In November 2022, OpenAI, an artificial intelligence (AI) research and deployment company, announced the official launch of ChatGPT (generative pre-trained transformer). ChatGPT is a large language model from the GPT-3.5 series using chatbot with machine learning and AI. This model has been designed to conduct interactive chats and maintain the flow of discussion in a manner that mimics human conversations by using a natural language processing (NLP) system to respond to the user in a conversational format. The model is able to understand a situation and also learn from its previous interactions, making it a highly compliant technological system. The dialogue format enables ChatGPT to respond to any type of query, admit errors, disprove false assumptions, and reject irrelevant requests.
ChatGPT in the Healthcare system:
As huge volumes of modern healthcare data are becoming available with rapid turnover and complex structures, efficient methods are needed to promptly generate useful evidence. The traditional approaches are time-consuming and expensive, thus increasing the need for the application of AI and machine learning processes to synthesize healthcare data in order to address problems in a timely manner. ChatGPT can possibly meet these demands; therefore, in this article, we focus on the potential applications of ChatGPT to bring about automation, efficiency, and cost savings especially in health economics and outcomes research (HEOR).
ChatGPT in HEOR:
Health economics involves measuring and valuing the outcomes of healthcare interventions. Outcomes research comprises a set of scientific disciplines evaluating the effect of healthcare interventions on patients. Thus, as per ISPOR—The Professional Society for Health Economics and Outcomes Research, HEOR is the confluence of these two fields that work together to provide powerful data and insights for healthcare decision-makers. HEOR is essential in the healthcare ecosystem to avoid potential resource losses resulting from uneconomical practices. For example, it plays an important role in reducing patient healthcare costs by helping identify unnecessary procedures that may result in delayed treatments with resultant decrease in the survival or remission rates for certain diseases. ChatGPT can help healthcare researchers process and synthesize the rapidly growing data available in the medical field, which, in turn, can optimize the use of cost-effective treatments and strategies. Thus, ChatGPT is a potentially valuable addition to the HEOR toolkit. It can support the search for complex information from vast datasets, such as those generated by electronic health records (EHRs) or mobile devices, and can be used to improve detection and classification of diseases, to identify cohorts of patients sharing characteristics that might not be obvious when using traditional methods, and to predict the course of health outcomes under alternative personalized treatment options. Machine learning and deep learning in ChatGPT can be used for performing HEOR tasks as their role is to learn with experience and enhance the algorithm over time. This process of understanding and transforming enormous data into a specific and correct action to perform desired tasks can be beneficial in the healthcare industry. It can be used to efficiently perform analyses using a combination of datasets from epidemiologic surveys, claims datasets, patient surveys, and registries. The ChatGPT model updates result in real-time for users and can be potentially applied across healthcare systems of various regions (both national and international).
Thus, ChatGPT may be potentially applied in the HEOR field in the following areas:
● Disease diagnosis by identifying patients who are at risk for rapid-onset diseases; HEOR can assess the burden of illness when an underdiagnosis occurs.
● Treatment of diseases by initiating early treatment and determining new treatments for patients with diagnosed diseases.
● Disease progression assessment across a wide range of medical conditions by identifying patients who are at risk for rapid progression, assisting clinicians in detecting and supporting patients who may benefit from more advanced treatments and/or closer monitoring. HEOR professionals can use this technology to analyze the cost of delayed treatment.
● Patient adherence to treatment by identifying the main reasons for nonadherence in patients so as to design targeted strategies to improve patient adherence. The HEOR team can subsequently analyze patient data and summarize the effect of patient adherence to treatment on the reduction in healthcare costs. Such real-world evidence can pave the way for future improvement in strategies to improve patient treatment adherence.
● Reduction in hospital readmissions may be possible if healthcare professionals use predictive analytics to guide patients in their recovery phases or in preventable health conditions, thus also improving overall care. The HEOR system can additionally reduce overall hospital costs by evaluating the cause of such readmission.
● Adverse events (AE) management by promptly identifying patients who are at risk for experiencing an AE and the cost of potential AE in terms of HEOR.
The application of ChatGPT in the following key areas may potentially result in a massive transformation:
● Information management: Extensive data can be processed and analyzed in less time and at reduced costs.
● Pragmatic (real-world) clinical trials: Patients can be identified as per the trial requirements by analyzing information with advanced predictive analytics and also determining the ideal sample size for trials and for shortening the trial length.
● Digital therapeutics: Thorough information about individual patients can be provided, thus ensuring personalized and more effective treatments.
● Disease diagnosis and treatment: New diseases can be rapidly identified and new treatments can be swiftly introduced.
● Drug development: The development, efficiency, and production of life-saving drugs can be rapidly increased and they can be launched in the market with reduced costs.
When aptly used, ChatGPT can play a significant role in the healthcare industry, specifically in the field of HEOR.
Bioviser has a strong core team supporting the healthcare industry by simplifying data-driven projects like original research, meta-analysis, systematic review, manuscript writing, and so on. Further, the team often supports HEOR activities such as those discussed in the blog. Also, we have an expert team aiding the automation and digital transformation of simplified data to develop enhanced programs and optimize key pharmaceutical processes that help save both time and costs so that products can be introduced quickly, safely, and effectively in the market.