Comparison of Shave and Punch Biopsy Utilization Among Dermatology Practices.

In 2019, the 2 Current Procedural Terminology (CPT) codes for skin biopsies were replaced with 6 new CPT codes to allow for technique specification and differential reimbursement. We sought to evaluate whether the concurrent decrease in reimbursement for shave biopsies and increase in reimbursement for punch biopsies led to utilization changes. We examined shave and punch biopsies submitted for pathologic examination at 3 academic centers in May 2018 and May 2019. We performed χ2 tests to evaluate for changes in the ratio of biopsy utilization over time, with subgroup analyses by practice setting and provider type. Totals included 11,785 (12.11% punch) and 11,291 (12.08% punch) biopsies submitted in May 2018 and May 2019, respectively. Our results demonstrate small yet important changes in biopsy use patterns within the context of recent reimbursement changes when analyzing academic and private practices separately. Although small in magnitude, this change in behavior may have a substantial impact when extrapolated to behavior across the nation.

Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.

Importance: The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the potential for direct-to-patient and clinician decision-support AI tools to classify skin lesions. Although AI is poised to change how patients engage in health care, patient perspectives remain poorly understood. Objective: To explore how patients conceptualize AI and perceive the use of AI for skin cancer screening. Design, Setting, and Participants: A qualitative study using a grounded theory approach to semistructured interview analysis was conducted in general dermatology clinics at the Brigham and Women's Hospital and melanoma clinics at the Dana-Farber Cancer Institute. Forty-eight patients were enrolled. Each interview was independently coded by 2 researchers with interrater reliability measurement; reconciled codes were used to assess code frequency. The study was conducted from May 6 to July 8, 2019. Main Outcomes and Measures: Artificial intelligence concept, perceived benefits and risks of AI, strengths and weaknesses of AI, AI implementation, response to conflict between human and AI clinical decision-making, and recommendation for or against AI. Results: Of 48 patients enrolled, 26 participants (54%) were women; mean (SD) age was 53.3 (21.7) years. Sixteen patients (33%) had a history of melanoma, 16 patients (33%) had a history of nonmelanoma skin cancer only, and 16 patients (33%) had no history of skin cancer. Twenty-four patients were interviewed about a direct-to-patient AI tool and 24 patients were interviewed about a clinician decision-support AI tool. Interrater reliability ratings for the 2 coding teams were κ = 0.94 and κ = 0.89. Patients primarily conceptualized AI in terms of cognition. Increased diagnostic speed (29 participants [60%]) and health care access (29 [60%]) were the most commonly perceived benefits of AI for skin cancer screening; increased patient anxiety was the most commonly perceived risk (19 [40%]). Patients perceived both more accurate diagnosis (33 [69%]) and less accurate diagnosis (41 [85%]) to be the greatest strength and weakness of AI, respectively. The dominant theme that emerged was the importance of symbiosis between humans and AI (45 [94%]). Seeking biopsy was the most common response to conflict between human and AI clinical decision-making (32 [67%]). Overall, 36 patients (75%) would recommend AI to family members and friends. Conclusions and Relevance: In this qualitative study, patients appeared to be receptive to the use of AI for skin cancer screening if implemented in a manner that preserves the integrity of the human physician-patient relationship.