Sociodemographic Characteristics of Adverse Event Reporting in the USA: An Ecologic Study.

INTRODUCTION: The Food and Drug Administration Adverse Event Reporting System (FAERS) is a vital source of new drug safety information, but whether adverse event (AE) information collected from these systems adequately captures experiences of the overall United States (US) population is unknown. OBJECTIVE: To examine determinants of consumer AE reporting in the USA. METHODS: Five-year AE reporting rate per 100,000 residents per US county were calculated, mapped, and quartiled for AE reports received directly from consumers between 2011 and 2015. Associations between county-level sociodemographic factors obtained from County Health Rankings and AE reporting rates were evaluated using negative binomial regression. RESULTS: Reporting rates were variable across US counties with > 17.6 reports versus ≤ 5.5 reports/100,000 residents in the highest and lowest reporting quartile, respectively. Controlling for drug utilization, counties with higher reporting rates had higher proportions of individuals age ≥ 65 years (e.g., 2.4% reporting increase per 1% increase in individuals age > 65, incidence rate ratio (IRR): 1.024, 95% confidence interval (CI): 1.017-1.030), higher proportions of females (IRR: 1.027, 95% CI 1.012-1.043), uninsured (IRR: 1.009, 95% CI 1.005-1.013), higher median log household incomes (IRR: 1.897, 95% CI 1.644-2.189) and more mental health providers per 100,000 residents (IRR: 1.003, 95% CI 1.001-1.004). Lower reporting was observed in counties with higher proportions of individuals age ≤ 18 years (IRR: 0.966, 95% CI 0.959-0.974), American Indian or Alaska Native individuals (IRR: 0.991, 95% CI 0.986-0.996), individuals not proficient in English (IRR: 0.978, 95% CI 0.965-0.991), and individuals residing in rural areas within a county (IRR: 0.998, 95% CI 0.997-0.998). CONCLUSIONS: Observed variations in consumer AE reporting may be related to sociodemographic factors and healthcare access. Because these factors may also correspond to AE susceptibility, voluntary AE reporting systems may be suboptimal for capturing emerging drug safety concerns among more vulnerable populations.

Evidence of housing instability identified by addresses, clinical notes, and diagnostic codes in a real-world population with substance use disorders.

Introduction: Housing instability is a social determinant of health associated with multiple negative health outcomes including substance use disorders (SUDs). Real-world evidence of housing instability is needed to improve translational research on populations with SUDs. Methods: We identified evidence of housing instability by leveraging structured diagnosis codes and unstructured clinical data from electronic health records of 20,556 patients from 2017 to 2021. We applied natural language processing with named-entity recognition and pattern matching to unstructured clinical notes with free-text documentation. Additionally, we analyzed semi-structured addresses containing explicit or implicit housing-related labels. We assessed agreement on identification methods by having three experts review of 300 records. Results: Diagnostic codes only identified 58.5% of the population identifiable as having housing instability, whereas 41.5% are identifiable from addresses only (7.1%), clinical notes only (30.4%), or both (4.0%). Reviewers unanimously agreed on 79.7% of cases reviewed; a Fleiss' Kappa score of 0.35 suggested fair agreement yet emphasized the difficulty of analyzing patients having ambiguous housing situations. Among those with poisoning episodes related to stimulants or opioids, diagnosis codes were only able to identify 63.9% of those with housing instability. Conclusions: All three data sources yield valid evidence of housing instability; each has their own inherent practical use and limitations. Translational researchers requiring comprehensive real-world evidence of housing instability should optimize and implement use of structured and unstructured data. Understanding the role of housing instability and temporary housing facilities is salient in populations with SUDs.

Xylazine-involved fatal overdoses and localized geographic clustering: Cook County, IL, 2019-2022.

