HyperglycaemiaNCT07037563
Developing an AI Pharmacy Chatbot for the Population of Hong Kong
A study testing An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemia in people with Hyperglycaemia and Hypertension, run by The University of Hong Kong at 2 sites in Hong Kong.
Trial summary
The primary objective of this study is to is to develop a conversational AI service (chatbot) in Hong Kong to assist patients and caregivers with inquires related to Hospital Authority (HA)-prescribed medications, and to evaluate its effectiveness in answering medication-related questions. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Hyperglycaemia, Hypertension, Hyperlipidaemia
- What is being tested?
- An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemia
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 280 participants
- Where
- 2 sitesHong Kong
- Study dates
- Jun 2025to 31 Oct 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Patients aged 18 years or older diagnosed with either hyperglycaemia, hypertension, or hyperlipidaemia, and currently receiving medication prescribed by the Hospital Authority in Hong Kong.
- Caregivers aged 18 years or older for patients described above.
Who cannot join
- There is no exclusion criterion, but they should meet the inclusion criteria above.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Hong Kong2 sites, 2 recruiting
- Recruiting
Laboratory of Data Discovery for Health
Hong Kong
Kathy Leung, PhD, +852 3917 6735, hkusph@hku.hk
Joseph Wu, PhD
- Recruiting
The University of Hong Kong
Hong Kong
Kathy Leung, PhD, +852 3917 6735, hkusph@hku.hk
Joseph Wu, PhD
About this study
The primary objective of this study is to is to develop a conversational AI service (chatbot) in Hong Kong to assist patients and caregivers with inquires related to Hospital Authority (HA)-prescribed medications, and to evaluate its effectiveness in answering medication-related questions. The main questions it aims to answer are:
- How satisfied are the patients and caregivers with this pharmacy chatbot?
- How will the pharmacy chatbot impact eligible patients or caregivers on their (or the patient they are caring for) medication adherence, knowledge, and the consultation time with HA pharmacists?
Read more
There will be an intervention group and a control group:
- The intervention group will be invited to use the AI Pharmacy Chatbot online for 7 days through WhatsApp, a commonly used social media platform in Hong Kong. They can inquire about their medications prescribed under HA and get instant, validated answers from the chatbot.
- The control group will not use the chatbot during the intervention period.
To evaluate the chatbot's usability, researchers will measure patient satisfaction through usability questionnaires issued to the intervention group after their intervention period. Differences in medication adherence, medication knowledge, and HA pharmacist consultation time will also be measured between the intervention and control groups after the intervention period, to determine the chatbot's impact.
Read the detailed description
In this study, we aim to develop an artificial intelligent (AI) pharmacy chatbot and evaluate its effectiveness in answering questions related to prescribed-medications.
We will first develop an AI pharmacy chatbot prototype utilizing advanced technologies such as AI and natural language processing. By implementing Hospital Authority (HA) drug database and suggestions from Chief Pharmacist's Office (CPO), a Proof-of-Concept phase will be conducted to validate the chatbot's ability to address medication-related questions for locally prevalent chronic conditions in Hong Kong: hyperglycaemia, hypertension, and hyperlipidaemia. After completing the prototype development, we will invite pharmacists from HA for testing and evaluation of the prototype, further finetuning the chatbot based on their feedback.
Then we aim to enhance the usability of the chatbot by incorporating feedback from patients and caregivers. We aim to recruit a minimum of 280 patients receiving HA-prescribed medication on hyperglycaemia, hypertension, and / or hyperlipidaemia, or their caregivers. According to a previous study, the medication adherence of patients with chronic conditions in Hong Kong was about 61.63%. For an increase to 80% of adherence would require a minimum of 140 participants per group, with a significance level (α) of 0.05, a test power (1-β) of 0.8, and a cluster design effect (D) of 1.5.
Recruitment of patients and caregivers will involve collaboration with HA to identify eligible participants. Designated pharmacists and other healthcare professionals from HA will help distribute recruitment materials to eligible patients and caregivers and provide researchers a list of participants who express the willingness to participate.
