JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI) tools are widely and freely available for clinical use, yet little is known about how physicians actually use them in routine practice. Understanding real-world adoption patterns is essential for healthcare institutions to develop governance frameworks and optimize AI integration.

Objective:

The objective of this study was to investigate hospitalist use of AI, examining the AI platforms being utilized, frequency of use, and clinical contexts of application.

Methods:

An anonymous online survey was distributed via email to all 70 hospitalists (physicians, nurse practitioners, physician assistants) providing direct patient care at a large urban academic tertiary care hospital. Demographic data, AI platform used if any, purpose(s) for AI use, and frequency of use information was collected. CHERRIES checklist was used for creating, testing, administering, and reporting the results of the survey.

Results:

Of 70 providers, 54 (77.1%) responded to the survey. Respondent demographics were representative of the overall provider group. No significant differences in AI usage were observed across shift type, years of independent practice, time allocation to hospitalist duties, sex, age, or provider designation, contrary to our hypothesis that younger, less experienced hospitalists would use AI more frequently. Overall, 36 of 54 respondents (66.7%) reported using AI in clinical practice. OpenEvidence was the most commonly used platform (28/54, 51.9%). Among non-users, primary concerns were AI accuracy and preference for established resources. The most common application was answering miscellaneous clinical questions (32/36, 88.9%), generating differential diagnoses (31/36, 86.1%) and determining management options (31/36, 86.1%), with much lower use for patient education materials (16/36, 44.4%). Pairwise comparisons revealed significant differences between use for answering miscellaneous questions and confirming suspected diagnosis (P=.003), and generating patient education materials (P=.004) respectively. Most respondents reported using AI for under 25% clinical encounters across all use cases.

Conclusions:

Two-thirds of hospitalists organically adopted AI despite the absence of institutional oversight. AI is predominantly used as a supplementary decision support tool for complex cases, with a preference for a medical-specific platform. Healthcare institutions must develop governance frameworks, validation protocols, and educational initiatives to ensure safe and effective AI deployment in clinical practice. Clinical Trial: Not applicable