An interventional study of Diabetes Management Package (DMP) and M-POWER Rewards in Diabetes Mellitus, Type 2, sponsored by Duke-NUS Graduate Medical School. Completed at 1 site in Singapore. Open to participants aged 21 Years to 70 Years. Per ClinicalTrials.gov, last updated 2023-06-22.
Sponsored by Duke-NUS Graduate Medical School · Not applicable, Interventional, and Health services research
The research objective of this one-year study is to test whether an evidence-based, low-cost mobile diabetes management package (DMP), with or without an incentive program grounded in economic theory (M-POWER Rewards), can effectively and cost-effectively improve health outcomes for adults with type 2 diabetes.
Technological and economic advancement have created a major challenge to public health agencies in Singapore and other first world countries: the challenge being how to get individuals to maintain a healthy lifestyle when that is no longer a requirement for economic prosperity (and in fact may be a hindrance). What is required is a low cost strategy that effectively manages risk factors for chronic disease without overwhelming the public healthcare infrastructure. Although technology and economic advancement are clearly part of the problem, they may also be part of the solution.
For patients with type 2 diabetes mellitus (T2DM), lifestyle modification can be highly effective at stemming the progression of the disease. Effective interventions include modules that teach appropriate strategies for weight management, increased physical activity, better diet, routine glucose monitoring, and strict compliance to prescribed diabetes medications. These components can now be effectively delivered electronically. A recent review and meta-analysis of 13 smartphone applications for diabetes management found that these applications offered modest benefits, with a mean difference in HbA1c of -0.40%.
Because of the high costs involved in treating people with chronic conditions, employers, insurers, and governments all have a financial incentive to contain the chronic disease epidemic. Therefore, each has shown a willingness to invest in some level of prevention and treatment efforts. It is our contention that contingent rewards may be necessary to help people overcome their preferences for current over future consumption, often called present bias. Behavioral economists recommend that, to overcome present bias, rewards should be tied to both short-term and long-term outcomes or behaviors, such as monitoring blood glucose and taking medications as prescribed (short term) and pre-defined outcomes such as achieving a target HbA1c level over a specified duration (long term). Based on a recent systematic review of incentive studies conducted by members of our team, an optimal rewards strategy has the potential to greatly increase the effectiveness of existing mobile diabetes applications. If shown to be effective and cost effective, the investigators also believe payers will subsidize such a strategy.
Specifically, the investigators propose to conduct a 52-week, three-arm randomized controlled trial to evaluate whether an evidence-based, low-cost mobile diabetes management package (DMP), with or without an incentive program grounded in economic theory, can effectively and cost-effectively improve outcomes for adults with diabetes. The control arm (Arm 1) will receive usual care, whereas participants in the intervention arms will receive the DMP alone (Arm 2) or the DMP with the M-POWER Rewards incentive program (Arm 3) in addition to their usual care. The investigators hypothesize that participants in Arms 2 and 3 will show improved glycemic control, as measured by HbA1c levels, at the Month 12 primary endpoint compared to participants in the Arm 1 control group. The investigators also hypothesize that Arm 3 will have improved HbA1c levels compared to Arm 2 at Month 12. Similar hypotheses will be tested for secondary outcomes measured at Month 6.
In addition, the investigators will quantify the incremental cost-effectiveness of DMP with M-POWER Rewards and the net cost implications of both from a third party payer's perspective. The investigators hypothesize that despite its higher implementation cost, effectiveness will be greater and net cost will be lower for Arm 3 relative to the Arm 1 control group due to the reduction in medical expenditures that result from improved glycaemic control.
10,925 studies on the registry are indexed under Diabetes Mellitus; 1,319 are open to participants now.
This study's enrollment of 269 is above the median of 80 across 8,367 interventional studies indexed under Diabetes Mellitus.
Browse Diabetes Mellitus studies →Duke-NUS Graduate Medical School is the lead sponsor of 62 studies on the registry; 6 are open to participants now.
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All eligibility criteria will be self-declared.
Inclusion Criteria:
Exclusion Criteria:
Participants will receive usual care by their diabetes clinics.
Participants will receive usual care by their diabetes clinics and the Diabetes Management Package (DMP).
Behavioral: Diabetes Management Package (DMP)
Participants will receive usual care by their diabetes clinics, the Diabetes Management Package (DMP), and the financial incentive program, M-POWER Rewards.
