The association between community social vulnerability and prescription opioid availability with individual opioid overdose.

BACKGROUND: This study aims to assess the association of community social vulnerability and community prescription opioid availability with individual non-fatal or fatal opioid overdose. METHODS: We identified patients 12 years of age or older from the Oregon All Payer Claims database (APCD) linked to other public health datasets. Community-level characteristics were captured in an exposure period (EP) (1/1/2018-12/31/2018) and included: census tract-level social vulnerability domains (socio-economic status, household composition, racial and ethnic minority status, and housing type and transportation), census tract-level prescriptions and community-level opioid use disorder (OUD) diagnoses per 100 capita binned into quartiles or quintiles. We employed Cox models to estimate the risk of fatal and non-fatal opioid overdoses events in the 12 months following the EP. MAIN FINDINGS: We identified 1,548,252 individuals. Patients were mostly female (54%), White (61%), commercially insured (54%), and lived in metropolitan areas (81%). Of the total sample, 2485 (0.2%) experienced a non-fatal opioid overdose and 297 died of opioid overdose. There was higher hazard for non-fatal overdose in communities with greater OUD per 100 capita. We also found higher non-fatal and fatal hazards for opioid overdose among patients in communities with higher housing type and transportation-related vulnerability compared to the lowest quintile. Conversely, patients were at less risk of opioid overdose when living in communities with greater prevalence of the young or the elderly, the disabled, single parent families or low English proficiency. CONCLUSION: These findings underscore the importance of the environmental context when considering public health policies to reduce opioid harms.

Association of Household Opioid Availability With Opioid Overdose.

Importance: Previous studies that examined the role of household opioid prescriptions in opioid overdose risk were limited to commercial claims, did not include fatal overdoses, and had limited inclusion of household prescription characteristics. Broader research is needed to expand understanding of the risk of overdose. Objective: To assess the role of household opioid availability and other household prescription factors associated with individuals' odds of fatal or nonfatal opioid overdose. Design, Setting, and Participants: A retrospective cohort study assessing patient outcomes from January 1, 2015, through December 31, 2018, was conducted on adults in the Oregon Comprehensive Opioid Risk Registry database in households of at least 2 members. Data analysis was performed between October 16, 2020, and January 26, 2023. Exposures: Household opioid prescription availability and household prescription characteristics. Main Outcomes and Measures: Opioid overdoses were captured from insurance claims, death records, and hospital discharge data. Household opioid prescription availability and prescription characteristics for individuals and households were modeled as 6-month cumulative time-dependent measures, updated monthly. To assess the association between household prescription availability, household prescription characteristics, and overdose, multilevel logistic regression models were developed, adjusting for demographic, clinical, household, and prescription characteristics. Results: The sample included 1 691 856 individuals in 1 187 140 households, of which most were women (53.2%), White race (70.7%), living in metropolitan areas (75.8%), and having commercial insurance (51.8%), no Elixhauser comorbidities (69.5%), and no opioid prescription fills in the study period (57.0%). A total of 28 747 opioid overdose events were observed during the study period (0.0526 per 100 person-months). Relative to individuals without personal or household opioid fills, the odds of opioid-related overdose increased by 60% when another household member had an opioid fill in the past 6 months (adjusted odds ratio [aOR], 1.60; 95% CI, 1.54-1.66) and were highest when both the individual and another household member had opioid fills in the preceding 6 months (aOR, 6.25; 95% CI, 6.09-6.40). Conclusions and Relevance: In this cohort study of adult Oregon residents in households of at least 2 members, the findings suggest that household prescription availability is associated with increased odds of opioid overdose for others in the household, even if they do not have their own opioid prescription. These findings underscore the importance of educating patients about proper opioid disposal and the risks of household opioids.

Opioid-related overdose and chronic use following an initial prescription of hydrocodone versus oxycodone.

