A Pennsylvania PDMP Analysis: Top 5 Pennsylvania Counties 
by Opioid-Related Overdose Deaths

Ramin Talebi, BS

Asif Ilyas, MD, FACS


SUMMARY POINTS

  • Opioid prescribing rates and prescription opioid overdose rates are trending down, but rates across Pennsylvania remain high compared to national averages.

  • The top 5 Pennsylvania counties relative to opioid-related overdose deaths are Lawrence, Wayne, Fayette, Lackawanna, and Washington.

  • These counties all demonstrated prescription opioid-related death rates nearly 2x or more than the average in all other PA counties during the same time period.

  • These counties by prescription opioid-related death rates exhibited signs of high risk prescribing, including high Hydrocodone/Oxycodone prescription amounts, average daily MMEs >50mg/day, and longer prescription durations.

  • Further county-level studies of opioid prescribing and overdose rates may better elaborate regional heterogeneity and inform targeted public health interventions.



ANALYSIS

Introduction

As opioid-related death rates continue to rise, public health organizations at every level have continued close surveillance in order to better inform prevention efforts. Recent reports from the CDC reveal that the overdose death rate in the US increased 7% from 2018 to 2019, owed largely to the rising number of deaths attributable to illicitly manufactured fentanyl and other synthetic opioids.1 While the overall opioid-related deaths are rising, deaths attributed to prescription opioid overdose declined 6% from 2018 to 2019.1 These evolving trends in opioid surveillance data highlight an opportunity to investigate associations among current opioid prescribing practices and overdose deaths.

Background

Reductions in prescription opioid-related deaths in 2018-2019 occurred alongside an observable decline in opioid prescriptions over the same period2 Since peaking in 2012, opioid prescribing rates have declined steadily which suggests broader recognition by prescribers about the potential harms of opioid use3. Among the efforts to promote provider awareness and curb opioid dispensing rates is state legislation regarding Prescription Drug Monitoring Programs (PDMPs). First enacted in 1939, state-based PDMPs have expanded to all 50 states after Missouri most recently passed legislation in 2021 to establish its own statewide program4. These programs allow prescribers to query a patient’s history of controlled substance prescriptions before dispensing opioids, and some states even have mandates in place that require prescribers to check the PDMP before prescribing.5

Studies on PDMP implementation in select states have shown that implementation of a PDMP was effective in reducing opioid prescribing, and more robust PDMPs– those with features such as mandatory registration, proactive prescribing reports, and utilization mandates– were more strongly associated with reduced prescribing rates.6-10 PDMPs show similar effects in studies on overdose rates. In several studies, adoption of a PDMP was associated with at least a modest reduction in fatal prescription opioid overdose, with more robust PDMP features again associated with larger reductions.11-14

Additionally, data from PDMPs are being increasingly used to study individual risks for opioid dependence and opioid-related death. A recent study using the Illinois PDMP found that 76% of individuals who died of a prescription opioid overdose filled an opioid prescription in the year prior to overdose.15 Another study using the Maryland PDMP found that risks associated with opioid overdose in adults included filling one or more long-acting opioid prescriptions, a prescription days supply ≥91 days, and an average daily dosage ≥120 morphine milligram equivalents (MME).16 To develop guidelines for opioid use in chronic pain, the CDC conducted a large systematic review of studies, including several PDMP-based studies, and found that overdose risk was associated with opioid prescription in a dose-dependent fashion.17

Although risks of an overdose in individuals have been well-described, few studies have examined associations between prescribing patterns and opioid overdose at the county level. In the below analysis, county-level data from the Pennsylvania state PDMP is used to briefly highlight prescribing characteristics for the top five Pennsylvania (PA) counties with the highest rates of overdose deaths involving prescription opioids.

