What is AI for healthcare?

Artificial intelligence (AI) for healthcare combines deep learning, machine learning, natural language processing, and a lot of data-driven insights that are revolutionizing how patients and providers view care.

The healthcare sector was in dire need of this improvement, which is probably why Fortune Business Insights projects that by 2032, the global market for AI in healthcare will reach $490.96 billion.

An AI solution for healthcare doesn’t just process mountains of data. No, it understands it fully. It’s able to spot patterns we’d miss, predict outcomes we wouldn’t even think to check, and speed up decisions that used to take weeks.

With this cutting-edge technology, healthcare professionals can finally manage resources intelligently.

What is AI used for in healthcare? Common use cases

You now know what it is, but how is AI used in the healthcare industry? There are several different use cases for AI in healthcare, including: 

AI in patient experience

In addition to helping and assisting doctors and practitioners, AI can improve patient experience.

While we're seeing improvement in patient satisfaction scores, especially in areas like ambulatory surgery, the reality is that disparities persist. According to Press Ganey’s 2024 report, while scores are up overall, underrepresented populations still face significant gaps in care, particularly around empathy and personalization.

With AI, you can tailor care to fit each patient’s unique needs. Algorithms can spot patterns and predict health risks by looking into patient data like their medical history, lifestyle factors, and genetics. This is often called precision medicine, which means that much more personalized and tailored treatment plans can be made.

On top of that, telehealth services powered by AI offer the opportunity to shift how doctors and other professionals interact with patients radically.

By automating routine tasks like appointment scheduling, sending lab results, and even providing 24/7 triage through virtual assistants, AI frees up precious time for healthcare professionals and ensures that patients have endless access to the help they need.

AI in healthcare data management

The healthcare sector is facing an overwhelming data explosion. Unfortunately, much of this valuable information remains siloed, disconnected, and underutilized, which slows down progress in patient care and hinders advancements in research, drug development, and even accurate diagnoses.

AI's ability to sift through, analyze, and synthesize massive amounts of data in real time is changing this. We no longer have to wait years for meaningful insights to pop up.

AI insights for healthcare are gained quickly thanks to powerful technology breaking down these barriers, connecting previously isolated data points, and creating a flow of information.

Types of AI used in healthcare

Let’s now get into the different types of AI powering healthcare. Each one brings a unique set of strengths to the table:

Machine learning (ML)

ML is about teaching algorithms to learn from data. For those who work in healthcare, this means feeding systems with data like patient records or imaging results to find patterns or predict outcomes.

For example, ML can flag early warning signs for chronic diseases or optimize treatment plans.

Deep learning

Now, deep learning takes it further. While ML works on patterns, deep learning uses neural networks modeled on the human brain. These networks tackle complex problems like interpreting medical images or predicting disease progression based on genetics.

Natural language processing (NLP)

Next up is natural language processing, or in other words, AI technology that understands us. It’s designed to make sense of human language, whether spoken or written.

Without this type of AI, healthcare professionals would have to read through mountains of patient records, clinical notes, and research papers to gain actionable insights.

Robotic process automation (RPA)

Finally, robotic process automation takes over repetitive tasks like billing, scheduling, or processing insurance claims. This isn’t glamorous, but it’s essential for an industry that’s so overworked. RPA frees up time, allowing clinicians and administrators to focus on their patients.

Benefits of AI for healthcare providers and patients

There doesn’t seem to be a person alive that hasn’t heard about AI. It’s been stealing headlines for years, trending in almost every industry imaginable.

This is because it is revolutionary for people and industries and has the potential to transform how we live and work. 

Here are some of the advantages of using it in healthcare:

1. Reduced staff burnout

Burnout among healthcare staff is reaching a breaking point. With the combination of shrinking workforces and four in 10 adults in the U.S. managing two or more chronic diseases, healthcare providers are under a lot of pressure. 

However, with AI, a solution is offered by advancing resource allocation. Through real-time prioritization, AI ensures that emergent conditions are addressed quickly at every patient touchpoint.

AI-enabled communications APIs demonstrate this in action. They enable seamless communication across voice, video, and messaging platforms to support healthcare use cases.

Patients can book appointments, access results, or connect with providers remotely, all through intuitive digital tools. Conversely, doctors and specialists can collaborate in real time, sharing data and insights to provide faster, more accurate care.

2. Improve patient-provider communication

Poor communication is one of the biggest pain points in healthcare. A recent study found that a massive 83% of patients say it's the worst part of their experience.