BACKGROUND: Hydrocodone and oxycodone are prescribed commonly to treat pain. However, differences in risk of opioid-related adverse outcomes after an initial prescription are unknown. This study aims to determine the risk of opioid-related adverse events, defined as either chronic use or opioid overdose, following a first prescription of hydrocodone or oxycodone to opioid naïve patients. METHODS: A retrospective analysis of multiple linked public health datasets in the state of Oregon. Adult patients ages 18 and older who a) received an initial prescription for oxycodone or hydrocodone between 2015-2017 and b) had no opioid prescriptions or opioid-related hospitalizations or emergency department visits in the year preceding the prescription were followed through the end of 2018. First-year chronic opioid use was defined as ≥6 opioid prescriptions (including index) and average ≤30 days uncovered between prescriptions. Fatal or non-fatal opioid overdose was indicated from insurance claims, hospital discharge data or vital records. RESULTS: After index prescription, 2.8% (n = 14,458) of individuals developed chronic use and 0.3% (n = 1,480) experienced overdose. After adjustment for patient and index prescription characteristics, patients receiving oxycodone had lower odds of developing chronic use relative to patients receiving hydrocodone (adjusted odds ratio = 0.95, 95% confidence interval (CI) 0.91-1.00) but a higher risk of overdose (adjusted hazard ratio (aHR) = 1.65, 95% CI 1.45-1.87). Oxycodone monotherapy appears to greatly increase the hazard of opioid overdose (aHR 2.18, 95% CI 1.86-2.57) compared with hydrocodone with acetaminophen. Oxycodone combined with acetaminophen also shows a significant increase (aHR 1.26, 95% CI 1.06-1.50), but not to the same extent. CONCLUSIONS: Among previously opioid-naïve patients, the risk of developing chronic use was slightly higher with hydrocodone, whereas the risk of overdose was higher after oxycodone, in combination with acetaminophen or monotherapy. With a goal of reducing overdose-related deaths, hydrocodone may be the favorable agent.

Factors Associated With Opioid Overdose After an Initial Opioid Prescription.

Importance: The opioid epidemic continues to be a public health crisis in the US. Objective: To assess the patient factors and early time-varying prescription-related factors associated with opioid-related fatal or nonfatal overdose. Design, Setting, and Participants: This cohort study evaluated opioid-naive adult patients in Oregon using data from the Oregon Comprehensive Opioid Risk Registry, which links all payer claims data to other health data sets in the state of Oregon. The observational, population-based sample filled a first (index) opioid prescription in 2015 and was followed up until December 31, 2018. Data analyses were performed from March 1, 2020, to June 15, 2021. Exposures: Overdose after the index opioid prescription. Main Outcomes and Measures: The outcome was an overdose event. The sample was followed up to identify fatal or nonfatal opioid overdoses. Patient and prescription characteristics were identified. Prescription characteristics in the first 6 months after the index prescription were modeled as cumulative, time-dependent measures that were updated monthly through the sixth month of follow-up. A time-dependent Cox proportional hazards regression model was used to assess patient and prescription characteristics that were associated with an increased risk for overdose events. Results: The cohort comprised 236 921 patients (133 839 women [56.5%]), of whom 667 (0.3%) experienced opioid overdose. Risk of overdose was highest among individuals 75 years or older (adjusted hazard ratio [aHR], 3.22; 95% CI, 1.94-5.36) compared with those aged 35 to 44 years; men (aHR, 1.29; 95% CI, 1.10-1.51); those who were dually eligible for Medicaid and Medicare Advantage (aHR, 4.37; 95% CI, 3.09-6.18), had Medicaid (aHR, 3.77; 95% CI, 2.97-4.80), or had Medicare Advantage (aHR, 2.18; 95% CI, 1.44-3.31) compared with those with commercial insurance; those with comorbid substance use disorder (aHR, 2.74; 95% CI, 2.15-3.50), with depression (aHR, 1.26; 95% CI, 1.03-1.55), or with 1 to 2 comorbidities (aHR, 1.32; 95% CI, 1.08-1.62) or 3 or more comorbidities (aHR, 1.90; 95% CI, 1.42-2.53) compared with none. Patients were at an increased overdose risk if they filled oxycodone (aHR, 1.70; 95% CI, 1.04-2.77) or tramadol (aHR, 2.80; 95% CI, 1.34-5.84) compared with codeine; used benzodiazepines (aHR, 1.06; 95% CI, 1.01-1.11); used concurrent opioids and benzodiazepines (aHR, 2.11; 95% CI, 1.70-2.62); or filled opioids from 3 or more pharmacies over 6 months (aHR, 1.38; 95% CI, 1.09-1.75). Conclusions and Relevance: This cohort study used a comprehensive data set to identify patient and prescription-related risk factors that were associated with opioid overdose. These findings may guide opioid counseling and monitoring, the development of clinical decision-making tools, and opioid prevention and treatment resources for individuals who are at greatest risk for opioid overdose.