BACKGROUND: Xylazine, a veterinary analgesic sedative, is circulating in the illicit drug markets of at least 23 states including Illinois. We conducted a geographic analysis to better identify the spatial distribution of xylazine-involved fatal overdoses in Cook County, IL. METHODS: Cook County Medical Examiner Office's (CCMEO) publicly available data was used to identify xylazine-involved fatal overdoses from January 1, 2019, to June 30, 2022. Xylazine-positive (cases) to xylazine-negative groups with drug mixtures involving fentanyl, alcohol and stimulants (controls) were matched on age, race, sex, and year of death. Ripley's K-function was used to examine the likelihood of case clustering compared to controls with the Bernoulli spatial scan deployed to identify specific geographic clusters. RESULTS: Almost all (94.4%) xylazine-positive overdoses contained fentanyl. Using coordinate-based matching, we found that approximately 3% of xylazine overdose incidents were co-located with other overdoses. Xylazine cases clustered to from 0 to 16.1 miles (max=10.6 miles). Results of the Bernoulli spatial scan varied by control group with two high-risk clusters found relative to alcohol and stimulants and a low-risk cluster relative to fentanyl. Differences in co-occurring drugs were found between xylazine and fentanyl groups like the absolute number of drugs (4.6v 3.4, p<0.0001) and fentanyl analog types. CONCLUSIONS: Xylazine fatal overdose incident locations exhibited localized clustering relative to fentanyl overdoses but clusters were not precisely detected at these scales. Even so, our results, especially relative to repeat overdose micro "hot spots", offer insight on targeting harm reduction and other services at the neighborhood-level.

Balancing Data Provision and Data Protection: A Natural Experiment With HIV and Syphilis Surveillance Data in the United States.

BACKGROUND: Public release of health data typically requires statistical disclosure limitation (SDL), but scant research demonstrates how real-world SDL affects data usability. Recent changes of federal data re-release policy allow a pseudo-counterfactual comparison of HIV and syphilis data suppression rules. METHODS: Incident counts (2019) of HIV and syphilis infections by county for Black and White populations were downloaded from the US Centers for Disease Control and Prevention. We quantified and compared suppression status by disease and county between Black and White populations and calculated incident rate ratios for counties with statistically reliable counts. RESULTS: Approximately 50% of US counties have incident HIV counts suppressed for Black and White populations compared with only 5% for syphilis, which has an alternative suppression strategy. The county population sizes protected by a numerator disclosure rule (<4) spans several orders of magnitude. Calculations of incident rate ratios, used as a measure of health disparity, were impossible in the 220 counties most susceptible to an HIV outbreak. CONCLUSIONS: Balancing tradeoffs between providing and protecting data are key to health initiatives worldwide. We encourage an increase in empirical research on the impact of SDL, especially in the context of health disparities, and recommend new approaches to avoid the "oppression of data suppression."

Prescribing Characteristics of Octreotide Immediate-Release and Long-Acting Release in Patients with Neuroendocrine Tumors.

BACKGROUND: Treatment recommendations for patients with neuroendocrine tumors (NETs) include the use of octreotide long-acting release (LAR) for long-term therapy and immediate-release (IR) as rescue therapy to control the breakthrough symptoms of carcinoid syndrome (CS). High doses of LAR are commonly used in clinical practice. This study aimed to evaluate the real-world utilization of LAR and preceding IR use at the prescription and patient levels. METHODS: We used an administrative claims database (2009-2018) containing privately insured enrollees. We calculated the normalized LAR dose from pharmacy claims and the initial mean IR daily dose at the prescription level. At the patient level, we conducted a retrospective cohort study that included patients continuously enrolled with ≥1 pharmacy claim of LAR and evaluated the frequency and the clinical reason for dose escalation of LAR. The definition of the above-label maximum dose of LAR was ≥30 mg/4 weeks. RESULTS: Nineteen percent of LAR prescriptions had an above-label maximum dose. Only 7% of LAR prescriptions had preceding IR use. There were 386 patients with NETs or CS vs. 570 with an unknown diagnosis. Comparing patients with NETs or CS to those with an unknown diagnosis, 22.3% vs. 11.0 % experienced dose escalations and 29.0% vs. 26.6% had IR use before dose escalation, respectively. LAR dose escalation occurred in 50.9% vs. 39.2% for symptom control, 12.3% vs. 7.1% for tumor progression control, and 16.6% vs. 6.0% for both reasons in NETs/CS and unknown groups, respectively. CONCLUSION: Octreotide LAR dosing above the label-maximum dose is common and IR rescue dosing appears to be underutilized.

The prevalence of opioid use disorder in Kentucky's counties: A two-year multi-sample capture-recapture analysis.

