Personalised health plan development using agentic AI in Singapore’s national preventive care programme: a pilot study

The workforce shortages caused by aging populations demand a transition from reactive to preventive healthcare strategies. Generative Artificial Intelligence offers a promising solution through the use of agents that can generate personalised guidance. We implement a digital assistant powered by a multi-agent framework that generates and refines personalised health plans based on user interactions. A pilot study with a cohort of 20 residents and 7 clinicians revealed positive user acceptance. Both groups rated four success metrics significantly above neutral satisfaction levels (p values: <0.05). The majority of residents valued the personalisation (p value: 0.003), appreciated the level of granularity (p value: 0.0003), and did not express major concerns about the recommended plans (p value: 0.941). More than 50% of the collected feedback reflected a positive sentiment on the personalised diet (p value: 0.110), personalised exercise (p value: 0.003), and general features (p value: 6e-06). This pilot study highlights the potential of AI-driven digital assistants in supporting preventive healthcare programmes.

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Publication Details

Journal
npj Digital Medicine
Published
2026-03-09
DOI
https://doi.org/10.1038/s41746-026-02514-8
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Personalised health plan development using agentic AI in Singapore’s national preventive care programme: a pilot study

Chia-Zhi Tan, Vicente Sancenón, Delia Teo, Corryne N. Thng et al.
npj Digital Medicine
Artificial Intelligence in Healthcare and Education
article

Personalised health plan development using agentic AI in Singapore’s national preventive care programme: a pilot study

Chia-Zhi Tan, Vicente Sancenón, Delia Teo, Corryne N. Thng, Han Leong Goh, Maybelline S. L. Ooi, Leroy Koh, Benjamin M. X. Chu, Andy W. A. Ta, David W. L. Chua, Gerald C. H. Koh
article en

Abstract

The workforce shortages caused by aging populations demand a transition from reactive to preventive healthcare strategies. Generative Artificial Intelligence offers a promising solution through the use of agents that can generate personalised guidance. We implement a digital assistant powered by a multi-agent framework that generates and refines personalised health plans based on user interactions. A pilot study with a cohort of 20 residents and 7 clinicians revealed positive user acceptance. Both groups rated four success metrics significantly above neutral satisfaction levels (p values: <0.05). The majority of residents valued the personalisation (p value: 0.003), appreciated the level of granularity (p value: 0.0003), and did not express major concerns about the recommended plans (p value: 0.941). More than 50% of the collected feedback reflected a positive sentiment on the personalised diet (p value: 0.110), personalised exercise (p value: 0.003), and general features (p value: 6e-06). This pilot study highlights the potential of AI-driven digital assistants in supporting preventive healthcare programmes.

npj Digital Medicine
Ministry of Health (SG), Health Promotion Board (SG), Synapse Biomedical (United States) (US), Institute of Materials Research and Engineering (SG), MOH Holdings (SG)
Partnerships for the goals
Openalex Percentile: Top 31%
Artificial Intelligence in Healthcare and Education
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Personalised health plan development using agentic AI in Singapore’s national preventive care programme: a pilot study — Chia-Zhi Tan, Vicente Sancenón, et al. · npj Digital Medicine (2026) | TGRS Research Map | TGRS