6 Takeaways: Artificial Intelligence to Optimize Revenue Integrity and Enhance Payer Alignment, HFMA Webinar

According to McKinsey & Company, administrative spending accounts for one quarter of the $4 trillion spent on healthcare annually in the United States.1 Of that $1 trillion, an estimated $265 billion could be saved without compromising quality or care access, with $210 billion directly related to revenue cycle and payment functions. McKinsey & Company suggests that one of the ways cost savings can be achieved is by investing in technology and collaboration across revenue cycle segments. An example of technology that can have an immediate impact on healthcare organizations are tools leveraging artificial intelligence (AI). These tools can help healthcare organizations better define medical necessity, improve care and efficiencies, prioritize denials, close risk gaps, and develop frictionless healthcare processes.

In a recent HFMA webinar, Tanya Sanderson, Senior Director of Revenue Integrity at Xsolis, discussed the following six key takeaways for top performing revenue cycle teams to consider when leveraging artificial intelligence

1. Automating Medical Necessity Scores Improves Care and Improves the Revenue Cycle

Correctly understanding a patient’s status throughout their care journey is vital to improving efficiencies and reducing the chances of a denial. The length of stay for a patient is 4.9 days on average, which is how long a healthcare organization has to correctly document care before the patient is discharged and a claim is submitted. Over that length of stay, a patient’s acuity and level of care will constantly fluctuate. If statuses are missed or documented incorrectly prior to discharge, lost revenue can occur from under payments or avoidable downgrades from self-denials.

AI predictions can translate patient status information into an easy-to-understand numerical representation of medical necessity. AI uses a variety of data points to generate a patient’s score, which can include history and physicals, lab results, vitals, medications, health management plans, discharge summaries, operative notes, and consultation information. This medical necessity score is continuously evaluated by AI through the care continuum and updated as new information is submitted. Higher scores align to inpatient care and lower scores align to observation or outpatient care. Additionally, the patient’s highest score, which represents when the patient was the sickest, remains visible within the system to provide a consistent view of the level of care decisions. Through this numerical representation, patient care is improved and care decisions are justified based on medical necessity, which can reduce the chance of denials

2. Integrating New Technologies Brings Patient Care and Revenue Cycle Together

Many hospitals struggle with bringing together the care that happens at the bedside with the proper documentation to include in the claim submission because these processes often occur within separate silos. Due to this separation, case details can become lost as the patient moves between departments, which can negatively impact the revenue received and the timeliness of payments.

As an example of how new technologies can help resolve this information disconnect, healthcare organizations can use the patient’s medical necessity score previously discussed to view in real time how the patient is progressing and when they may be ready for discharge. Team members can then ensure all remaining care processes are addressed, such as providing acute care, discharge planning, and post-discharge care coordination. Denials can be resolved prior to discharge and documentation to support coding and DRG assignment can be completed.

3. Implement a New Approach to Help Address High-Volume and High-Value Denials

Historically, healthcare organizations have concentrated on denial management on the back end; however, this workflow can miss important opportunities to reduce revenue leakage earlier in the revenue cycle. Many organizations are now seeking to be proactive with denial management and have added a front-end focus to their process in an attempt to reduce the overall volume of denials. While correcting front-end issues can reduce the overall volume of denials, healthcare organizations should consider focusing more attention on the middle of the revenue cycle to ensure high-value denials, usually related to patient stays, are corrected as soon as possible to expedite reimbursement.

High-dollar denials can negatively impact any healthcare organization, but these denials are especially devastating for smaller facilities, which can result in a reduction in workforce, budget cuts, and limit the services offered. Healthcare organizations may have staff dedicated to tracking and rectifying high-value denials, but this approach can be expensive.

Instead, investing in technology that mitigates denials proactively can be more cost effective. Tools equipped with AI automation help organizations prioritize denials and appeals to ensure high-value denials are addressed first. Quickly resolving these high-value denials can be imperative to sustaining many provider organizations while longer term reducing friction with health plan partners. 

4. Implementing New Tools Helps Address High-Volume and High-Value Denials

Utilization management is not without its challenges. While guidelines are extensively reviewed and are regularly updated to reflect advances in healthcare treatment, denial decisions can occasionally be incorrect, which could negatively impact patient care through the denial of treatment or through care delays while a decision is being rendered. These types of care obstacles can create animosity between the health plan, clinicians, and patients. 

5. Embracing Denials Can Help Close Risk Gap 

A healthy revenue cycle is when a healthcare organization is paid appropriately for all of the services provided at the appropriate level and in the most efficient manner, which should be the focus, not on having zero denials. If eliminating all denials is the goal, then teams could adjust processes to reduce the chances of a denial. A significant reduction in denials could result in healthcare organizations wondering if all services were billed correctly, paid for appropriately, or downgraded to avoid denials, resulting in missing out on payments for appropriately provided care.

While revenue cycle audits can be beneficial, they do not have to be labor intensive. AI-enabled tools can help close the loop on risk gaps and inefficiencies internally and with the payer. By taking such a two-pronged approach, organizations can optimize revenue integrity and denial management efforts, which are two of the biggest drivers of waste inefficiencies and revenue leakage from an inpatient level of care.

6. Creating Frictionless Healthcare Benefits Everyone

The current state of healthcare administration creates waste and lost revenue largely due to a misalignment across the
care continuum. As an example:

• Providers are administering care to patients not knowing if the healthcare organization will be reimbursed due to
  inconsistent payer policies.
• Payers are adjudicating claims based on limited clinical insights and applying subjective criteria to patient stays after
  care has already been administered.
• Revenue cycle back-end teams are attempting to address denial issues while working with retrospective insights based
  on payer claim and audit denial information without the benefit of a real-time clinical picture.

These types of disconnects create friction across all organizations; however, AI-enabled tools eliminate this friction by driving collaboration and coordination across revenue cycle teams and helping improve focus, performance, and alignment throughout the revenue cycle. A more integrated and focused approach using objective AI helps create optimal outcomes with less friction and less waste, even with limited resources, both clinically and financially.

AI-enabled tools can help create sustainable, frictionless healthcare where decisions are made based on the standards of medical care and the clinical needs of the patient. Healthcare then becomes a system where authorizations and claim adjudication are seamless and automated, denials and appeals are minimal, and non-clinical, non-value-added administrative waste is significantly reduced, which allows healthcare organizations to focus their efforts on what matters
most – patient care.

Sahni, N. R., Mishra, P., Carrus, B., & Cutler, D. M. (2021, October 20). Administrative simplification: How to save a quarter-trillion dollars in US healthcare. McKinsey & Company. https://www.mckinsey.com/industries/healthcare/our-insights/administrative-simplification-how-to-save-a-quarter-trillion-dollars-in-us-healthcare