Characteristics and health care events of patients admitted to treatment for both heroin and methamphetamine compared to patients admitted for heroin only.

INTRODUCTION: Co-occurring heroin and methamphetamine use is a growing public health problem. This study assessed the characteristics of Medicaid patients admitted to substance use disorder (SUD) treatment programs for heroin and methamphetamine use compared with patients admitted for heroin only. METHODS: The study identified patients who entered treatment for heroin and methamphetamine and those admitted for heroin only between 2014 and 2017 from the Oregon Treatment Episode Data Set linked with Medicaid enrollment, and medical and pharmacy claims. We used a cross-sectional design to compare demographics, type of treatment, and substance use characteristics between the two groups. We used logistic regression models to assess differences in the odds of opioid-related and all-cause adverse events. RESULTS: Among the 3802 study sample, 2004 (53%) were admitted for both heroin and methamphetamine use. The heroin and methamphetamine group were more likely to be younger, female, White or American Indian/Alaska Native; and had more comorbidities than patients admitted for heroin only. Patients admitted for heroin and methamphetamine treatment were less likely to receive any medication for opioid use disorder (MOUD) (56% vs 75%, p < 0.001) and received fewer days of MOUD treatment (mean 188 vs. 265 days, p < 0.001) compared to the heroin only group. The heroin and methamphetamine group were more likely to receive buprenorphine (28.1% vs 24.2%) and less likely to receive methadone (39.9% vs 62.5%). The heroin and methamphetamine group began use at a younger age, used and injected more frequently than those admitted for heroin only. Patients treated for heroin and methamphetamine had 17% lower odds of OUD-related adverse events (aOR 0.83; 95% CI 0.70-0.99) and 52% higher odds of all-cause adverse events (aOR 1.52; 95% CI 1.14-2.03) relative to the heroin only group. CONCLUSION: Patients admitted for both heroin and methamphetamine reported greater addiction severity (more frequent use, earlier onset of use, and injection use), yet less commonly received MOUD compared to those who were admitted for heroin only. These findings indicate substantial missed opportunities for MOUD treatment even among people who successfully engage with the SUD treatment system.

Patient outcomes after opioid dose reduction among patients with chronic opioid therapy.

ABSTRACT: The net effects of prescribing initiatives that encourage dose reductions are uncertain. We examined whether rapid dose reduction after high-dose chronic opioid therapy (COT) associates with suicide, overdose, or other opioid-related adverse events. This retrospective cohort study included Oregon Medicaid recipients with high-dose COT. Claims were linked with prescription data from the prescription drug monitoring program and death data from vital statistics, 2014 to 2017. Participants were placed into 4 mutually exclusive dose trajectory groups after the high-dose COT period, and Cox proportional hazard models were used to examine the effect of dose changes on patient outcomes in the following year. Of the 14,596 high-dose COT patients, 4191 (28.7%) abruptly discontinued opioid prescriptions, 1648 (11.3%) reduced opioid dose before discontinuing, 6480 (44.4%) had a dose reduction but never discontinued, and 2277 (15.6%) had a stable or increasing dose. Discontinuation, whether abrupt (adjusted hazard ratio [aHR] 3.63; 95% confidence interval [CI] 1.42-9.25) or with dose reduction (aHR 4.47, 95% CI 1.68-11.88) significantly increased risk of suicide compared with those with stable or increasing dose. By contrast, discontinuation or dose reduction reduced the risk of overdose compared with those with a stable or increasing dose (aHR 0.36-0.62, 95% CI 0.20-0.94). Patients with an abrupt discontinuation were more likely to overdose on heroin (vs. prescription opioids) than patients in other groups (P < 0.0001). Our study suggests that patients on COT require careful risk assessment and supportive interventions when considering opioid discontinuation or continuation at a high dose.

