Physician views of artificial intelligence in otolaryngology and rhinology: A mixed methods study

Author:

Asokan Annapoorani1ORCID,Massey Conner J.2,Tietbohl Caroline34,Kroenke Kurt56,Morris Megan47,Ramakrishnan Vijay R.68

Affiliation:

1. Department of Internal Medicine USC/LA General Medical Center Los Angeles California USA

2. Department of Otolaryngology—Head & Neck Surgery University of Colorado School of Medicine Aurora Colorado USA

3. Department of Family Medicine University of Colorado School of Medicine Aurora Colorado USA

4. Qualitative and Mixed Methods Research Core, Adult and Child Center for Outcomes Research Delivery Science (ACCORDS) University of Colorado School of Medicine Aurora Colorado USA

5. Indiana University School of Medicine Indianapolis Indiana USA

6. Regenstrief Institute, Inc. Indianapolis Indiana USA

7. Department of Internal Medicine University of Colorado School of Medicine Aurora Colorado USA

8. Department of Otolaryngology—Head & Neck Surgery Indiana University School of Medicine Indianapolis Indiana USA

Abstract

AbstractObjectiveThe study aimed to investigate otolaryngologists' knowledge, trust, acceptance, and concerns with clinical applications of artificial intelligence (AI).MethodsThis study used mixed methods with survey and semistructured interviews. Survey was e‐mailed to American Rhinologic Society members, of which a volunteer sample of 86 members responded. Nineteen otolaryngologists were purposefully recruited and interviewed until thematic saturation was achieved.ResultsSeventy‐six respondents (10% response rate) completed the majority of the survey: 49% worked in academic settings and 43% completed residency 10 or fewer years ago. Of 19 interviewees, 58% worked in academic settings, and 47% completed residency 10 or fewer years ago. Familiarity: Only 8% of survey respondents reported having AI training in residency, although 72% had familiarity with general AI concepts; 0 interviewees had personal experience with AI in clinical settings. Expected uses: Of the surveyed otolaryngologists, 82% would use an AI‐based clinical decision aid and 74% were comfortable with AI proposing treatment recommendations. However, only 44% of participants would trust AI to identify malignancy and 53% to interpret radiographic images. Interviewees trusted AI for simple tasks, such as labeling septal deviation, more than complex ones, such as identifying tumors. Factors influencing AI adoption: 89% of survey participants would use AI if it improved patient satisfaction, 78% would be willing to use AI if experts and studies validated the technologies, and 73% would only use AI if it increased efficiency. Sixty‐one percent of survey respondents expected AI incorporation into clinical practice within 5 years. Interviewees emphasized that AI adoption depends on its similarity to their clinical judgment and to expert opinion. Concerns included nuanced or complex cases, poor design or accuracy, and the personal nature of physician‐patient relationships.ConclusionFew physicians have experience with AI technologies but expect rapid adoption in the clinic, highlighting the urgent need for clinical education and research. Otolaryngologists are most receptive to AI “augmenting” physician expertise and administrative capacity, with respect for physician autonomy and maintaining relationships with patients.Level of EvidenceLevel VI, descriptive or qualitative study.

Publisher

Wiley

Subject

General Medicine

Reference32 articles.

1. Medicine and the Computer

2. Machine Learning in Medicine

3. Otorhinolaryngology and Artificial Intelligence

4. NIH strategic plan for data science.National Institutes of Health.2018Accessed March 15 2023.https://datascience.nih.gov/sites/default/files/NIH_Strategic_Plan_for_Data_Science_Final_508.pdf

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