3 Benefits of AI in the Operations of Healthcare

The future of AI in healthcare is a bright one. It’s already proven its value in diagnosing and treating disease, as well as supporting more efficient administrative functions. Artificial intelligence is poised to transform nearly every aspect of the healthcare industry.

Healthcare AI conferences such as AIMed and professional learning series like Harvard Medical School’s Designing and Implementing AI Solutions for Health Care are becoming more common. And some of the healthcare industry’s largest conferences such as HIMSS, CHIME, HLTH and ViVE, each have increasingly many learning tracts dedicated to AI. Publications like the book “AI First Healthcare” have also increased the visibility of AI among providers, administrators, and the general public. And healthcare AI consulting is an increasingly important consideration for hospitals and health systems across the country.

AI’s wide-ranging influence can’t be ignored. Let’s look at four examples of AI in healthcare operations to learn more.

1. More Accurate Identification of Patient Status

Appropriately classifying patients is a critical need in healthcare. Accurate identification supports positive resolutions for patients while also helping facilities manage resources and receive appropriate compensation. This means fewer denial risks and better conversion opportunities for providers as they interface with their payer partners.

AI can draw on a variety of information, including past activity, to make accurate and timely status determinations for many patients. Automating these decisions empowers nurses with more time to spend on high-risk patients with more complex concerns. With volumes of patient data turned into actionable insights, it’s easier to prioritize the right cases at the right time.

2. More Productive Interactions with Payers

The right application of AI technology can help to address a variety of issues across the industry of healthcare, including more business or operational concerns. That includes administrative issues that some professionals in the field may see as intractable, like inefficient communication with payers.

AI technologies can easily gather and share the most relevant and important patient data, then apply machine learning (ML) to help predict the appropriate care status for patients within a hospital system with over 98% accuracy. This can be shared with providers and payers alike to reduce unnecessary administrative work typically exacerbated by digging through the EHR, thus creating objectivity for both parties in the process.

This use of an AI-driven system is particularly valuable. Why? Because it gives all stakeholders a common tool for sharing and viewing information. That creates an environment where everyone can reference the same data and leverage the same analytics and reporting.

3. Support for Patient Prioritization

Nurses and other clinicians only have so much time in a single shift. Putting that time, and their expertise, toward the most complex and demanding cases offers some clear benefits.

How can providers efficiently organize their days without tools that help them identify and prioritize the most at-risk patient cases? AI can help solve this issue by pointing clinicians toward the cases presenting the most challenges.

Ultimately, this means more targeted opportunities to provide care when the need for staff efficiency is at an all-time high – hospitals must do more with less staff, due to staffing shortages and revenue challenges. AI has the power to transform tasks like scheduling and prioritization of cases in healthcare.

There is a wide range of benefits of AI in healthcare, but it’s important to find the right solution for your organization’s unique needs. Xsolis’ Dragonfly solutions offer all of the advantages for providers listed in this article and also has a payer view available, for shared data insights that drive collaboration and improve efficiency. Learn more about Dragonfly today, or schedule a demo customized for your needs.