COVID-19-related adaptations to the implementation and evaluation of a clinic-based intervention designed to improve opioid safety.

The United States faces an opioid crisis with an unprecedented and increasing death rate from opioid overdose. Successfully reducing the rates of opioid use disorder (OUD) and overdose will require the engagement of frontline clinicians to prescribe opioids more safely and to build their capacity to treat patients with OUD using evidence-based approaches. The COVID-19 pandemic has created significant challenges for patients, clinicians and health systems and has been associated with increasing risks of overdoses and deaths. Herein, we review a multidisciplinary project designed to implement and evaluate clinic-based interventions in Oregon, USA, to improve pain management, opioid prescribing and treatment of OUD. The intervention, called Improving PaIn aNd OPiOId MaNagemenT in Primary Care (PINPOINT), combines practice facilitation, academic detailing and education through the Oregon ECHO Network. Implementation of PINPOINT has occurred across the Oregon Rural Practice-based Research Network and has involved 49 clinic sites to date. To evaluate the impact of the intervention, the research team created the Provider Results of Opioid Management and Prescribing Training (PROMPT), a dataset that links information from the state prescription drug monitoring program, all-payer claims database, emergency medical services, vital records and substance use disorder treatment system. The PROMPT dataset will allow evaluation of the impact of the intervention at both the clinician and clinic levels. Due to the constraints of the COVID-19 pandemic, elements of both implementation and evaluation required significant adaptations to continue to meet the original project goals.

Linkage of public health and all payer claims data for population-level opioid research.

OBJECTIVE: Our objective is to describe how we combine, at an individual level, multiple administrative datasets to create a Comprehensive Opioid Risk Registry (CORR). The CORR will characterize the role that individual characteristics, household characteristics, and community characteristics have on an individual's risk of opioid use disorder or opioid overdose. DATA SOURCES: Study data sources include the voluntary Oregon All Payer Claims Database (APCD), American Community Survey Census Data, Oregon Death Certificate data, Oregon Hospital Discharge Data (HDD), and Oregon Prescription Drug Monitoring (PDMP) Data in 2013-2018. STUDY DESIGN: To create the CORR we first prepared the APCD data set by cleaning and geocoding addresses, creating a community grouper and adding census indices, creating household grouper, and imputing patient race. Then we deployed a probabilistic linkage methodology to incorporate other data sources maintaining compliance with strict data governance regulations. DATA COLLECTION/EXTRACTION METHODS: Administrative datasets were obtained through an executed data use agreement with each data owner. The APCD served as the population universe to which all other data sources were linked. PRINCIPAL FINDINGS: There were 3 628 992 unique people in the APCD over the entire study period. We identified 968 767 unique households in 2013 and 1 209 236 in 2018, and geocoded patient addresses representing all census tracts in Oregon. Census, death certificate, HDD, and PDMP datasets were successfully linked to this population universe. CONCLUSIONS: This methodology can be replicated in other states and may also apply to a broad array of health services research topics.

Suicide Distribution and Trends Among Male Older Adults in the U.S., 1999-2018.

INTRODUCTION: This study examines the distribution and trends in suicide death rates among male adults aged ≥65 years in the U.S. from 1999 to 2018. METHODS: Suicide mortality data were derived from Multiple Cause of Death from the Center for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research database. Suicides were identified from the underlying causes of death. Joinpoint regression examined the distribution and shift in suicide age-adjusted death rates overall and by age groups, race/ethnicity, method of suicide, and urbanicity. Analyses were conducted in 2020. RESULTS: Between 1999 and 2018, a total of 106,861 male adults aged ≥65 years died of suicide (age-adjusted rate=31.4 per 100,000 population, 95% CI=31.2, 31.6). Suicide rates showed a V-shaped trend. They were declining annually by 1.8% (95% CI= -2.4, -1.2); however, starting in 2007, there was a shift upward, increasing significantly by 1.7% per year for the next decade (95% CI=1.0, 1.6). Suicide rates were highest among those aged ≥85 years (48.8 per 100,000 population with an upward shift in 2008), Whites (35.3 per 100,000 population with an upward shift in trend in 2007), and the most rural communities (39.0 per 100,000 population). Most suicides were due to firearms (78.3% at a rate of 24.7 per 100,000 population), especially in rural areas, and shifted upward after 2007. CONCLUSIONS: Increases in suicide rates among male older adults in the U.S., particularly after the 2007-2008 economic recession, are concerning. Tailored suicide prevention intervention strategies are needed to address suicide-related risk factors.

