Better Risk Perception Via Patient Similarity to Control Hyperglycemia and Sustained by Telemonitoring

Summary

Background: Diabetes significantly raises the likelihood of complications, thereby increasing the risk of diabetes-related mortality, particularly due to vascular complications. It is vital to address this rising trend of mortality, by enhancing awareness of diabetes complications to improve risk perception and ultimately reduce mortality rates. Managing diabetes effectively requires interventions addressing both risk communication and monitoring, helping patients better understand and make informed decisions about their health.

Objectives: The primary aim is to evaluate and compare the effectiveness of combined risk communication session using an AI module (PERDICT.AI) and home-based diabetes monitoring (PTEC-DM) versus a standalone risk communication session in improving health outcomes (risk perception, medication adherence, self-care activities and glycaemic control) among poorly controlled diabetes patients. Secondary aims are to explore participants' views and experiences of risk communication session using PERDICT.AI, PTEC-DM and usual care and clinician' views on utility of the new approach to improve risk perception.

Methods: A mixed-method study design will be employed to conduct a multi-arm randomized controlled trial across four of the SingHealth Polyclinics cluster (Pasir Ris, Eunos, Sengkang, Tampines North). Patient participants will be randomly allocated in a 1:1:1 ratio to one of the three arms. Arm 1 will receive risk communication session using PERDICT.AI and home-based diabetes monitoring using PTEC-DM alongside usual care. Arm 2 participants will undergo a standalone risk communication session using PERDICT.AI with usual care while arm 3 will serve as the control group with usual care. A total of 360 (120 in each group) participants will be enrolled by simple randomization. Eligible patient must be of age between 36 and 65 years with HbA1c \>8.0% within the last 6 months.

Significance of the study: Findings from the study may add evidence to the scientific knowledge of using these approaches to improve risk perception and recommend development of similar interventions.

Conditions

• Diabetes Mellitus, Type 2

Interventions

OTHER

Intervention using an AI enabled risk communication tool (PERDICT.AI)

Risk communication using PERDICT.AI dynamically communicates an individual's glycemic control, offering a comparative ranking among peers to enhance motivation and awareness. Furthermore, it assesses the risk of potential complications comparing with peer data with exemplary cases to underscore the consequences of suboptimal management. In addition, it will generate personalized recommendations including medication adjustment and personalized health plans.

OTHER

Telemonitoring with Primary Tech Enhanced Care (PTEC-DM)

The Primary Tech-Enhanced Care (PTEC) programme focuses on encouraging patients to manage chronic conditions at home through user-friendly kits. The Home Diabetes Monitoring programme (PTEC-DM) enables home-based glucose and blood pressure monitoring once a week using a Bluetooth enabled device. These reading will be securely transmitted to the study team via the app and managed appropriately through teleconsultation. Additionally, participants will receive health nudges, encouragements, and reminders through in-app messages to support their well-being.

Sponsors & Collaborators

• AISG Health Grand Challenge

  collaborator UNKNOWN

• SingHealth Polyclinics

  lead OTHER

Principal Investigators

• Ngiap Chuan Tan, MMed · SingHealth Polyclinics

Study Design

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

36 Years

Max Age

65 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2024-07-15

Primary Completion

2026-12-31

Completion

2026-12-31

Countries

• Singapore

Study Locations