Generative AI in Healthcare: Definition, Use Cases, Examples

The healthcare world is wrestling with big problems like not having enough staff, doctors feeling overwhelmed, making less money, and seeing health issues get worse, especially in places that don’t get enough attention. These problems need smart, new solutions to keep healthcare organizations going strong and make patient care better.

Enter generative AI technology – it’s shaping up to be a game-changer, with something to offer for big companies and regular folks alike. This tech builds on stuff like understanding natural language and learning from data (that’s NLP and ML for short), and it’s getting really good at things like creating text, summing up info, translating languages, and pulling out important insights.

The goal of generative AI is to make it easier for everyone to get the info they need, work together better, speed up scientific breakthroughs, and make healthcare more personal. It’s like we’re on the doorstep of a new era where tech gets healthcare to a whole new level.

We’re about to dive into all this cool stuff, so let’s jump in and see what’s up.

Generative AI in healthcare refers to the application of artificial intelligence models that can generate new data, insights, or content by learning from existing datasets.

This is super useful in healthcare because it means we can make fake (but realistic) patient info, tailor-made treatment plans, and even dream up new drugs. With all the health data out there, these AI programs can help figure out what might happen to patients in the future and help doctors make the best calls, making healthcare faster and more tailored to each person.

According to the Deloitte Center for Health Solutions, about 75% of top healthcare companies are either giving generative AI a test drive or planning to make it a big part of their world. And they’re serious about it—82% are setting up special teams to make sure everything’s on the up and up with generative AI.

Moreover, as per Deloitte’s 2023 Health Care Consumer Survey, they’re seeing it make things smoother (92% give it the thumbs up) and help make smart choices faster (65% are all for it). When regular folks were asked, over half (53%) said they think this tech could make getting healthcare a breeze, and almost half (46%) reckon it could make it easier on the wallet, too. Those who’ve had a taste of generative AI are even more jazzed, with 69% saying it’ll open doors to healthcare and 63% believing it’ll help save some cash.

And here’s a kicker: experts predict the cash flowing into generative AI in healthcare could balloon to $17.2 billion by 2032, shooting up from $800 million. That’s a whole lot of growth, driven by our quest for care that’s just right and the smart tech that’s getting us there.

Healthcare faces big problems today, like finding diseases too late, treatments not fitting everyone, and new medicines taking too long to come out. We need new approaches to fix these issues. Generative AI is one of those novel approaches.

The role of Generative AI in healthcare is not just about making processes faster or more efficient. It’s about making healthcare better for the people who need it and the people who work in it.

The following are the reasons why Generative AI is important for healthcare:

From the back office to the operating room, Generative AI seems to greatly impact healthcare settings. Here are some of the most awaited generative AI healthcare use cases – as we’ve already discussed some of these use cases throughout the article, you can go briefly:

Generative AI transforms medical imaging by applying convolutional neural networks and deep learning to enhance the detection of conditions. This innovation supports:

By analyzing vast health datasets, generative AI predicts diseases before symptoms manifest, enabling:

Generative AI in patient monitoring offers continuous oversight for those with chronic conditions, featuring:

In healthcare management, generative AI revolutionizes care plan creation by:

Generative AI elevates member services by:

AI plays a pivotal role in provider network management by:

Generative AI ensures seamless patient information flow across healthcare transitions, enabling:

AI significantly streamlines clinical operations by:

In value-based care, generative AI leverages data to:

Generative AI contributes to financial management in healthcare by:

Generative AI aids healthcare organizations in maintaining high ethical standards and adhering to regulations. It does this by:

By integrating these functions, generative AI supports healthcare providers in delivering services that are not only efficient but also ethically sound and compliant with healthcare standards.

While Generative AI adoption in healthcare remains nascent, several US companies are actively exploring its potential. Here are some latest deployments:

Overview: UC San Diego, a renowned research university, is actively working towards streamlining patient interactions and elevating the quality of care through technology-enhanced communication.

Gen AI is utilized for answering patient inquiries, where AI-generated responses have been found to be of higher quality and empathy compared to those from human healthcare providers. – Source

Overview: Teladoc Health is a leading telemedicine company offering virtual healthcare services across various specialties, including primary care, mental health, and dermatology.

Overview: Basys.ai is among the top Generative ai healthcare startups focused on using generative AI to streamline the prior authorization process in health plans.

Automating Authorization Requests: Uses natural language processing (NLP) to reduce manual labor and expedite approvals, minimizing errors and ensuring regulatory compliance. – Source

Overview: Intermountain Healthcare is a non-profit healthcare system offering a broad spectrum of services in Utah, Idaho, and Wyoming, including hospitals, clinics, and home care.

Overview: HCA Healthcare is a for-profit healthcare system with facilities in the United States and the United Kingdom, known for its hospitals and clinics.

Partnership with Google Cloud and Augmedix: Investigates the use of generative AI tools in emergency rooms to improve documentation accuracy through voice-activated AI and reduce physician burnout by alleviating the documentation workload.: Although still in early development, this project holds promise for enhancing care quality in emergency settings by improving information capture and supporting physician well-being. – Source

Implementing the latest AI technologies into a precision-driven industry like healthcare comes with critical challenges. However, with careful implementation and the right AI software development partner, they can be avoided.

Here are some of the challenges you should know of:

Solving these issues is key to making the most of what AI can offer healthcare.

Creating a healthcare environment where AI contributes positively involves tackling these challenges and ethical dilemmas head-on. Now, let’s just move ahead and take a look at the predictions for 2024 and beyond. However, if you wonder what we predicted last year, here is the blog for you – Trends of AI in Healthcare in 2023.

Looking ahead, generative AI is set to play a key role in advancing healthcare. Real-time, predictive analytics promise to shift the healthcare paradigm towards more proactive and preventative care, identifying health risks before they manifest into serious conditions.

The drug discovery and development process stands to be revolutionized by AI, making it faster, more efficient, and significantly less costly.

Moreover, generative AI has the potential to inform policy and public health decisions by providing data-driven insights that were previously unattainable. This could lead to a more responsive and effective healthcare system, tailored to meet the evolving needs of the population.

The most awaited combo – Generative AI and healthcare – is making waves, from sharpening the accuracy of diagnosing through medical images to predicting health concerns before they become problematic. It simplifies patient care and makes the healthcare data handling more efficient. Moreover, it’s speeding up the discovery and development of new drugs, promising a future where effective treatments are more quickly available.

However, the exploration of generative AI’s full potential in healthcare is still in its early stages. There’s much more to learn and discover.

At Techtic, we picture a world where, through the analysis of your health data, potential issues are addressed even before you notice any symptoms, much like a weather forecast that helps you prepare for a storm before it arrives.

This proactive approach to healthcare isn’t just a convenience; it represents a fundamental shift towards keeping us healthier for longer.