Ambulance Calls for Substance-Related Issues Before and After COVID-19.

Background: The United States is currently facing 2 epidemics: sustained morbidity and mortality from substance use and the more recent COVID-19 pandemic. We tested the hypothesis that the pandemic has disproportionately affected individuals with substance use disorder by evaluating average daily 9-1-1 ambulance calls for substance use-related issues compared with all other calls. Methods: This was a retrospective cross-sectional analysis of 9-1-1 ambulance calls before and after the start of COVID-19 in Massachusetts. We used consecutive samples of 9-1-1 ambulance calls, categorized into those which were substance-related or not. An interrupted time series analysis was performed to determine if there were changes in numbers of daily calls before a statewide declaration of emergency for COVID-19 (February 15-March 9, 2020), from the emergency declaration until a stay-at-home advisory (March 10-March 22, 2020) and following the stay-at-home advisory (March 23-May 15, 2020). Results: Compared with prior to the statewide emergency, the post-statewide emergency average of daily ambulance calls decreased from 2,453.2 to 1,969.6, a 19.7% decrease. Similarly, calls for substance-related reasons decreased by 16.4% compared with prior to the statewide emergency. However, despite an initial decrease in calls, after the stay-at-home advisory calls for substance use began increasing by 0.7 (95% confidence interval (CI) 0.4-1.1) calls/day, while calls for other reasons did not significantly change (+1.2 (95% CI -0.8 to 3.1) calls/day). Refusal of transport for substance-related calls increased from 5.0% before the statewide emergency to 7.5% after the declaration (p < 0.001). Conclusions: After an initial decline in substance-related ambulance calls following a statewide declaration of emergency, calls for substance use increased to pre-COVID-19 levels, while those for other reasons remained at a lower rate. The results suggest that COVID-19 is disproportionately affecting individuals with substance use disorder.

Prescription and Prescriber Specialty Characteristics of Initial Opioid Prescriptions Associated with Chronic Use.

OBJECTIVE: This study evaluated the characteristics of opioid prescriptions, including prescriber specialty, given to opioid-naïve patients and their association with chronic use. DESIGN: Cross-sectional analysis of the Ohio prescription drug monitoring program from January 2010 to November 2017. SETTING: Ohio, USA. SUBJECTS: Patients who had no opioid prescriptions from 2010 to 2012 and a first-time prescription from January 2013 to November 2016. METHODS: Chronic use was defined as at least six opioid prescriptions in one year and either one or more years between the first and last prescription or an average of ≤30 days not covered by an opioid during that year. RESULTS: A total of 4,252,809 opioid-naïve patients received their first opioid prescription between 2013 and 2016; 364,947 (8.6%) met the definition for chronic use. Those who developed chronic use were older (51.7 vs 45.6 years) and more likely to be female (53.6% vs 52.8%), and their first prescription had higher pill quantities (44.9 vs 30.2), higher morphine milligram equivalents (MME; 355.3 vs 200.0), and was more likely to be an extended-release formulation (2.9% vs 0.7%, all P < 0.001). When compared with internal medicine, the adjusted odds of chronic use were highest with anesthesiology (odds ratio [OR] = 1.46) and neurology (OR = 1.43) and lowest with ophthalmology (OR = 0.33) and gynecology (OR = 0.37). CONCLUSIONS: Eight point six percent of opioid-naïve individuals who received an opioid prescription developed chronic use. This rate varied depending on the specialty of the provider who wrote the prescription. The risk of chronic use increased with higher MME content of the initial prescription and use of extended-release opioids.

A comparison of trends in opioid dispensing patterns between Medicaid pharmacy claims and prescription drug monitoring program data.