Participants will be randomized in a 1:1 ratio to either the control group or the intervention group. Before the intervention period, they will all receive a consent form and an information sheet which provides details on the study. They will also be asked to complete a pre-study survey, which includes questions on socio-demographics, drug usage habits, medical history and experience with chatbots.
Participants in the intervention group will then be invited to use the pharmacy chatbot and receive a usability test guideline, with an emphasis on the chatbot's role as a support tool for medication inquiries. The intervention duration will last for 7 days and the control group will have no exposure to the chatbot during the period. After 7 days, a post-study survey will be conducted to all participants in both the intervention and control groups. Participants in the intervention group will also receive a usability questionnaire to feedback on the chatbot.
A convergent mixed methods design, combining qualitative and quantitative approaches, will be used to evaluate the intervention effect of the chatbot.
- Being tested
- An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemia
- Keywords
- Chatbot, Intelligent Conversational Agent, Artificial Intelligence, Implementation Science
- Medical subject headings
- Hyperglycemia, Hypertension, Hyperlipidemias
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemiaOther
It is a chatbot for HA-prescribed medication used for treating hyperglycaemia, hypertension, and hyperlipidaemia, available through WhatsApp. All the responses will be extracted from a database, in which the content was obtained from and validated by pharmacists from the Chief Pharmacist's Office of the Hospital Authority in Hong Kong. The intervention period will last for 7 days.
| Study group | Role | What they receive |
|---|---|---|
| Pharmacy chatbot intervention group | Experimental | In this arm, participants will receive a pharmacy chatbot intervention. They will be invited to use the chatbot through WhatsApp. They can ask questions regarding their (or the patient they are caring for) prescribed medications and get immediate responses from the chatbot. The intervention will last for 7 days. Receives: Other: An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemia |
| Control group | No intervention | The control group will not have any exposure with the chatbot during the intervention period. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Medical knowledge
Before the intervention period, all participants will be asked whether they disagree or agree with the following statements on a 5-point Likert scale (Strongly agree, Agree, Neutral, Disagree and Strongly disagree):
- I understand the main indications of my medications (or the medications of the patient I care for).
- I understand the potential side effects of my medications (or the medications of the patient I care for).
- I know how to take my medications (or administer the medications of the patient I care), including the dosage and frequency, thereby promoting my medication adherence.
- I have concerns or worries about my medications (or the medications of the patient I care for).
- I can obtain medication-related information efficiently and easily.
After the 7-day intervention period, they will be asked again the same questions.
Measured: 1 week
Medical adherence
Before the intervention period, all participants will be asked whether they disagree or agree with the following statement on a 5-point Likert scale (Strongly agree, Agree, Neutral, Disagree and Strongly disagree): I know how to take my medications (or administer the medications of the patient I care), including the dosage and frequency, thereby promoting my medication adherence.
After the 7-day intervention period, they will be asked again the same questions.
Measured: 1 week
Secondary outcomes (3)
Response time
We will calculate from the backend the chatbot's response time when responding to user's input (text, image and voice).
Measured: 1 week
User satisfaction
Participants in the intervention group will be asked whether they disagree or agree to the following statements on a 5-point Likert scale (Strongly disagree, Disagree, Neutral, Agree and Strongly agree):
- The chatbot is simple to use and user-friendly.
- The chatbot understands my queries and is able to address them.
- The chatbot's responses are relevant and sufficient.
Moreover, they will also be asked to rate their overall experience with the chatbot on a 5-point Likert scale (Very Good, Good, Moderate, Poor, and Very Poor), and whether they will use the chatbot again in the future and whether they would recommend others to use the chatbot.
Measured: 1 week
Consultation with pharmacists
Before the intervention period, we will ask all participants their frequency and consultation time with pharmacists. After the 7-days intervention period, we will ask them again whether they have visited any pharmacists during the time, and if so, the frequency and consultation time.
Measured: 1 week
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Jun 2025
- Study startJun 2025 (estimated)
- Primary completion31 Oct 2026 (estimated)
- Study completion31 Oct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HyperglycaemiaStudies of the same condition, open and under way.
