According to the Centers for Disease Control and Prevention (CDC), the number of overdose deaths in 2016 involving opioids (including prescription opioids and heroin) was 5 times higher than in 1999. From 2000 to 2016, more than 600,000 people died from drug overdoses. On average, 115 Americans die each day from an opioid overdose
Several solutions have been discussed and utilized to address specific parts of the medication lifetime cycle. These include research into “abuse deterrent” opioids, regulations limiting distribution, expanding safe drug disposal programs and supporting the use of alternative methods of perioperative pain control. Informatics can certainly play a role in addressing multiple aspects of the crisis.
In this blog we will discuss three technological approaches among many which may help pharmacies:
- Tools to help pharmacies detect diversion
- Analytic tools to monitor/predict opioid abuse
- Value of Data and Forecast Models for Evidence-Based Decisions
Tools to help pharmacies detect diversion:
Analytical tools can help detect suspected diversion during a medication transaction audit. Finding inconsistencies during reconciliation of opioid transactions (ex. Dispenses, wastes, returns) is possible by looking within electronic health record (EHR) databases. There are several challenges with this approach. For example, different patient care areas may have different workflows for obtaining, administering, documenting, wasting and/or returning controlled substance (for example procedural areas workflows vs nursing units workflows). With total access to EHR data, similar tools by design can account for all workflows and practices in order to achieve a closed loop in the medication use cycle. These programs utilize algorithms to identify suspicious patterns compared to peer activities and presenting the diversion patterns very easily while cancelling all the noises presented in basic reports.
Analytic tools to monitor and predict opioid abuse:
By utilizing Big Data and analytics, we can get a deeper understanding of prescribing and utilization patterns. The aggregation, analysis, and sharing of accurate, real-time data can make an enormous impact in the fight against opioid abuse.
For example, statewide prescription drug monitoring program data are a powerful tool for identifying individuals who may be opioid abusers by identifying primary care offices, urgent care and emergency department visiting habits. This data can alert and prevent clinicians from prescribing opioids to an at-risk patient.
When similar data is available to the whole care team, healthcare providers can take treatment for those individuals a step further by utilizing standardized order sets within the EHR. These order sets provide safe and effective pain management without inducing more abuse risk. Similar order sets should be designed to limit selections to appropriate therapeutic options based on patient-specific characteristics. Utilizing this systematic approach allows providers to receive specific direction that takes patient specifics into consideration, while simultaneously eliminating duplicate choices.
Value of Data and Forecast Models for Evidence-Based Decisions:
In collaboration with schools of public health and academic centers, forecasting models are valuable tools. They utilize mortality data and substance data to reconstruct the history of opioid epidemics. Key data should be collected and leveraged to make critical public health decisions at local jurisdiction levels. A few examples that are valuable in comprehending system dynamics include, but not limited to:
- Overdose deaths, by drug causing death
- Non-fatal overdoses
- Amount of opioids prescribed
- Number of treatment providers and slots
- Persons undergoing treatment
Leveraging informatics enables a systematic approach to the opioid and heroin epidemic, provides potential recommendations and implementations of those recommendations to National Heroin Task Forces, and reviews proposed opioid policies in various states.
Bringing data from all these sources will help healthcare providers across the continuum of care work effectively together. It can provide a more comprehensive overview of the issue and identify areas for improvement. Through informatics, pharmacies can develop effective strategies that will make a real impact in the fight against opioid abuse.
Published on behalf of the Inpatient Workgroup for the Clinical Application SAG:
Andrew Liu, Pharm.D., CPHIMS. Informatics Pharmacist. Rush University Medical Center. Chicago, IL
Butch Parks, B.S.Pharm., M.S. Senior Consultant. HealthmarkIT. Springdale, AR
Hesham Mourad, Pharm.D., BCPS, BCCCP, CPHIMS, Pharmacy Informatics Team Leader. Mayo Clinic. Jacksonville, FL
Kathy Yount, B.S.Pharm., R.Ph. Clinical Informatics Pharmacist. Deaconess Hospital. Evansville, IN
Marie-Elsie Ade, Pharm.D., M.H.A., M.S., BI. Director of Pharmacy. Baptist Health South Florida. Cutler Bay, FL
Paolo Valerio, Pharm.D. PGY-2 Health System Pharmacy Administration Resident. Allegheny General Hospital. Pittsburgh, PA
Raymond Chan, Pharm.D. Pharmacy IS Specialist. Sentara Healthcare. Virginia Beach, VA
1- CDC, 2016. Understanding the Epidemic. Available from: https://www.cdc.gov/drugoverdose/epidemic/index.html
2- Jennifer Conner, 2017. Fighting the Opioid Epidemic with Predictive Analytics. Available from: https://www.cerner.com/blog/fighting-the-opioid-epidemic-with-predictive-analytics/
3- Kimberly New, 2015. Using Analytics to Detect Diversion. Available from: https://transform-healthcare.com/2015/06/09/using-analytics-to-detect-diversion/
4- Greg Horne, 2017. How Data Analytics Can Combat the Opioid Crisis. Available from: https://www.sas.com/en_ca/insights/articles/analytics/local/how-data-analytics-can-combat-the-opioid-crisis.html
5- Isaacs AN, Knight KL, Nisly SA. Analysis of a Standardized Perioperative Pain Management Order Set in Highly Opioid-Tolerant Patients. J Patient Saf. 2015 Nov 10.