Changes in Outpatient Health Care Use After COVID-19 Infection Among Veterans.

Importance: The association of COVID-19 infection with outpatient care utilization is unclear. Many studies reported population surveillance studies rather than comparing outpatient health care use between COVID-19-infected and uninfected cohorts. Objective: To compare outpatient health care use across 6 categories of care (primary care, specialty care, surgery care, mental health, emergency care, and diagnostic and/or other care) between veterans with or without COVID-19 infection. Design, Setting, and Participants: In a retrospective cohort study of Veterans Affairs primary care patients, veterans with COVID-19 infection were matched to a cohort of uninfected veterans. Data were obtained from the Veterans Affairs Corporate Data Warehouse and the Centers for Medicare & Medicaid Services Fee-for-Service Carrier/Physician Supplier file from January 2019 through December 2022. Data analysis was performed from September 2022 to April 2023. Exposure: COVID-19 infection. Main Outcomes and Measures: The primary outcome was the count of outpatient visits after COVID-19 infection. Negative binomial regression models compared outpatient use over a 1-year preinfection period, and peri-infection (0-30 days), intermediate (31-183 days), and long-term (184-365 days) postinfection periods. Results: The infected (202 803 veterans; mean [SD] age, 60.5 [16.2] years; 178 624 men [88.1%]) and uninfected (202 803 veterans; mean [SD] age, 60.4 [16.5] years; 178 624 men [88.1%]) cohorts were well matched across all covariates. Outpatient use in all categories (except surgical care) was significantly elevated during the peri-infection period for veterans with COVID-19 infection compared with the uninfected cohort, with an increase in all visits of 5.12 visits per 30 days (95% CI, 5.09-5.16 visits per 30 days), predominantly owing to primary care visits (increase of 1.86 visits per 30 days; 95% CI, 1.85-1.87 visits per 30 days). Differences in outpatient use attenuated over time but remained statistically significantly higher at 184 to 365 days after infection (increase of 0.25 visit per 30 days; 95% CI, 0.23-0.27 visit per 30 days). One-half of the increased outpatient visits were delivered via telehealth. The utilization increase was greatest for veterans aged 85 years and older (6.1 visits, 95% CI, 5.9-6.3 visits) vs those aged 20 to 44 years (4.8 visits, 95% CI, 4.7-4.8 visits) and unvaccinated veterans (4.5 visits, 95% CI, 4.3-4.6 visits) vs vaccinated veterans (3.2 visits; 95% CI, 3.4-4.8 visits). Conclusions and Relevance: This study found that outpatient use increased significantly in the month after infection, then attenuated but remained greater than the uninfected cohorts' use through 12 months, which suggests that there are sustained impacts of COVID-19 infection.

Mental health care utilization among men with castration-resistant prostate cancer receiving abiraterone or enzalutamide.

BACKGROUND: Abiraterone and enzalutamide are castration-resistant prostate cancer (CRPC) therapies with potentially distinct associations with mental health symptoms given their differing antiandrogen targets. METHODS: We used national Veterans Health Administration data to identify patients with CRPC who received first-line abiraterone or enzalutamide from 2010 to 2017. Using Poisson regression, we compared outpatient mental health encounters per 100 patient-months on drug between the abiraterone and enzalutamide cohorts adjusting for patient factors (e.g., age). We compared mental health encounters in the year before versus after starting therapy using the McNemar test. RESULTS: We identified 2902 CRPC patients who received abiraterone (n = 1992) or enzalutamide (n = 910). We found no difference in outpatient mental health encounters between the two groups (adjusted incident rate ratio [aIRR] 1.04, 95% confidence interval [CI] 0.95-1.15). However, men with preexisting mental health diagnoses received 81.3% of the outpatient mental health encounters and had higher rates of these encounters with enzalutamide (aIRR 1.21, 95% CI 1.09-1.34). Among patients with ≥1 year of enrollment before and after starting abiraterone (n = 1139) or enzalutamide (n = 446), there was no difference in mental health care utilization before versus after starting treatment (17.0% of patients vs. 17.6%, p = 0.60, abiraterone; 16.4% vs. 18.4%, p = 0.26, enzalutamide). CONCLUSION: We found no overall differences in mental health care utilization between CRPC patients who received first-line abiraterone versus enzalutamide. However, men with preexisting mental health diagnoses received the majority of mental health care and had more mental health visits with enzalutamide.