- More trials run by The University of Hong KongThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 280 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The University of Hong Kong
- Sponsor type
- University, hospital or other
- Collaborators
- Laboratory of Data Discovery for Health, Hospital Authority, Hong Kong
- Responsible party
- Principal investigator, Joseph Tsz Kei Wu, The University of Hong Kong
- Investigators
- Joseph Wu, PhD, Principal investigator, The University of Hong Kong
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07037563
- Sponsor's protocol ID
- UW 23-518
- Status last verified
- Jun 2025
- First submitted
- 17 Jun 2025
- Last updated
- 25 Jun 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Individual participant data that underlie the results reported in the article, after de-identification (text, tables, figures, and appendices), will be shared. A written data-sharing request for meta-analysis should be submitted by email with a methodologically sound proposal. To gain access, data requestors will need to sign a data access agreement.
Study at a glance
From the registry record, last updated by the sponsor on 25 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Developing an AI Pharmacy Chatbot for the Population of Hong Kong
- ClinicalTrials.gov ID
- NCT07037563
- Acronym / sponsor ID
- UW 23-518
- Keywords
- Chatbot, Intelligent Conversational Agent, Artificial Intelligence, Implementation Science
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 280 participants (estimated)
- Lead sponsor
- The University of Hong KongUniversity, hospital or other
- Collaborators
- Laboratory of Data Discovery for Health, Hospital Authority, Hong Kong
- Study start
- Jun 2025 (estimated)
- Primary completion
- 31 Oct 2026 (estimated)
- Study completion
- 31 Oct 2026 (estimated)
- First posted
- 25 Jun 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The primary objective of this study is to is to develop a conversational AI service (chatbot) in Hong Kong to assist patients and caregivers with inquires related to Hospital Authority (HA)-prescribed medications, and to evaluate its effectiveness in answering medication-related questions. The main questions it aims to answer are:
- How satisfied are the patients and caregivers with this pharmacy chatbot?
- How will the pharmacy chatbot impact eligible patients or caregivers on their (or the patient they are caring for) medication adherence, knowledge, and the consultation time with HA pharmacists?
There will be an intervention group and a control group:
- The intervention group will be invited to use the AI Pharmacy Chatbot online for 7 days through WhatsApp, a commonly used social media platform in Hong Kong. They can inquire about their medications prescribed under HA and get instant, validated answers from the chatbot.
- The control group will not use the chatbot during the intervention period.
To evaluate the chatbot's usability, researchers will measure patient satisfaction through usability questionnaires issued to the intervention group after their intervention period. Differences in medication adherence, medication knowledge, and HA pharmacist consultation time will also be measured between the intervention and control groups after the intervention period, to determine the chatbot's impact.
Detailed description
In this study, we aim to develop an artificial intelligent (AI) pharmacy chatbot and evaluate its effectiveness in answering questions related to prescribed-medications.
We will first develop an AI pharmacy chatbot prototype utilizing advanced technologies such as AI and natural language processing. By implementing Hospital Authority (HA) drug database and suggestions from Chief Pharmacist's Office (CPO), a Proof-of-Concept phase will be conducted to validate the chatbot's ability to address medication-related questions for locally prevalent chronic conditions in Hong Kong: hyperglycaemia, hypertension, and hyperlipidaemia. After completing the prototype development, we will invite pharmacists from HA for testing and evaluation of the prototype, further finetuning the chatbot based on their feedback.
Then we aim to enhance the usability of the chatbot by incorporating feedback from patients and caregivers. We aim to recruit a minimum of 280 patients receiving HA-prescribed medication on hyperglycaemia, hypertension, and / or hyperlipidaemia, or their caregivers. According to a previous study, the medication adherence of patients with chronic conditions in Hong Kong was about 61.63%. For an increase to 80% of adherence would require a minimum of 140 participants per group, with a significance level (α) of 0.05, a test power (1-β) of 0.8, and a cluster design effect (D) of 1.5.
Recruitment of patients and caregivers will involve collaboration with HA to identify eligible participants. Designated pharmacists and other healthcare professionals from HA will help distribute recruitment materials to eligible patients and caregivers and provide researchers a list of participants who express the willingness to participate.
