Effectiveness and cost‐effectiveness of an app and rewards‐based intervention in type 2 diabetes: A randomised controlled trial
Aim
Digital health interventions and economic incentives have shown promise in facilitating diabetes self‐management, though evidence is limited. Therefore, this study aimed to evaluate the effectiveness and cost‐effectiveness of a comprehensive app‐based diabetes self‐management programme with rewards for healthy behaviours and health outcomes.
Materials and Methods
The TRIal to slow the Progression Of Diabetes (TRIPOD) study was an open‐label, parallel‐group, randomised controlled trial conducted at Duke‐NUS Medical School, Singapore. Adults with Type 2 Diabetes (diabetes), HbA
1c
of 7.5%‐11.0% (inclusive) and taking at least one oral diabetes medication were eligible. In total, 269 participants were randomised across three arms [Usual care (UC): 117, diabetes management programme (DMP) (intervention without rewards): 36, DMP+ (intervention with rewards): 116]. Data were analysed using intention‐to‐treat analysis with change in HbA
1c
at month 12 between DMP+ and UC as the primary outcome. Cost‐effectiveness of DMP+ relative to UC was also calculated.
Results
Mean HbA
1c
improved by 0.1% in UC and by 0.5% in DMP+ at 12 months, revealing a mean difference of 0.4% (95% confidence interval (CI): −0.70, −0.08,
p
= 0.015). The odds ratio of HbA
1c
improvements of >0.5% was 2.12 (95% CI: 1.17, 3.85,
p
= 0.013) for DMP+ relative to UC. The incremental cost‐effectiveness ratio of DMP+ relative to UC was SGD8,516 (USD6,531) per quality‐adjusted life year gained if effectiveness could be maintained with a single year of intervention.
Conclusions
A comprehensive app‐based diabetes self‐management programme with rewards for healthy behaviours and health outcomes (DMP+) cost‐effectively improved glycaemic control in Type 2 diabetes patients. Organizations focusing on value‐based healthcare should consider subsidising similar interventions.
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May Ee Png, Joanne Yoong, Thao Phuong Phan et al.
Saki Amagai, Sarah Pila, Aaron J Kaat et al.
R E Glasgow, T M Vogt, S M Boles
- Published
- Dec 05, 2024
- Vol/Issue
- 27(2)
- Pages
- 729-739
- License
- View
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