Analysis

The CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) database was used to identify the top five PA counties with the highest rates per 100,000 of prescription opioid-related overdose deaths from 2016-2019. Data collection methodology was derived from the CDC Annual Surveillance Report of Drug-Related Risks and Outcomes.18 First, county rates of total opioid-related overdose deaths during the timespan were determined using the International Classification of Diseases, Tenth Revision (ICD-10). Opioid-related deaths were those that included underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), and/or Y10–Y14 (undetermined) plus ICD-10-CM codes T40.1 (heroin); T40.2 and T40.3 (prescription opioids); and T40.4 (synthetic opioids other than methadone). The five counties chosen for analysis (Lawrence, Wayne, Fayette, Lackawanna, Washington) were those with the highest rates per 100,000 of prescription opioid-related overdose deaths, which were determined using ICD-10-CM codes T40.2 and T40.3 specifically (Figure 1). For comparison, average rates for each outcome (total opioid deaths and prescription opioid deaths) were calculated using all counties and separately using counties excluding the top five. In line with CDC WONDER guidelines, counties with less than 10 total deaths within the timespan for each outcome were excluded from average rate calculations. Overall, 50 and 26 counties were included in average rate calculations for total opioid deaths and prescription opioid deaths, respectively.

To examine opioid prescribing patterns during the same period, the Pennsylvania state PDMP was used to determine prescribing indices for the five counties within the analysis (Figure 2). Features included were hydrocodone and oxycodone prescription rates per 100,000, average daily MME per prescription (mg/day), rates per 100,000 of total opioid prescriptions by the quantity of pills, and rates per 100,000 of total opioid prescriptions by days supply. Average rates of these features were calculated for all PA counties (n = 67) and all counties excluding the top 5 (n = 62) for comparison.



The top five PA counties all demonstrated prescription opioid-related death rates nearly 2x or more than the average in all other PA counties during the time period. A look at the prescribing patterns among the top 5 counties shows that four out of the five counties had hydrocodone prescription rates greater than the average among all other PA counties. All five counties prescribed oxycodone at rates higher than the average for all other PA counties. Compared to other opioids, hydrocodone and oxycodone were the most prescribed for all PA counties. Notably, four of the five counties prescribed opioid dosages at average daily MMEs >50 mg/day, a marker of significant overdose risk.17 In terms of quantity and days supply, the five PA counties demonstrated greater rates of prescriptions with quantities ≤60 than >60 pills; however, four of the five counties prescribed greater rates of prescriptions with durations >21 days than ≤21 days.

Conclusions

The present analysis reviews opioid prescribing patterns and overdose death rates among Pennsylvania counties with the highest rates of prescription opioid overdose in recent years. The findings suggest a potential tendency towards high-risk prescribing practices among the PA counties with the highest rates of prescription opioid-related deaths. Although opioid prescribing and prescription opioid overdose is trending down, county data show that Pennsylvania prescription rates and overdose deaths remain high compared to national averages.3 Importantly, this analysis was limited to general prescribing features of Pennsylvania counties and did not consider variability in county demographics, which the CDC suggests may be associated with differences in prescribing rates.3 Additionally, the analysis did not account for the involvement of non-opioid medications or psychiatric conditions in opioid-related deaths, though it should be noted that concurrent use of drugs such as benzodiazepines and antipsychotics as well as conditions such as alcohol use disorder or mood disorders may increase the risk of opioid overdose.19-22

While progress has been made in curbing opioid prescribing, evidence on the overall impact of efforts combating the opioid epidemic is mixed, as some studies suggest policy interventions have had unintended effects on nonmedical and illicit drug use.23 Other studies have examined limitations in the existing literature– notably the lack of time-series studies, inadequate consideration of confounding variables, and inadequate consideration of interactions between multiple drug classes– arguing that the small number of high-quality studies makes it difficult to draw conclusions regarding opioid policies.23-25 Future studies should focus methodology on time series analysis and the influence of multiple risk factors in order to better elucidate characteristics that contribute to the regional heterogeneity of the opioid crisis.

Undoubtedly, there remains much to learn regarding current trends in the opioid epidemic, particularly as data from PDMPs and other surveillance efforts are accumulated every year. The limited number of studies assessing opioid prescribing and overdose variability at the county level underscores the need for more research on regional trends. Understanding the evolving heterogeneity among states and counties will be crucial to designing targeted interventions to continue combating the opioid crisis.

REFERENCES

  1. "Understanding the Epidemic." Opioid Overdose. Centers for Disease Control and Prevention, 17 Mar. 2021. Web. 23 June 2021. <https://www.cdc.gov/drugoverdose/epidemic/index.html>

  2. "U.S. Opioid Dispensing Rate Maps." Opioid Overdose. Centers for Disease Control and Prevention, 07 Dec. 2020. Web. 23 June 2021. <https://www.cdc.gov/drugoverdose/maps/rxrate-maps.html>.

