Ramin Talebi, BS
Asif Ilyas, MD, FACS
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.
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.
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.
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.
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.
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