The purpose of this project is to demonstrate how CancelRx, an e-prescribing functionality that communicates medication discontinuation orders between the clinic and pharmacy, impacts the cancellation and dispensing of controlled substances prescriptions.

Background

In March 2018, the National Institute on Drug Abuse reported that more than 115 people die in the United States every day due to opioid overdoses. Opioids include prescription pain relievers such as hydrocodone, oxycodone, and fentanyl, as well as non-prescription, illicit drugs, such as heroin. The Centers for Disease Control and Prevention (CDC) cites this as a “serious national crisis” and estimates that the total economic burden of prescription opioid misuse amounts to $78.5 billion in the United States each year. More recent data from the CDC’s National Vital Statistics Report in December 2018 stated that the number of annual drug overdose deaths has increased 54% between 2011 and 2016.

In light of this crisis, agencies are promoting and requiring the use of electronic prescribing of all controlled prescriptions to reduce drug diversion and misuse. This presents an opportunity to assess the impact of CancelRx on the cancellation and dispensing of these prescription drugs which may be contributing to the opioid crisis. By electronically communicating medications that are discontinued in the physician’s office to the pharmacy, this health IT functionality can potentially minimize the number of extraneous or unnecessary controlled medications dispensed and available to patients as well as reduce potential for diversion. This study is timely and relevant given CancelRx’s inclusion in the 2020 CMS Meaningful Use Criteria as well as ongoing need to address the serious opioid crisis.

Aims and Outcomes

To measure the impact of CancelRx on reducing controlled substance medication discrepancies in the pharmacy management software, specifically pain medications (opioids), stimulants, and benzodiazepines.

Specifically, the grant has the following outcomes:

  • Outcome 1: Percentage of Successful Controlled Substance Discontinuations Over Time
  • Outcome 2: Percentage of Successful Discontinuations Over Time for Controlled Substances and Non-Controlled Substances
  • Outcome 3: Time to Discontinuation Between Clinic and Pharmacy Over Time
Scope

This grant capitalizes on an academic health system, UW Health in Dane County, Wisconsin that previously implemented CancelRx in October of 2017. We simultaneously conducted a project with UW Health to measure the impact of CancelRx on medication discrepancies as part of an Agency for Healthcare Research and Quality (AHRQ) R21 funded grant.  At the time of grant submission, schedule II controlled substances (including most opioids pain medications and stimulants) were not e-prescribed in the UW Health System. As a result, we excluded schedule II prescriptions from the analysis. Further, we did not propose a separate analysis of controlled substance prescriptions.  This focus of this project is to address a critical gap in the understanding of how CancelRx impacts the availability of controlled substance prescriptions, with a special emphasis on the following therapeutic classes: pain medications (opioids), stimulants, and benzodiazepines.

Methods

The research team extracted data from the health system EHR (Epic) regarding controlled substance medications discontinued in the outpatient clinics at 12-months prior to CancelRx implementation and for 12-months post implementation (allowing for a 4-week a priori burn-in period).

An interrupted time series analysis (ITSA) was used to determine the impact of CancelRx on controlled substance medication list discrepancies over time. Specifically, the ITSA allowed the research team to compare the proportion of controlled substances that were discontinued clinic EHR and successfully discontinued in the pharmacy dispensing software within 72-hours. The study utilized Prais-Winsten estimation, meant to address the serial correlation of type AR(1) in a linear model, with analysis conducted in STATA. A one-week period constituted a measurement in the time series.

Furthermore, time-to-discontinuation event analyses were also conducted to compare the length of time between EHR and pharmacy system discontinuation before and after CancelRx implementation. The time to discontinuation was aggregated and averaged for each week in the study period and compared over time using Regression with Newey-West standard errors.

Results

After CancelRx implementation there was an immediate and significant increase in the proportion of controlled substance medications that were successfully discontinued at the pharmacy after being cancelled in the clinic (78% increase). The drastic and sustained success may be attributable to how CancelRx was created. CancelRx was designed to work “behind the scenes” and automate the process, eliminating the need for clinic staff to intervene, except in rare instances such as when the prescription was not electronically transmitted to the pharmacy, the CancelRx could not be sent, or the pharmacy was unable to find a match for the discontinued prescription. The health IT functionality was able to efficiently take over tasks and potentially reduce workload for clinic staff.

Overall, this study demonstrates the role that technology can play in promoting communication between clinics and pharmacies, especially when medications such as controlled substances are discontinued.

Effective communication regarding medication discontinuation yields accurate medication lists at the pharmacy. As the last checkpoint before a medication reaches the patient, up-to-date medication lists are crucial to ensure patient safety and avoiding unintended medication errors. Considering the opioid epidemic, CancelRx is a tool that promotes medication safety—ensuring high risk medications like opioids, stimulants, and benzodiazepines are appropriately discontinued.

Research Team

Principal Investigator

  • Michelle Chui

Co-Investigators and Collaborators

  • Roger Brown
  • Peter Kleinschmidt
  • Edmond Ramly
  • Michael Seminak

Research Staff

  • Anthony Schiefelbein
  • Jamie Stone
  • Taylor Watterson
  • Ka Z Xiong

Grant information

National Council for Prescription Drug Programs (NCPDP)

This project was supported by the National Council for Prescription Drug Programs. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Council for Prescription Drug Programs.