Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners

A Baki Kocaballi; Kiran Ijaz; Liliana Laranjo; Juan C Quiroz; Dana Rezazadegan; Huong Ly Tong; Simon Willcock; Shlomo Berkovsky; Enrico Coiera

doi:10.1093/jamia/ocaa131

Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners

J Am Med Inform Assoc. 2020 Nov 1;27(11):1695-1704. doi: 10.1093/jamia/ocaa131.

Authors

A Baki Kocaballi^{1

2}, Kiran Ijaz¹, Liliana Laranjo^{1

3}, Juan C Quiroz¹, Dana Rezazadegan^{1

4}, Huong Ly Tong¹, Simon Willcock⁵, Shlomo Berkovsky¹, Enrico Coiera¹

Affiliations

¹ Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
² Faculty of Engineering & IT, University of Technology Sydney, Sydney, Australia.
³ Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
⁴ Faculty of Science, Engineering and Technology, Swinburne University of Technology, Victoria, Australia.
⁵ Health Sciences Centre, Macquarie University, Sydney, Australia.

Abstract

Objective: The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners.

Materials and methods: Co-design workshops with general practitioners were conducted. The workshops focused on (1) understanding the current consultation context and identifying existing problems, (2) ideating future solutions to these problems, and (3) discussing future roles for AI in primary care. The workshop activities included affinity diagramming, brainwriting, and video prototyping methods. The workshops were audio-recorded and transcribed verbatim. Inductive thematic analysis of the transcripts of conversations was performed.

Results: Two researchers facilitated 3 co-design workshops with 16 general practitioners. Three main themes emerged: professional autonomy, human-AI collaboration, and new models of care. Major implications identified within these themes included (1) concerns with medico-legal aspects arising from constant recording and accessibility of full consultation records, (2) future consultations taking place out of the exam rooms in a distributed system involving empowered patients, (3) human conversation and empathy remaining the core tasks of doctors in any future AI-enabled consultations, and (4) questioning the current focus of AI initiatives on improved efficiency as opposed to patient care.

Conclusions: AI documentation assistants will likely to be integral to the future primary care consultations. However, these technologies will still need to be supervised by a human until strong evidence for reliable autonomous performance is available. Therefore, different human-AI collaboration models will need to be designed and evaluated to ensure patient safety, quality of care, doctor safety, and doctor autonomy.

Keywords: artificial intelligence; general practitioners; medical informatics; primary health care; qualitative study.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence*
Attitude of Health Personnel*
Attitude to Computers
Decision Making, Computer-Assisted
Documentation* / trends
Electronic Health Records
Forecasting
General Practitioners*
Humans
Primary Health Care*
Professional Autonomy*
Referral and Consultation
User-Computer Interface