GPT Technology to Help Address Longstanding Barriers to Care in Free Medical Clinics.

Journal: Annals of biomedical engineering
PMID:

Abstract

The implementation of technology in healthcare has revolutionized patient-centered decision making by providing contextualized information about a patient's healthcare journey, leading to increased efficiency (Keyworth et al. in BMC Med Inform Decis Mak 18:93, 2018, https://doi.org/10.1186/s12911-018-0661-3 ). Artificial intelligence has been integrated within Electronic Health Records (EHR) to prompt screenings or diagnostic tests based on a patient's holistic health profile. While larger hospitals have already widely adopted these technologies, free clinics hold lower utilization of these advanced capability EHRs. The patient population at a free clinic faces a multitude of factors that limits their access to comprehensive care, thus requiring necessary efforts and measures to close the gap in healthcare disparities. Emerging Artificial Intelligence (AI) technology, such as OpenAI's ChatGPT, GPT-4, and other large language models (LLMs) have remarkable potential to improve patient care outcomes, promote health equity, and enhance comprehensive and holistic care in resource-limited settings. This paper aims to identify areas in which integrating these LLM AI advancements into free clinics operations can optimize and streamline healthcare delivery to underserved patient populations. This paper also identifies areas of improvements in GPT that are necessary to deliver those services.

Authors

  • Hannah Ong
    College of Medicine, The Ohio State University, Columbus, OH, 43210, USA. Hannah.ong@osumc.edu.
  • Joshua Ong
  • Rebekah Cheng
    Department of Physical Therapy, Virginia Commonwealth University, Richmond, VA, USA.
  • Calvin Wang
    College of Medicine - Robert Wood Johnson, Rutgers University, New Brunswick, NJ, USA.
  • Murong Lin
    Distinguished Engineer, Verizon, San Jose, CA, USA.
  • Dennis Ong
    Amazon Web Services, Amazon, Seattle, WA, USA.