Preventing Drug Diversion in the COVID-19 Era

Diversion during Covid

Hospitals face a critical problem. As they are taking the heroic steps to handle COVID-19 at their facilities, the increased demand for medication has left them vulnerable for drug diverters. These individuals have taken advantage of the chaos and the sudden influx of patients to swipe medications already in short supply. This whitepaper examines the inherent flaws of existing drug diversion prevention software and focuses on a new platform that fulfills the promise others have not. This revolutionary platform has the capability to uncover risks in minutes, protecting patient lives and hospital workers during this COVID-19 era.

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Let’s be clear. Most healthcare workers do not divert drugs. They are dedicated to the oath of “thou shalt do no harm.” They enter these professions with the hope of saving lives, improving quality of care, and protecting the underserved. During the pandemic they have shown more than grit, they’ve revealed their courage and served others at great risk to their own lives.

That said, about 10% of healthcare workers abuse drugs, according from US Substance Abuse and Mental Health Services. Drug diversion is a symptom of an illness, and unfortunately, it only takes one diverter to endanger patients and a hospital’s reputation. While there’s no easily available data that lists the extent of drug diversion at health care facilities, most organizations agree that the problem exists.

The Drug Enforcement Administration (DEA) recognizes five classes of drugs that are frequently abused: opioids, depressants, hallucinogens, stimulants, and anabolic steroids. This past spring, the DEA approved increased production of opioids such as morphine and fentanyl as a response to the pandemic. Also, the production of new coronavirus treatment drugs such as hydroxychloroquine and dextramethasone have already been targeted for diversion by those afraid of contracting COVID-19 or those interested in reselling the drug. (Luckily remdesivir is administered intravenously and is difficult for individuals to divert.)

The pressures of the pandemic are increasing as those vulnerable to substance abuse become injured, sick, stressed, or overworked.

Most organizations, such as the Joint Commission on Accreditation of Healthcare Organizations (Joint Commission) and the American Hospital Association (AHA), recommend that a system be created to deter diversion. The problem is that most drug diversion prevention products available in the market currently lack the necessary features, such as accuracy and comprehensiveness, to proactively prevent diversion from occurring.

First-generation drug diversion products have multiple flaws

In the early 2000s, companies began offering drug diversion prevention products to answer the concerns hospitals expressed. The first products grew from a report-based model, which primarily “counts” the inventory and transactions (i.e., each drug is counted when it enters and leaves the system) and creates a tally. Unfortunately, it could take 30-60 days later before an inventory report is produced.

Report-based models were not designed to be proactive. By the time most reports are reviewed, the diverter may have already moved to a different department or left the healthcare facility.

These software products also didn’t consider instances where diverters purposely miscount inventory, don’t complete the documentation, or even remove records. The report produced so much noise that it was difficult to distinguish who was diverting in the system. Some studies suggest that one out of every five transactions seen in reports are “noise.”

These types of products also don’t take into consideration unique workflows. For example, an orthopedic surgeon may prefer a certain type of pain control medication because of familiarity of use. The surgeon may run multiple procedures in one day, using the current preferred drug. Many report-based models could “tag” the surgeon’s nurse as a potential drug diverter, when in all likelihood the report is simply tracking the surgical nurse’s workflow.

“Peer-comparative” models are not truly peer to peer

Drug diversion companies began offering peer comparative products, purporting them as improved versions of report-based models. The original intent of these peer-comparative products is to analyze similar job functions. If one nurse has been taking out more controlled substances than his peers, he may be diverting. The premise appears simple, but lacks context.


The premise of peer comparative
products is simple,
but lack context.

Not all job functions are equal. A nurse who works during the day in a medical surgical unit may have a different workflow than a nurse practitioner tending to patients at night on the clinical floor. Comparing the roles and behavior of all nurses is far from accurate, not to mention risky.

Another shortcoming of these products is its inability to accurately compare full-time workers with contract employees or those who work part time. The flaw is significant because in many instances, drug diverters tend to be employed as temporary or part-time healthcare workers. They often appear willing to stay later than usual, offer to help at other departments when they are short staffed, or go above and beyond to help patients.

Similar to report-based products, it can also take weeks or even months before reports from peer-comparative products can be produced —enough time for a drug diverter to contaminate patients, compromise care, or cause the hospital reputational harm.

The truth about most drug diversion prevention products

In reality, it’s extremely uncommon for a drug diversion software to actually identify a healthcare worker stealing medications. Despite the multiple number of drug diversion prevention products available in the marketplace, few —if any —diverters have been identified with the use of a current software product. Most drug diverters are still only discovered when they’ve been caught hurting themselves, such as as in the act of diverting, found unconscious, or have been reported by a concerned colleague.

Most products currently on the market are unable to fulfill the promise of identifying and predicting drug diverters because they don’t have the capability to pull all data from all sources, such as automated dispensing cabinets (ADCs) and electronic health records (EHRs). Merging large volumes of information from ADCs and EHRs is difficult because there are thousands of variables to consider.

Until recently there were no software products capable of truly tracking, identifying, and predicting drug diversion.

The breakthrough

In 2014, the supervisor of the drug diversion prevention program at Mayo Clinic Arizona decided to tackle the challenge of identifying drug diversion quickly and proactively. As a pharmacist with more than 25 years of experience, he was frustrated at the inherent flaws of current products. He sought to create a surveillance process designed to incorporate a facility’s ability to track, monitor, and collect data pulled from multiple sources. Medication Administration Analysis Program (MAAP) was born.

