- ICH GCP
- Yhdysvaltain kliinisten tutkimusten rekisteri
- Kliininen tutkimus NCT07649577
Generative AI for Medication Counselling and Adherence in Community Pharmacies
Human-AI Collaboration in the Pharmacy: A Cluster Randomized Controlled Trial of Generative AI for Medication Counselling and Adherence
Tutkimuksen yleiskatsaus
Tila
Ehdot
Interventio / Hoito
Yksityiskohtainen kuvaus
Opintotyyppi
Ilmoittautuminen (Todellinen)
Vaihe
- Ei sovellettavissa
Yhteystiedot ja paikat
Opiskelupaikat
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-
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Amman, Jordania
- Petra University
-
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Osallistumiskriteerit
Kelpoisuusvaatimukset
Opintokelpoiset iät
- Aikuinen
- Vanhempi Aikuinen
Hyväksyy terveitä vapaaehtoisia
Kuvaus
Patient Eligibility Criteria
Inclusion Criteria:
Adults aged 18 years or older. Presenting with a new prescription or a refill for a chronic medication requiring counseling within one of the following classes: antihypertensives, oral antidiabetics, lipid-lowering agents, anticoagulants, or inhaled maintenance therapies.
Willing and able to provide informed consent.
Exclusion Criteria:
Presence of acute infections. Diagnosis of psychiatric disorders or oncological conditions. Presence of severe acute illness requiring urgent medical referral. Cognitive impairment precluding informed consent. Hearing or communication barriers that prevent interview completion without the presence of a caregiver.
Inability to provide a follow-up phone number for the 30-day adherence assessment.
Pharmacy and Pharmacist (Cluster) Eligibility Criteria
Inclusion Criteria:
Pharmacies legally registered in Jordan, providing routine prescription dispensing services, having at least one licensed pharmacist available during recruitment hours, and agreeing to participate for the full trial period.
Licensed pharmacists with a minimum of 2 years of clinical experience, working in participating pharmacies, providing direct patient counseling, and consenting to take part in the study.
Exclusion Criteria:
Pharmacies that are already using structured AI-assisted counseling tools as part of their routine practice.
Pharmacists on temporary placement for less than one month. Pharmacists not involved in patient-facing counseling.
Opintosuunnitelma
Miten tutkimus on suunniteltu?
Suunnittelun yksityiskohdat
- Ensisijainen käyttötarkoitus: Muut
- Jako: Satunnaistettu
- Inventiomalli: Rinnakkaistehtävä
- Naamiointi: Nelinkertaistaa
Aseet ja interventiot
Osallistujaryhmä / Arm |
Interventio / Hoito |
|---|---|
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Active Comparator: Intervention arm procedures
For all eligible patients in the intervention arm, the pharmacist performed the standard patient assessment and determined which medicine(s) needed counselling.
Then, the pharmacist input a prompt in a de-identified format into ChatGPT®.
The prompt was a request for an easy-to-understand counselling document with information regarding the indications for the medication, dosage, schedule, route, course, missed doses, possible side effects, important precautions, storage, and advice on taking the medicine as prescribed (Appendix A).
The pharmacist ensured that the content generated by the AI was accurate and clear, making corrections where necessary, and then gave verbal counselling to the patient.
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For all eligible patients in the intervention arm, the pharmacist performed the standard patient assessment and determined which medicine(s) needed counselling. Then, the pharmacist input a prompt in a de-identified format into ChatGPT®. The prompt was a request for an easy-to-understand counselling document with information regarding the indications for the medication, dosage, schedule, route, course, missed doses, possible side effects, important precautions, storage, and advice on taking the medicine as prescribed (Appendix A). The pharmacist ensured that the content generated by the AI was accurate and clear, making corrections where necessary, and then gave verbal counselling to the patient. The AI output was never provided to the patients without pharmacist evaluation. It is worth noting that pharmacists could also reject the AI output as inaccurate, insufficient, hazardous, and inappropriate altogether. Reproducibility was ensured through documenting the date and time, prompt te
Muut nimet:
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Ei väliintuloa: Control arm procedures
Pharmacies randomized to the control arm continued to provide usual medication counselling according to their standard routine practice, without access to the AI prompt templates or study AI workflow.
