An interventional study of AI-assisted primary care intervention in Influenza Vaccination, sponsored by Fudan University. Not yet recruiting. Open to participants aged 18 Years to 64 Years. Per ClinicalTrials.gov, last updated 2026-10-14.
Sponsored by Fudan University · Not applicable, Interventional, and Health services research
The goal of this clinical trial is to evaluate whether an AI-assisted primary care intervention can increase influenza vaccination uptake among patients with chronic diseases and to assess the cost-effectiveness and potential for implementing the intervention in routine primary care.
The main questions it aims to answer are:
Researchers will compare patients with chronic diseases who receive the AI-assisted primary care intervention with those who do not receive it to determine whether the intervention improves patients' literacy, confidence, intention, and uptake of influenza vaccination.
Participants will:
A randomized controlled trial will be conducted to evaluate the effectiveness of an AI-assisted primary care intervention to improve influenza vaccination uptake among patients with chronic diseases in China, with additional health economic and feasibility evaluations to assess its cost-effectiveness and potential for scale-up.
The sample size calculation is based on the primary outcome measure (influenza vaccination uptake) and the main analysis method (comparison of rates between two groups). Based on the literature review and survey, the current influenza vaccination uptake among patients with chronic diseases is estimated to be approximately 5%. We assume that the uptake rate could increase to 10% following the intervention. Using the formula for comparing two independent proportions, the minimum required sample size is calculated to be 578 participants in each group, with a significance level (α) of 0.05 and a statistical power (1-β) of 0.90. To account for potential loss to follow-up, assuming a 10% loss to follow-up rate, each group will include 650 participants, with a total sample size of 1,300.
A randomized controlled design will be employed across four representative regions in China, selected to reflect different levels of economic development and geography: a municipality, a provincial capital, an ordinary city, and a rural county. In each region, 2-4 community health centers (CHCs) will be selected, and eligible adults aged 18-64 years with one or more chronic diseases will be recruited in CHCs, where all eligible attendees will be invited to participate. Eligible patients with chronic diseases who provide written informed consent will be randomly assigned in a 1:1 ratio to either the intervention group or the control group. The randomization sequence will be generated in advance by a statistician using a computer-generated random number method. At each study site, participants will be allocated sequentially according to their order of enrollment. Due to the nature of the intervention, blinding of participants and on-site intervention implementers is not feasible. Local coordinators, outcome assessors, data managers, and statistical analysts will remain blinded to group allocation throughout the study to minimize assessment and analysis bias.
Building on the evaluation of intervention effectiveness, we will conduct a health economic evaluation to assess the economic value of the influenza AI-assisted primary care intervention. Costs will be estimated using a micro-costing approach from both health-system and societal perspectives, covering the costs of developing, deploying, and maintaining the AI assistant as well as the primary care physicians' labor-time costs; incremental cost-effectiveness ratios (ICERs) will be calculated as the additional cost per additional person vaccinated, per percentage-point increase in vaccination uptake, and per quality-adjusted life-year (QALY) gained, complemented by sensitivity and budget-impact analyses. In addition, a feasibility evaluation combining quantitative and qualitative methods will assess the real-world feasibility and scalability of the influenza AI-assisted primary care intervention. Quantitatively, a questionnaire survey will assess chronic-disease patients' experience with and acceptability of the AI assistant and the physician recommendation. Qualitatively, semi-structured interviews will be conducted with CDC staffs, primary care physicians, and patients with chronic diseases to explore the reasons underlying vaccination decisions, the acceptability of the AI-assisted intervention, and the role of primary care physicians in promoting vaccination.
Statistical Analysis
Primary Outcome Analysis An intention-to-treat (ITT) approach will be used as the primary analysis strategy, with all randomly assigned participants analyzed according to their original group allocation. Between-group comparisons will be performed using t-tests for continuous variables and chi-square tests for categorical variables.
The primary outcome is influenza vaccination uptake among participants within one and three months after the intervention. A log-binomial regression model will be used to estimate the relative risk (RR) and its 95% confidence interval (95% CI), with CHCs included as a fixed effect and adjustment for prespecified covariates. If the log-binomial model fails to converge, a modified Poisson regression model will be used instead. The adjusted absolute risk difference and its 95% CI will also be estimated from the regression model to evaluate the public health significance of the intervention. Prespecified covariates will include region, sex, age, type of chronic disease, previous influenza vaccination history, education level, occupation, type of health insurance, and income. Prespecified subgroup analyses will be conducted by including subgroup variables and their interaction terms with the intervention group in the primary analysis model to assess heterogeneity of intervention effects across participant characteristics. Prespecified subgroups will include region, sex, age group (18-54 vs. 55-64 years), type of chronic disease, previous influenza vaccination history, education level, occupation, type of health insurance, and income.