BACKGROUND: Kentucky has one of the highest opioid overdose mortality rates in the United States. Accurate estimates of people with opioid use disorder (OUD) are critical to plan for the scope of interventions required to reduce overdose and opioid misuse. Commonly used household surveys are known to underestimate OUD at the state-level and do not provide county-level estimates. METHODS: We performed a multi-sample capture-recapture analysis to estimate OUD prevalence in Kentucky in 2018 and 2019. We utilized four statewide datasets that were linked at the individual level: 1) Registry of Vital Statistics, 2) Emergency Medical Services (EMS), 3) Kentucky's Prescription Drug Monitoring Program (PDMP), and 4) Kentucky Medicaid. We included persons aged 18-64 years who resided in Kentucky between 2018 and 2019. We identified individuals with administrative data consistent with OUD in each of the datasets, including a fatal opioid-involved overdose (Vital Statistics), EMS runs for suspected opioid overdose, receipt of buprenorphine for OUD treatment (PDMP), or Medicaid claims for OUD. Observed and estimated counts of OUD cases and prevalence of OUD among the adult population in Kentucky. RESULTS: The estimated statewide OUD prevalence was 5.5 % and 5.9 % for 2018 and 2019, respectively, ranging from 1.3 % to 17.7 % across Kentucky counties. As expected, counties with the highest OUD rates were Appalachian counties (eastern area) of the state. CONCLUSIONS: Our analysis reveals a substantially larger proportion of KY residents have OUD than previously estimated. Our approach offers a model for states needing county-level estimates of OUD.

The Impact of Naloxone Coprescribing Mandates on Opioid-Involved Overdose Deaths.

INTRODUCTION: Since 2017, a total of 10 states have mandated naloxone coprescribing intended to prevent fatal opioid overdoses. This study aims to assess the association between naloxone coprescribing/offering mandates and opioid-involved overdose deaths on the basis of the opioid type. METHODS: Data on overdose deaths from 1999 to 2020 came from the National Center for Health Statistics CDC WONDER Online Database. This study examined deaths stratified by illicit/synthetic opioids and prescription/treatment opioids. Difference-in-difference negative binomial regression models estimated average marginal effects and 95% CIs. Covariates included opioid dispensing rate, Good Samaritan law, pharmacy-based naloxone access law, mandatory use of prescription drug monitoring program, and recreational cannabis dispensaries. Data collection and analysis were conducted in 2022. RESULTS: Ten states implemented naloxone coprescribing/offering mandates during the period. Coprescribing/offering mandates significantly reduced the number of prescription/treatment overdose deaths by 8.61 per state per quarter (95% CI= -15.13, -2.09), a 16% reduction from the counterfactual estimates. Coprescribing/offering mandates did not significantly impact illicit/synthetic overdose deaths (average marginal effect=0.32; 95% CI= -18.27, 18.91). CONCLUSIONS: Coprescribing/offering mandates prevent overdose deaths for its target population, individuals using prescription/treatment opioids. These mandates do not appear to impact populations using illicit/synthetic opioids; thus, expanded efforts are needed to reach these individuals.

Medicaid expansion and access to naloxone in metropolitan and nonmetropolitan areas.

PURPOSE: The opioid crisis remains a major public health concern in the United States. Naloxone is used to reverse opioid overdoses. This study examined Medicaid expansion on naloxone prescriptions in retail pharmacies in metropolitan (metro) and nonmetropolitan (nonmetro) areas (2011-2017). METHODS: We used population average models to evaluate the association of Medicaid expansion at the state level on the number of naloxone prescriptions dispensed and the percentage paid by Medicaid, including adjustment for opioid-related and state-level policy covariates. Difference-in-difference modeling was performed as a sensitivity analysis. FINDINGS: States that expanded Medicaid had higher unadjusted naloxone dispensing rates and Medicaid-paid percentage of naloxone in metro and nonmetro areas. Medicaid expansion was not associated with the number of naloxone dispensed in either metro (adjusted rate ratio (ARR) = 1.26, 95% CI: [0.80, 1.97]) or nonmetro (ARR = 0.67, 95% CI: [0.37, 1.19]) areas after covariate adjustment. In metro areas, Medicaid expansion was associated with a significant increase of 3.86 percentage points (95% CI: [0.09, 7.63]) in the Medicaid-paid percentage of naloxone dispensing compared to nonexpansion states, but this association was not significant in nonmetro areas. There was also a significant time by Medicaid expansion interaction on the Medicaid-paid percentage of naloxone dispensed (metro: estimate = 0.74, 95% CI: [0.36, 1.12]; nonmetro: estimate = 0.68, 95% CI: [0.17, 1.18]). CONCLUSIONS: Medicaid expansion increased naloxone access by increasing the Medicaid-paid percentage of naloxone prescriptions in metro areas. States with Medicaid expansion had a faster rate of increase in the Medicaid-paid percentage of naloxone than states without Medicaid expansion in nonmetro areas.