Patterns in Nonopioid Pain Medication Prescribing After the Release of the 2016 Guideline for Prescribing Opioids for Chronic Pain.

Importance: In 2016, the Centers for Disease Control and Prevention (CDC) released the evidence-based Guideline for Prescribing Opioids for Chronic Pain. How the release of this guideline coincided with changes in nonopioid pain medication prescribing rates remains unknown. Objective: To evaluate changes in nonopioid pain medication prescribing after the 2016 CDC guideline release and to assess the heterogeneity in these changes as a function of patient demographic and clinical characteristics. Design, Setting, and Participants: This cohort study constructed 7 (4 preguideline and 3 postguideline) annual cohorts using claims data from the national Optum Clinformatics Data Mart Database for the period January 1, 2011, through December 31, 2018. The cohorts included adults with commercial insurance, no cancer or palliative care claims, and 2 years of continuous insurance enrollment. Individuals could qualify for inclusion in multiple cohorts. Each cohort covered a 2-year period, with year 1 as the baseline period used to calculate opioid exposure and other clinical characteristics and year 2 as the follow-up period used to calculate prescribing outcomes. Data were analyzed in March 2022. Exposures: The CDC guideline, which was released in March 2016. Main Outcomes and Measures: The primary outcome was receipt of any nonopioid pain medication prescriptions (analgesics or antipyretics, anticonvulsants, antidepressants, and nonsteroidal anti-inflammatory drugs) during the follow-up period. This postguideline prescribing pattern was compared with estimates based on the preguideline prescribing pattern, and then the differences were stratified by patient clinical characteristics (chronic pain, recent opioid exposure, substance use disorder, anxiety disorder, and mood disorder). Results: A total of 15 879 241 individuals (2015 mean [SD] age, 50.2 [18.6] years; 8 298 271 female patients [52.3%]) qualified for inclusion in 1 or more cohorts. Logistic regression models showed that nonopioid pain medication prescribing odds were higher by 3.0% (95% CI, 2.6%-3.3%) in postguideline year 1, by 8.7% (95% CI, 8.3%-9.2%) in postguideline year 2, and by 9.7% (95% CI, 9.2%-10.3%) in postguideline year 3 than the preguideline pattern-based estimates. The magnitude of the postguideline departures from the preguideline pattern varied by several clinical characteristics (chronic pain, recent opioid exposure, anxiety disorder, and mood disorder). The largest departure was found among those with chronic pain, with postguideline prescribing being higher than estimated in postguideline year 2 (13.6%; 95% CI, 12.7%-14.6%) and postguideline year 3 (14.9%; 95% CI, 13.8%-16.0%). Conclusions and Relevance: Results of this study showed increases in nonopioid pain medication prescribing after the release of the 2016 CDC guideline, suggesting that the guideline may be associated with an increase in guideline-concordant care, but additional studies are needed to understand the role of other secular changes in the opioid policy landscape and other sources of nonopioid medication use.

Depression, Anxiety, and Patterns of Mental Health Care Among Men With Prostate Cancer Receiving Androgen Deprivation Therapy.

BACKGROUND: Androgen deprivation therapy (ADT) use is associated with an increased risk of developing depression and anxiety. Little is known about how the mental health of these men is treated. MATERIALS AND METHODS: We identified men with prostate cancer who received ADT between 2001 and 2015 using Optum's de-identified Clinformatics Data Mart Database. We determined the incidence of depression or anxiety diagnoses, mental health treatments, and the specialty of providers initiating psychotropic medications, after the start of ADT. Outcomes were compared with those of men with prostate cancer not receiving ADT and men without prostate cancer. RESULTS: Of 37 388 men with prostate cancer treated with ADT, 3964 (10.6%) received a new diagnosis of depression or anxiety. Of those 3964 men, 1892 (47.7%) did not receive a documented treatment, 10 (0.3%) received psychotherapy, 1321 (33.3%) a selective serotonin reuptake inhibitor, and 744 (18.8%) a benzodiazepine. The median time from initiation of ADT to a depression or anxiety diagnosis was 9.3 months. Primary care physicians were the most common prescribers of psychotropic medications (72.2%). The proportion of men not receiving mental health treatments of interest (47.7%) was similar compared to men without prostate cancer (49.1%), but statistically significantly lower compared to men with prostate cancer not receiving ADT (52.7%). CONCLUSIONS: In men with prostate cancer receiving ADT with a new diagnosis of depression or anxiety, nearly half are not receiving mental health care while one in five is introduced to a benzodiazepine. Further investigation toward improving the mental health care for men on ADT is needed.

