Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.

BACKGROUND: Increasing patient loads, healthcare inflation and ageing population have put pressure on the healthcare system. Artificial intelligence and machine learning innovations can aid in task shifting to help healthcare systems remain efficient and cost effective. To gain an understanding of patients' acceptance toward such task shifting with the aid of AI, this study adapted the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), looking at performance and effort expectancy, facilitating conditions, social influence, hedonic motivation and behavioural intention. METHODS: This was a cross-sectional study which took place between September 2021 to June 2022 at the National Heart Centre, Singapore. One hundred patients, aged ≥ 21 years with at least one heart failure symptom (pedal oedema, New York Heart Association II-III effort limitation, orthopnoea, breathlessness), who presented to the cardiac imaging laboratory for physician-ordered clinical echocardiogram, underwent both echocardiogram by skilled sonographers and the experience of echocardiogram by a novice guided by AI technologies. They were then given a survey which looked at the above-mentioned constructs using the UTAUT2 framework. RESULTS: Significant, direct, and positive effects of all constructs on the behavioral intention of accepting the AI-novice combination were found. Facilitating conditions, hedonic motivation and performance expectancy were the top 3 constructs. The analysis of the moderating variables, age, gender and education levels, found no impact on behavioral intention. CONCLUSIONS: These results are important for stakeholders and changemakers such as policymakers, governments, physicians, and insurance companies, as they design adoption strategies to ensure successful patient engagement by focusing on factors affecting the facilitating conditions, hedonic motivation and performance expectancy for AI technologies used in healthcare task shifting.

CYP2C19 and PON1 polymorphisms regulating clopidogrel bioactivation in Chinese, Malay and Indian subjects.

UNLABELLED: AIM, MATERIALS & METHODS: We investigated the functional significance of CYP2C19*2, *3, *17 and PON1 Q192R SNPs in 89 consecutive Asian patients on clopidogrel treatment and the prevalence of functionally significant polymorphisms among 300 Chinese, Malays and Asian Indians. RESULTS: Both CYP2C19 loss-of-function alleles (*2 or *3) were associated with higher platelet reactivity while the CYP2C19 gain-of-function allele (*17) had lower platelet reactivity. For PON1, the median PRI was not significantly different between the QQ, QR and RR groups. The allele frequencies of CYP2C19*2, CYP2C19*3 and CYP2C19*17 were 0.280, 0.065 and 0.010 (rare) for Chinese, 0.310, 0.050 and 0.025 for Malays, and 0.375, 0.010 (rare) and 0.165 for Indians, respectively. CONCLUSION: Our data suggest that genotyping studies to investigate clopidogrel response should include CYP2C19*2 and *3 but not *17 polymorphisms in Chinese, and CYP2C19*2 and *17 polymorphisms but not *3 in Indians. All three polymorphisms should preferably be genotyped in Malays.