Hyperlipidemia, Medication Nonadherence
Conditions
Brief 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.
Detailed 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.
Interventions
BEHAVIORALHuman Coach-supported Digital/AI Personal Health Assistant to Improve Adherence to Lipid-Lowering Medications
Receive personalised feedback and educational content curated by local clinicians and pharmacists through the CADENCE D-PHA app coupled with six sessions of human coaching on top of usual clinical care for lipid management over 6 months
Sponsors
National University Polyclinics, Singapore
Nanyang Technological University
National Healthcare Group Polyclinics
Consortium for Clinical Research and Innovation, Singapore (CRIS)
National University Heart Centre, Singapore
National University of Singapore
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
Intervention group receives coaching from trained coaches and health-related information through an app, curated by coaches. Control group follows the standard of care of hyperlipidaemia patients.
Eligibility
Sex/Gender
ALL
Age
21 Years to 84 Years
Healthy volunteers
Yes
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 criteria
* Does not read or understand English. Current use of smartphone medication adherence app(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 event reporting * Uncorrected thyroid conditions, especially poorly-controlled hypothyroidism * Documented psychiatric diagnosis or history of mental illness or deemed as unable to give informed consent. * Currently pregnant, breastfeeding or expecting to get pregnant during the course of the study (1 year). * Guarded prognosis with expectant mortality within 12 months or less.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Evaluate effectiveness of adherence to lipid-lowering medication | 6 and 12 months | Evaluate effectiveness of adherence to lipid-lowering medication through the use of pill counts |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Cardiovascular Risk score | 6 and 12 months | Different in Singapore-modified Framingham Risk Scores between intervention and control groups. The risk scores range between -5 and 20 for men and between 0 and 27 for women. Higher scores indicate higher 10-year coronary artery disease risk. |
| Changes in health motivation and attitudes | 6 and 12 months | Changes in health motivation and attitudes using Motivation and Attitude toward Changing Health (MATCH) Scale. It consists of 9 items rated on five-point Likert scale. Higher average scores indicate greater motivation and attitude. |
| Changes in self-care efficacy | 6 and 12 months | Changes in self-care efficacy using Self-efficacy for Appropriate Medication Use Scale (SEAMS) in low-literacy patients with chronic disease. The scores range between 13 to 39, with higher scores indicating higher self-efficacy for medication adherence |
| Blood LDL-cholesterol levels | 6 and 12 months | Blood LDL-cholesterol levels compared with those receiving standard care. |
| Changes in quality of life | 6 and 12 months | Change in quality of life using Single-Item Quality of Life Scale (SI-QOL). A seven-point scale is used, with higher score indicating better quality of life. |
| Safety of a new model of care | 6 and 12 months | The health coaching integrated in the app is designed with a "do no harm" principle, ensuring that coaching interventions do not cause physical, psychological, or emotional harm to the participants. This principle is embedded both in the content delivered by the coaches and in the app. Adverse Event (AE) Monitoring: AE are uncommon for health coaching intervention. However, in the case that adverse psychological events do occur, (e.g., increased anxiety or nervousness), immediate emotional support will be provided. Health coaches will ensure that participants are in emotionally stable state through check-ins (built-in in the coaching checklist), and if necessary, refer them to the healthcare team. AE will be documented in the case notes. Participants will be encouraged to report any negative experiences /symptoms, related to the intervention by using the app or via direct communication with the coach. User feedback on the app-experiences will be collected. |
| Acceptability of a new model of care | 6 and 12 months | Evaluate the acceptability of a new model of care with the use of Chatbot Usability Questionnaire. A higher score would imply better acceptability. |
| Changes in self-care behaviours | 6 and 12 months | Changes in self-care behaviours using EQ-5D-5L, where index scores range from -0.59 to 1, with 1 being the best possible health state. The accompanying EQ VAS scores range from 0 to 100, with 100 being the best possible health state. |
Countries
Singapore
Contacts
Primary ContactDoreen Su-Yin Tan, Pharm.D.
Outcome results
None listed