Substance use disorders and social determinants of health from electronic medical records obtained during Kentucky's "triple wave".

Social determinants of health (SDOH) play a critical role in the risk of harmful drug use. Examining SDOH as a means of differentiating populations with multiple co-occurring substance use disorders (SUDs) is particularly salient in the era of prevalent opioid and stimulant use known as the "Third Wave". This study uses electronic medical records (EMRs) from a safety net hospital system from 14,032 patients in Kentucky from 2017 to 2019 in order to 1) define three types of SUD cohorts with shared/unique risk factors, 2) identify patients with unstable housing using novel methods for EMRs and 3) link patients to their residential neighborhood to obtain quantitative perspective on social vulnerability. We identified patients in three cohorts with statistically significant unique risk factors that included race, biological sex, insurance type, smoking status, and urban/rural residential location. Adjusting for these variables, we found a statistically significant, increasing risk gradient for patients experiencing unstable housing by cohort type: opioid-only (n = 7385, reference), stimulant-only (n = 4794, odds ratio (aOR) 1.86 95 % confidence interval (CI): 1.66-2.09), and co-diagnosed (n = 1853, aOR = 2.75, 95 % CI: 2.39 to 3.16). At the neighborhood-level, we used 8 different measures of social vulnerability and found that, for the most part, increasing proportions of patients with stimulant use living in a census tract was associated with more social vulnerability. Our study identifies potentially modifiable factors that can be tailored by substance type and demonstrates robust use of EMRs to meet national goals of enhancing research on social determinants of health.

The impact of California wildfires on patient access to prescription opioids.

BACKGROUND: Patients on long-term opioid therapy are particularly vulnerable to disruptions in medication access, especially during traumatic and chaotic events such as wildfires and other natural disasters. OBJECTIVES: To determine whether past highly destructive California wildfires were associated with disrupted access to prescription opioids for patients receiving long-term, and therefore physically dependent on, opioid medications. METHODS: Using California prescription drug monitoring program data, this retrospective study selected patients with long-term prescription opioid use episodes residing in ZIP code tabulation areas impacted by either the Camp Fire or Tubbs Fire. Autoregressive integrated moving average time series models were fit to pre-fire data to forecast post-fire expected values and then compared with observed post-fire data, specifically for weekly proportions of long-term episodes with early fills, late fills, changes in patients' prescriber and pharmacy, and fills within a different ZIP code tabulation area than the patient's residence. RESULTS: After the Camp Fire, there were significant spikes in the proportions of early fills (peak at 56% of total, week 1 after fire), late fills (peak at 29%, week 6), and immediate significant increases in prescriber (peak at 37%, week 3) and pharmacy changes (peak at 71%, week 1) in high-impact ZIP code tabulation areas. Low-impact ZIP code tabulation areas experienced no similar disruptions. Disruptions due to the Tubbs Fire were far less severe. CONCLUSION: Access to prescription opioids was greatly disrupted for patients living in areas most impacted by the Camp Fire. Future research should explore effectiveness of current state and federal controlled substance prescribing policies to determine what improvements are needed to minimize disruptions in medication access due to wildfires and other natural disasters.

Dosing profiles of concurrent opioid and benzodiazepine use associated with overdose risk among US Medicare beneficiaries: group-based multi-trajectory models.

