Healthcare.AI™ Product Suite and Expert Services Use Cases

Learn how organizations are expanding the use of AI in healthcare through the New Healthcare.AI product suite and expert services.

Innovative Uses of the New Healthcare.AI™

$2M Increase in Revenue with a Multi-Feature Predictive Model

One health system employed numerous technologies and methodologies with vendors to reduce bad debt by accurately predicting propensity to pay. Frustrated and unsuccessful, they turned to Healthcare.AI to create a predictive model that incorporates multiple meaningful features, including credit scores, previous payment behavior, payment balance, and previous interactions, rather than relying on a single feature. With accurate predictions, the organization can focus collection efforts on accounts with the highest probability of success.

Millions in Labor Cost Savings Achieved

Coders at this healthcare organization were tasked with assigning accurate and complete MS-DRG codes to more than 1.5M hospital-based outpatient encounters. The manual coding process was labor-intensive. Healthcare.AI enables them to automate their complicated coding processes, accurately predict the service line and MS-DRG code for each outpatient encounter, and reduce labor costs.

Reducing Tens of Millions of Dollars in Waste

More than 10 percent of this health care delivery system’s inpatients received red blood cell (RBC) transfusions at the cost of more than $10M each year. Healthcare.AI enables risk-adjust blood utilization predictive modeling at the ordering provider level. Peer comparison is an integral factor in the program’s success.

Strategic Planning Enablement

Like many healthcare systems, an integrated delivery network (IDN) had an abundance of data but lacked the accurate and actionable insights necessary to drive improved performance. Healthcare.AI allows them to separate signals from noise in the data and establish an effective strategic direction. The clear insights give the IDN confidence in determining the clinical areas of focus at the system and individual facility levels and appropriately align executive incentives to truly meaningful goals.

Improvement Resource Optimization and $1.3M Penalty Reduction

Using mortality and readmission rates data, an integrated delivery network (IDN) planned to spend 6-12 months and hundreds of thousands of dollars on an improvement initiative—including standing up and running a team of nurses, physicians, and operational leaders. The problem was that only minimal benefits could be achieved. Healthcare.AI provides risk-adjusted observed over expected (O:E) ratios for more than 20 different system measures and more than a dozen individual hospitals. The advanced insights allow the IDN to establish the right strategic priorities—ensuring resource optimization—improve quality, save lives, and reduce penalties.

Early Identification of Worsening Performance

Utilizing a run chart to monitor performance on their acute myocardial infarction (AMI) mortality observed to expected ratio, a regional medical center could not identify outlier data or change in performance. Healthcare.AI allows the center to immediately detect worsening performance without having an analyst provide an in-depth analysis. Recognizing a shift in performance, the center can quickly stand up a team to work on areas with increased mortality rates, resulting in improved performance and the avoidance of CMS penalties that can be hundreds of thousands of dollars.

Tens of Millions of Dollars in Revenue Restored

The COVID-19 pandemic caused this health system to face resource and capacity restrictions, and they canceled elective surgeries due to concerns about resource availability. Healthcare.AI enables the organization to use dynamic regional infection spread and market share data, augmented with the internal clinical, operational, length of stay, staff, and supply data to anticipate COVID-19 activity and accurately forecast demand and resource requirements. The new insights revealed that the organization has adequate resources to meet demand, so they resumed elective surgeries, recovering tens of millions of dollars in critical revenue.

Millions in Labor Cost Savings with Improved Staffing Effectiveness

This health system’s labor costs had increased dramatically over the last ten years, compelling them to develop a comprehensive staffing strategy. Using Healthcare.AI, the organization uses features like XXX to forecast patient demand and model patient flow. They are establishing staff schedules based on forecasted demand, improving efficiency, and reducing spending on overtime and premium shifts—all of which lead to substantially lower labor costs.

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