Workforce Characteristics of Non-Physician Clinicians in Dermatology in the United States

Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4

Large language models (LLMs) are seen to have tremendous potential in advancing medical diagnosis recently, particularly in dermatological diagnosis, which is a very important task as skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases. Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors' notes, and designing a two-step training strategy. We have quantitatively evaluated SkinGPT-4 on 150 real-life cases with board-certified dermatologists. With SkinGPT-4, users could upload their own skin photos for diagnosis, and the system could autonomously evaluate the images, identify the characteristics and categories of the skin conditions, perform in-depth analysis, and provide interactive treatment recommendations.

Comparison of prescribing patterns of non-physician clinicians and dermatologists in the Medicare population

Non-physician clinicians (NPCs) are playing an increasing role in dermatologic patient care. This study expands upon existing workforce assessments of dermatology NPCs through the use of publicly-available Medicare datasets to better clarify prescribing patterns among independently-billing dermatology NPCs. The findings demonstrate prescribing similarities between NPCs and dermatologists for most medications, including biologic and immunosuppressive medications, although with higher use of oral prednisone, gabapentin, and hydroxyzine among NPCs. Dermatologists more frequently utilized high-potency topical steroids. These data provide initial insights into NPC prescribing patterns and should motivate further study of the identified differences and potential implications for patient care.

Dermatology Workforce in the United States - Part 1: Overview, Transformations, and Implications

The dermatology workforce continues to evolve to meet the growing and diversified demands of the United States population. Part 1 of this continuing medical education (CME) series is designed to provide an overview of the dermatology workforce as well as delineate the motivators and socio-economic implications of significant workforce transformations which are impacting dermatologic health care. Part 2 of the series will consider the impact of workforce challenges on patient outcomes and discuss potential actions that may help to optimize workforce organization and care delivery.