Artificial Intelligence in Primary Health Care: Perceptions, Issues, and Challenges - Liyanage, Harshana; Liaw, Siaw-Teng; Jonnagaddala, Jitendra; Schreiber, Richard; Kuziemsky, Craig; Terry, Amanda L; de Lusignan, Simon (Yearbook of Medical Informatics, 2019)
Background: Artificial intelligence (AI) is heralded as an approach that might augment or substitute for the limited processing power of the human brain of primary health care (PHC) professionals. However, there are concerns that AI-mediated decisions may be hard to validate and challenge, or may result in rogue decisions.Objective: To form consensus about perceptions, issues, and challenges of AI in primary care.Method: A three-round Delphi study was conducted. Round 1 explored experts’ viewpoints on AI in PHC (n=20). Round 2 rated the appropriateness of statements arising from round one (n=12). The third round was an online panel discussion of findings (n=8) with the members of both the International Medical Informatics Association and the European Federation of Medical Informatics Primary Health Care Informatics Working Groups.Results: PHC and informatics experts reported AI has potential to improve managerial and clinical decisions and processes, and this would be facilitated by common data standards. The respondents did not agree that AI applications should learn and adapt to clinician preferences or behaviour and they did not agree on the extent of AI potential for harm to patients. It was more difficult to assess the impact of AI-based applications on continuity and coordination of care.Conclusion: While the use of AI in medicine should enhance healthcare delivery, we need to ensure meticulous design and evaluation of AI applications. The primary care informatics community needs to be proactive and to guide the ethical and rigorous development of AI applications so that they will be safe and effective.
Keywords: Medical record systems, computerised; privacy; general practice; Delphi technique; Artificial Intelligence