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Health care analytics

The latest weapon in fighting the opioid abuse epidemic

According to the Institute of Medicine of the National Academies, 100 million Americans, or nearly one out of every three people, suffer each day with chronic pain. That's roughly quadruple the number of Americans with diabetes (25.8 million), and nearly 10 times as many as the number of cancer patients (11.9 million).

Fortunately, we live in an era when modern medicine offers effective and readily available treatment for pain in the form of prescription medications. Prescription painkillers help improve daily function, and therefore the quality of life, for millions of Americans and even more people across the globe.

These benefits, however, come at a cost. According to the Centers for Disease Control and Prevention, the U.S. is now in the midst of an opioid abuse epidemic. In 2010, 5.1 million Americans abused painkillers to some degree, which made them the most abused prescription medications by far, according to the National Institute on Drug Abuse. In addition, the 2012 National Survey on Drug Use and Health stated that 2.1 million Americans were addicted to opioid pain relievers. And in 2013, opioid analgesics caused more than 16,000 deaths, far more than any other drug class.

The problem hasn't gone unnoticed: As of May 2015, the U.S. government had 540 pending complaints and cases involving fraud, waste and abuse (FWA) in prescription drug billing related to Medicare and Medicaid. These cases account for 60 percent of the FWA total, and don't take into account instances with commercial insurance.

States are addressing the opioid epidemic by using databases to detect patterns of FWA to help drive prevention and intervention. A Weill Cornell Medicine study published in June 2016 found a 30 percent decline in the prescribing rate for opioids in the 24 states using these types of databases between 2001 and 2010.

The media also has been helpful in publicizing the issue. Local and national outlets have been actively and persistently increasing awareness of opioid abuse and encouraging dialog to address it.

While these are good initial steps, they won't be enough to stem the tide and overcome the opioid epidemic. Consider that spending for commonly abused opioids among Medicare Part D beneficiaries alone increased 156 percent from 2006 to 2014, and the total number of beneficiaries receiving opioids grew by 92 percent in that time, compared to 68 percent for all other drugs. This translates to $7.8 billion spending now on controlled substances. Left unchecked, these numbers are expected to grow as Baby Boomers, who make up a large patient group for these drugs, continue to age.

Why is it such a challenge to control opioid abuse? It's a combination of the sheer number of pharmacy claims and the woefully outdated manual methods used to review them. The slow, labor-intensive process of manually inspecting spreadsheets, even those generated from a database, can lead to false positives. It also uses time and resources that should be spent tracking down those who are actually committing FWA. The sheer size of data can cause processing time and infrastructure issues, and overwhelm the system.

Next-generation analytics overcome these challenges by using multiple data points — more than humans can process at one time — to identify and uncover purchasing and prescribing patterns that indicate a high probability of abuse. Experts can then focus their time evaluating actionable insights rather than sifting through data to determine those members or prescribers to target.

Here's how analytics can help in two key areas.

Member drug-seeking behavior

Analytics make it easier to find behaviors that are unusual. Rather than paging through spreadsheets, color-coded dashboards can assign scores based on risk factors and bring the most likely cases of FWA to the top of the list based on pre-set thresholds, such as health plan members who are seeing more than 10 physicians or filling prescriptions at more than 10 pharmacies. These thresholds can be set based on industry benchmarks or adjusted to the preferences of the payer or pharmacy benefit manager (PBM).

One of the challenges of uncovering FWA among members is that on the surface, the patterns that could indicate it might also reflect legitimate (non-FWA) behavior. For example, a common indicator of potential fraud is when a patient receives an opioid and/or other prescription from multiple providers and fills them at different pharmacies. Yet an oncology patient who receives multiple prescriptions from several different specialists might have a legitimate reason for this behavior.

This is where next-generation analytics brings in additional data, such as displaying the locations of prescribers and pharmacies on a map relative to the member's home. If several prescriptions are being filled at different locations far from the member's home, it's a strong indicator of possible FWA.

The intelligent application of analytics will help automate the process of revealing the most likely FWA perpetrators while minimizing false positives, which ensures that the payer's or PBM's resources are being used most effectively to reduce costs while not alienating members in good standing.

Detecting FWA in pharmacies

Of course, members aren't the only ones committing FWA. Pharmacies, along with prescribers, have plenty of incentive, as well. Analytics can uncover such activity by using retrospective analytics to establish a benchmark of patterns over a specified time period, such as a year. Advanced analytics can then determine the acceptable deviation from the norm for each of the metrics and monitor activities weekly against that benchmark thereafter.

Each pharmacy is assigned an overall score based on that week's activity. This score shows whether the pharmacy is remaining within its typical pattern. If there are significant deviations from the benchmark, a pharmacy can be highlighted to determine whether a closer look into their activities is needed.

Each of the designated metrics is also monitored individually, which makes it easier to quickly determine the reason behind a falling score. More sophisticated analytics packages can even color code pharmacies based on the severity of their deviations. This simplifies the process of determining those pharmacies that require immediate action, those that should be on the internal "watch list" and those that might have had an unusual week. It also enables payers and PBMs to comply with the watch lists that the Centers for Medicare and Medicaid Services monitor.

Some of the metrics that can be monitored include:

  • Rate of "new billing."
  • Reversal rate (very high and very low).
  • Percentage of high member co-pays.
  • Average ingredient cost.
  • Average paid per prescription.
  • Average paid per member.
  • Brand and generic percentages.
  • Average number of prescriptions per member (stratified by age).
  • Percentage of controlled substances.
  • Dispense-as-written (DAW)-1 percentage.
  • Percentage of compound claims.

Displaying the results on a dashboard makes it easy to spot overall trends. It also helps identify pharmacies that might require corrective interventions, such as putting claims through closer examinations or withholding payment, as well as those that require onsite visits or other more severe actions.

By overlaying geographic information in the analytics, investigators can also find pockets of activity that indicate possible collusion — either between two or more pharmacies or in combination with physicians or patients — in an effort to avoid detection. Elevated levels might remain within the benchmarks for any one pharmacy. But when compared to others in the region, a "hot spot" might show up that tells fraud examiners that those pharmacies deserve a closer look.

Flexibility is key

While 90 percent of FWA analytics packages tend to be the same, each organization likely has some unique requirements. When selecting an analytics package, it's important to ensure it has the flexibility to meet those needs.

Retail pharmacies, for example, might want to be able to configure the analytics to compare the performance of its locations to those of its competitors, or its affiliates, to determine if a one- or two-week spike in controlled substances is specific to its organization or other retailers are also seeing them.

This ability to adjust what's being measured and how the information's being displayed will help health payers and PBMs focus their efforts where they'll yield the greatest benefits and return on investment while limiting wasted effort chasing false positives.

Developing the cure

The opioid epidemic is currently running rampant, and it's affecting most of the country either directly or indirectly. In some cases, individuals feed an addiction that puts their lives at risk. In others, people or groups look to turn a quick, illicit profit by perpetuating that addiction. No matter the reason, given that prescription medications are already a nearly $375 billion industry in the U.S. alone, the potential financial rewards of FWA surrounding opioids ensure this issue will continue to grow unless action is taken now.

Next-generation analytics offer a cure for this scourge, which helps payers and PBMs reduce intentional fraud at the source while lowering the cost of pharmaceuticals for themselves and their members. It also ensures that members receive the medications their providers intended, or proper intervention, to improve their health outcomes.

Rena Bielinski, Pharm.D., AHFI, is senior vice president, Strategic Accounts, and chief pharmacy officer at SCIO Health Analytics®, an organization dedicated to using healthcare analytics to improve clinical outcomes, operational performance and business results. She can be reached at: