Small area Forecasting of Opioid-Related Mortality: Bayesian Spatiotemporal Dynamic Modeling approach

BACKGROUND: Opioid-related overdose mortality has remained at crisis levels across the United States, increasing 5-fold and worsened during the COVID-19 pandemic. The ability to provide forecasts of opioid-related mortality at granular geographical and temporal scales may help guide preemptive public health responses. Current forecasting models focus on prediction on a large geographical scale, such as states or counties, lacking the spatial granularity that local public health officials desire to guide policy decisions and resource allocation. OBJECTIVE: The overarching objective of our study was to develop Bayesian spatiotemporal dynamic models to predict opioid-related mortality counts and rates at temporally and geographically granular scales (ie, ZIP Code Tabulation Areas [ZCTAs]) for Massachusetts. METHODS: We obtained decedent data from the Massachusetts Registry of Vital Records and Statistics for 2005 through 2019. We developed Bayesian spatiotemporal dynamic models to predict opioid-related mortality across Massachusetts\u27 537 ZCTAs. We evaluated the prediction performance of our models using the one-year ahead approach. We investigated the potential improvement of prediction accuracy by incorporating ZCTA-level demographic and socioeconomic determinants. We identified ZCTAs with the highest predicted opioid-related mortality in terms of rates and counts and stratified them by rural and urban areas. RESULTS: Bayesian dynamic models with the full spatial and temporal dependency performed best. Inclusion of the ZCTA-level demographic and socioeconomic variables as predictors improved the prediction accuracy, but only in the model that did not account for the neighborhood-level spatial dependency of the ZCTAs. Predictions were better for urban areas than for rural areas, which were more sparsely populated. Using the best performing model and the Massachusetts opioid-related mortality data from 2005 through 2019, our models suggested a stabilizing pattern in opioid-related overdose mortality in 2020 and 2021 if there were no disruptive changes to the trends observed for 2005-2019. CONCLUSIONS: Our Bayesian spatiotemporal models focused on opioid-related overdose mortality data facilitated prediction approaches that can inform preemptive public health decision-making and resource allocation. While sparse data from rural and less populated locales typically pose special challenges in small area predictions, our dynamic Bayesian models, which maximized information borrowing across geographic areas and time points, were used to provide more accurate predictions for small areas. Such approaches can be replicated in other jurisdictions and at varying temporal and geographical levels. We encourage the formation of a modeling consortium for fatal opioid-related overdose predictions, where different modeling techniques could be ensembled to inform public health policy

Opioid overdose deaths and potentially inappropriate opioid prescribing practices (PIP): A spatial epidemiological study

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 \u3e98% of Massachusetts residents between 2011-2015, were linked in 2017 to better investigate the opioid epidemic. PIP was defined by six measures: \u3e /=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 \u3c 0.05). Large PIP clusters for \u3e /=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 \u3c 0.05). Co-prescriptions and cash payment clusters were localized and nearly identical (p \u3c 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

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality.

peer reviewedDespite advances in COVID-19 management, identifying patients evolving toward death remains challenging. To identify early predictors of mortality within 60 days of symptom onset (DSO), we performed immunovirological assessments on plasma from 279 individuals. On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain–specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation. A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA’s predictive accuracy was maintained at earlier time points, its quantitation can help us understand disease heterogeneity and identify patients who may benefit from new therapies

Alcohol or benzodiazepine co-involvement with opioid overdose deaths in the United States, 1999-2017.

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

Validating opioid use disorder diagnoses in administrative data: a commentary on existing evidence and future directions

Abstract Background A valid opioid use disorder (OUD) identification algorithm for use in administrative medical record data would enhance investigators’ ability to study consequences of OUD, OUD treatment seeking and treatment outcomes. Main body Existing studies indicate ICD-9 and ICD-10 codes for opioid abuse and dependence do not accurately measure OUD. However, critical appraisal of existing literature suggests alternative validation methods would improve the validity of OUD identification algorithms in administrative data. Chart abstraction may not be sufficient to validate OUD, and primary data collection via structured diagnostic interviews might be an ideal gold standard. Conclusion and commentary Generating valid OUD identification algorithms is critical for OUD research and quality measurement in real world health care settings

Patient Perspectives on Improving Patient-Provider Relationships and Provider Communication During Opioid Tapering.

BackgroundEfforts to reduce opioid overdose fatalities have resulted in tapering (i.e., reducing or discontinuing) opioid prescriptions despite a limited understanding of patients' experiences.ObjectiveTo explore patients' perspectives on opioid taper experiences to ultimately improve taper processes and outcomes.DesignQualitative study.ParticipantsPatients on long-term opioid therapy for chronic pain who had undergone a reduction of opioid daily prescribed dosage of ≥50% in the past 2 years in two distinct medical systems and regions.ApproachFrom 2019 to 2020, we conducted semi-structured interviews that were audio-recorded, transcribed, systematically coded, and analyzed to summarize the content and identify key themes regarding taper experiences overall and with particular attention to patient-provider relationships and provider communication during tapers.Key resultsParticipants (n=41) had lived with chronic pain for an average of 17.4 years (range, 3-36 years) and described generally adverse experiences with opioid tapers, the initiation of which was not always adequately justified or explained to them. Consequences of tapers ranged from minor to substantial and included withdrawal, mobility issues, emotional distress, exacerbated mental health symptoms, and feelings of social stigmatization for which adequate supports were typically unavailable. Narratives highlighted the consequential role of patient-provider relationships throughout taper experiences, with most participants describing significant interpersonal challenges including poor provider communication and limited patient engagement in decision making. A few participants identified qualities of providers, relationships, and communication that fostered more positive taper experiences and outcomes.ConclusionsFrom patients' perspectives, opioid tapers can produce significant physical, emotional, and social consequences, sometimes reducing trust and engagement in healthcare. Patient-provider relationships and communication influence patients' perceptions of the quality and outcomes of opioid tapers. To improve patients' experiences of opioid tapers, tapering plans should be based on individualized risk-benefit assessments and involve patient-centered approaches and improved provider communication