Participants will be randomized in a 1:1 ratio to either the control group or the intervention group. Before the intervention period, they will all receive a consent form and an information sheet which provides details on the study. They will also be asked to complete a pre-study survey, which includes questions on socio-demographics, drug usage habits, medical history and experience with chatbots.
Participants in the intervention group will then be invited to use the pharmacy chatbot and receive a usability test guideline, with an emphasis on the chatbot's role as a support tool for medication inquiries. The intervention duration will last for 7 days and the control group will have no exposure to the chatbot during the period. After 7 days, a post-study survey will be conducted to all participants in both the intervention and control groups. Participants in the intervention group will also receive a usability questionnaire to feedback on the chatbot.
A convergent mixed methods design, combining qualitative and quantitative approaches, will be used to evaluate the intervention effect of the chatbot.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Pharmacy chatbot intervention group | Experimental | Other: An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemiaIn this arm, participants will receive a pharmacy chatbot intervention. They will be invited to use the chatbot through WhatsApp. They can ask questions regarding their (or the patient they are caring for) prescribed medications and get immediate responses from the chatbot. The intervention will last for 7 days. |
| Control group | No intervention | –The control group will not have any exposure with the chatbot during the intervention period. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Patients aged 18 years or older diagnosed with either hyperglycaemia, hypertension, or hyperlipidaemia, and currently receiving medication prescribed by the Hospital Authority in Hong Kong.
- Caregivers aged 18 years or older for patients described above.
Key exclusion criteria (1 listed)
- There is no exclusion criterion, but they should meet the inclusion criteria above.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemiaIt is a chatbot for HA-prescribed medication used for treating hyperglycaemia, hypertension, and hyperlipidaemia, available through WhatsApp. All the responses will be extracted from a database, in which the content was obtained from and validated by pharmacists from the Chief Pharmacist's Office of the Hospital Authority in Hong Kong. The intervention period will last for 7 days. | Other | Pharmacy chatbot intervention group |
Primary outcome
Medical knowledge
Time frame: 1 week
Before the intervention period, all participants will be asked whether they disagree or agree with the following statements on a 5-point Likert scale (Strongly agree, Agree, Neutral, Disagree and Strongly disagree): 1. I understand the main indications of my medications (or the medications of the patient I care for). 2. I understand the potential side effects of my medications (or the medications of the patient I care for). 3. I know how to take my medications (or administer the medications of the patient I care), including the dosage and frequency, thereby promoting my medication adherence. 4. I have concerns or worries about my medications (or the medications of the patient I care for). 5. I can obtain medication-related information efficiently and easily. After the 7-day intervention period, they will be asked again the same questions.
Medical adherence
Time frame: 1 week
Before the intervention period, all participants will be asked whether they disagree or agree with the following statement on a 5-point Likert scale (Strongly agree, Agree, Neutral, Disagree and Strongly disagree): I know how to take my medications (or administer the medications of the patient I care), including the dosage and frequency, thereby promoting my medication adherence. After the 7-day intervention period, they will be asked again the same questions.
3 secondary outcomes
Response time
Time frame: 1 week
User satisfaction
Time frame: 1 week
Consultation with pharmacists
Time frame: 1 week
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Jun 2025.
- Individual participant dataSharing planned: Yes. Individual participant data that underlie the results reported in the article, after de-identification (text, tables, figures, and appendices), will be shared. A written data-sharing request for meta-analysis should be submitted by email with a methodologically sound proposal. To gain access, data requestors will need to sign a data access agreement.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Joseph Wu, PhD principal investigator
The University of Hong Kong
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing An AI pharmacy chatbot offering information related to HA-prescribed medication for hyperglycaemia, hypertension, and hyperlipidaemia in people with Hyperglycaemia and Hypertension, run by The University of Hong Kong at 2 sites in Hong Kong.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 25 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Hong Kong. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Joseph Wu, PhD (+852 3917 6709, hkusph@hku.hk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Medical knowledge (time frame: 1 week). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Jun 2025.