Now, why is that still the case in the mid-2020s? We have the tools to change this, and AI is at the forefront of that change. Technologies like natural language processing (NLP), predictive analytics, and speech recognition have resulted in big changes and advancements in how we communicate with patients. 

These tools both improve the clarity of our conversations and let us tailor information to each patient's unique situation, making shared decision-making more meaningful and effective.

We can deliver these conversations more securely, trusted, and privately with Branded Calling. 

3. Better patient outcomes 

AI’s ability to improve outcomes is undeniable. For instance, studies show that AI tools can reduce the length of stay for conditions like intracranial hemorrhage and pulmonary embolism by streamlining diagnosis and treatment plans. But that’s just the start.

There’s been fascinating research into this. Aidoc’s whitepaper, Maximizing Patient Care With Limited Resources, shows how AI-driven systems speed up patient workflows.

The difference is staggering when you compare a hospital equipped with AI tools to one without. AI helps to give patients the best possible chance at recovery, no matter how strained the system might be. 

Challenges of AI for healthcare

With all good things, there are challenges. And, when we’re discussing the use of technology in an industry that can quite literally save lives, the stakes are even higher. So, be sure to take these considerations into account:

• Access to quality data: With healthcare data expected to grow, we face exciting opportunities and significant challenges. The issue, however, isn’t the sheer volume of data. No, it's its quality and accessibility. It must be more cohesive across many systems, creating inconsistencies and inaccuracies. So, you must look at your infrastructure that connects and integrates this information. TIP: A Vonage feature-rich platform with telehealth integration can help improve connection and collaboration between colleagues and clients.

• Cost of infrastructure: The Cleveland Clinic, for instance, has made remarkable strides in reducing wait times by 10% through AI-driven patient flow and scheduling. However, achieving this level of AI adoption demands a lot of financial investments in infrastructure, compliance, and training. Working with experienced partners who streamline the process can ease the financial burden.

• Acceptance of new technology: The real barrier to adopting AI in healthcare (and in other industries) is the lack of human trust in this new tech. A 2023 study shows that healthcare professionals often resist AI because it forces them to learn new skills and adapt to more complex tasks. The way forward here is education, transparency, and technology partners who can help prioritize projects and guide or manage implementation. We must show clinicians how AI can integrate smoothly with their existing workflows and benefit them.

When did AI solutions for healthcare become popular?

To answer this, we will have to look into the history of AI within this industry. Let’s go back in time together, back to the 1970s. People were grooving to disco hits like "Stayin' Alive," the first Star Wars movie was just around the corner, and the world was still processing the moon landing.

But at the same time, AI for healthcare solutions was first used to assist with biomedical issues.

Since then, the number of AI-powered applications has expanded enormously and is continuing to adapt to help the industry reduce spend, improve patient outcomes, and increase business efficiencies overall

How AI for healthcare is reshaping decision-making

AI is also shaking up decision-making in healthcare, and it’s about time. Gone are the days of guesswork or treating everyone the same with a one-size-fits-all approach to medicine.

Thanks to predictive models, doctors can now identify high-risk situations before they even happen. AI also lets providers compare a patient’s data with a bigger picture (like a whole population, for example), catching patterns that would otherwise slip through the cracks.

It doesn’t just help with immediate care (although that’s a big benefit). AI is boosting research, too, and helping identify disease risks and trends. It’s all about smarter, more personal, and more efficient care.

The future of AI in healthcare

Today, we’re already seeing glimpses of a patient journey powered by AI, but tomorrow, this technology will become the backbone of personalized, preventive care.

It will be possible to monitor every step of your health in real time using various tools, from wearable devices analyzing blood sugar trends to AI predicting and notifying providers of early disease indicators.

But let’s go further. AI will transform how care is delivered, making it seamless and intuitive. Your voice could check you into clinics using healthcare communications solutions, and your data (secured, de-identified, and ever-learning) will feed a system that treats individuals and identifies global health trends.

This isn’t some distant dream but the trajectory we’re on, where human expertise meets computational genius. 

AI for healthcare: reduce burnout, enhance patient care, and improve operational efficiency

So there you have it — our complete guide on AI for healthcare packed with all this brilliant technology's latest and greatest applications.

At Vonage, we believe that everyday encounters make all the difference in the healthcare industry. These things include patients being able to book appointments without waiting days, weeks, or sometimes even months to be seen by an actual person or having access to the information they need to make decisions.

Vonage Communications APIs can enhance patient care, streamline provider operations, and improve outcomes, all while reducing costs and making healthcare more accessible.

Ready to elevate your healthcare apps? Check out Vonage AI-enabled healthcare solutions today.