Control pharmacists used their usual professional references, as would occur in routine care, but they were not trained in or asked to use ChatGPT® during the trial period.
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Mitä tutkimuksessa mitataan?
Ensisijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
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Percentage of Applicable Counseling Domains Provided Correctly
Aikaikkuna: day 0
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Defined as the proportion of clinically applicable counseling domains communicated accurately during the encounter, compared with a medication-specific reference sheet.
Scored on a 0-100 scale, calculated as (Number of applicable domains correctly informed / Total number of applicable domains) x 100.Correctness score= (Number of applicable domains
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day 0
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Percentage of Essential Counseling Domains Addressed
Aikaikkuna: Day 0
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Defined as the proportion of essential counseling domains that were addressed during the encounter.
Scored on a 0-100 scale, calculated as (Number of applicable domains addressed / Total number of applicable domains) x 100.
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Day 0
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Toissijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
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Number of Counseling Deficiencies Categorized by Clinical Severity
Aikaikkuna: Day 0
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The frequency of omitted or incorrect counseling information, independently assessed by a panel of pharmacists using a 3-point scale: Low Severity (minor wording issues), Moderate Severity (errors leading to sub-therapeutic effects), and High Severity (errors with high potential for significant patient harm).
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Day 0
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Score on the General Medication Adherence Scale (GMAS)
Aikaikkuna: 30 Days Post-Encounter
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Medication adherence assessed via telephone follow-up using the continuous total score from the General Medication Adherence Scale (GMAS).
Higher scores indicate better medication adherence.
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30 Days Post-Encounter
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Number of Participants Achieving Good Adherence
Aikaikkuna: 30 Days Post-Encounter
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The number of participants meeting the validated threshold for "good adherence" based on their GMAS survey responses.
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30 Days Post-Encounter
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Total Score on the Immediate Patient Understanding (Teach-Back) Assessment
Aikaikkuna: Day 0
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A brief interviewer-administered understanding assessment based on teach-back principles.
Scores range from 0 to 4, with higher scores indicating a better understanding of the medication.
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Day 0
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Total Score on the Patient Satisfaction Questionnaire
Aikaikkuna: Day 0
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A questionnaire covering clarity, usefulness, confidence, and overall satisfaction.
Total scores range from 5 to 25, with higher scores indicating greater patient satisfaction.
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Day 0
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Time Spent on Face-to-Face Counseling
Aikaikkuna: Day 0
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Total face-to-face counseling time measured in minutes using audio timestamps from the start of counseling to completion.
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Day 0
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Number of Encounters Based on AI Output Acceptance Level
Aikaikkuna: Day 0
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The proportion of encounters in which the AI-generated counseling output was fully accepted, edited before delivery, or rejected outright by the pharmacist.
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Day 0
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Number of AI-Related Discrepancies Identified
Aikaikkuna: Day 0
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The frequency of detected AI inaccuracies prior to counseling, such as omitted counseling points, overly technical wording, or incomplete missed-dose advice.
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Day 0
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Number of Clinical Near Misses and Safety Incidents
Aikaikkuna: Day 0
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The number of encounters featuring a "near miss" (an AI error identified and corrected by the pharmacist before reaching the patient) or an "incident" (inaccurate information that actually reached the patient).
