How digital health companies are adopting ChatGPT

The healthcare industry is experiencing a paradigm shift towards telemedicine and remote patient care, driven by the need for accessible and convenient healthcare services. If embedded into healthcare technology, ChatGPT could play a pivotal role in this transformation by simplifying the non-clinical aspects of care delivery: patient intake, appointment scheduling, and patient education.

One example is Oncora Medical, which is a platform that is leveraging AI to collect the relevant medical data of patients, evaluate the quality of care provided, present population-level oncology outcomes, and support data and imaging workflows.

CloudMedX is transforming how clinicians ingest data so they can track things like chronic disease progression. They take unstructured data, such as clinician notes, discharge summaries, diagnoses, and hospital notes and decode them. When used with traditional EHRs, CloudMedX purports to unlock valuable clinical insights and ensure patients are receiving data-driven treatment plans. In essence, bringing a more data-driven approach to chronic condition management.

Another area where ChatGPT’s advanced capabilities are speculated to have massive potential is in clinical decision support. By analyzing vast amounts of medical literature and clinical guidelines, ChatGPT can flag potential drug interactions, suggest treatment options for specific conditions, and assist in diagnosing complex cases. This streamlines the decision-making process, allowing providers to deliver accurate and efficient care to their patients. According to the National Center for Biotechnology Information:

There are already notable FDA-approved AI-related advancements in the SaMD space that assist providers with diagnoses.

GE Healthcare has already received clearance for 42 AI- and machine-learning-enabled medical devices. One example is the Critical Care Suite 2.0* powered by Edison which involves a collection of on-device algorithms that integrate seamlessly with existing X-ray workflows and assist in delivering the highest quality care to patients. GE Healthcare’s AIR™ Recon DL MR image reconstruction is also notable for its deep-learning-based reconstruction algorithm that enables radiologists to achieve pin-sharp images quicker.

Symptom checkers play a crucial role in helping patients assess their health conditions and determine when to seek medical attention. With ChatGPT’s advanced language processing capabilities, digital health companies may be able to leverage the technology to provide more precise guidance to patients regarding the severity or risk of symptoms. By analyzing symptom descriptions, medical histories, and relevant data, AI-driven models can offer personalized recommendations, helping patients navigate to the appropriate type of care depending on symptoms or side effects.

Linus Health is one such innovator in the space, attempting to digitize a formerly manual process with its early-detection platform for cognitive assessments. Its proprietary assessment technology, DCTclock, takes the gold standard pen-and paper clock drawing test for early signs of cognitive impairment and digitizes it, bringing together the most recent advances in neuroscience and AI to analyze over 50 metrics that reflect the patient’s cognitive function.

Additionally, ChatGPT may be able to facilitate the remote monitoring of patients, enabling providers to track vital signs and provide timely interventions. Home or remote health monitoring most often involves tracking things like blood pressure, heart rate, and sugar levels using devices. Those devices then share their data with healthcare providers. This data exchange can be optimized through AI. ChatGPT may be able to analyze the data being collected and translate it into understandable, actionable language for patients and providers.

The development of new treatments and therapies heavily relies on clinical trials and research studies. AI can significantly decrease the time it takes to launch a clinical trial by streamlining the identification of potential participants who meet specific criteria. This reduces the time and resources required for patient recruitment, facilitating the advancement of medical research. Additionally, ChatGPT’s ability to analyze vast amounts of scientific literature can support healthcare leaders in identifying patterns, generating hypotheses, and accelerating the discovery of new drugs and treatment approaches.

Despite the potential of ChatGPT in healthcare, there are crucial ethical considerations and risks associated with its implementation, not to mention a range of infrastructure challenges that will impede its use in legacy healthcare settings.

Healthcare software companies must deeply understand the risk posed by AI in any clinical setting, especially related to triage, diagnosis, or image analysis where incorrect information could mean harm to patients. Instead, experts encourage adoption of AI to streamline and increase efficiency in clinical workflows while still keeping doctors at the center of all clinical decision making.

Another important topic that has been central across industries is how AI may replicate biases found in the material upon which it was trained. Healthcare has a long history of bias, prejudice, and poor information especially connected to marginalized patient populations and conditions. As organizations lean upon new technologies like ChatGPT, it will become increasingly important to proactively correct for bias that may affect equal and accurate care.

Privacy and data protection are also paramount, especially when dealing with confidential patient information. For the time being, current rules and regulations prevent healthcare information from being submitted into AI technologies like ChatGPT, but it’s important for healthcare companies to be prepared given how quickly the technology is evolving. Robust systems must be established to ensure that patient data remains secure and private. Additionally, there is a risk of users blindly trusting the AI system’s accuracy, which could have serious implications if incorrect information is provided. Therefore, caution when developing the technology must be exercised, and all information and work provided by ChatGPT should be thoroughly verified by human healthcare professionals.

Regulatory frameworks and guidelines must be established to govern the deployment of AI systems in healthcare. This includes defining the boundaries of AI’s role in decision-making, establishing protocols for data privacy and security, and outlining the legal responsibilities of AI developers and users. Collaboration between technology companies, healthcare professionals, policymakers, and ethicists is essential to navigate these complex issues and create a framework that maximizes the benefits of AI while minimizing potential risks.

In conclusion, ChatGPT represents a remarkable leap forward in AI technology and could have significant impact on healthcare software development. The potential impact on healthcare software is vast, from facilitating quicker time to market, lower costs, and better health outcomes for patients. However, the ethical considerations surrounding their use cannot be overlooked.

HTD Health has AI advisors and technology experts to help clients explore how new technologies can be safely adopted and leveraged in their care delivery systems.

Contact info@htdhealth.com to learn more about our healthcare technology strategy and software services.