For the Record: Rev Cycling to a Better Bottom Line
“Measuring every touch in the revenue cycle is key to future sustainability—because every touch means money out of your pocket.” ~ Matt Seefeld
Pre-service patient collections
Net collection rate for closed claims
Increase in staff efficiency
Cash acceleration
Atlas Healthcare Partners has quickly become one of the nation’s fastest growing ambulatory surgery center (ASC) management companies. The organization’s focus on successful integration and execution of its proprietary ASC development strategy spurred growth that landed it on the Fortune 5000 Fastest Growing Private Companies in 2022 and 2023. Atlas was formed in 2018 to develop and manage Banner Health’s ASC network in Arizona, Colorado and Wyoming. Notably, that network grew from eight to 30 centers in just five years.
In 2022, Atlas formed its second not-for-profit health system partnership with Corewell Health (formerly the Spectrum Health and Beaumont Health systems), now the largest health system in Michigan. Since that time, Corewell has introduced a new orthopedic ASC, three cardiovascular ASCs, two multi-specialty de novo ASCs and a robust acquisition pipeline. In addition, Atlas formed a first-of-a-kind national cardiovascular ASC management company in mid-2022 in partnership with MedAxiom, a highly regarded cardiovascular consulting company owned by the American College of Cardiology.
Our existing EMR and practice management systems did not have analytics capabilities to produce the level of granularity and visibility our team needed to identify top performers and reward performance. We wanted answers to questions such as: “How much work effort does it typically take for staff to resolve a claim?” and “Where are financial clearance strategies falling short on the front-end?”
Reducing cost to collect is top of mind for financial executives in today’s ambulatory surgery settings, where declining reimbursements, growing patient financial responsibility and staff shortages are wreaking havoc on operational margin. ASCs must capitalize on existing staff resources and create greater capacity for effective workflow performance, especially given that labor shortfalls in the majority of healthcare revenue cycle departments are here to stay for the foreseeable future. Yet too often the answer to revenue cycle improvement is to “throw more bodies” at multiplying reimbursement problems.
Following the Covid pandemic, Atlas Health Partners saw patient volumes soar due to pent up demand. At the same time, the opening of nine new centers quickly overwhelmed staff and systems due to labor shortages, the challenges of managing a remote workforce and lack of enterprise workflow automation and analytics. In addition, lack of transparency into the productivity and effectiveness of individual team members made it difficult to identify root problems and hold staff accountable. Finally, breakdowns in financial clearance processes were driving up denial rates.
Atlas revenue cycle leaders sought to get ahead of converging issues by seeking solutions to help optimize revenue cycle processes across its rapidly growing network. Primary objectives included reducing dependence on labor, arming staff with tools to work smarter and increasing the system’s zero-touch rate—a key performance indicator that illustrates the percentage of claims that get paid without any human intervention.
In addition, Atlas revenue cycle leaders needed visibility into daily staff work effort to better identify, incentivize and retain top performers. Unfortunately, without data on how staff members moved through their workday, this strategy was a non-starter.
MedEvolve solutions have been a game changer for our revenue cycle processes. The implementation process went smoothly, and we received uncommon support getting our staff up to speed. Now, we have the workflow automation and advanced analytics tools needed to really understand performance improvement drivers within our revenue cycle teams and processes.”
Atlas identified MedEvolve Effective Intelligence (Ei) Suite, which includes intelligent analytics, insurance workforce automation and financial clearance workforce automation, as the answer to holistically addressing the full scope of revenue cycle processes. The solutions address everything from front-end registration to daily workflow guidance to lay the needed foundation for streamlining workflows and improving zero-touch rates.
On the front-end, Effective Intelligence automates and centralizes pre-registration financial clearance functions, ensuring the claims process begins as accurately as possible. It also equips staff with the information needed to collect co-pays up front. Workflow automation then provides the guidance needed to ensure Atlas staff are not only productive, but also effective, in their work. These tools highlight tasks that have potential to produce the most ROI, rather than having staff waste time on claims need little to no attention.
The Atlas executive team was confident MedEvolve’s Ei solutions would provide the transparency she needed to create greater capacity within their workforce and reduce dependence on offshore labor.
We are thrilled with the outcomes achieved with MedEvolve. Our leaders have tremendous confidence in the partnership. We look forward to expanding our work with the MedEvolve team to derive even greater value from data insights, which is key to our success as a growing business.
The value of the MedEvolve partnership speaks for itself. In less than a year, Atlas has considerably improved its financial performance based on overall cash collections and net collection rate (NCR) percentage. Additionally, Atlas’ ability to increase productivity and the effectiveness of work completed has increased staff capacity by one-third.
Richards notes that improved coordination across all teams—including patient access, payments, refunds, medical records, collections, billing and coding—has increased centralized accountability and eliminated role redundancies. The organization has also experienced a boost in morale due to the added efficiencies as indicated by their annual employee engagement survey.
Increase in zero touch rate
Decrease in refiled claims
Reduction in denials
Decrease in tasks per claim
Effective Intelligence combines Patient Financial Clearance Automation, Medical Billing Workflow Automation, and Real-Time RCM Analytics in a cloud-based platform designed to integration with your current EMR/PM technology to measure the effectiveness of your RCM staff.
Review and assess your practice’s financial status in 5 min or less and know exact where you are losing money and why. Measure the work effort of every revenue cycle employee, incentivize and retain your top performers, and help employees that need improvement.
You can prevent most common denials, rejections and write-offs during the scheduling and pre-registration process in advance of the appointment. Configure checkpoints and use central task management to quickly clear patients and keep your front office staffing needs at a minimum.
As team members log in to the web-based application and record each “touch” of a claim, outcome, and next task, key data points are recorded like who completed the task and when, outcome, task notes, internal / external messages sent, collection success and other data points that feed into our real-time analytics.
Reduce RCM labor dependence with financial clearance, coding, insurance A/R, & patient A/R automation modules with real-time analytics.
Increase productivity and simplify front & back office processes while keeping your staff focused with our flagship PM system.
“Measuring every touch in the revenue cycle is key to future sustainability—because every touch means money out of your pocket.” ~ Matt Seefeld
Healthcare organizations are already facing razor thin margins, and administrative waste could be the linchpin for future sustainability. Billions of dollars are at stake. I’m always surprised when I talk
Healthcare revenue cycles are primed for the benefits of automation & AI, but many are missing a critical link: human-generated data.
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