PURPOSE: Public and private payers have implemented benefit limitations to reduce high-risk opioid prescriptions. The effect of these policies on the increase of out-pocket payment is unclear. To understand this gap, we compared the discrepancies in trends between opioid prescription fills vs claims among Medicaid beneficiaries. METHODS: Data from the Oregon Prescription Drug Monitoring Program (PDMP) and Oregon Medicaid administrative claims were used to identify Medicaid beneficiaries 18 years and older enrolled at least one full month from 2015 to 2017. Generalized linear models assessed the trends in the monthly rates of opioid PDMP prescription fills and pharmacy claims per 1000 eligible members. Rates by morphine equivalent dose (MED) tier (<50, 50-89, 90-120, >120 MED) and co-prescribed opioid and benzodiazepine were also assessed. RESULTS: During the study period, an average of 495 355 Medicaid members had 2 797 054 opioid PDMP fills and 2 472 155 opioid Medicaid pharmacy claims. Study participants had 15.4 (95% confidence interval [CI] 13.6 to 17.0; P < .001) more prescriptions per 1000 member per month in the PDMP data (114.1 [SD 7.4]) compared with the Medicaid claims data (98.7 [SD 7.9]). Similarly, there were 1.9 more co-occurring opioid/benzodiazepine prescriptions per 1000 members per month observed in the PDMP data than the Medicaid claims data (95% CI 1.7 to 2.1; P < .001). At each MED tier, the PDMP fills were consistently higher than the claims (P < .001). CONCLUSIONS: Higher rate of fills in the PDMP compared to pharmacy claims suggests that there may be an increasing trend of out-of-pocket payment among Medicaid beneficiaries.

The effect of marriage on stage at diagnosis and survival in women with cervical cancer.

PURPOSE: This study assessed the effect of marital status on stage at diagnosis and survival in women with cervical cancer. METHODS: Cervical cancer cases diagnosed between 2000 and 2010 were identified from the Surveillance, Epidemiology and End Results (SEER) program. Patient demographic and clinical characteristics were compared by marital status. Multivariate logistic and Cox proportional hazard regression models were performed to calculate odds ratios of advanced stage at diagnosis and hazard ratios of death risk respectively. RESULTS: Among 31 425 women, 46% of cases were married at the time of diagnosis. Married women were more commonly diagnosed at a localized stage (55%) compared to other non-marital groups (47% of singles, 42% of separated/divorced, and 28% of widowers, p < 0.001). After controlling for age, race/ethnicity, period of diagnosis, histology, and SEER area, single [adjusted odds ratio (aOR) 1.41; 95% Confidence Interval (CI) 1.33-1.49], separated/divorced [aOR 1.44; 95% CI 1.34-1.55], and widowed women [aOR 1.43; 95% CI 1.31-1.58] were all more likely to be diagnosed at an advanced stage compared to married women. In terms of prognosis, single (adjusted hazard ratio (aHR) 1.35; 95% CI 1.28-1.43), separated/divorced (aHR 1.22; 95% CI 1.15-1.29), and widowed women (aHR 1.28; 95% CI 1.19-1.36) had significant increased risk of death compared to married women. Adjusting for insurance status did not change the findings. CONCLUSION: Being married is associated with earlier diagnosis and a more favorable prognosis for cervical cancer among US women. Interventions to improve prognosis for unmarried women, including increasing use of cervical cancer screenings, are warranted.

No differences in cervical cancer stage at diagnosis for Blacks and Whites in the Mountain West.

This study assesses cervical cancer disparities between Blacks and Whites in terms of stage at diagnosis in a Mountain West state. A total of 1,408 women diagnosed with cervical cancer between 1995 and 2010 were identified from the Nevada Central Cancer Registry. Logistic regression modeling examined the effect of race on stage at diagnosis in both Nevada and the Surveillance, Epidemiology and End Results (SEER) population. After controlling for the main confounders, no significant differences in stage at diagnosis were observed between Black and White females in Nevada (aOR 0.91; 95% CI 0.57-1.43). In contrast, Black women in SEER areas had a 21% higher odds of being diagnosed at an advanced stage compared to Whites. Our findings suggest a favorable disparity balance for cervical cancer in Nevada where Blacks are largely recent arrivals in relation to the remaining US, where Blacks have long been established.