Via Research Recognition Day 2024 VCOM-Carolinas

Educational Reports

Opioid and Stimulant Co-Prescriptions Amongst South Carolina Residents Cole Harp, OMS-III; Martin Groke, OMS-III; Lindsay Tjiattas-Saleski, DO, MBA; David Redden, PhD Edward via College of Osteopathic Medicine – Carolinas Campus, Spartanburg, SC

Abstract

Results

Conclusions

The South Carolina Department of Health and Environmental Control (SC DHEC) Prescription Drug Monitoring Program (PDMP) is used to monitor the prescribing patterns of controlled substances including opioids and stimulants. Data collected by The National Center for Health Statistics shows that the number of drug overdose deaths involving opioids and stimulants has been increasing since 1999. While databases such as The PDMP monitor prescribing habits of opioids and stimulants individually, there has been little research in opioid-stimulant co-prescribing. Considering increasing death rates, and lack of research, data from the SC DHEC PDMP was utilized to identify factors that influence opioid-stimulant co-prescribing. It was hypothesized that younger age, higher daily Morphine Milligram Equivalents (MME), increased duration of prescription, and male gender would be associated with increased opioid-stimulant co-prescriptions. Data was gathered from the SC DHEC PDMP from 2016 to 2021. The data set included: patient, prescriber, pharmacy consolidation ID, state, three-digit zip code, patient age, patient gender, written date, filled date, drug generic name, drug brand name, dosage, supply length, DEA schedule, strength, daily MME, total MME, and Lexicomp Drug Classification. Using SAS statistical software, a linear regression statistical analysis was performed to analyze the data. Individuals with a 30 day or longer opioid prescription were more likely to have a concurrent stimulant prescription (odds ratio (OR) 3.188). Increasing age was associated with co-prescriptions (OR 0.858). While increasing MME was associated with co prescriptions (OR 1.016), the association was minimal. Men were less likely than women to experience opioid-stimulant co-prescription (OR 1.532). This study indicates that longer opioid prescriptions, younger individuals, and women are at an increased risk of opioid-stimulant co-prescription. Future research will investigate other factors associated with opioid-stimulant co-prescribing, such as education status, rurality, and if specific opioid or stimulant agents are linked to co-prescribing. The South Carolina Department of Health and Environmental Control (SC DHEC) tracks, among other things, stimulant and opioid prescriptions in South Carolina via it’s Prescription Drug Monitoring Program (PDMP). The PDMP keeps track of every stimulant and opioid prescription that is written in South Carolina, filled in South Carolina, or prescribed to a South Carolina resident. In this study, access was granted to data from the PDMP program which included: patient, prescriber, and pharmacy consolidation ID, state, three-digit zip code, patient age, patient gender, written date, filled date, drug generic name, drug brand name, dosage, supply length, DEA schedule, strength, daily MME, total MME, and Lexicomp Drug Classification. Temporally, the data in this study was between the years 2016 and 2021. The data was then examined for the purpose of analyzing and determining stimulant-opioid polypharmacy and risk factors. The population included in this study was South Carolina residents who had a minimum of a 30-day concurrent opioid and stimulant prescription. This minimum length of polypharmacy was chosen to allow for the exclusion of patients who were prescribed opioids in the short term. The odds ratio of having a concurrent stimulant and opioid prescription was determined for age, daily MME, Length of Opioid Prescription, and Gender. Due to its size, the dataset was split into 23 replicants that were analyzed independently. The 23 replicants were then coalesced into a single odds ratio with a 95% Confidence Interval via meta analysis for each of the four studied variables. Introduction and Methods

• Age had an odds ratio of 0.858 with a p-value of <0.0001. This result indicates that there is a statistically significant association between age and opioid-stimulant polypharmacy. Moreover, the association between age and opioid-stimulant polypharmacy is stronger with younger patients. • Daily MME was found to have an odds ratio of 1.016 with a p-value of <0.0001. This result indicates a statistically significant, albeit small, association between increasing daily MME and opioid stimulant polypharmacy. • Length of opioid prescription had an odds ratio of 3.188 with a p-value of <0.0001, indicating that there is a strongly positive association between the length of an opioid prescription, and the frequency of opioid stimulant polypharmacy. • Gender (Female) was found to have an odds ratio of 1.532 with a p value of <0.0001. This result indicates that females are more associated with opioid-stimulant polypharmacy than males. All the results obtained in this study had a 95% confidence interval and were statistically significant. The results of this study supported the hypothesis that decreasing age, increasing daily MME, and increasing duration of prescription are associated with opioid-stimulant polypharmacy. However, the hypothesis that males are more associated with opioid stimulant polypharmacy was rejected, as there was a stronger association with females. The analysis indicates that of the variables analyzed, length of prescription has the strongest association with opioid-stimulant polypharmacy having an odds ratio of 3.188. Interestingly, daily MME seems to have a minimal association with opioid-stimulant polypharmacy having an odds ratio of 1.016. These results seem to indicate that it is not how many MME a patient is prescribed that puts them at risk for opioid-stimulant polypharmacy, but how long they are prescribed opiates. Additionally, this study indicates that younger individuals and women are at an increased risk of opioid-stimulant polypharmacy with odds ratios of 0.858, and 1.532 respectively.

Forest Plot 1 . Represents age odds ratio and confidence interval.

Forest Plot 2 . Represents daily MME odds ratio and confidence interval.

Forest Plot 4 . Represents prescription duration (30 days or more) odds ratio and confidence interval.

Forest Plot 3 . Represents gender (Female) odds ratio and confidence interval.

References

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We would like to thank Samantha Donnelly and Chelsea Townsend of SC DHEC for their assistance and help in obtaining data from the DHEC PDMP. An IRB was submitted, however was determined to not be needed as the research conducted did not involve any Human Subjects.

Table 1 . Summary of data analyzed in forest plots 1-4 with averages and weighted statistics.

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2024 Research Recognition Day