Explore the top five ways AI will revolutionize healthcare by 2025. These advancements will enhance diagnostics, tailor treatments, and improve patient outcomes.

With rapid advancements in healthcare and technology, life expectancy has surged, driving an unprecedented demand for healthcare services. In 2023, healthcare spending in the US was projected to grow at a 5.5% annual rate—yet this growth isn’t enough to meet the needs of an aging, expanding patient population. To make matters worse, the healthcare workforce is not able to keep pace with it. 

Healthcare delivery systems in the United States are using the triple aim to improve healthcare. The goals are to enhance the care experience, improve the health of communities, and lower healthcare costs.

The Evolution of the Healthcare Data

Healthcare is shifting from its long-standing model of simply billable fees-for-service to a more patient-centered model known as value-based care. This encourages an emphasis on patients but potentially leads to reduced cost and better care. In this blog, we will discuss what value-based care is, the importance of moving from a volume to a value model, how the VBC model differs from the fee-for-service model, key principles of value-based care, and the various existing value-based purchasing programs.

Healthcare providers face a heavy administrative load with every patient encounter. From typing notes rapidly and sifting through charts to entering data manually into the EMR, it often feels like documentation overshadows patient care. Research by the American Medical Association shows that physicians spend an average of 36 minutes on the EHR per visit, with time ranging from 29 to 46 minutes. This includes 6.2 minutes of after-hours “pajama time” and 8 minutes managing the EHR inbox—an overwhelming demand, especially considering most primary care visits are scheduled for just 30 minutes.

Healthcare organizations in the US are at a critical juncture when it comes to revenue cycle management. As care delivery becomes more complex, traditional Revenue Cycle Management (RCM) processes are simply unable to keep up. With hospitals losing around $20 billion in claim denials annually,  providers can no longer afford to rely on manual and error-prone RCM processes.

Every decision, medication, and follow-up appointment shapes a patient's path to wellness, especially during the critical 30-day post-discharge period. This is particularly vital given the scope of chronic disease in America: According to recent CDC data, chronic diseases represent a massive burden on the US healthcare system.

Imagine walking into a medical facility in rural America. You are highly unlikely to find a specialist who can attend to your healthcare needs. This is the reality for over 90% of rural counties in the US facing a shortage of physicians.

Leveraging AI and Predictive Analytics for Population Health Management