Behavioral: Diabetes Management Package (DMP) · Behavioral: M-POWER Rewards
M-POWER app: A one-stop portal to monitor diabetes self-management activities and progress. The app syncs and displays relevant data from study devices and apps. GlycoLeap: A 24-week, digitally-delivered education and behavior change program for T2DM patients. 4 study devices with accompanying apps to aid in diabetes self-management: weighing scale, pedometer, glucometer, and pill tracker. Recommended activities: * Complete all 24 GlycoLeap lessons and quizzes * Weight Monitoring: Weigh at least once a week. * Physical Activity: At least 150 minutes of moderate-to-vigorous activity per week, targeting at least 420 Fitbit active minutes per week. * Blood Glucose Monitoring: At least three post-meal measurements within 4.0-10.0 mmol/L per week, with each reading taken on different days. * Medication: Take medications as prescribed.
A financial incentive program were participants can earn up to 516 M-Points (1 M-Point is equivalent to S$1) over the one-year study period for performing specific activities according to recommendations that are meant to improve glycemic control and for achieving HbA1c and weight loss goals. M-Points can be reimbursed in the form of financial rebates for approved non-inpatient healthcare-related expenses incurred during the study period.
Change in HbA1c levels at Month 12
HbA1c or glycated hemoglobin is a measure of blood glucose levels. HbA1c blood tests will be conducted at baseline and Month 12 and the difference will be calculated.
Time frame: Baseline, Month 12
Change in HbA1c levels at Month 6
HbA1c or glycated hemoglobin is a measure of blood glucose levels. HbA1c blood tests will be conducted at baseline and Month 6 and the difference between the follow-up assessment (Months 6) and baseline will be calculated.
Time frame: Baseline, Month 6
Change in weight at Months 6 and 12
Weight will be measured at baseline, Month 6, and Month 12. The difference in weight between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in blood pressure at Months 6 and 12
Blood pressure will be measured at baseline, Month 6, and Month 12. The difference in blood pressure between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Proportion of participants that had insulin treatment initiated by Months 6 and 12
Percentage of participants that had insulin treatment initiated by their diabetes care physician by each follow-up assessment (Months 6 and 12).
Time frame: Baseline, Month 6, Month 12
Change in self-reported physical activity at Months 6 and 12
Self-reported physical activity data will be collected at baseline, Month 6, and Month 12 via the Global Physical Activity Questionnaire (GPAQ). The difference in self-reported physical activity between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported weight monitoring at Months 6 and 12
Self-reported weight monitoring data will be collected at baseline, Month 6, and Month 12. The difference in self-reported weight monitoring between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported blood glucose monitoring at Months 6 and 12
Self-reported blood glucose monitoring data will be collected at baseline, Month 6, and Month 12. The difference in self-reported blood glucose monitoring between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported medication adherence at Months 6 and 12
Self-reported medication adherence data will be collected at baseline, Month 6, and Month 12. The difference in self-reported medication adherence between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported diabetes self-management at Months 6 and 12
Self-reported diabetes self-management data will be collected at baseline, Month 6, and Month 12 via the Diabetes Self-Management Questionnaire (DSMQ). The difference in self-reported diabetes self-management between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported sleep quality at Months 6 and 12
Self-reported sleep quality data will be collected at baseline, Month 6, and Month 12 via the Pittsburgh Sleep Quality Index (PSQI). The difference in self-reported sleep quality between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported work productivity and daily activity impairment at Months 6 and 12
Self-reported work productivity and daily activity impairment data will be collected at baseline, Month 6, and Month 12 via a modified Work Productivity and Activity Impairment: Specific Health Problem instrument (WPAI:SHP). The difference in self-reported work productivity and daily activity impairment between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Change in self-reported health utility index at Months 6 and 12
Self-reported health utility index data will be collected at baseline, Month 6, and Month 12 via the EQ-5D-5L questionnaire. The difference in self-reported health utility index between each follow-up assessment (Months 6 and 12) and baseline will be calculated.
Time frame: Baseline, Month 6, Month 12
Incremental cost-effectiveness ratios based on HbA1c at Month 12
Incremental cost-effectiveness ratios will be determined by calculating the incremental cost per unit reduction in HbA1c at Month 12 (primary endpoint) compared to baseline.
Time frame: Baseline, Month 12
Incremental cost-effectiveness ratios based on QALY at Month 12
Incremental cost-effectiveness ratios will be determined by calculating the incremental cost per quality adjusted life year (QALY) gained at Month 12 (primary endpoint) compared to baseline.
Time frame: Baseline, Month 12
This study is completed, as verified in Jun 2023. You cannot join it, but the record below documents what was studied.
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Duke-NUS Graduate Medical School