BACKGROUND AND AIMS: One-third of opioid (OPI) overdose deaths involve concurrent benzodiazepine (BZD) use. Little is known about concurrent opioid and benzodiazepine use (OPI-BZD) most associated with overdose risk. We aimed to examine associations between OPI-BZD dose and duration trajectories, and subsequent OPI or BZD overdose in US Medicare. DESIGN: Retrospective cohort study. SETTING: US Medicare. PARTICIPANTS: Using a 5% national Medicare data sample (2013-16) of fee-for-service beneficiaries without cancer initiating OPI prescriptions, we identified 37 879 beneficiaries (age ≥ 65 = 59.3%, female = 71.9%, white = 87.6%, having OPI overdose = 0.3%). MEASUREMENTS: During the 6 months following OPI initiation (i.e. trajectory period), we identified OPI-BZD dose and duration patterns using group-based multi-trajectory models, based on average daily morphine milligram equivalents (MME) for OPIs and diazepam milligram equivalents (DME) for BZDs. To label dose levels in each trajectory, we defined OPI use as very low (< 25 MME), low (25-50 MME), moderate (51-90 MME), high (91-150 MME) and very high (>150 MME) dose. Similarly, we defined BZD use as very low (< 10 DME), low (10-20 DME), moderate (21-40 DME), high (41-60 DME) and very high (> 60 DME) dose. Our primary analysis was to estimate the risk of time to first hospital or emergency department visit for OPI overdose within 6 months following the trajectory period using inverse probability of treatment-weighted Cox proportional hazards models. FINDINGS: We identified nine distinct OPI-BZD trajectories: group A: very low OPI (early discontinuation)-very low declining BZD (n = 10 598; 28.0% of the cohort); B: very low OPI (early discontinuation)-very low stable BZD (n = 4923; 13.0%); C: very low OPI (early discontinuation)-medium BZD (n = 4997; 13.2%); D: low OPI-low BZD (n = 5083; 13.4%); E: low OPI-high BZD (n = 3906; 10.3%); F: medium OPI-low BZD (n = 3948; 10.4%); G: very high OPI-high BZD (n = 1371; 3.6%); H: very high OPI-very high BZD (n = 957; 2.5%); and I: very high OPI-low BZD (n = 2096; 5.5%). Compared with group A, five trajectories (32.3% of the study cohort) were associated with increased 6-month OPI overdose risks: E: low OPI-high BZD [hazard ratio (HR) = 3.27, 95% confidence interval (CI) = 1.61-6.63]; F: medium OPI-low BZD (HR = 4.04, 95% CI = 2.06-7.95); G: very high OPI-high BZD (HR = 6.98, 95% CI = 3.11-15.64); H: very high OPI-very high BZD (HR = 4.41, 95% CI = 1.51-12.85); and I: very high OPI-low BZD (HR = 6.50, 95% CI = 3.15-13.42). CONCLUSIONS: Patterns of concurrent opioid and benzodiazepine use most associated with overdose risk among fee-for-service US Medicare beneficiaries initiating opioid prescriptions include very high-dose opioid use (MME > 150), high-dose benzodiazepine use (DME > 40) or medium-dose opioid with low-dose benzodiazepine use.

Frequency and Types of Healthcare Encounters in the Week Preceding a Sepsis Hospitalization: A Systematic Review.

OBJECTIVES: Early recognition and treatment are critical to improving sepsis outcomes. We sought to identify the frequency and types of encounters that patients have with the healthcare system in the week prior to a sepsis hospitalization. DATA SOURCES: PubMed, Cumulative Index to Nursing and Allied Health Literature, Scopus, and the Cochrane Library. STUDY SELECTION: Observational cohort studies of patients hospitalized with sepsis or septic shock that were assessed for an outpatient or emergency department encounter with the healthcare system in the week prior to hospital admission. DATA EXTRACTION: The primary outcome was the proportion of patients with a healthcare encounter in the time period assessed (up to 1 week) prior to a hospitalization with sepsis. DATA SYNTHESIS: Six retrospective observational studies encompassing 6,785,728 sepsis admissions were included for evaluation, ranging from a 263-patient single-center cohort to a large database evaluating 6,731,827 sepsis admissions. The average (unweighted) proportion of patients having an encounter with the healthcare system in the week prior to a sepsis hospitalization was 32.7% and ranged from 10.3% to 52.9%. These encounters commonly involved presentation or potential symptoms of infectious diseases, antibiotic prescriptions, and appeared to increase in frequency closer to a sepsis hospitalization admission. No consistent factors were identified that distinguished a healthcare encounter as more or less likely to precede a sepsis hospitalization in the subsequent week. CONCLUSIONS: Patients that present to the hospital with sepsis are frequently evaluated in the healthcare system in the week prior to admission. Further research is necessary to understand if these encounters offer earlier opportunities for intervention to prevent the transition from infection to sepsis, whether they merely reflect the comorbidities of sepsis patients with a high baseline rate of healthcare encounters, or the declining trajectory of a patient's overall health in response to infection.

geoPIPE: Geospatial Pipeline for Enhancing Open Data for Substance Use Disorders Research.