  3. "Prescribing Practices." Opioid Overdose. Centers for Disease Control and Prevention, 13 Aug. 2019. Web. 23 June 2021. <https://www.cdc.gov/drugoverdose/data/prescribing/prescribing-practices.html>.

  4. Gerber, Cameron. "Missouri Legislature Gives Final Approval to Statewide PDMP Bill." The Missouri Times. 11 May 2021. Web. 23 June 2021. <https://themissouritimes.com/missouri-legislature-gives-final-approval-to-statewide-pdmp-bill/>.

  5. Haffajee RL, Jena AB, Weiner SG. Mandatory use of prescription drug monitoring programs. JAMA. 2015 Mar 3;313(9):891-2. doi: 10.1001/jama.2014.18514. PMID: 25622279; PMCID: PMC4465450.

  6. Moyo P, Simoni-Wastila L, Griffin BA, Onukwugha E, Harrington D, Alexander GC, Palumbo F. Impact of prescription drug monitoring programs (PDMPs) on opioid utilization among Medicare beneficiaries in 10 US States. Addiction. 2017 Oct;112(10):1784-1796. doi: 10.1111/add.13860. Epub 2017 Jun 27. PMID: 28498498.

  7. Strickler GK, Zhang K, Halpin JF, Bohnert ASB, Baldwin GT, Kreiner PW. Effects of mandatory prescription drug monitoring program (PDMP) use laws on prescriber registration and use and on risky prescribing. Drug Alcohol Depend. 2019 Jun 1;199:1-9. doi: 10.1016/j.drugalcdep.2019.02.010. Epub 2019 Mar 22. PMID: 30954863.

  8. Castillo-Carniglia A, González-Santa Cruz A, Cerdá M, Delcher C, Shev AB, Wintemute GJ, Henry SG. Changes in opioid prescribing after implementation of mandatory registration and proactive reports within California's prescription drug monitoring program. Drug Alcohol Depend. 2021 Jan 1;218:108405. doi: 10.1016/j.drugalcdep.2020.108405. Epub 2020 Nov 12. Erratum in: Drug Alcohol Depend. 2021 Apr 1;221:108606. PMID: 33234299; PMCID: PMC7750250.

  9. Haffajee RL, Mello MM, Zhang F, Zaslavsky AM, Larochelle MR, Wharam JF. Four States With Robust Prescription Drug Monitoring Programs Reduced Opioid Dosages. Health Aff (Millwood). 2018 Jun;37(6):964-974. doi: 10.1377/hlthaff.2017.1321. PMID: 29863921; PMCID: PMC6298032.

  10. Ayres I, Jalal A. The Impact of Prescription Drug Monitoring Programs on U.S. Opioid Prescriptions. J Law Med Ethics. 2018 Jun;46(2):387-403. doi: 10.1177/1073110518782948. PMID: 30146997.

  11. Cerdá M, Ponicki WR, Smith N, Rivera-Aguirre A, Davis CS, Marshall BDL, Fink DS, Henry SG, Castillo-Carniglia A, Wintemute GJ, Gaidus A, Gruenewald PJ, Martins SS. Measuring Relationships Between Proactive Reporting State-level Prescription Drug Monitoring Programs and County-level Fatal Prescription Opioid Overdoses. Epidemiology. 2020 Jan;31(1):32-42. doi: 10.1097/EDE.0000000000001123. PMID: 31596794; PMCID: PMC7027962.

  12. Brown R, Riley MR, Ulrich L, Kraly EP, Jenkins P, Krupa NL, Gadomski A. Impact of New York prescription drug monitoring program, I-STOP, on statewide overdose morbidity. Drug Alcohol Depend. 2017 Sep 1;178:348-354. doi: 10.1016/j.drugalcdep.2017.05.023. Epub 2017 Jun 23. PMID: 28692945.

  13. Delcher C, Wagenaar AC, Goldberger BA, Cook RL, Maldonado-Molina MM. Abrupt decline in oxycodone-caused mortality after implementation of Florida's Prescription Drug Monitoring Program. Drug Alcohol Depend. 2015 May 1;150:63-8. doi: 10.1016/j.drugalcdep.2015.02.010. Epub 2015 Feb 19. PMID: 25746236.