Did prescribing laws disproportionately affect opioid dispensing to Black patients?

OBJECTIVE: To evaluate whether pain management clinic laws and prescription drug monitoring program (PDMP) prescriber check mandates, two state opioid policies with relatively rapid adoption across states, reduced opioid dispensing more or less in Black versus White patients. DATA SOURCES: Pharmacy claims data, US sample of commercially insured adults, 2007-2018. STUDY DESIGN: Stratifying by race, we used generalized estimating equations with an event-study specification to estimate time-varying effects of each policy on opioid dispensing, comparing to the four pre-policy quarters and states without the policy. Outcomes included high-dosage opioids, overlapping opioid prescriptions, concurrent opioid/benzodiazepines, opioids from >3 prescribers, opioids from >3 pharmacies. DATA EXTRACTION METHODS: We identified all prescription opioid dispensing to Black and White adults aged 18-64 without a palliative care or cancer diagnosis code. PRINCIPAL FINDINGS: Exactly 7,096,592 White and 1,167,310 Black individuals met inclusion criteria. Pain management clinic laws were associated with reductions in two outcomes; their association with high-dosage receipt was larger among White patients. In contrast, reductions due to PDMP mandates appeared limited to, or larger in, Black patients compared with White patients in four of five outcomes. For example, PDMP mandates reduced high-dosage receipt in Black patients by 0.7 percentage points (95% CI: 0.36-1.08 ppt.) over 4 years: an 8.4% decrease from baseline; there was no apparent effect in White patients. Similarly, while there was limited evidence that mandates reduced overlapping opioid receipt in White patients, they appeared to reduce overlapping opioid receipt in Black patients by 1.3 ppt. (95% CI: -1.66--1.01 ppt.) across post-policy years-a 14.4% decrease from baseline. CONCLUSIONS: PDMP prescriber check mandates but not pain management clinic laws appeared to reduce opioid dispensing more in Black patients than White patients. Future research should discern the mechanisms underlying these disparities and their consequences for pain management.

Has Declining Opioid Dispensing to Cancer Patients Been Tailored to Risk of Opioid Harms?

CONTEXT: Opioid prescribing to cancer patients is declining, but it is unknown whether reductions have been tailored to those at highest risk of opioid-related harms. OBJECTIVES: Examine whether declines in opioid dispensing to patients receiving active cancer treatment are sharper in patients with substance use disorder (SUD) or mental health diagnoses. METHODS: We used 2008-2018 national, commercial healthcare claims data to examine adjusted and unadjusted trends in opioid dispensing (receipt of ≥1 fill; average daily dosage; receipt of high-dose opioids; receipt of concurrent opioids and benzodiazepines) to patients ages ≥18 receiving treatment for one of four cancer types (breast; colorectal; head and neck; sarcoma; N = 324,789 patients). To compare declines across subgroups with varying risk of opioid-related harms, we stratified by SUD and mental health diagnosis. To address potential confounding, we estimated subgroup-specific trends using generalized estimating equations, adjusting for covariates. RESULTS: Across groups, rate of ≥1 opioid fill per quarter fell 32.5% (95% CI: 31.8%-33.2%) from 2008 to 2018; daily dose among those receiving opioids fell 37.6% (95% CI: 36.7%-38.6%). In most cases, these declines were not sharper in subgroups at greater risk of opioid-related harms. For example, patients with opioid use disorder experienced the smallest declines in dispensing frequency, and there was no evidence that declines were sharper in patients with mental health diagnoses. CONCLUSION: Sharp declines in opioid prescribing during the drug overdose crisis have affected a wide range of patients undergoing cancer treatment and may not have been sufficiently tailored to patient characteristics. Research on implications for opioid-related harms and pain management is needed.

Association Between Receipt of Overlapping Opioid and Benzodiazepine Prescriptions From Multiple Prescribers and Overdose Risk.