We present our open-source pipeline for quickly enhancing open data sets with research-focused expansions and show its effectiveness on a cornerstone open data set released by the Cook County government in Illinois. The City of Chicago and Cook County were both early adopters of open data portals and have made a wide variety of data available to the public; we focus on the medical examiner case archive which provides information about deaths recorded by Cook County's Office of the Medical Examiner, including overdoses invaluable to substance use disorder research. Our pipeline derives key variables from open data and links to other publicly available data sets in support of accelerating translational research on substance use disorders. Our methods apply to location-based analyses of overdoses in general and, as an example, we highlight their impact on opioid research. We provide our pipeline as open-source software to act as open infrastructure for open data to help fill the gap between data release and data use.

Opioid Overdoses Increase at Home During the COVID-19 Stay-At-Home Order Period in Cook County, Illinois.

Introduction: Stay-at-home orders during the COVID-19 pandemic decreased population mobility to reduce SARS-CoV-2 infection rates. We empirically tested the hypothesis that this public health measure was associated with a higher likelihood of opioid- and stimulant-involved deaths occurring in homes located in Cook County, Illinois. Methods: The stay-at-home period was from March 21, 2020 to May 30, 2020. We analyzed overdose data from the Cook County Medical Examiner's Office using a death location description from case investigations categorized as home, medical, motel, scene, and other. Two groups of decedents were defined as either having an opioid or stimulant listed in the primary cause of death field. We modeled a weekly time series to detect changes in deaths (number) and trends during segmented time periods. Chi-square or Fisher's exact and adjusted logistic regression was used for testing the differences between the stay-at-home and a 13-week preceding period. Results: There were 4,169 and 2,012 opioid- and stimulant-involved deaths, respectively, from 2018 to 2020. Both groups were demographically similar: 75% male, 52% White, and aged 45 years (mean). In the 13 weeks before stay-at-home orders, 51% of opioid-involved deaths occurred in homes, which increased to 59% (p<0.0001) during the 10 weeks of the order and decreased back to 51% in the 18 weeks after the order expired. For stimulant-involved deaths, 51% were residential immediately before the orders, with a nonsignificant increase to 52% during the stay-at-home period. Before the pandemic, there were 20 deaths/week, increasing to 37 deaths/week (p<0.0001) during stay-at-home enactment. Deaths involving fentanyl among the opioid-involved group increased from 76% to 89%, whereas those involving heroin decreased from 55% to 37%. The adjusted OR for opioid-involved fatal overdoses occurring at home during this period compared with that occurring the 13 weeks before was 1.37 (95% CI=1.05, 1.79). Conclusions: The likelihood of a death occurring at home, especially for people using opioids, increased during the stay-at-home order period. Findings have implications for mitigating overdose risks during social isolation.

Defining "Doctor Shopping" with Dispensing Data: A Scoping Review.

BACKGROUND: "Doctor shopping" typically refers to patients that seek controlled substance prescriptions from multiple providers with the presumed intent to obtain these medications for non-medical use and/or diversion. The purpose of this scoping review is to document and examine the criteria used to identify "doctor shopping" from dispensing data in the United States. METHODS: A scoping review was conducted on "doctor shopping" or analogous terminology from January 1, 2000, through December 31, 2020, using the Web of Science Core Collection (seven citation indexes). Our search was limited to the United States only, English-language, peer-reviewed and US federal government studies. Studies without explicit "doctor shopping" criteria were excluded. Key components of these criteria included the number of prescribers and dispensers, dispensing period, and drug class (e.g., opioids). RESULTS: Of 9,845 records identified, 95 articles met the inclusion criteria and our pool of studies ranged from years 2003 to 2020. The most common threshold-based or count definition was (≥4 Prescribers [P] AND ≥4 Dispensers [D]) (n = 12). Thirty-three studies used a 365-day detection window. Opioids alone were studied most commonly (n = 69), followed by benzodiazepines and stimulants (n = 5 and n = 2, respectively). Only 39 (41%) studies provided specific drug lists with active ingredients. CONCLUSION: Relatively simple P x D criteria for identifying "doctor shopping" are still the dominant paradigm with the need for ongoing validation. The value of P x D criteria may change through time with more diverse methods applied to dispensing data emerging.

