AdLip: Human Coach-supported Digital/AI Personal Health Assistant to Improve Adherence to Lipid-Lowering Medication

Last updated: October 1, 2024
Sponsor: National University of Singapore
Overall Status: Active - Recruiting

Phase

N/A

Condition

Dyslipidemia

Elevated Triglycerides (Hypertriglyceridemia)

Hypercholesterolemia

Treatment

Human Coach-supported Digital/AI Personal Health Assistant to Improve Adherence to Lipid-Lowering Medications

Clinical Study ID

NCT06614049
2023/00438
  • Ages 21-84
  • All Genders
  • Accepts Healthy Volunteers

Study Summary

Investigators hypothesize that the use of a human coach-supported digital/AI personal health assistant (app) will improve adherence to cholesterol-lowering medications (statins with or without ezetimibe) among patients with hyperlipidaemia and suboptimal LDL-C control, when compared to standard care.

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Between 21 to 84 years old

  • Prescribed statins with or without ezetimibe for hyperlipidaemia.

  • Medication non-adherence as defined by the "Extent to Non-adherence"sub-scale of the DOSE Non-Adherence Measure), with a score > 1 (range from 0-15)

  • Singapore residents (citizens, permanent residents, or long-term pass holders).

  • In possession of a smartphone or tablet with Android or iOS operating systems.

  • Have internet access on their mobile devices.

Exclusion

Exclusion Criteria:

  • Does not read or understand English. Current use of smartphone medication adherenceapp(s) that include statins.

  • Concurrent use of PCSK9 Inhibitors in addition to statins and/or ezetimibe

  • Participation in another study that uses medications that could affect lipid levels

  • Severe renal impairment defined as chronic kidney disease stage 4 and above.

  • Severe liver disease (Child-Pugh Class C)

  • Existing muscular-related complaints or diagnoses which may confound adverse eventreporting

  • Uncorrected thyroid conditions, especially poorly-controlled hypothyroidism

  • Documented psychiatric diagnosis or history of mental illness or deemed as unable togive informed consent.

  • Currently pregnant, breastfeeding or expecting to get pregnant during the course ofthe study (1 year).

  • Guarded prognosis with expectant mortality within 12 months or less.

Study Design

Total Participants: 450
Treatment Group(s): 1
Primary Treatment: Human Coach-supported Digital/AI Personal Health Assistant to Improve Adherence to Lipid-Lowering Medications
Phase:
Study Start date:
June 10, 2024
Estimated Completion Date:
February 14, 2026

Study Description

Hyperlipidemia remains as one of the three leading metabolic risk factors underlying AMI onset by 2050. In recent study 3 Asian ethnicities with AMI, the incidence of hyperlipidemia is projected to increase by 205% (341 to 1041 per 100,000 population) from 2025 to 2050. A combination of lifestyle modifications and lipid-lowering therapy is typically recommended for individuals with high LDL-C levels to reduce the risk of CVD. The World Health Organization (WHO) defines adherence as "the extent to which the person's behaviour (including medication-taking) corresponds with agreed recommendations from a healthcare provider"

Poor medication adherence portends poorer health outcomes. In Singapore, around 60% of adults not taking their medications as prescribed (as above) and this creates a considerable economic and clinical burden to individuals and health systems.

The use of digital technology in medication adherence has continued to grow as more healthcare providers and patients recognise its benefits in improving adherence and overall health outcome. Digital interventions have effectively helped patients manage their medication by reminding patients to take their medications on time and providing them with more information about their medications and treatment plan. In the busy world today, the provision of appropriately timed and that perceived to be important would be key to effectively convince intentionally non-adherent patients to take their medicines as prescribed.

This study is a multicentre, open-label, two-arm parallel randomized controlled trial. We intent to randomly assign patients with hyperlipidaemia into one of the two groups: human coach-supported Digital/AI Personal Health Assistant app (intervention group) and standard care (control group) with a 1:1 allocation ratio. The intervention group will receive personalised feedback through the app coupled with human coaching on top of usual clinical care for cholesterol management. The control group will receive usual standard of care for lipid management but will not receive the personalised app nor have access to health coaching.

Participants with hyperlipidaemia (n=376) will be enrolled in polyclinics, and key inclusion criteria are participants who are non-adherent to statins "Extent to Non-adherence" sub-scale of the DOSE Non-Adherence Measure), with a score > 1 (range from 0-15) with or without on ezetimibe and have LDL-C level above the recommended target levels stratified by risk category. Participants will be followed up at Visit 2 @Month 3, Visit 3 @ Month 6 and Visit 4 @ Month 12 while pill counts will be collected @3m, 6m, and 12m visits. As part of Standard-of-Care, clinical pharmacist will follow-up with patients, titrating lipid-lowering medication (such as statin, ezetimibe etc) as required, and review and take action clinical blood test results.

Only those in intervention group, Human-AI-Health coach will use the information gathered by the AI chatbot to guide the targeted behavioural intervention during phone consultation. The scope of coaching will be strictly related to the medication adherence and general well-being. The coach will not start, stop, or titrate any medication. Coach will escalate concerns to clinical pharmacists when deemed fit. A sub-study of focus group discussion will be conducted with a nested sample of 30-50 intervention group patients. The aims are: (a) to collect insights from intervention patients on their experiences with the app and human health coaching, (b) insights into which intervention components work best for them and under what circumstances, (c) insights into concerns which might impact intervention effectiveness, (d) factors that draw their participation and sustained engagement, (e) factors that deter them from sustainable engagement, (f) factors that may lead other CVD patients to be more inclined to partake in such a intervention and (g) ideas and suggestions to make the intervention more appealing and effective.

Connect with a study center

  • National Healthcare Group Polyclinics

    Singapore, 138543
    Singapore

    Active - Recruiting

  • National University Polyclinics

    Singapore, 609606
    Singapore

    Active - Recruiting

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