Article

Calling Dr. GPT: The Impact of Generative AI on Healthcare

Generative artificial intelligence is the latest technology positioned to disrupt healthcare.

By Brian Jones, DO, Rod Fontecilla

There’s a new form of AI that could transform every major industry. It’s called generative AI and it leverages machine learning models and algorithms – such as a generative pre-trained transformer (GPT) model – to consolidate and produce content, including images, art, and music, in seconds from sources across the internet.

While using generative AI tools like ChatGPT to create art or write essays without human assistance has been trending on social media and among students, it can also write code without a data scientist. And when it comes to healthcare, generative AI can identify breast cancer in radiology images via its machine-learning algorithms or provide patients with in-depth information about their diagnoses.

Generative AI has the potential to be a game changer that revolutionizes the healthcare ecosystem in ways we can only begin to predict today. It’s vital that healthcare organizations prepare for and understand the exciting possibilities these new technologies could have across the industry.

 

Four Ways to Use Generative AI in Healthcare

Personalized Medicine

Generative AI algorithms can analyze large amounts of data, including social drivers of health and genomic data, to identify patterns, predict outcomes, and ultimately improve care and wellness. With these personalized medicine techniques, healthcare providers could easily tailor more informed treatment plans to individuals, increasing the chances of success and reducing the risk of side effects or non-adherence. For example, generative AI algorithms embedded with the most current practice guidelines, social drivers, and health monitoring information could act as a “driver assist” for clinicians to help them analyze whole health and generate recommendations for diagnosis, treatment, and follow-up care, helping clinicians make more informed decisions.

Drug Development and Clinical Trials

By analyzing data from clinical trials and other sources, generative AI algorithms can identify potential targets for new drugs and predict which compounds are most likely to be effective. This could accelerate drug development, potentially bringing new treatments to market faster and at a lower cost. Taking it a step further, generative AI could run compound data over genomic data to remove biases and pinpoint correlations that advance existing treatment pathways.

Screening and Diagnosis

By integrating data traditionally in the electronic health record (EHR) along with data from outside of the EHR like social determinants of health and social networking data, generative AI algorithms could help identify chronic disease earlier to improve health outcomes. This could help healthcare providers make more accurate and timely diagnoses, leading to earlier treatment and better patient outcomes.

Predictive Maintenance

By analyzing data from medical devices, such as imaging equipment or ventilators, generative AI algorithms could predict when maintenance is needed. This could help healthcare providers activate their supply chain processes earlier to proactively maintain their equipment and reduce the risk of equipment failure.

 

The Complex Opportunity to Advance Generative AI in Healthcare

While generative AI shows promise in advancing healthcare, its complex capabilities can pose concerns. One being the potential for bias in the algorithms, which could lead to unequal access to care or discrimination against certain groups of patients. Ensuring that generative AI algorithms are trained on diverse and representative datasets will be critical to mitigating these risks.

Another challenge is the need for regulatory frameworks to ensure the safety and effectiveness of generative AI in healthcare. Developing these frameworks will require collaboration between industry, regulators, and other stakeholders, and will be essential to ensure that generative AI is used responsibly and ethically.

Though complex, generative AI is the capability the healthcare industry has been waiting for. If leveraged appropriately, it could be the solution to digital transformation in healthcare. Put simply, it brings disparate sources of data together in seconds to create meaningful insights that decrease the burden for the end user. Forward-thinking healthcare organizations will take advantage of generative AI technology by focusing on:

Building a Data Infrastructure

To fully leverage the potential of generative AI, healthcare organizations will need to integrate large, diverse, and high-quality datasets. This will require investments in a data infrastructure, including data architecture, storage, management, and analysis tools.

Partnering with AI Experts

Healthcare providers, payers, and other organizations may not have the in-house expertise to develop and implement generative AI solutions. Partnering with AI experts, such as AI startups or consulting firms, can help them get up to speed and access the expertise needed to implement generative AI projects successfully.

Training and Educating Staff 

To fully leverage the potential of generative AI, healthcare organizations will need to ensure that their staff understands technology and how it can be used. Providing training and change management support on generative AI can help staff understand its capabilities and limitations so they confidently integrate these new capabilities into established workflows.

Collaborating with Regulatory Agencies 

Working closely with regulatory agencies, such as the US Food and Drug Administration, will be essential to ensuring that generative AI solutions are safe, effective, and transparent to those who would like to gain greater insights into their inner workings. Collaborating with regulatory agencies can help healthcare organizations navigate the regulatory landscape and comply with relevant laws and guidelines.

To learn more about how Guidehouse is actively using generative AI to build digital twin models that mimic real-world objects, check out our AI and machine-learning capabilities in Guidehouse’s Discover Innovation platform.

 

 Guidehouse's Discover Innovation Platform

 

Authors

Brian Jones, DO, Partner
A practicing physician, Dr. Jones is the digital health transformation leader at Guidehouse. He has two decades of experience helping healthcare organizations navigate clinical and financial healthcare processes.

Rod Fontecilla, PhD, Partner and Chief Innovation Officer
With more than 25 years of experience, Dr. Fontecilla oversees the firm’s strategic innovation initiatives to transform technical business competencies and curate next generation solutions.

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