Readers Write: The Revenue Cycle’s Transformation with Big Data

The Revenue Cycle’s Transformation with Big Data
By Steve Johnson

Big data is pushing clinical care to new heights as healthcare organizations use it to support diagnoses, target care delivery, and improve patient health outcomes. Organizations can realize a similar level of success in the revenue cycle when they apply data and analytics to the myriad of steps involved in billing and collections.

When organizations effectively leverage financial and administrative information — such as claims, payer payment, cost, patient financial, and patient demographic data — they can see improvement on both the front and back end of the revenue cycle. For example, organizations can use data to increase collections by detecting fraud at registration, quantifying patient payment responsibility, identifying patients who qualify for financial assistance, and revealing errors that impact billing.

Strong data and analytics can also drive more accurate revenue forecasting. Unlike the past, where healthcare organizations relied on historical summary statistics to predict future financial trends, big data empowers a real-time view of individual patients and their financial situations. When aggregated, this data allows an organization to make an accurate bottom-up forecast of revenue. In other words, organizations can leverage specific account information to build a collective model of overall performance based on each patient’s unique financial situation.

Just as big data can improve forecasting, it also can enable more exact patient population benchmarking and assist in decision-making relative to those populations. For instance, data and analytics can show how a facility’s patient population compares with the general patient population regarding financial need. This level of data and analysis facilitates deeper patient segmentation, clearly differentiating those more likely to qualify for assistance compared to the surrounding geographic area. In addition, data and analytics help define optimal workflows or interventions for specific groups.

Organizations already have all the big data they need to effect change: financial, administrative, and claims and payment data are all present in an organization. To get the most out of this data, organizations need to link it together and form one complete picture of the patient experience. This will provide a better understanding of the patient’s current and historical situation and allow for stronger forecasting and risk mitigation as well as enable better financial conversations with patients.

Patients usually welcome conversations about their financial responsibility and how they can meet it, especially those who do not understand the complexity of their coverage and may not know the right questions to ask. By using financial and administrative data to determine the best financial course of action for a patient, staff can proactively offer different payment options and answer patient questions, increasing the likelihood of patient payment, improving collections, and strengthening the revenue cycle. This data-driven, customer-focused approach also reaps the added benefit of higher levels of patient satisfaction.

Clinical use of big data has dramatically impacted care delivery. The time is right to adopt the same philosophy for the revenue cycle and leverage big data as a business tool to strengthen billing, collections, and overall financial operations.

Steve Johnson is chief technology officer and vice president of data and analytics at Experian Healthcare of Austin, TX.