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

Journal: BMC health services research
PMID:

Abstract

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.

Authors

  • Weiting Huang
    National Heart Centre Singapore, 5 Hospital Drive, Singapore, 169609, Singapore. huang.weiting@singhealth.com.sg.
  • Wen Chong Ong
    National Healthcare Group Polyclinics, Singapore, Singapore.
  • Mark Kei Fong Wong
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore.
  • Eddie Yin Kwee Ng
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore. Electronic address: mykng@ntu.edu.sg.
  • Tracy Koh
    National Heart Centre Singapore, 5 Hospital Drive, Singapore, 169609, Singapore.
  • Chanchal Chandramouli
    National Heart Centre Singapore, 5 Hospital Drive, Singapore, 169609, Singapore.
  • Choon Ta Ng
    National Heart Centre Singapore, 5 Hospital Drive, Singapore, 169609, Singapore.
  • Yoran Hummel
    Us2.ai, 2 College Rd, #02-00, Singapore 169850, Singapore.
  • Feiqiong Huang
    , Us2.ai, Singapore, Singapore.
  • Carolyn Su Ping Lam
    National Heart Centre Singapore, 5 Hospital Drive, Singapore, 169609, Singapore.
  • Jasper Tromp
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.