INTRODUCTION: Opioid 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. METHODS: Sixteen 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. RESULTS: More 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. CONCLUSIONS: Overdose 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.

BACKGROUND: Opioid-related overdoses and deaths among adolescents in the United States continue to increase, but little is known about adolescents who experience opioid-related non-fatal overdose (NFOD). Our objective was to describe (1) the characteristics of adolescents aged 11-17 who experienced NFOD and (2) their receipt of medications for opioid use disorder (MOUD) in the 12 months following NFOD, compared with adults. METHODS: We created a retrospective cohort using six Massachusetts state agency datasets linked at the individual level, with information on 98% of state residents. Individuals entered the cohort if they experienced NFOD between January 1, 2012 and December 31, 2014. We compared adolescents to adults experiencing NFOD, examining individual characteristics and receipt of medications for opioid use disorder (MOUD)-methadone, buprenorphine, or naltrexone. RESULTS: Among 22,506 individuals who experienced NFOD during the study period, 195 (0.9%) were aged 11-17. Fifty-two percent (102/195) of adolescents were female, whereas only 38% of adults were female (P < 0.001). In the year prior to NFOD, 11% (21/195) of adolescents received a prescription opioid, compared to 43% of adults (P < 0.001), and < 5% ( < 10/195) received any MOUD compared to 23% of adults (P < 0.001). In the 12 months after NFOD, only 8% (15/195) of adolescents received MOUD, compared to 29% of adults. CONCLUSION: Among individuals experiencing NFOD, adolescents were more likely to be female and less likely to have been prescribed opioids in the year prior. Few adolescents received MOUD before or after NFOD. Non-fatal overdose is a missed opportunity for starting evidence-based treatment in adolescents.

OBJECTIVES: To estimate the annual prevalence of opioid use disorder (OUD) in Massachusetts from 2011 to 2015. METHODS: We performed a multisample stratified capture-recapture analysis to estimate OUD prevalence in Massachusetts. Individuals identified from 6 administrative databases for 2011 to 2012 and 7 databases for 2013 to 2015 were linked at the individual level and included in the analysis. Individuals were stratified by age group, sex, and county of residence. RESULTS: The OUD prevalence in Massachusetts among people aged 11 years or older was 2.72% in 2011 and 2.87% in 2012. Between 2013 and 2015, the prevalence increased from 3.87% to 4.60%. The greatest increase in prevalence was observed among those in the youngest age group (11-25 years), a 76% increase from 2011 to 2012 and a 42% increase from 2013 to 2015. CONCLUSIONS: In Massachusetts, the OUD prevalence was 4.6% among people 11 years or older in 2015. The number of individuals with OUD is likely increasing, particularly among young people.

OBJECTIVES: To examine the effect of age on the likelihood of PIP of opioids and the effect of PIP on adverse outcomes. DESIGN: Retrospective cohort study. SETTING: Data from multiple state agencies in Massachusetts from 2011 to 2015. PARTICIPANTS: Adult Massachusetts residents (N=3,078,163) who received at least one prescription opioid during the study period; approximately half (1,589,365) aged 50 and older. MEASUREMENTS: We measured exposure to 5 types of PIP: high-dose opioids, coprescription with benzodiazepines, multiple opioid prescribers, multiple opioid pharmacies, and continuous opioid therapy without a pain diagnosis. We examined 3 adverse outcomes: nonfatal opioid overdose, fatal opioid overdose, and all-cause mortality. RESULTS: The rate of any PIP increased with age, from 2% of individuals age 18 to 29 to 14% of those aged 50 and older. Older adults also had higher rates of exposure to 2 or more different types of PIP (40-49, 2.5%; 50-69, 5%; > /=70, 4%). Of covariates assessed, older age was the greatest predictor of PIP. In analyses stratified according to age, any PIP and specific types of PIP were associated with nonfatal overdose, fatal overdose, and all-cause mortality in younger and older adults. CONCLUSION: Older adults are more likely to be exposed to PIP, which increases their risk of adverse events. Strategies to reduce exposure to PIP and to improve outcomes in those already exposed will be instrumental to addressing the opioid crisis in older adults.