Opioid prescribing and opioid-overdose deaths in Michigan: Urban-rural comparisons and changes across 2013-2017.
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ABSTRACT:
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.
| S-EPMC6685426 | biostudies-literature
Project description:BackgroundRising opioid-related death rates have prompted reductions of opioid prescribing, yet limited data exist on population-level associations between opioid prescribing and opioid-related deaths.ObjectiveTo evaluate population-level associations between five opioid prescribing measures and opioid-related deaths.DesignAn ecological panel analysis was performed using linear regression models with year and commuting zone fixed effects.ParticipantsPeople ≥10 years aggregated into 886 commuting zones, which are geographic regions collectively comprising the entire USA.Main measuresAnnual opioid prescriptions were measured with IQVIA Real World Longitudinal Prescription Data including 76.5% (2009) to 90.0% (2017) of US prescriptions. Prescription measures included opioid prescriptions per capita, percent of population with ≥1 opioid prescription, percent with high-dose prescription, percent with long-term prescription, and percent with opioid prescriptions from ≥3 prescribers. Outcomes were age- and sex-standardized associations of change in opioid prescriptions with change in deaths involving any opioids, synthetics other than methadone, heroin but not synthetics or methadone, and prescription opioids, but not other opioids.Key resultsChange in total regional opioid-related deaths was positively correlated with change in regional opioid prescriptions per capita (β=.110, p<.001), percent with ≥1 opioid prescription (β=.100, p=.001), and percent with high-dose prescription (β=.081, p<.001). Change in total regional deaths involving prescription opioids was positively correlated with change in all five opioid prescribing measures. Conversely, change in total regional deaths involving synthetic opioids was negatively correlated with change in percent with long-term opioid prescriptions and percent with ≥3 prescribers, but not for persons ≥45 years. Change in total regional deaths in heroin was not associated with change in any prescription measure.ConclusionsRegional decreases in opioid prescriptions were associated with declines in overdose deaths involving prescription opioids, but were also associated with increases in deaths involving synthetic opioids (primarily fentanyl). Individual-level inferences are limited by the ecological nature of the analysis.
| S-EPMC9905341 | biostudies-literature
Project description:Community rapid response may reduce opioid overdose harms, but is hindered by the lack of timely data. To address this need, we created and evaluated the Michigan system for opioid overdose surveillance (SOS). SOS integrates suspected fatal overdose data from Medical Examiners (MEs), and suspected non-fatal overdoses (proxied by naloxone administration) from the Michigan Emergency Medical Services (EMS) into a web-based dashboard that was developed with stakeholder feedback. Authorised stakeholders can view approximate incident locations and automated spatiotemporal data summaries, while the general public can view county-level summaries. Following Centers for Disease Control and Prevention (CDC) surveillance system evaluation guidelines, we assessed simplicity, flexibility, data quality, acceptability, sensitivity, positive value positive (PVP), representativeness, timeliness and stability of SOS. Data are usually integrated into SOS 1-day postincident, and the interface is updated weekly for debugging and new feature addition, suggesting high timeliness, stability and flexibility. Regarding representativeness, SOS data cover 100% of EMS-based naloxone adminstrations in Michigan, and receives suspected fatal overdoses from MEs covering 79.1% of Michigan's population, but misses those receiving naloxone from non-EMS. PVP of the suspected fatal overdose indicator is nearly 80% across MEs. Because SOS uses pre-existing data, added burden on MEs/EMS is minimal, leading to high acceptability; there are over 300 authorised SOS stakeholders (~6 new registrations/week) as of this writing, suggesting high user acceptability. Using a collaborative, cross-sector approach we created a timely opioid overdose surveillance system that is flexible, acceptable, and is reasonably accurate and complete. Lessons learnt can aid other jurisdictions in creating analogous systems.
| S-EPMC9983877 | biostudies-literature
Project description:BackgroundPrescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown.MethodsIn this serial cross-sectional study of zip codes in 17 states, 2002-2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes.ResultsPercent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06-1.07]; 5% low education: 1.02 [1.02-1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87-0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11-1.13]; 5% unemployment: 1.04 [1.02-1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87-0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02-1.16]).ConclusionsRegardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.
| S-EPMC6375680 | biostudies-literature
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.
| S-EPMC7146101 | biostudies-literature
Project description:Pain management clinic (PMC) laws were enacted by 12 states to promote appropriate opioid prescribing, but their impact is inadequately understood. We analyzed county-level opioid overdose deaths (National Vital Statistics System) and patients filling long-duration (≥30 day) or high-dose (≥90 morphine milligram equivalents per day) opioid prescriptions (IQVIA, Inc.) in the United States in 2010-2018. We fitted Besag-York-Mollié spatiotemporal models to estimate annual relative rates (RRs) of overdose and prevalence ratios (PRs) of high-risk prescribing associated with any PMC law and 3 provisions: payment restrictions, site inspections, and criminal penalties. Laws with criminal penalties were significantly associated with reduced PRs of long-duration and high-dose opioid prescriptions (adjusted PR = 0.82, 95% credible interval (CrI): 0.82, 0.82, and adjusted PR = 0.73, 95% CI: 0.73, 0.74 respectively) and reduced RRs of total and natural/semisynthetic opioid overdoses (adjusted RR = 0.86, 95% CrI: 0.80, 0.92, and adjusted RR = 0.84, and 95% CrI: 0.77, 0.92, respectively). Conversely, PMC laws were associated with increased relative rates of synthetic opioid and heroin overdose deaths, especially criminal penalties (adjusted RR = 1.83, 95% CrI: 1.59, 2.11, and adjusted RR = 2.59, 95% CrI: 2.22, 3.02, respectively). Findings suggest that laws with criminal penalties were associated with intended reductions in high-risk opioid prescribing and some opioid overdoses but raise concerns regarding unintended consequences on heroin/synthetic overdoses.