Importance: The receipt of overlapping opioid and benzodiazepine prescriptions is associated with increased overdose risk. It is unknown whether this increase in risk varies when overlapping prescriptions are written by multiple prescribers vs 1 prescriber. Objective: To evaluate the association between receipt of overlapping opioid and benzodiazepine prescriptions from multiple prescribers and overdose risk. Design, Setting, and Participants: This cohort study was conducted using 2017 to 2018 claims from the Optum deidentified Clinformatics Data Mart. Participants were patients with private insurance or Medicare Advantage aged 12 years or older with overlapping opioid and benzodiazepine prescriptions. Data were analyzed from March through November 2020. Exposures: For each patient, person-days on which opioid and benzodiazepine prescriptions overlapped were identified. The exposure was whether these prescriptions were written by multiple prescribers vs 1 prescriber. Main Outcomes and Measures: The outcome was a treated overdose, defined as the occurrence of 1 or more claims containing a diagnosis code for opioid or benzodiazepine poisoning on a person-day of opioid-benzodiazepine overlap. The association between exposure and outcome at the person-day level was estimated using logistic regression, controlling for opioid and benzodiazepine prescribing patterns, demographics, and comorbidities. The average marginal effect (AME) of the exposure, defined as the absolute difference in the probability of a treated overdose if all person-days of overlap involved prescriptions from multiple prescribers vs 1 prescriber, was calculated. Results: Among 529 053 patients, the mean (SD) age was 61.2 (15.6) years and 350 857 (66.3%) were female patients. Mean (SD) follow-up was 198.7 (249.8) days. During follow-up, overdose occurred on 1 or more person-days of opioid-benzodiazepine overlap for 2288 patients (0.4%, or 1 in 231 patients). There were 52 989 316 person-days of opioid-benzodiazepine overlap. Among 19 895 457 person-days (37.5%) involving prescriptions from multiple prescribers, there were 1390 overdoses (7.0 per 100 000 person-days), and among 33 093 859 person-days (62.5%) involving prescriptions from 1 prescriber, there were 1302 overdoses (3.9 per 100 000 person-days). Overdose risk was increased 1.8-fold (95% CI, 1.6-1.9) on person-days of overlap involving prescriptions from multiple prescribers vs 1 prescriber. The association between multiple prescribers and increased risk of overdose persisted in adjusted analyses (adjusted odds ratio, 1.20; 95% CI, 1.10-1.31; AME, 0.91 per 100 000 person-days of overlap; 95% CI, 0.46-1.37). Conclusions and Relevance: This study found that among patients already at increased risk of overdose owing to concurrent treatment with opioids and benzodiazepines, overdose risk was increased further when multiple prescribers were responsible for this treatment regimen compared with 1 prescriber. This increased risk was not fully accounted for by differences in prescribing patterns, demographics, or comorbidities. This finding suggests that other factors, such as poor care coordination, may be associated with the increase in risk.

Optimizing scalable, technology-supported behavioral interventions to prevent opioid misuse among adolescents and young adults in the emergency department: A randomized controlled trial protocol.

Preventing opioid misuse and opioid use disorder is critical among at-risk adolescents and young adults (AYAs). An Emergency Department (ED) visit provides an opportunity for delivering interventions during a rapidly changing opioid landscape. This paper describes pilot data and the protocol for a 2 × 2 factorial randomized controlled trial testing efficacy of early interventions to reduce escalation of opioid (prescription or illicit) misuse among at-risk AYAs. Interventions are delivered using technology by health coaches. AYAs ages 16-30 in the ED screening positive for prescription opioid use (+ ≥ 1 risk factor) or opioid misuse will be stratified by risk severity, sex, and age group. Participants will be randomly assigned to a condition at intake, either a live video health coach-delivered single session or a control condition of an enhanced usual care (EUC) community resource brochure. They are also randomly assigned to one of two post-intake conditions: health coach-delivered portal-like messaging via web portal over 30 days or EUC delivered at 30 days post-intake. Thus, the trial has four groups: health coach-delivered session+portal, health coach-delivered session+EUC, EUC + portal, and EUC + EUC. Outcomes will be measured at 3-, 6-, and 12-months. The primary outcome is opioid misuse based on a modified Alcohol Smoking and Substance Involvement Screening Test. Secondary outcomes include other opioid outcomes (e.g., days of opioid misuse, overdose risk behaviors), other substance misuse and consequences, and impaired driving. This study is innovative by testing the efficacy of feasible and scalable technology-enabled interventions to reduce and prevent opioid misuse and opioid use disorder. Trial Registration:ClinicalTrials.gov University of Michigan HUM00177625 NCT Registration: NCT04550715.

Changes in Initial Opioid Prescribing Practices After the 2016 Release of the CDC Guideline for Prescribing Opioids for Chronic Pain.