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Day 0
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Yhteistyökumppanit ja tutkijat
Sponsori
Julkaisuja ja hyödyllisiä linkkejä
Yleiset julkaisut
- Abdel-Qader, D. H., Al Meslamani, A. Z., Lewis, P. J., & Hamadi, S. (2021). Incidence, nature, severity, and causes of dispensing errors in community pharmacies in Jordan. International journal of clinical pharmacy, 43(1), 165-173. https://doi.org/10.1007/s11096-020-01126-w Abdel-Qader, D. H., et al. (2024). A comprehensive analysis of public satisfaction: Community pharmacists' pandemic preparedness in Jordan. Journal of Applied Pharmaceutical Science, 14(8), 160-168. Abdel-Qader, D. H., et al. (2025). Drug-Drug interaction management among pharmacists in Jordan: A national comparative survey. Pharmacy, 137. https://doi.org/10.3390/pharmacy13050137 Abu Hammour, K., et al. (2023). ChatGPT in pharmacy practice: A cross-sectional exploration of Jordanian pharmacists' perception, practice, and concerns. Journal of Pharmaceutical Policy and Practice, 16(1), 115. Ali, S., Shimels, T., & Bilal, A. I. (2019). Assessment of patient counseling on dispensing of medicines in outpatient pharmacy of Tikur-Anbessa Specialized Hospital, Ethiopia. Ethiopian journal of health sciences, 29(6), 727. Campbell, M. K., et al. (2012). Consort 2010 statement: Extension to cluster randomised trials. BMJ, 345. Chan, A.-W., et al. (2015). SPIRIT 2013 Statement: Defining standard protocol items for clinical trials. Revista Panamericana de Salud Pública, 38, 506-514. Elayeh, E. R., et al. (2019). Use of secret simulated patient followed by workshop based education to assess and improve inhaler counseling in community pharmacy in Jordan. Pharmacy Practice (Granada), 17(4). Fattah, F. H., et al. (2025). Comparative analysis of ChatGPT and Gemini (Bard) in medical inquiry: A scoping review. Frontiers in digital health, 7, 1482712. FIP, I. P. F. (2021). Medication review and medicines use review: A toolkit for pharmacists Colophon. FIP, I. P. F. (2025). An artificial intelligence toolkit for pharmacy: An introduction and resource guide for pharmacists. (March). Hammad, E. A., et al. (2022). Feasibi
Opintojen ennätyspäivät
Opi tärkeimmät päivämäärät
Opiskelun aloitus (Todellinen)
Ensisijainen valmistuminen (Todellinen)
Opintojen valmistuminen (Todellinen)
Opintoihin ilmoittautumispäivät
Ensimmäinen lähetetty
Ensimmäinen toimitettu, joka täytti QC-kriteerit
Ensimmäinen Lähetetty (Todellinen)
Tutkimustietojen päivitykset
Viimeisin päivitys julkaistu (Todellinen)
Viimeisin lähetetty päivitys, joka täytti QC-kriteerit
Viimeksi vahvistettu
Lisää tietoa
Tähän tutkimukseen liittyvät termit
Muita asiaankuuluvia MeSH-ehtoja
- Endokriinisen järjestelmän sairaudet
- Verisuonisairaudet
- Patologiset prosessit
- Sairauden ominaisuudet
- Metaboliset sairaudet
- Immuunijärjestelmän sairaudet
- Hengityselinten sairaudet
- Keuhkosairaudet
- Glukoosiaineenvaihduntahäiriöt
- Keuhkoputken sairaudet
- Keuhkosairaudet, obstruktiiviset
- Hengitysteiden yliherkkyys
- Yliherkkyys, välitön
- Yliherkkyys
- Lipidiaineenvaihduntahäiriöt
- Patologiset tilat, merkit ja oireet
- Ravitsemukselliset ja aineenvaihduntataudit
- Keuhkosairaus, krooninen obstruktiivinen
- Hypertensio
- Astma
- Sydän-ja verisuonitaudit
- Diabetes mellitus
- Dyslipidemiat
- Krooninen sairaus
Muut tutkimustunnusnumerot
- Petrauniversity
Yksittäisten osallistujien tietojen suunnitelma (IPD)
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