JMIR Publications

ABSTRACT

Background:

Clinical Decision Support Systems (CDSSs) based on routine care data using artificial intelligence (AI) are increasingly being developed. Previous studies focused largely on technical aspects; however, the acceptability of patients remains unclear.

Objective:

We aimed to investigate whether patient-physician trust is affected when supported by a CDSS.

Methods:

We conducted a vignette study among the patient panel (N=860) of the University Medical Center Utrecht, the Netherlands. Patients were randomly assigned into four groups, either the intervention or control group of the high-risk case or low-risk case. In both, a physician made a treatment decision with (intervention group) or without (control group) the support of a CDSS. Using a questionnaire with a 7-point Likert scale, with 1 indicating “strongly disagree” and 7 indicating “strongly agree”, we collected data on patient-physician trust in three dimensions: competence, integrity, and benevolence. We assessed differences in patient-physician trust between the control and intervention groups per case using Mann-Whitney U tests and potential effect modification by sex, age, education level, general trust in healthcare and general trust in technology using multivariate analyses of (co)variance.

Results:

In total, 398 patients participated. In the high-risk case, median perceived competence and integrity was lower in the intervention group compared to the control group but not statistically significant (5.8 vs. 5.6; P=.16 and 6.3 vs. 6.0; P=.06, respectively). However, the effect of a CDSS application on the perceived competence of the physician depended on the participant’s sex (P=.03). Although no between group differences were found in men, in women, the perception of the physician’s competence and integrity was significantly lower in the intervention compared to the control group (P=.009 and P=.01, respectively). In the low-risk case, no differences in trust between the groups were found. However, increased trust in technology positively influenced the perceived benevolence and integrity in the low-risk case (P=.009 and P=.04, respectively).

Conclusions:

We found that, in general, patient-physician trust was high. However, our findings indicate a potentially negative effect of AI applications on the patient-physician relationship, especially in women and high-risk situations. Trust in technology in general might increase the likelihood of embracing the use of CDSSs by the treating professional.