Can a “Cookie” Mentality Help You Collect More Patient Payments?

March 5, 2018 2:44 pm

The growing retail focus in health care is envisioned by many as a way to enable patients to mimic their shopping habits when choosing a healthcare provider. The problem is that healthcare payment transactions aren’t quite as simple as a shopping cart checkout. Healthcare organizations can improve the payment experience for patients, and thereby collect more payments, by taking a cue from today’s online retailers and moving away from one-size-fits-all billing and embracing a modern, customized approach.

Apply a Little Online Retail Therapy

Marketers get to know consumers through each online purchase and behavior, dropping a trail of “cookies” that helps them learn more. E-commerce shops routinely deliver personalized advertisements that are more likely to convert into sales. By sending the right message to the right person at the right time, retailers are not only boosting revenues, but also improving the overall shopping experience.

Health systems can take a page from the retail playbook and deliver personalized billing statements and processes to their patients for a better experience and greater payment adherence.

Consider this scenario: A 50-year-old male patient has just completed his annual physical. Based on results, he’s developed a heart condition that requires immediate action to ensure conditions don’t worsen. The adoption of personalized billing statements can offer him healthy eating and physical activity tips right on the statement. As such, the added effort can help increase patient loyalty and, of course, incentivize payment compliance. 

Personalize Through Predictive Modeling

Consumers are  demanding personalized content from businesses in all industries, including health care. The traditional one-size-fits-all approach to billing simply isn’t working for patient payment collection, which has become increasingly important as patients assume more personal responsibility for their healthcare bills.

In fact, in a May 2013 report, McKinsey & Co. estimated that balance after insurance transactions would increase from 15 percent in 2010 up to 35 percent in 2018. Yet an article published by HFMA in 2015 states that, on average, patient bills sit in accounts receivable for more than 60 days before they are paid, and providers then collect an average of just 17 cents on the dollar of what is owed.

Predictive modeling enables healthcare organizations to review past payments to tailor the billing process to each patient. Every transaction provides an opportunity to learn more about patients and generate valuable insights. Because patient experience is intertwined with patient payments, the ability to learn about patients through data and deliver a customized payment experience can result in a compelling ROI. Predictive modeling can help an organization increase its operating margin by 50 basis points or more.

Predict Future Revenue with Smart Segmentation

Behavior-based data can lead to more accurate and timely predictions. Even more exciting is the ability to improve future revenue based on these past behaviors. To both predict and improve patient revenue, organizations must first understand patients’ payment preferences to segment their patient populations strategically.

Like insurers, patients can be segmented by virtually any data point, including payment preferences. Healthcare organizations should consider measurements and data points such as payment plans, financing, electronic bills, and pay-in-full discounts, and further tailoring by looking at bill balance or insurance status. Organizations can choose the most relevant data points for their specific patient populations.

After patient populations are segmented, an organization can approach each segment with a customized patient payment strategy. Just as Amazon and other e-commerce sites tailor their offers based on consumer preference, and can predict with confidence the result of those offers, providers can do the same. These are not considered upsells, but rather complementary value-added opportunities. As an example, if a patient paid their last bill via a payment plan online, providers can anticipate a similar reoccurrence and can therefore offer the payment option upfront resulting in a more likelihood to pay.  

For the best results, organizations should continually test which levers to pull. Even small changes in the payment experience—–payment prompts, for instance—can lead to a big difference in patient payment collection. By testing various methods of communication and different times of day, an organization can continue to learn how each patient population likes to pay. The more organizations test and learn, the more patient revenue will improve.

Patient payment collection is a growing challenge for healthcare organizations, and the experiences of companies that specialize in individualized consumer transactions can provide helpful knowledge.

Online retailers and marketers take the time to learn as much as they can about every customer through behavior-based data and predictive modeling. This same predictive modeling approach can give hospitals and health systems the insights they need to customize patient payments and improve future revenue.

Alan Nalle is chief strategy officer at Patientco, Atlanta. 


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