Scientific Poster Session IV - Original Research

Original Research
  Tuesday, October 15, 2024
  08:30 AM–10:00 AM

Abstract

Introduction: The use of Artificial intelligence (AI)-enabled risk stratification model has gained interest among policy makers and researchers as a potential catalyst to population health management and value-based care success. Gaining insights into the perceptions about facilitators and barriers of the healthcare professionals (HCPs) using Normalization Process Theory (NPT) is important towards successful implementation of the complex intervention.

Research Question or Hypothesis: How ready are HCPs in implementing AI-enabled risk stratification tool to predict risk of Type 2 diabetes mellitus control for targeted pharmaceutical care in Singapore?

Study Design: Quantitative cross-sectional questionnaire

Methods: A web-based, voluntary, anonymous survey using the Normalization Measure Development questionnaire (NoMAD) was used to gather views and perceptions from HCPs at Singapore General Hospital.

Results: Three professionals, including doctors (n=7, 23.3%), pharmacists (n=22, 73.3%) and data scientist (n=1, 3.3%) responded to the questionnaire. All groups saw the value of the intervention and were willing to support it. Respondents reported the highest score (mean ± SD, out of 5) in cognitive participation – relation work (4.13 ± 0.53), reflective monitoring – appraisal work (3.89 ± 0.75) and coherence – sense-making work (3.83 ± 0.72). The weakest score was in the collective action – operational work (3.70 ± 0.84). Of note, the doctors showed greater positive tendency than the pharmacists in the NPT constructs of coherence (4.11 ± 0.79 for doctors vs 3.74 ± 0.69 for pharmacists), cognitive participation (4.36 ± 0.62 for doctors vs 4.02 ± 0.45 for pharmacists) and reflective monitoring (4.13 ± 0.76 for doctors vs 3.82 ± 0.76 for pharmacists).

Conclusion: The AI-enabled risk stratification tool implementation should pay attention to the operational work involved in its use and implementation. It should also assess and communicate the ways in which the intervention can affect the pharmacists’ work. A common ground is needed to integrate the AI tool as new common practice for successful implementation.

Presenting Author

Rachel Ee Ling Gan Bachelor of Science (Pharmacy), BCPS
Singapore General Hospital

Authors

Yong Mong Bee Bachelor of Medicine, Bachelor of Surgery (MBBS)
Singapore General Hospital

Tse Lert Chua Bachelor of Science (Nursing)
Singapore General Hospital

Giat Yeng Khee Doctor of Pharmacy, BCPS
Singapore General Hospital

Paik Shia Lim Doctor of Pharmacy, BCPS
Singapore General Hospital

Yu Ling Cheryl Lim Masters of Clinical Pharmacy, BCPS
Singapore General Hospital

Jenny Ng Bachelor of Science (Pharmacy)
Singapore General Hospital

Wan Chee Ong Doctor of Pharmacy, BCPS
Singapore General Hospital