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Opioid prescribing and opioid-overdose deaths in Michigan: Urban-rural comparisons and changes across 2013-2017.

ABSTRACT: Background:Opioid-overdose deaths and opioid prescriptions have increased substantially within the past decade, leading to examinations of urban-rural differences for these opioid-related outcomes, and whether annual trends differ by urban-rural status. Most investigations have examined differences using national data, whereas few studies have identified patterns in hard-hit regions. Therefore, we examined urban-rural differences for opioid-related outcomes in Michigan, a state with overdose death and prescribing rates above the national average. Methods:This study used county-level public data on opioid prescribing and opioid-overdose death rates in Michigan. Bivariate and joinpoint regression analyses tested for annual differences and annual changes in opioid-related outcomes across 2013-2017. Rural Urban Continuum Codes classified urban-rural county status. Results:Bivariate analyses demonstrated that urban counties had consistently higher opioid-overdose death rates than rural, whereas rural counties had consistently higher opioid prescribing rates than urban. Joinpoint regression (2013-2017) revealed opioid-overdose death rates increased in urban (Annual Percent Change = 25.0%, p = .001) and rural counties (Annual Percent Change = 21.7%, p = .002), though no changes for opioid prescribing rates were observed among urban or rural counties. Conclusions:Our study highlights nuanced urban-rural patterns in Michigan, a hard-hit state, compared to trends in national data. Both urban and rural counties experienced rising rates of opioid-overdose deaths, and rural counties experienced higher opioid prescribing rates than urban. Though urban counties experienced higher opioid-overdose death rates than rural, the rise in both county types was similar. Future research directions, implications for public health, and healthcare policy recommendations are discussed.

SUBMITTER: Lister JJ

PROVIDER: S-EPMC7244930 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionOpioid overdose deaths quintupled in Massachusetts between 2000 and 2016. Potentially inappropriate opioid prescribing practices (PIP) are associated with increases in overdoses. The purpose of this study was to conduct spatial epidemiological analyses of novel comprehensively linked data to identify overdose and PIP hotspots.MethodsSixteen administrative datasets, including prescription monitoring, medical claims, vital statistics, and medical examiner data, covering >98% of Massachusetts residents between 2011-2015, were linked in 2017 to better investigate the opioid epidemic. PIP was defined by six measures: ≥100 morphine milligram equivalents (MMEs), co-prescription of benzodiazepines and opioids, cash purchases of opioid prescriptions, opioid prescriptions without a recorded pain diagnosis, and opioid prescriptions through multiple prescribers or pharmacies. Using spatial autocorrelation and cluster analyses, overdose and PIP hotspots were identified among 538 ZIP codes.ResultsMore than half of the adult population (n = 3,143,817, ages 18 and older) were prescribed opioids. Nearly all ZIP codes showed increasing rates of overdose over time. Overdose clusters were identified in Worcester, Northampton, Lee/Tyringham, Wareham/Bourne, Lynn, and Revere/Chelsea (Getis-Ord Gi*; p < 0.05). Large PIP clusters for ≥100 MMEs and prescription without pain diagnosis were identified in Western Massachusetts; and smaller clusters for multiple prescribers in Nantucket, Berkshire, and Hampden Counties (p < 0.05). Co-prescriptions and cash payment clusters were localized and nearly identical (p < 0.05). Overlap in PIP and overdose clusters was identified in Cape Cod and Berkshire County. However, we also found contradictory patterns in overdose and PIP hotspots.ConclusionsOverdose and PIP hotspots were identified, as well as regions where the two overlapped, and where they diverged. Results indicate that PIP clustering alone does not explain overdose clustering patterns. Our findings can inform public health policy decisions at the local level, which include a focus on PIP and misuse of heroin and fentanyl that aim to curb opioid overdoses.