Attitudes toward pharmacy-based HCV/HIV testing among people who use drugs in rural Kentucky.

PURPOSE: Rural areas of the United States have experienced outbreaks of human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections among people who use drugs (PWUD). Pharmacy-based interventions may play a crucial role in prevention and entry into care, especially when traditional health care access is limited. The willingness of rural PWUD to use pharmacies for HIV/HCV-related services remains unknown. The purpose of this study was to describe the factors associated with the perceived likelihood of participating in free pharmacy-based HIV and HCV testing among PWUD living in rural Kentucky. METHODS: Baseline data from the CARE2HOPE study in five Appalachian counties in eastern Kentucky were used. Participants were recruited using respondent-driven sampling and completed interviewer-administered surveys. Guided by the Andersen and Newman Framework of Health Services Utilization, we examined distributions and correlates of items regarding willingness to participate in free pharmacy-based HIV/HCV testing using logistic regression. Analyses included individuals who reported being HIV (N = 304) or HCV (N = 185) negative. FINDINGS: Seventy-five percent of PWUD reported being "very likely" to participate in free pharmacy-based HIV testing and 80% for HCV testing. Two factors were associated with being less willing to participate in free HIV testing: PWUD who previously tested for HIV (OR: 0.47, CI: 0.25-0.88) and PWUD who obtained a high school diploma or equivalent compared to those who completed less (OR: 0.50, CI: 0.26-0.99). CONCLUSION: Free pharmacy-based HIV and HCV testing was invariably acceptable among most of the rural PWUD in our sample, suggesting that pharmacies might be acceptable testing venues for this population.

Predictors of chronic opioid therapy in Medicaid beneficiaries with HIV who initiated antiretroviral therapy.

The factors associated with chronic opioid therapy (COT) in patients with HIV is understudied. Using Medicaid data (2002-2009), this retrospective cohort study examines COT in beneficiaries with HIV who initiated standard combination anti-retroviral therapy (cART). We used generalized estimating equations on logistic regression models with backward selection to identify significant predictors of COT initiation. COT was initiated among 1014 out of 9615 beneficiaries with HIV (male: 10.4%; female: 10.7%). Those with older age, any malignancy, Hepatitis C infection, back pain, arthritis, neuropathy pain, substance use disorder, polypharmacy, (use of) benzodiazepines, gabapentinoids, antidepressants, and prior opioid therapies were positively associated with COT. In sex-stratified analyses, multiple predictors were shared between male and female beneficiaries; however, chronic obstructive pulmonary disease, liver disease, any malignancy, and antipsychotic therapy were unique to female beneficiaries. Comorbidities and polypharmacy were important predictors of COT in Medicaid beneficiaries with HIV who initiated cART.

Inches, Centimeters, and Yards: Overlooked Definition Choices Inhibit Interpretation of Morphine Equivalence.

OBJECTIVE: Morphine-standardized doses are used in clinical practice and research to account for molecular potency. Ninety milligrams of morphine equivalents (MME) per day are considered a "high dose" risk threshold in guidelines, laws, and by payers. Although ubiquitously cited, the "CDC definition" of daily MME lacks a clearly defined denominator. Our objective was to assess denominator-dependency on "high dose" classification across competing definitions. METHODS: To identify definitional variants, we reviewed literature and electronic prescribing tools, yielding 4 unique definitions. Using Prescription Drug Monitoring Programs data (July to September 2018), we conducted a population-based cohort study of 3,916,461 patients receiving outpatient opioid analgesics in California (CA) and Florida (FL). The binary outcome was whether patients were deemed "high dose" (>90 MME/d) compared across 4 definitions. We calculated I2 for heterogeneity attributable to the definition. RESULTS: Among 9,436,640 prescriptions, 42% overlapped, which led denominator definitions to impact daily MME values. Across definitions, average daily MME varied 3-fold (range: 17 to 52 [CA] and 23 to 65 mg [FL]). Across definitions, prevalence of "high dose" individuals ranged 5.9% to 14.2% (FL) and 3.5% to 10.3% (CA). Definitional variation alone would impact a hypothetical surveillance study trying to establish how much more "high dose" prescribing was present in FL than CA: from 39% to 84% more. Meta-analyses revealed strong heterogeneity (I2 range: 86% to 99%). In sensitivity analysis, including unit interval 90.0 to 90.9 increased "high dose" population fraction by 15%. DISCUSSION: While 90 MME may have cautionary mnemonic benefits, without harmonization of calculation, its utility is limited. Comparison between studies using daily MME requires explicit attention to definitional variation.