| S-EPMC8796812 | biostudies-literature
Project description:IntroductionIn response to the role of opioid prescribing in the U.S. opioid crisis, states have enacted laws intended to curb high risk opioid prescribing practices. This study assessed the effects of state prescribing cap laws that limit the dose and/or duration of dispensed opioid prescriptions on opioid prescribing patterns and opioid overdose.MethodsWe identified 1,414,908 adults from a large U.S. administrative insurance claims database. Treatment states included 32 states that implemented a prescribing cap law between 2017 and 2019. Comparison states included 16 states and DC without a prescribing cap law by 2019. A difference-in-differences approach with staggered policy adoption was used to assess effects of these laws on opioid analgesic prescribing and opioid overdose.ResultsState opioid prescribing cap laws were not associated with changes in the proportion of people receiving opioid analgesic prescriptions, the dose or duration of opioid prescriptions, or opioid overdose. States with laws that imposed days' supply limits only versus days' supply and dosage limits, as well as with specific law provisions also showed no association with opioid prescribing or opioid overdose outcomes.ConclusionsState opioid prescribing cap laws did not appear to impact outcomes related to opioid analgesic prescribing or opioid overdose. These findings are potentially due to the limited scope of these laws, which often apply only to a subset of opioid prescriptions and include professional judgment exemptions.
| S-EPMC9893520 | biostudies-literature
Project description:IntroductionFatal overdoses from opioids increased four-fold from 1999 to 2009, and they are now the leading cause of death among Americans under 50. Legislation has been passed by every state to increase access to naloxone but dispensing by community pharmacies remains low.ObjectivesThe objective of this study was to pilot test a proactive opioid overdose counseling intervention and a passive naloxone intervention, and the implementation strategies developed to support their delivery, in rural community pharmacies on relevant implementation outcomes.MethodsThe interventions, implementation strategies, and the overall pilot study approach were developed in a collaborative partnership with a regional supermarket pharmacy chain. They selected 2 rural pharmacies to participate in the pilot study and 2 non-intervention pharmacies to serve as comparison sites. Two interventions were pilot tested in the 2 intervention pharmacies: 1)a proactive opioid overdose counseling intervention and 2) a passive naloxone intervention. An explanatory sequential mixed-methods design was utilized to evaluate adoption, feasibility, acceptability, and appropriateness outcomes after the 3-month observation period.ResultsBetween the 2 intervention pharmacies, 130 patients received the opioid overdose counseling intervention. 44 (33.8%) were prescribed and dispensed naloxone. Zero naloxone prescriptions were written or dispensed at the comparison pharmacies. Interviews with pharmacy staff found the interventions to be feasible, acceptable, and appropriate in their settings.ConclusionThis small scale pilot study in partnership with a regional supermarket pharmacy chain had positive results with a third of patients who received the opioid overdose counseling intervention being dispensed naloxone. However, the majority of patients did not receive naloxone indicating additional revisions to the intervention components and/or implementation strategies are needed to improve the overall impact of the interventions.
| S-EPMC8813166 | biostudies-literature
Project description:PURPOSE:Opioid overdose death rates rose 36% from 2015 to 2016 in Missouri, indicating a worsening of the opioid overdose epidemic. To better understand urban and rural differences in nonfatal opioid overdoses treated in Missouri emergency departments, this paper analyzed hospital billing data from emergency departments due to opioid overdose from 2012 to 2016. METHODS:Emergency department records meeting the opioid overdose case definition were aggregated into 6 progressively rural groups using the National Center for Health Statistics (NCHS) urban-rural county classification from 2013. These data were analyzed to determine significant trends amongst and between the geographic groups. FINDINGS:Generally, the magnitude of opioid overdose morbidity decreased as levels of rurality increased, using annual percentage change as the metric of change. Over the study period, Missouri's most urban counties had significantly higher rates of opioid overdose and saw larger percentage increases in rates compared to more rural areas. Statewide, all rural-urban classifications experienced increases in heroin overdose morbidity; however, there was extreme variation in the trajectory of those increases. Heroin overdose rates were much higher in urban areas than rural areas. Conversely, rural and urban areas saw relatively similar patterns for non-heroin opioid overdoses, though overall magnitude of these increases was more modest across all geographic groups. CONCLUSIONS:The results from this analysis can help inform prioritization of strategies and resources to implement activities addressing the opioid overdose epidemic. Using a rich hospital discharge database could allow for further analysis of subpopulations to enhance personalization and customization of care.
| S-EPMC6920583 | biostudies-literature
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.
| S-EPMC6439853 | biostudies-literature