Project description:Importance:The use of benzodiazepines or alcohol together with opioids increases overdose risk, but characterization of co-involvement by predominant opioid subtype is incomplete to date. Understanding the use of respiratory depressants in opioid overdose deaths (OODs) is important for prevention efforts and policy making. Objective:To assess the prevalence and number of alcohol- or benzodiazepine-involved OODs by opioid subtypes in the United States from 1999 to 2017. Design and Setting:This repeated cross-sectional analysis used data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database of all opioid-involved poisoning deaths from January 1, 1999, to December 31, 2017, for the United States. State-level binge drinking prevalence rates for 2015 to 2017 were obtained from the Behavior Risk Factor Surveillance System of the Centers for Disease Control and Prevention, and benzodiazepine prescribing rates for 2012 (most recent available data) were obtained from IMS Health, a commercial database. Data were analyzed from July 10, 2018, to May 16, 2019. Main Outcomes and Measures:Prevalence of alcohol or benzodiazepine co-involvement for all OODs and by opioid subtype, nationally and by state. Results:From 1999 to 2017, 399?230 poisoning deaths involved opioids, of which 263 601 (66.0%) were male, and 204?560 (51.2%) were aged 35 to 54 years. Alcohol co-involvement for all opioid overdose deaths increased nonlinearly from 12.4% in 1999 to 14.7% in 2017. By opioid subtype, deaths involving heroin and synthetic opioids (eg, fentanyl; excluding methadone) had the highest alcohol co-involvement at 15.5% and 14.9%, respectively, in 2017. Benzodiazepine co-involvement in all OODs increased nonlinearly from 8.7% in 1999 to 21.0% in 2017. Benzodiazepines were present in 33.1% of prescription OODs and 17.1% of synthetic OODs in 2017. State-level rates of binge drinking were significantly correlated with alcohol co-involvement in all OODs (r?=?0.34; P?=?.02). State benzodiazepine prescribing rates were significantly correlated with benzodiazepine co-involvement in all OODs (r?=?0.57; P?<?.001). Conclusions and Relevance:This study found that alcohol and benzodiazepine co-involvement in opioid-involved overdose deaths was common, varied by opioid subtype, and was associated with state-level binge drinking and benzodiazepine prescribing rates. These results may inform state policy initiatives in harm reduction and overdose prevention efforts.

Project description:ImportanceThere is growing evidence that opioids are overprescribed following surgery. Improving prescribing requires understanding factors associated with opioid consumption.ObjectiveTo describe opioid prescribing and consumption for a variety of surgical procedures and determine factors associated with opioid consumption after surgery.Design, setting, and participantsA retrospective, population-based analysis of the quantity of opioids prescribed and patient-reported opioid consumption across 33 health systems in Michigan, using a sample of adults 18 years and older undergoing surgery. Patients were included if they were prescribed an opioid after surgery. Surgical procedures took place between January 1, 2017, and September 30, 2017, and were included if they were performed in at least 25 patients.ExposuresOpioid prescription size in the initial postoperative prescription.Main outcomes and measuresPatient-reported opioid consumption in oral morphine equivalents. Linear regression analysis was used to calculate risk-adjusted opioid consumption with robust standard errors.ResultsIn this study, 2392 patients (mean age, 55 years; 1353 women [57%]) underwent 1 of 12 surgical procedures. Overall, the quantity of opioid prescribed was significantly higher than patient-reported opioid consumption (median, 30 pills; IQR, 27-45 pills of hydrocodone/acetaminophen, 5/325 mg, vs 9 pills; IQR, 1-25 pills; P < .001). The quantity of opioid prescribed had the strongest association with patient-reported opioid consumption, with patients using 0.53 more pills (95% CI, 0.40-0.65; P < .001) for every additional pill prescribed. Patient-reported pain in the week after surgery was also significantly associated with consumption but not as strongly as prescription size. Compared with patients reporting no pain, patients used a mean (SD) 9 (1) more pills if they reported moderate pain and 16 (2) more pills if they reported severe pain (P < .001). Other significant risk factors included history of tobacco use, American Society of Anesthesiologists class, age, procedure type, and inpatient surgery status. After adjusting for these risk factors, patients in the lowest quintile of opioid prescribing had significantly lower mean (SD) opioid consumption compared with those in the highest quintile (5 [2] pills vs 37 [3] pills; P < .001).Conclusions and relevanceThe quantity of opioid prescribed is associated with higher patient-reported opioid consumption. Using patient-reported opioid consumption to develop better prescribing practices is an important step in combating the opioid epidemic.

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Opioid prescribing and opioid-overdose deaths in Michigan: Urban-rural comparisons and changes across 2013-2017.

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