| Literature DB >> 35216591 |
Taylor L Watterson1, Jamie A Stone1, Aaron Gilson1, Roger Brown2,3, Ka Z Xiong4, Anthony Schiefelbein2, Edmond Ramly3,5, Peter Kleinschmidt3, Michael Semanik3, Lauren Craddock6, Samantha I Pitts7, Taylor Woodroof7, Michelle A Chui8.
Abstract
BACKGROUND: Prescription opioid misuse is a serious national crisis; in 2018 the top drugs involved in prescription overdose deaths included pain medications (opioids), benzodiazepines, and stimulants. Health information technology (health IT) provides a means to address this crisis through technologies that streamline the prescribing and discontinuation process. CancelRx is a health IT function that communicates when medications, such as controlled substances, are discontinued at the clinic and therefore should not be filled at the pharmacy. Prior to CancelRx, the communication of discontinued medications was a manual process, requiring the patient or a clinic staff member to personally contact the pharmacy to inform them of the change. The objective of this study was to assess how controlled substance medication discontinuations were communicated over time, before and after the implementation of CancelRx.Entities:
Keywords: Controlled substances; Health information technology; Interrupted time series; Opioid epidemic; Prescriptions
Mesh:
Substances:
Year: 2022 PMID: 35216591 PMCID: PMC8876377 DOI: 10.1186/s12911-022-01779-9
Source DB: PubMed Journal: BMC Med Inform Decis Mak ISSN: 1472-6947 Impact factor: 2.796
Fig. 1Controlled substance discontinuations over time. Prior to CancelRx implementation 18,969 controlled substances were discontinued at the clinic. After CancelRx implementation, 30,160 controlled substances were discontinued by providers and/or clinic staff
Fig. 2Successful controlled substance medication discontinuations over time. Immediately following CancelRx implementation, there was a 77.75 percentage point increase in the percentage of medications successfully discontinued in both the clinic EHR and pharmacy dispensing systems
Overall interrupted time series analysis
| Coef | Std. Err | t | P >|t| | 95% CI | ||
|---|---|---|---|---|---|---|
| Pre-intervention trend (β1) | 0.474 | 0.065 | 7.29 | < 0.001 | 0.34559 | 0.6035 |
| Immediate effect (β2) | 77.754 | 3.7191 | 20.91 | < 0.001 | 70.382 | 85.1262 |
| Difference in pre and post trends (β1 + β3) | − 0.4424 | 0.07246 | − 6.11 | < 0.001 | − 0.586 | − 0.298 |
| Post-intervention trend (β3) | 0.03 | 0.04 | 0.77 | 0.441 | − 0.05 | 0.11 |
| Adjusting covariate (β4) number of weekly discontinuations | 0.0608 | 0.0278 | 2.18 | 0.031 | 0.00562 | 0.116 |
| Predicted initial level (Intercept β0) | − 10.667 | 3.062 | − 3.48 | 0.001 | − 16.7364 | − 4.597 |
Fig. 3Successful controlled substance and non-controlled substance medication discontinuations over time. Prior to CancelRx, non-controlled substances had a higher percentage of successful discontinuations than controlled substances. After CancelRx, controlled substances demonstrated a slightly higher percentage
Fig. 4Average time to controlled substance discontinuation over time. The average time (in hours) between when a medication was discontinued at the clinic to when it was discontinued at the pharmacy decreased after CancelRx implementation
Fig. 5“Opioid epidemic” interest over time. Data
Source: Google Trends. Within the figure, numbers represent search interest relative to the highest point on the chart for the given region and time. A value of 100 is the peak popularity for the term, approximately October 2017, which coincides with CancelRx implementation