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

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

Article By:  Brian Jones, DO, Rod Fontecilla

Blog Source From : https://discover.guidehouse.com/

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 indepth 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.

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