11 operational applications for healthcare AI

February 25, 2022

Updated from the original, published February 16, 2021

For many executives in the healthcare industry, artificial intelligence brings to mind robot-assisted surgeries, AI-developed drugs or automated image diagnoses. While such clinical applications may be exciting, operational AI applications represent a significant opportunity for optimization and savings across health system administration.

Healthcare’s complex behind-the-scenes administrative and operational workflows are causing inefficiencies, prompting physician frustration and burnout and increasing costs and a diminished patient experience. The 2021 Internet of Healthcare Report found that 92% of clinicians agree that too much time spent on administrative tasks is a major contributor to healthcare worker burnout. The solution to these problems may just be artificial intelligence and an AI-powered workforce.

AI applications in operations management can quickly provide positive ROI and free up valuable employee time to work on higher-value projects.

Healthcare technology advances such as machine learning and computer vision have increased the potential for applications across operational AI — today, artificial intelligence is already automating many of healthcare’s most costly, high-volume routine processes. Healthcare AI has been proven to improve workflows, cut waste, reduce errors and shift human employees’ focus from manual data entry to more complex tasks that require a human touch. Here are 11 ways that healthcare is already using AI in operations management to create efficiencies, reduce costs and improve the patient experience.

Applications of artificial intelligence and automation in healthcare operations

1. Eligibility checks and prior authorizations

By combining robotic process automation (RPA) with computer vision (CV) and machine learning (ML), artificial intelligence can automate many of the eligibility check and prior authorization processes that bog down healthcare administration today. For instance, an AI workforce can securely log in to EMRs, check insurance information and verify benefits with increased speed and accuracy. Healthcare AI can also determine when a prior authorization is needed, automate submissions, check statuses and increase the speed of approvals and reimbursement. One hospital saw a 30% reduction in days (PDF) in A/R after hiring Olive to automate eligibility checks.

2. Denials management

The economic magnitude of claim denials is huge, costing $407 billion across over 1,500 hospitals in the U.S. Using AI for automated eligibility checks, prior authorizations and claims management significantly reduces denials before they happen, but AI can also manage those that still occur. Artificial intelligence can identify the problems with a claim submission, resubmit claims and monitor the resubmission process. Advanced solutions with machine learning capabilities can even identify trends and make recommendations for resolving the recurring denials that cost health systems billions of dollars each year.

3. Claims management

Claims management is a growing challenge in healthcare. An AI workforce can log in to disparate systems to complete and submit claims faster and more accurately than humans using RPA — Olive checks claims status seven times faster than a human, to be exact. Once claims are submitted, claim statuses are checked and updated daily, alerting staff to those claims that need attention and human intervention. Automating daily claims status checks with Olive frees up 11 FTEs per day on average, giving the revenue cycle staff time to focus on the claims that need follow-up.

4. Supply chain management

The average annual supply expense reduction opportunity for individual hospitals was $12.1 million in 2019. AI can analyze millions of data points about current inventory, past utilization trends and expected future utilization to provide insights and recommendations for reducing supply costs. These solutions can optimize inventory levels, increase standardization and , improve workflow efficiency and supply throughput — AI can even alert staff to expired and recalled supplies.

5. Cybersecurity

While cybersecurity may not fall strictly under operations, it is still one of the top 10 AI applications in healthcare according to a recent Accenture report. AI-enabled solutions can help health systems reduce risk by recognizing behaviors that are unlikely to be taken by humans, such as a user trying to access patient logs from a remote location. They run continuously in the background to monitor activity and can even automatically add additional layers of security when a potential threat is recognized, helping hospitals avoid data leaks and other security threats.

6. Invoice processing

The largest suppliers typically invoice through a hospital’s own electronic data interchange system, but finance teams still process and pay many invoices manually. Artificial intelligence solutions — like an AI workforce — can automate that process, extracting the necessary data and, then routing for internal approval and payment. With advances in healthcare technology, including computer vision and machine learning, AI can process limitless invoices or receipts, no matter the format. This helps hospitals reduce late payment penalties and fees, eliminate mistakes and lost invoices, get greater visibility into finances and improve compliance.

7. Patient flow and staffing

Healthcare AI can combine hospital historical data, patient data, current status of internal resources, external factors such as weather or epidemics and even behavioral science to optimize patient flow and staffing resources. And with an AI workforce, these AI-powered, more accurate models of patient demand and bed utilization can reduce the average length of stay, more efficiently dispatch ambulances, prevent discharge delays and shorten patient wait times.

8. Scheduling

Using data on the number and types of medical appointments, available physicians and anticipated patient demand, artificial intelligence is significantly improving appointment scheduling for patients and physicians. With artificial intelligence, patients can easily book, confirm, cancel and reschedule appointments. Waitlists can be created that auto-fill cancellations and open spots. And automatic reminders help reduce no-shows and optimize clinician time.

9. Vendor contract management

Finding the best products for the best price is critical to de-risking net assets and delivering value-based care. That means the larger the health system, the more ongoing contracts to manage. Healthcare artificial intelligence solutions can easily scan contracts and automatically extract the relevant information to compare to other contracts. An AI workforce helps manage a robust and well-maintained item file, helping health systems assess risk, look for savings opportunities, manage supplier relations and increase compliance.

10. Data migrations

Health systems today still struggle with legacy systems, custom applications and data in disparate programs across the enterprise. Healthcare AI solutions, especially RPA, are the easiest and most accurate solutions for aggregating and migrating this data into the appropriate system. Automation not only reduces the time needed to migrate data, but also increases the accuracy by doing so without any errors, missed records or typos.

11. Medical billing and coding

Using RPA, computer vision and natural language processing (NLP), healthcare AI applications can recognize and extract data from medical documents, patient records and clinical notes to prepopulate ICD codes. This is how an AI workforce can speed up the billing process, improve documentation and reduce billing errors that lead to costly rework.

Operational artificial intelligence is transforming the back office of healthcare

These are only some of the current applications of healthcare artificial intelligence. More are being implemented every day — and healthcare AI solutions like Olive are continually getting more intelligent. With healthcare artificial intelligence innovation, we can continue to tackle the waste and inefficiency in healthcare, reduce physician and nurse burnout and improve the patient experience.

Learn more about healthcare’s AI workforce

Want to develop a real-world action plan for implementing artificial intelligence — one that’s proven and optimized for healthcare’s changing environment? Learn more about Olive and our plan for the future of healthcare.