Using Smart Big Data to Transform the Collection Process By Bill Marvin As healthcare reform adds millions of new consumers to the U.S. healthcare system, and copays, deductibles, and coinsurances accelerate the rise in patient payments, billing services and their clients must operate more efficiently to keep administrative costs low and collect more from patients. Many industry experts believe that the recent influx of data and analytics due to innovation in healthcare technology, or “Big Data,” will give healthcare organizations the ability to navigate the changes and, ultimately, to thrive. In fact, a recent McKinsey report estimates that Big Data could save the healthcare industry $300 to $450 billion annually. Is Big Data the key to efficiency in collections? Big Data is exactly that: a large, cumbersome amount of information that is not easily compressed for everyday, real-time decisions or processes. In an industry with billions of transactions per year flowing among millions of patients and thousands of payors and providers, billing services are not able to leverage massive amounts of data quickly to facilitate effective operational decisions. In fact, the mcKinsey report warns that the potential value and savings of Big Data will only be realized if the healthcare industry undergoes major changes to leverage it, such as adopting new technology and processes to act quickly on data received. What if Big Data got smart? Big Data is made up of large, complex data sets collected over a long period of time and used to make strategic business decisions. Collecting and analyzing Big Data can take months and even years, and the results generally are used only by C-level executives to make high-level plans and decisions. For Big Data to improve efficiencies for billing services, it needs to get smarter and go beyond the executive conference room – and beyond the strategic – to the day-to-day tactical. There are opportunities for billing services to use Big Data to trigger automated processes and real-time decisions at the staff level in daily operations. now, that would indeed be smart Big Data. 30 HBma BIllIng • maRCH.aPRIl.2014 How can billing services use Smart Big Data to collect payments more efficiently? When you stay at a hotel, are you able to check in without providing your payment card? Of course not. However, patients receive access to healthcare services with no assurance that they will pay their portion of the bill on time, or at all. as a result, you may spend up to 90 days, send multiple paper statements, and even make phone calls to collect payments. even still, the patient responsibility is frequently written off as bad debt. This is costing your business a lot of money. Billing services have opportunities to use smart Big Data and technology to accurately estimate patient responsibility and automatically collect payments. Here is how: 1. Before a patient's initial visit, verify patient eligibility information and generate an estimate of the patient’s payment responsibility, using data stored from payor remittance information. 2. automatically send a communication to the patient to set clear payment expectations upfront. 3. securely save the patient’s payment card on file. 4. When the claim is adjudicated, automatically collect the exact amount due, or set up an automated payment plan. as a best practice, send another communication to the patient to remind them of their payment. 5. automatically post the payment to your accounting system. When billing services can leverage Big Data to accurately estimate patient responsibility in real-time, the process becomes more functional on a day-to-day basis, enabling you to efficiently collect payments and thrive in the evolving healthcare industry. Bill Marvin is the president and CEO of InstaMed, the leading Healthcare Payments Network. Prior to InstaMed, Bill was an executive in Accenture's Health and Life Sciences practice, focused on payor to provider connectivity. Resources 1 www.nytimes.com/2013/12/09/us/on-health-exchangespremiums may-be-low-but-other-costs-can-be-high.html 2 www.mckinsey.com/insights/health_systems/the_bigdata_ revolution_in_us_health_care
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