outpatient Process Optimization System Based on Intelligent Guidance in a Large Tertiary Hospital in China: Implementation Report.JMIR medical informatics · 2025Article
- Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study.JMIR medical informatics · 2025Observational
- Applying the unattainable triangle in cardio-oncology care: Balancing cost, quality, and time.Oncotarget · 2025Review
- Effect of teleradiology on patient waiting time and service satisfaction in public hospitals, Northwest Ethiopia: a quasi-experimental study.BMC health services research · 2025Article
- Article
- Systematic review of machine learning applications using nonoptical motion tracking in surgery.NPJ digital medicine · 2025Article
- Artificial intelligence in outpatient management: a simulation-based study in a Chinese tertiary hospital.Frontiers in artificial intelligence · 2025Article
- Digital transformation to overcoming access barriers.Revista panamericana de salud publica = Pan American journal of public health · 2025Article
- National Patient Satisfaction Survey as a Predictor for Quality of Care and Quality Improvement - Experience and Practice.Patient preference and adherence · 2025Article
- Large language models for disease diagnosis: a scoping review.NPJ artificial intelligence · 2025Review
- Parkinson's disease screening using a fusion of gait point cloud and silhouette features.PloS one · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
backgroundMany studies suggest that patient satisfaction is significantly negatively correlated with the waiting time. A well-designed healthcare system should not keep patients waiting too long for an appointment and consultation. However, in China, patients spend notable time waiting, and the actual time spent on diagnosis and treatment in the consulting room is comparatively less.
methodsWe developed an artificial intelligence (AI)-assisted module and name it XIAO YI. It could help outpatients automatically order imaging examinations or laboratory tests based on their chief complaints. Thus, outpatients could get examined or tested before they went to see the doctor. People who saw the doctor in the traditional way were allocated to the conventional group, and those who used XIAO YI were assigned to the AI-assisted group. We conducted a retrospective cohort study from August 1, 2019 to January 31, 2020. Propensity score matching was used to balance the confounding factor between the two groups. And waiting time was defined as the time from registration to preparation for laboratory tests or imaging examinations. The total cost included the registration fee, test fee, examination fee, and drug fee. We used Wilcoxon rank-sum test to compare the differences in time and cost. The statistical significance level was set at 0.05 for two sides.
resultsTwelve thousand and three hundred forty-two visits were recruited, consisting of 6171 visits in the conventional group and 6171 visits in the AI-assisted group. The median waiting time was 0.38 (interquartile 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). The total cost was 335.97 (interquartile range: 244.80, 437.60) CNY (Chinese Yuan) for the AI-assisted group and 364.58 (249.70, 497.76) CNY for the conventional group (p < 0.05).
conclusionsUsing XIAO YI can significantly reduce the waiting time of patients, and thus, improve the outpatient service process of hospitals.
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