JMIR Publications

ABSTRACT

Background:

General practitioners (GPs) take care of a large number of patients with various diseases in very short timeframes under high uncertainty. Thus, artificial intelli-gence (AI) is a promising and time-saving solution that may increase the quality of care.

Objective:

This study seeks to understand GPs' attitudes towards AI solutions in medical diagnosis.

Methods:

We interviewed 18 GPs from Germany between March and May 2020 to identify determinants of GPs' attitudes towards AI solutions in diagnosis. By analyzing the interview transcripts, we identified 307 open codes which we then further struc-tured to derive relevant attitude determinants.

Results:

We merged the open codes into 21 concepts and finally into five categories: (1) concerns, (2) expectations, (3) environmental influences, (4) individual characteristics, and (5) minimum requirements of AI. Concerns include all doubts and fears of the interviewees concerning AI solutions. Expectations reflect GPs' thoughts and beliefs about expected benefits and limitations of AI solutions regarding GP care. Environmental influences include influences resulting from an evolving working environment, key stakeholders' perspectives and opinions, the available IT hardware and software resources, and the media environment. Individual characteristics are determinants that describe a physician as a person, including character traits, demographic specifics, and knowledge. Besides, the interviews also revealed minimum requirements of AI, which are preconditions that must be met for GPs to contemplate using AI. Moreover, we identified relationships between these categories, which we conflate in our proposed model.

Conclusions:

This study provides a thorough understanding of the perspective of future users of AI solutions in primary care and lays the foundation for successful market penetration. We contribute to the research stream of analyzing and designing socio-technical systems and the literature on attitude towards technology and practice by fostering the understanding of GPs and their attitude on AI solutions. Our findings provide relevant information to technology developers as well as policy makers and stakeholder institutions of GP care.