Patient Payments

How Do You Optimize Patient Collections During COVID-19?

Post by
Justin Nicols

For healthcare providers, right now, clinical problems are massive. Collectively, as a nation, we must acknowledge (and be incredibly grateful) for the burden our healthcare system is shouldering — and the lifesaving work that is underway in every state.

For those who are responsible for the revenue cycle, the day-to-day challenges have undoubtedly become more complex, and the pressure to maintain revenue as well as a patient-centered focus is higher than ever. While triage around COVID-19 continues, patient bills are going to pile up, cash on hand is going to dwindle and a more significant number of patients will struggle to pay their bills.

Amid COVID-19, a chaotic situation that is in constant flux, how should healthcare providers and RCMs handle patient collections? How do you provide payment flexibility while still working towards the financial health of your organization?

A good start is in applying predictive analytics. Predictive analytics can leverage historical payments data to mine a wealth of intelligence that can help you navigate revenue cycle changes and operations in this COVID-19 storm. Predictive analytics give you an advantage in how to communicate with patients, how you forecast revenue and how to best manage your human resources.

Here are four examples of how to use predictive analytics to better manage the revenue cycle in the wake of COVID-19.

1. Proactively offer the most appropriate payment plan to each patient.

Now is the time to truly be a flexible payment partner to your patients. The loss of jobs due to COVID-19 has caused unemployment to skyrocket. More patients are going to struggle to meet their financial obligations. Predictive models around propensity to pay, payment amount and payment timing work to identify which patients will benefit from payment plans in the early-out period. The models also determine how to best structure a payment plan for each patient (amount and duration). This intelligence can be fed into your patient collections workflows, equipping you to proactively work with patients, offering the most effective payment plan to each patient from your first interaction with them.

2. Optimize how you utilize the people you actually have on staff during this time.

Staff is in flux. Between shelter-in-place orders, remote workforces, a backlog of denials and patient accounts, having a strategy that optimizes your workflows to match your workforce is essential. Predictive modeling can work to help prioritize the denials, focus outbound patient calls on the right accounts and optimize revenue cycle work queues.

3. Reduce outbound contacts while maximizing dollars collected.

Not every patient needs a phone call. Some patients need one. Some need three. And, there is a sweet spot for calling for each patient, whether it’s day 36, 42, or 49. If you know what combination of who to call and when, you can reduce outbound efforts while maintaining or increasing collections. Predictive modeling around call cadence focuses your efforts and makes collections more efficient.

4. Real-time reporting on the revenue cycle

Revenue cycle leaders at healthcare organizations are needing to maximize human capital resources to most effectively collect payment while treating patients with respect. To balance these objectives it is essential to track progress daily, have access to updated reports, and respond to the evolving situation with data-driven recommendations for patient contact and payment plan structure. Advanced analytics that are accessible and updated in near real-time provide the details leaders need to best manage the revenue cycle during this time.

Patient collections may be frozen for the short term — but as the dust settles, healthcare providers will face navigating patient collections in the aftermath. Now is the time to plan a strategic, efficient and empathetic approach. Predictive analytics is a powerful place to start.

More From Blog

You Might Also Like

Patient Payments
How a 120-Day Machine Learning Experiment Led to a 6.5% Increase in Patient Collections
Read More
Healthcare Payments
Healthcare Providers Have Become Lending Organizations
Read More
Claim Denials
The 25% Challenge
Read More

Stay in the know

Join our newsletter for industry and company news, product announcements, and more.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.