Artificial intelligence and predictive analytics continue to make transformational changes throughout the business world. While healthcare IT is seeing some impacts from AI and machine learning, it lags behind other industry sectors in fully adopting this emerging technology. However, necessity is sometimes the mother of invention, as evidenced by the Coronavirus pandemic still ravaging the planet.

Because of the strain and unpredictability COVID-19 is causing hospitals and medical establishments, faster adoption of AI is now critical. Unfortunately, healthcare IT departments suffer from a skills gap as well as other issues when implementing new systems using machine learning. Nonetheless, the demand for AI remains strong.

Here are some of the major 2021 trends related to AI in the healthcare industry:

AI Making Inroads in Healthcare over the Last Year

 The healthcare industry has seen some impacts from AI over the last year or two. For example, at-risk populations benefit from the AI-powered monitoring of chronic issues. This area especially holds promise for the treatment of COVID-19 patients; illustrating how machine learning models have the potential to augment the decision-making processes of medical professionals. Additionally, this proactive monitoring approach prevents costly emergency hospital trips.

As noted earlier, COVID-19 is driving the increased adoption of AI and ML in healthcare. One benefit is improved decision-making regarding patients, both in diagnosing the virus and in treatment. Additionally, predictive analytics helps healthcare organizations improve operational efficiency to better handle a physician shortage exacerbated by the pandemic. AI also helps doctors better diagnose diseases by using image analysis powered by machine learning algorithms. It’s another example of how ML enhances the ability of the medical professional. This image interpretation use-case applies to X-Rays, angiograms, CT, and MRI scans.

Improving Efficiency in Hospital Operations

In addition to helping hospitals streamline their operations, AI provides notable benefits in the area of revenue cycle management.  AI reduces the task of manually reviewing thousands of medical claims, and instead focuses our staff on performing warm, human outreach, and thinking through complex problems together with our members. Machine learning algorithms help hospitals perform information retrieval more effectively. These ML-powered software search agents automatically ensure patient or other data is up to date. As the use of EMR for patient data becomes more commonplace, expect AI to play a significant role in ensuring efficient data management.

The Benefits of an Open-Source AI-Layer for Databases

Data for many healthcare organizations remains difficult to access; requiring the skills of a data scientist to wean actionable information. In this scenario, an easy-to-use AI-layer able to connect to and query a database offers significant benefits. Users execute ML models with a simple SQL query. They receive relevant results along with an explanation of how the model derived its result set.

Making the power of AI/ML-driven solutions easily accessible to medical and insurance professionals improves the adoption of these nascent technologies. The ultimate result is increased efficiencies and improved benefits for the healthcare industry.

Learn more about AI trends in healthcare:

https://www.sciencedirect.com/book/9780128184387/artificial-intelligence-in-healthcare

https://www.sciencedirect.com/science/article/pii/B9780128184387000022

https://www.sciencedirect.com/science/article/pii/B978012818438700006X