“I felt like I had a scarlet letter”: Recurring experiences of structural stigma surrounding opioid tapers among patients with chronic, non-cancer pain

BackgroundEfforts to address opioid-involved overdose fatalities have led to widespread implementation of various initiatives to taper (i.e., reduce or discontinue) opioid prescriptions despite a limited understanding of patients' experience.MethodsFrom 2019-2020, we recruited patients with chronic, non-cancer pain who had undergone a reduction in opioid daily dosage of ≥50 % in the past two years at Boston Medical Center or Michigan Medicine. Participants completed semi-structured interviews exploring health history, opioid use, and taper experiences. Inductive analysis, guided by theoretical conceptualizations of structural stigma, identified emergent themes.ResultsAmong 41 participants, three elements of structural stigma were identified across participants' lives. First, participants identified themselves as overlooked subjects of the U.S. opioid crisis, who experienced overprescribing, subsequent stigmatization and surveillance of opioid use (e.g., toxicology screening, "pill counts"), and various tapering initiatives. Second, during the course of pain treatment, participants felt stigmatized and invalidated by cultural norms linking chronic pain to stereotypes of acting disingenuously (e.g., "drug-seeking"). Finally, during and after tapers, institutional policies and programs further increased participants' feelings of marginalization, producing multiple unintended consequences, including reduced access to medical care and feeling "orphaned by the system."ConclusionsOpioid tapers may exacerbate the social production and burden of stigma among patients with chronic pain, especially when processes are perceived to invalidate pain, endorse stereotypes, and label previously effective, acceptable treatment as inappropriate. Findings highlight how various tapering initiatives reinforce the devalued status of people living with chronic pain while also reducing patients' wellbeing and confidence in medical systems

Prevalence of HIV preexposure prophylaxis prescribing among persons with commercial insurance and likely injection drug use.

Importance: Although HIV preexposure prophylaxis (PrEP) implementation among persons who inject drugs has been inadequate, national HIV monitoring programs do not include data on PrEP, and specific trends in PrEP use are not well understood. Objective: To estimate HIV PrEP uptake among commercially insured persons with opioid or stimulant use disorder by injection drug use (IDU) status. Design, Setting, and Participants: This cross-sectional study used deidentified data from the MarketScan Commercial Claims and Encounters Database to identify a sample of 547 709 commercially insured persons without HIV but with opioid and/or stimulant use disorder, including 110 592 with evidence of IDU between January 1, 2010, and December 31, 2019. Data were analyzed from November 1, 2020, to July 1, 2021. Persons with opioid and/or stimulant use disorder and evidence of IDU were identified through claims data. Main Outcomes and Measures: The outcome was receipt of tenofovir disoproxil fumarate and emtricitabine for PrEP as identified from filled pharmacy claims. Multivariable logistic regression was used to assess the association of demographic and clinical characteristics with receipt of PrEP. Results: The study cohort included 211 609 (28.6%) females and 336 100 (61.4%) males with a combined mean (SD) age of 34.8 (13.1) years, including 110 592 individuals with evidence of IDU. During the study period, 508 (0.09%) persons with opioid and/or stimulant use disorder, including 170 (0.15%) with evidence of IDU, received PrEP. Receipt of PrEP increased from 0.001 to 0.243 per 100 person-years from 2010 through 2019 among the entire cohort and from 0.000 to 0.295 per 100 person-years among those with IDU. In multivariable analysis, PrEP use was more likely among males (adjusted odds ratio [aOR] 8.72; 95% CI, 6.39-11.89), persons with evidence of IDU (aOR, 1.47; 95% CI, 1.21-1.79), and persons with evidence of sexual risk indications for PrEP (aOR, 23.68; 95% CI, 19.57-28.66). Conclusions and Relevance: In this cross-sectional study of commercially insured persons with opioid and/or stimulant use disorder, HIV PrEP delivery remained low, including among those with evidence of IDU. PrEP should be consistently offered alongside substance use disorder treatment and other harm reduction and HIV prevention services

Comparative effectiveness of opioid tapering or abrupt discontinuation vs no dosage change for opioid overdose or suicide for patients receiving stable long-term opioid.

Importance: Opioid dosage tapering has emerged as a strategy to reduce harms associated with long-term opioid therapy; however, evidence supporting this approach is limited. Question: For patients receiving stable long-term opioid therapy compared with a stable opioid dosage, what is the association of opioid dosage tapering or abrupt discontinuation with opioid overdose or suicide? Findings: In this comparative effectiveness study of 415 123 episodes of stable long-term opioid therapy among 199 836 individuals, opioid tapering was associated with a small absolute increase in opioid overdose or suicide compared with a stable opioid dosage. No significant difference in outcomes between abrupt discontinuation and stable opioid therapy was identified. Meaning: These findings do not support opioid dosage tapering as a strategy to reduce harms for patients receiving stable long-term opioid therapy without evidence of misuse