  14. Patrick SW, Fry CE, Jones TF, Buntin MB. Implementation Of Prescription Drug Monitoring Programs Associated With Reductions In Opioid-Related Death Rates. Health Aff (Millwood). 2016 Jul 1;35(7):1324-32. doi: 10.1377/hlthaff.2015.1496. Epub 2016 Jun 22. PMID: 27335101; PMCID: PMC5155336.

  15. Abbasi AB, Salisbury-Afshar E, Berberet CE, Layden JE, Pho MT. Opioid Prescribing Patterns Before Fatal Opioid Overdose. Am J Prev Med. 2020 Feb;58(2):250-253. doi: 10.1016/j.amepre.2019.09.022. PMID: 31959322; PMCID: PMC6986381.

  16. Ferris LM, Saloner B, Krawczyk N, Schneider KE, Jarman MP, Jackson K, Lyons BC, Eisenberg MD, Richards TM, Lemke KW, Weiner JP. Predicting Opioid Overdose Deaths Using Prescription Drug Monitoring Program Data. Am J Prev Med. 2019 Dec;57(6):e211-e217. doi: 10.1016/j.amepre.2019.07.026. PMID: 31753274; PMCID: PMC7996003.

  17. Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain– United States, 2016. MMWR Recomm Rep 2016;65(No. RR-1):1–49. DOI: http://dx.doi.org/10.15585/mmwr.rr6501e1

  18. Centers for Disease Control and Prevention. “2019 Annual Surveillance Report of Drug‐Related Risks and Outcomes – United States. Surveillance Special Report.” Centers for Disease Control and Prevention, U.S. Department of Health and Human Services. October 28, 2019. Accessed 23 June 2021. <www.cdc.gov/drugoverdose/pdf/pubs/2019‐cdc‐drug‐surveillance‐report.pdf>

  19. Garg RK, Fulton-Kehoe D, Franklin GM. Patterns of Opioid Use and Risk of Opioid Overdose Death Among Medicaid Patients. Med Care. 2017 Jul;55(7):661-668. doi: 10.1097/MLR.0000000000000738. PMID: 28614178.

  20. Chua KP, Brummett CM, Conti RM, Bohnert A. Association of Opioid Prescribing Patterns With Prescription Opioid Overdose in Adolescents and Young Adults. JAMA Pediatr. 2020 Feb 1;174(2):141-148. doi: 10.1001/jamapediatrics.2019.4878. PMID: 31841589; PMCID: PMC6990690.

  21. Groenewald CB, Zhou C, Palermo TM, Van Cleve WC. Associations Between Opioid Prescribing Patterns and Overdose Among Privately Insured Adolescents. Pediatrics. 2019 Nov;144(5):e20184070. doi: 10.1542/peds.2018-4070. Epub 2019 Oct 1. PMID: 31575622; PMCID: PMC6856776.

  22. Leece P, Cavacuiti C, Macdonald EM, Gomes T, Kahan M, Srivastava A, Steele L, Luo J, Mamdani MM, Juurlink DN; Canadian Drug Safety and Effectiveness Research Network. Predictors of Opioid-Related Death During Methadone Therapy. J Subst Abuse Treat. 2015 Oct;57:30-5. doi: 10.1016/j.jsat.2015.04.008. Epub 2015 Apr 15. PMID: 26014916.

  23. Compton WM, Jones CM, Baldwin GT. Relationship between Nonmedical Prescription-Opioid Use and Heroin Use. N Engl J Med. 2016 Jan 14;374(2):154-63. doi: 10.1056/NEJMra1508490. PMID: 26760086.

  24. Haegerich TM, Paulozzi LJ, Manns BJ, Jones CM. What we know, and don't know, about the impact of state policy and systems-level interventions on prescription drug overdose. Drug Alcohol Depend. 2014 Dec 1;145:34-47. doi: 10.1016/j.drugalcdep.2014.10.001. Epub 2014 Oct 14. PMID: 25454406; PMCID: PMC6557270.

  25. Nam YH, Shea DG, Shi Y, Moran JR. State prescription drug monitoring programs and fatal drug overdoses. Am J Manag Care. 2017 May;23(5):297-303. PMID: 28738683.

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