"Doctor and pharmacy shopping": A fading signal for prescription opioid use monitoring?

BACKGROUND: The term "doctor and pharmacy shopping" colloquially describes patients with high multiple provider episodes (MPEs)-a threshold count of distinct prescribers and/or pharmacies involved in prescription fulfillment. Opioid-related MPEs are implicated in the global opioid crisis and heavily monitored by government databases such as U.S. state prescription drug monitoring programs (PDMPs). We applied a widely-used MPE definition to examine U.S. trends from a large, commercially-insured population from 2010 to 2017. Further, we examined the proportion of enrollees identified as "doctor shoppers" with evidence of a cancer diagnosis to examine the risk of false positives. METHODS: Using a large, commercially-insured population, we identified patients with opioid-related MPEs: opioid prescriptions (Schedule II-V, no buprenorphine) filled from ≥5 prescribers AND ≥ 5 pharmacies within the past 90 days ("5x5x90d"). Quarterly rates per 100,000 enrollees (two specifications) were calculated between 2010 and 2017. We examined the trend in a recently published all-payer, 7 state cohort from the U.S. Centers for Disease Control and Prevention for comparison. Cancer-related ICD-9/10-CM codes were used. RESULTS: Quarterly MPE rates declined by approximately 73 % from 18.2-4.9 per 100,000 enrollee population with controlled substance prescriptions. In 2017, nearly one fifth of these commercially-insured enrollees identified by the 5x5x90d algorithm were diagnosed with cancer. Approximately 8% of this sample included patients with ≥ 1 buprenorphine prescriptions. CONCLUSIONS: Opioid "shopping" flags are a long-standing but rapidly fading PDMP signal. To avoid unintended consequences, such as identifying legitimate medical encounters requiring high healthcare utilization or opioid treatment, while maintaining vigilance, more nuanced and sophisticated approaches are needed.

Utilization Patterns of Skeletal Muscle Relaxants Among Commercially Insured Adults in the United States from 2006 to 2018.

OBJECTIVE: To examine the prevalence and duration of skeletal muscle relaxant (SMR) treatment among commercially insured adults in the United States. METHODS: We used the MarketScan Research Database to identify a cohort of adults 18 to 64 years who had ≥2-year continuous enrollment between 2005 and 2018. We estimated the prevalence of SMR treatment using a repeated cross-sectional design and derived treatment duration using the Kaplan-Meier method. Analyses were stratified by age group, sex, geographic region, individual SMR agent, and musculoskeletal disorder. RESULTS: 48.7 million individuals were included. Treatment prevalence ranged from 61.5 to 68.3 per 1,000. About one-third of users did not have a preceding musculoskeletal disorder diagnosis. Cyclobenzaprine was the dominant agent accounting for >50% of prescriptions. The considerable growth in the use of baclofen, tizanidine, and methocarbamol paralleled with a decline in carisoprodol and metaxalone use. The prevalence was highest in the South while lowest in the Northeast. The median treatment duration was 14 days with 4.0%, 1.9%, and 1.0% of individuals using SMRs for more than 90, 180, and 365 days, respectively. Compared with cyclobenzaprine, patients initiating baclofen, tizanidine, and carisoprodol had longer treatment duration. CONCLUSIONS: SMRs are widely used in the United States. Their use slightly increased in recent years, but trends varied among individual agents, patient groups, and geographic regions. Despite limited evidence to support efficacy, a sizable number of U.S. adults used SMRs for long-term and off-label conditions. Further study is needed to understand determinants of treatment as well as outcomes associated with such use.