Dataset Information

Potentially Inappropriate Opioid Prescribing, Overdose, and Mortality in Massachusetts, 2011-2015.

ABSTRACT: BACKGROUND:Potentially inappropriate prescribing (PIP) may contribute to opioid overdose. OBJECTIVE:To examine the association between PIP and adverse events. DESIGN:Cohort study. PARTICIPANTS:Three million seventy-eight thousand thirty-four individuals age ≥ 18, without disseminated cancer, who received prescription opioids between 2011 and 2015. MAIN MEASURES:We defined PIP as (a) morphine equivalent dose ≥ 100 mg/day in ≥ 3 months; (b) overlapping opioid and benzodiazepine prescriptions in ≥ 3 months; (c) ≥ 4 opioid prescribers in any quarter; (d) ≥ 4 opioid-dispensing pharmacies in any quarter; (e) cash purchase of prescription opioids on ≥ 3 occasions; and (f) receipt of opioids in 3 consecutive months without a documented pain diagnosis. We used Cox proportional hazards models to identify PIP practices associated with non-fatal opioid overdose, fatal opioid overdose, and all-cause mortality, controlling for covariates. KEY RESULTS:All six types of PIP were associated with higher adjusted hazard for all-cause mortality, four of six with non-fatal overdose, and five of six with fatal overdose. Lacking a documented pain diagnosis was associated with non-fatal overdose (adjusted hazard ratio [AHR] 2.21, 95% confidence interval [CI] 2.02-2.41), as was high-dose opioids (AHR 1.68, 95% CI 1.59-1.76). Co-prescription of benzodiazepines was associated with fatal overdose (AHR 4.23, 95% CI 3.85-4.65). High-dose opioids were associated with all-cause mortality (AHR 2.18, 95% CI 2.14-2.23), as was lacking a documented pain diagnosis (AHR 2.05, 95% CI 2.01-2.09). Compared to those who received opioids without PIP, the hazard for fatal opioid overdose with one, two, three, and ≥ four PIP subtypes were 4.24, 7.05, 10.28, and 12.99 (test of linear trend, p < 0.001). CONCLUSIONS:PIP was associated with higher hazard for all-cause mortality, fatal overdose, and non-fatal overdose. Our study implies the possibility of creating a risk score incorporating multiple PIP subtypes, which could be displayed to prescribers in real time.

SUBMITTER: Rose AJ

PROVIDER: S-EPMC6109008 | biostudies-other | 2018 Sep

REPOSITORIES: biostudies-other

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Potentially Inappropriate Opioid Prescribing, Overdose, and Mortality in Massachusetts, 2011-2015.

Rose Adam J AJ Bernson Dana D Chui Kenneth Kwan Ho KKH Land Thomas T Walley Alexander Y AY LaRochelle Marc R MR Stein Bradley D BD Stopka Thomas J TJ

Journal of general internal medicine 20180614 9

<h4>Background</h4>Potentially inappropriate prescribing (PIP) may contribute to opioid overdose.<h4>Objective</h4>To examine the association between PIP and adverse events.<h4>Design</h4>Cohort study.<h4>Participants</h4>Three million seventy-eight thousand thirty-four individuals age ≥ 18, without disseminated cancer, who received prescription opioids between 2011 and 2015.<h4>Main measures</h4>We defined PIP as (a) morphine equivalent dose ≥ 100 mg/day in ≥ 3 months; (b) overlapping opioid an ...[more]

PMID: 29948815

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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:Opioid-tolerant only (OTO) medications, such as transmucosal immediate-release fentanyl products and certain extended-release opioid analgesics, require prior opioid tolerance for safe use, as patients without tolerance may be at increased risk of overdose. Studies using insurance claims have found that many patients initiating these medications do not appear to be opioid tolerant. Objectives:To measure prevalence of opioid tolerance in patients initiating OTO medications and to determine whether linked electronic health record (EHR) data contribute evidence of opioid tolerance not found in insurance claims data. Design, Setting, and Participants:This retrospective cohort study used a national database of deidentified longitudinal health information, including medical and pharmacy claims, insurance enrollment, and EHR data, from January 1, 2007, to December 31, 2016. Data included 131?756 US residents with at least 183 days of continuous enrollment in commercial or Medicare Advantage insurance (including medical and pharmacy benefits) who had received an OTO medication and who had no inpatient stays in the 30 days prior to starting an OTO medication; of these, 20?044 individuals had linked EHR data within the prior 183 days. Data were analyzed from July 1, 2017, to August 31, 2018. Exposures:Initiating an OTO medication. Main Outcomes and Measures:Prior opioid tolerance demonstrated through pharmacy fills or EHR data on prescriptions written. Results:Among 153?385 OTO use episodes identified, 89?029 (58.0%) occurred among women, 62?900 (41.0%) occurred among patients with Medicare Advantage insurance, 39?394 (25.7%) occurred in the Midwest, 17?366 (11.3%) occurred in the Northeast, 73?316 (47.8%) occurred in the South, and 23?309 (15.2%) occurred in the West. Less than half of use episodes (73?117 episodes [47.7%]) involved patients with evidence in claims data of opioid tolerance prior to initiating therapy with an OTO medication, including 31?392 of 101?676 episodes (30.9%) involving transdermal fentanyl, 1561 of 2440 episodes (64.0%) involving transmucosal fentanyl, 36?596 of 43?559 episodes (84.0%) involving extended-release oxycodone, and 3568 of 5710 episodes (62.5%) involving extended-release hydromorphone. Among 20?044 OTO use episodes with linked EHR and claims data, less than 1% of OTO episodes identified in claims had evidence of opioid tolerance in structured EHR data that was not present in claims data (108 episodes [0.5%]). After limiting the sample to OTO episodes identified in claims with a matching OTO prescription within 14 days in the structured EHR data, only 40 of 939 episodes (4.0%) occurred among patients with evidence of tolerance that was not present in claims data. Conclusions and Relevance:This cohort study found that most patients initiating OTO medications did not have evidence of prior opioid tolerance, suggesting they were at increased risk of opioid-related harms, including fatal overdose. Data from EHRs did not contribute substantial additional evidence of opioid tolerance beyond the data found in prescription claims. Future research is needed to understand the clinical rationale behind these observed prescribing patterns and to quantify the risk of harm to patients associated with potentially inappropriate prescribing.

Dataset Information

Potentially Inappropriate Opioid Prescribing, Overdose, and Mortality in Massachusetts, 2011-2015.

Publications

Potentially Inappropriate Opioid Prescribing, Overdose, and Mortality in Massachusetts, 2011-2015.

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