3 Case Studies of Successful Implementations of AI in Healthcare

Artificial intelligence (AI) has transformed the healthcare sector. With broadly useful applications across administrative and clinical work, healthcare professionals depend on AI in many contexts. While there are pros and cons to AI in healthcare, it’s clear the benefits far outweigh any potential drawbacks.

AI jobs in healthcare are increasingly prevalent as well. A simple search on leading job boards like Indeed yields hundreds of open positions related to machine learning, robotic process automation (RPA), and AI in healthcare.

AI in healthcare case studies offer powerful examples of how real individuals and organizations have realized positive change through the power of this technology. Let’s review three examples of artificial intelligence in healthcare.


1. AI Technology Offers Valuable Clinical Decision Support 

Big data analytics and AI in healthcare have transformed the way clinicians work at TidalHealth Peninsula Regional, a hospital in Maryland.

The facility identified issues with clinicians having to spend too much time searching for information. The hospital partnered with IBM to implement IBM Micromedex with Watson, a clinical decision support software. This AI solution combines clinical decision support and AI with patients’ electronic medical records, making it easier to find relevant and useful information.

For TidalHealth, that meant cutting down on the time providers spend on clinical searches. The many steps involved in that process, and the dozens of instances in which it may have to be completed in a single shift, took significant time away from providers.

With a dependable AI tool supporting more efficient information gathering, the hospital cut time per clinical search from 3-4 minutes to less than 1. That’s more time for medical professionals to spend with patients each day, thanks to AI optimizing a time-consuming process.

2. A Broad Goal: Leveraging Data More Effectively 

The Healthcare Information and Management Systems Society (HIMSS) details how the Mayo Clinic and Google Cloud developed an AI and ML platform to support patient care and research.

By collaborating to build a strong foundation, the provider and tech company delivered a variety of benefits to practitioners. In-depth calculations, like the kind used to assess changes related to polycystic kidney disease, can be completed automatically. Another algorithm helps to assess breast cancer risk.

Now, clinicians are armed with a wide variety of AI tools to support patient care and research.

3. Transforming Utilization Management 

Valley Medical Center in Renton, WA, implemented the CORTEX® solution to right-size its observation rates. With AI leading to efficiencies in case review and management, the facility’s nurses could focus on clinical merit in case determinations. Instead of relying on inefficient, criteria-based solutions, they could use their skills and experience to better support patients.

In addition to right-sizing its observation rates to keep them more within the Centers for Medicare and Medicaid Services (CMS) and other local facilities’ averages, Valley Medical Center also reduced its extended stay observation rates (those patients who are discharged in an observation status who stay longer than two midnights), while also dramatically improving case review volume. The facility went from completing 60% of reviews to 100% — a 67% improvement.

The history of AI in healthcare is still being written, as AI, algorithms and similar tools continue to transform the healthcare industry.

XSOLIS can help your organization make major and positive changes to its utilization review and management processes with purpose-built AI designed to not only meet the needs of providers, but to bridge the gap between payers and providers, accelerating collaboration for a new path forward. Learn more about the possibilities when purpose-built technologies are adopted.