2,264 studies on the registry are indexed under Influenza, Human; 173 are open to participants now.
This study's planned enrollment of 1,300 is above the median of 240 across 1,894 interventional studies indexed under Influenza, Human.
Browse Influenza, Human studies →Fudan University is the lead sponsor of 1,308 studies on the registry; 637 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Primary care physicians will provide brief health education to patients with chronic diseases about influenza vaccination, and will recommend the use of the influenza vaccine AI assistant via an educational pamphlet. Participants and their family members will interact with the AI assistant on site for at least 5 minutes. For those who are eligible and express willingness to receive influenza vaccination, primary care physicians will assist with appointment scheduling or guide them to vaccination services. Participants who do not complete vaccination on site will subsequently receive phone reminders to schedule an appointment and complete vaccination. In addition, primary care physicians will establish WeChat groups to deliver intervention reinforcement. Brief educational pamphlet with access links to the AI assistant, accompanied by voice explanations, will be sent to participants on the day of the intervention and at two weeks, one month, and two months thereafter as reminders.
Behavioral: AI-assisted primary care intervention
Participants will receive only routine health education without additional intervention. After completion of the study, access to the influenza vaccine AI assistant will be made available to participants in the control group.
Primary care physicians will provide brief health education to participants on influenza vaccination and will recommend the use of an AI-powered influenza vaccine chatbot for at least 5 minutes. For those who are eligible and express willingness to receive influenza vaccination, primary care physicians will assist with appointment scheduling and vaccination. The AI-powered influenza vaccine chatbot is designed to provide information and health education about influenza vaccination. It is powered by large language models and is trained on an expert-validated knowledge base derived from authoritative sources such as the National Health Commission and China CDC to ensure accuracy. The chatbot engages users in interactive, conversational dialogue to answer questions and address concerns regarding influenza vaccination. It is delivered via WeChat or a web browser for user access and offers both conversational and navigational interaction modes, supporting text and voice input.
Influenza vaccine uptake
Whether participants get vaccinated against influenza during the study period, measured by official vaccination records.
Time frame: Within one and three months after the intervention initiation
Time to influenza vaccine uptake
Time from the intervention initiation to influenza vaccine uptake among participants, measured by official vaccination records. Unit of Measure: days.
Time frame: From date of the intervention initiation until the date of first dose vaccinated, assessed up to three months
Intention to receive influenza vaccine
Whether participants plan to receive influenza vaccine within the flu season, assessed by questionnaire. It is a binary variable and categorized as intended or unintended.
Time frame: Day 1, within one day after the on-site intervention completion
Influenza risk perception
Perceived susceptibility to and severity of influenza, assessed by questionnaire. It is a binary variable and categorized as high or low risk perception.
Time frame: Day 1, within one day after the on-site intervention completion
Influenza vaccine literacy
Participants' literacy, assessed by the total number of correct answers on a series of questions about influenza and influenza vaccine.
Time frame: Day 1, within one day after the on-site intervention completion
Influenza vaccine confidence
Participants' confidence in the importance, effectiveness, and safety of influenza vaccine, assessed by questionnaire. It is a binary variable and categorized as high or low confidence.
Time frame: Day 1, within one day after the on-site intervention completion
Usability of AI-assisted primary care intervention
The usability of the AIPC intervention will be evaluated using a series of questions on its acceptability, feasibility, and sustainability, including AI chatbot and primary care physician recommendation. The Likert 5-point scale is used, with scores ranging from 1 to 5 on a scale of "completely disagree" to "completely agree". Higher scores indicating greater perceived usability of the AIPC intervention.
Time frame: Day 1, within one day after the on-site intervention completion
Cost of AI-assisted primary care intervention
The cost of designing and implementing the influenza vaccine AI assisted primary care interventions. Unit of Measure: Chinese Yuan (CNY).
Time frame: Within three months after the intervention initiation
No study locations are listed for this record.
Plan to share: No — Individual participant data will not be shared due to participant privacy concerns and institutional data protection policies.
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
This study is not yet recruiting, as verified in Oct 2026. You cannot join it, but the record below documents what was studied.
Get an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.