MAAP became the first integrated solution with the ability to identify potential drug diversion. It pinpoints root causes and automatically tracks and monitors behavioral patterns to predict potential diversion.

MAAP Analytics™: The comprehensive solution

Designed from the clinical floor, MAAP was created to fill the void that drug diversion products could not fulfill. After five years of benchmark studies, MAAP was the only system that proactively tackled drug diversion prevention and significantly reduced inefficiencies. Encouraged by its initial results, the Mayo Clinic invested heavily to refine MAAP and implement it enterprise-wide:

  • Creating a diversion monitoring methodology and best practices
  • Demonstrating effectiveness through years of clinical practice improvement
MAAP Analytics is different from current products in
the marketplace. It offers a multi-dimensional
approach and applies machine learning to
harmonize data,

Bolstered by its effectiveness, the Mayo Clinic and ANiGENT joined forces to commercialize the product. After including additional features and refining its algorithms to incorporate machine learning, the product was renamed: MAAP Analytics™. The cloud-based software is patent pending and is built to comply with protected health information securely. Analytics of its application at its own facilities, the product naturally was built to comply with the Health Insurance Portability and Accountability Act (HIPPA), Joint Commission standards, and DEA requirements.

MAAP Analytics is different from current products in the marketplace. It offers a multidimensional approach and applies machine learning to harmonize data, creating a trending analysis that can predict occurrences of drug diversion.

The components of an effective drug diversion prevention system

As outlined earlier, most products that purport capturing drug diversion data are limited. At their simplest, these products are either report based (i.e., tallying inventory number to get a summary report) or peer-comparative (i.e., an attempt at comparing similar job functions). Based on a five-year benchmarking study at Mayo Clinic, an effective drug diversion prevention product should have the capability to pull and harmonize all data from:

  • Inventory of pharmacy-controlled substances
  • Electronic medical records
  • Automated dispensing cabinets
  • Pharmacy compounding waste
  • Waste retrieval
  • Waste assays

No drug diversion product has been able to collect these various data points into one repository for analysis except for MAAP Analytics™. The innovative platform leverages machine-learning algorithms to:

  • Continually capture and analyze data
  • Rapidly identify and prevent drug diversion
  • Pinpoint areas that need process improvement

MAAP Analytics was designed with the knowledge that every potential drug diversion case (99%) must begin with a clinical investigation. In comparison, most drug diversion products approach all cases as a criminal investigation despite the fact that only a very small percentage begins as such. When applied as a clinical investigation lens, all information is then mined from various sources (e.g., ADCs, EHRs, waste assays, etc.). Data pulled from a potential diverter is compared with true peer-to-peer analysis to determine if the behavior is anomalous to the typical standard of care.

MAAP Analytics is also capable of analyzing data taken from waste assays and retrieving information from waste sources. Importantly, the product is capable of executing as a “oneperson” wasting system, saving health facilities a significant amount of additional staff time. MAAP Analytics also can generate reports in minutes instead of days or weeks.

Implications in business intelligence

For many health systems, data lives in functional, technological, or departmental silos, which negatively impacts efficiencies, productivity and revenues. Critical insights needed by decision makers are often trapped in these silos and can take days to weeks before they’re unraveled, delaying any decisions.

MAAP Analytics allows enterprise systems to quickly turn insights into action. As such, the platform is a critical component of any business intelligence (BI) strategy. It can also take recent historical data and run the algorithms that would enable health care team members to forecast predictive behavior. Rather than reacting, health systems become proactive.

According to Health Informatics, 90% of healthcare systems are now capable of churning out big data, yet only a small percentage are able to use it enterprise-wide to achieve their goals. In drug diversion prevention, immediate access to large data from multiple sources enables companies to not only proactively protect patients from harm, but also protect their reputation within the communities they serve. It needs a specific purpose, timeliness, and a feedback loop where members can easily, track, monitor, and produce results.

The COVID-19 pandemic has drastically altered the healthcare landscape. Now more than ever, there is a need to obtain information that could protect patients and other healthcare workers quickly.

Today, it can take nearly 18 months before a drug diversion incident is discovered —too late to protect patients or recoup cost from lost doses. For most drug diversion products, rapid response has never been a priority. Until now. ANiGENT has changed the paradigm. Formed in partnership with the Mayo Clinic, MAAP Analytics is one of the most comprehensive drug diversion platforms in the market, capable of uncovering potential drug diversion events in minutes.

MOST DRUG DIVERSION PREVENTION PRODUCTS ARE FLAWED EXCEPT FOR ONE: MAAP ANALYTICS™

The impact of COVID-19 on drug diversion

According to HealthcareDiversion.org, a nonprofit website aimed at shining light on the diversion problem, the number of drug thefts in healthcare facilities are rising.

As healthcare workers continue to take heroic steps during this pandemic, the increased demand for medication has left facilities vulnerable for drug diverters, individuals who take advantage of the chaotic landscape and swipe medications already in short supply.

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Health systems need an effective drug diversion prevention product that is advanced enough to collect and harmonize all information from all data sources, but also robust enough to analyze and produce reports within minutes, vs. days or weeks. Importantly, when compared with other software solutions, MAAP Analytics rises to the top as the most accurate and comprehensive drug diversion prevention platform. It is, the next evolution in improving patient safety.