Prescription Practices/Third Party Payer
This session will discuss a comprehensive approach to addressing the opioid epidemic — tackling both upstream and downstream misuse and abuse. Presenters will use case studies to highlight real-world evidence and data analytics from a pharmacy benefit manager with more than 27 million members. They will address two critical components for addressing drug misuse and abuse. The first is an individual’s complete claims history — both medical and pharmacy data — to better predict risk for misuse/abuse before addiction occurs. This predictive modeling takes two separate modeling techniques for new opioid users and current users. It is incumbent upon health insurers to develop processes to identify, as soon as possible, individuals newly initiating opioids at increased risk for future high-dose opioid prescription use. Presenters will share predictive modeling results using medical claims and sociodemographic data, demonstrating how predictive modeling techniques are incorporated into a comprehensive opioid risk management program. The second component is the analytical capabilities to identify existing fraud, waste, and abuse (FWA) in the system — by all parties, including members, prescribers, and pharmacies. Opioid FWA occurs when people “doctor shop” to get more medicines than appropriate by seeing multiple doctors. It also occurs when pharmacies or patients create or alter prescription orders, or when prescribers overprescribe drugs beyond guidelines, a practice that can have potentially deadly results. Collaboration with health insurers is imperative to identify potential FWA, research collected data, and obtain evidence to best determine next steps.
This session is accredited for the following accreditation types: CME, CNE, CPE, APA, AAFP, AAHCPAD*, NAADAC*, ASWB*
*State and provincial regulatory boards have the final authority to determine whether an individual course may be accepted for continuing education credit.