Importance: The Centers for Disease Control and Prevention (CDC) released the "Guideline For Prescribing Opioids For Chronic Pain" (hereafter, CDC guideline) in 2016, but its association with prescribing practices for patients who are opioid naive is unknown. Objective: To estimate changes in initial prescribing rates, duration, and dosage practices to patients who are opioid naive after the release of the CDC guideline. Design, Setting, and Participants: This cohort study used 6 sequential cohorts to estimate preguideline trends in prescribing among patients who were opioid naive, project that trend forward, and compare it with postguideline prescribing practices. Participants included commercially insured adults without current cancer or hospice care diagnoses and with no past-year opioid claims in the US from 2011 to 2017. All adjusted models were controlled for patient demographics and state-fixed effects. Data were analyzed from January 2020 to May 2021. Exposures: The release of the CDC guideline. Main Outcomes and Measures: Indicators of any opioid prescription fills during a 9-month period, the number of days' supply of the initial prescription, and the binary indicator of whether the initial prescription was for 50 or more morphine milligram equivalents (MMEs) per day. Results: There were 12 870 612 eligible unique patients across cohorts (mean [SD] age in 2016, 51.2 [18.7] years; 6 553 458 [50.9%] women); and the mean (SD) age of the cohorts increased annually, from 48.7 (17.9) years in the April 2011 to December 2012 cohort to 51.9 (19.2) years in the April 2016 to December 2017 cohort. The postguideline prescribing prevalence was 532 962 of 5 834 088 individuals (9.1%), which exceeded that projected from the preguideline trend, estimated at 9.0% (95% CI, 9.0%-9.1%). Among patients receiving prescriptions during follow-up, adjusted mean days' supply was 4.7% (95% CI, 4.3%-5.1%) lower in the first year after release of the guideline and 9.8% (95% CI, 9.3%-10.3%) lower in the second year after release, compared with the expected rate from the preguideline trend. The adjusted odds of receiving a high-dose (ie, ≥50 MME/d) initial prescription were lower in the first year (odds ratio, 0.97; 95% CI, 0.96-0.98) and in the second year (odds ratio, 0.94; 95% CI, 0.93-0.96) after the release of the CDC guideline compared with the odds expected from the preguideline trend. Conclusions and Relevance: This cohort study found that patients who were opioid naive continued to initiate opioid therapy after the release of opioid prescribing guidelines by the CDC, but trends in prescribing duration reversed and decreased, after increasing in each of 4 preguideline cohorts examined. High-dose prescribing rates were already decreasing, but those trends accelerated after the CDC guideline release. These results suggest that nonmandatory, evidence-based guidelines from trusted sources were associated with prescribing practices. Guideline-concordant care has potential to improve pain management and reduce opioid-related harms.

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

BACKGROUND: Efforts 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. METHODS: From 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. RESULTS: Among 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." CONCLUSIONS: Opioid 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.

Assessment of Prescriber and Pharmacy Shopping Among the Family Members of Patients Prescribed Opioids.

Importance: Most prescription opioid misuse involves opioids prescribed to others-a form of opioid diversion. However, few indicators of diversion risk exist. Because family members can often access patients' opioids, one such indicator may be the frequency with which opioid prescriptions are filled by patients when their family members are engaged in opioid prescriber and pharmacy shopping ("doctor and pharmacy shopping"). To date, this frequency has not been estimated. Objective: To estimate the proportion of opioid prescription fills for which family members meet prescriber and pharmacy shopping criteria. Design, Setting, and Participants: A cross-sectional analysis of 2015-2016 claims from a national commercial insurer was conducted from August to October, 2018. The sample included patients without cancer who were covered by family insurance plans and had 1 or more opioid prescription fill in 2016, as measured by prescription drug claims. Fills were the unit of analysis. Main Outcomes and Measures: For each fill in 2016 by the patient and each family member enrolled in the same plan (eg, spouse or child), the number of prescribers and number of pharmacies in the prior 12 months were counted. Prescriber and pharmacy shopping was defined as 4 or more prescribers and 4 or more pharmacies, following a National Quality Forum-endorsed measure. The proportion of fills for which 1 or more family member met criteria and the proportion for which the patient met criteria were calculated. Results: Among 554 417 patients in the sample, 301 297 (54.3%) were female and 48 047 (8.7%) were children. Mean (SD) age was 41.4 (16.4) years. Patients were enrolled in 469 913 plans and, after exclusions, filled 1 471 971 opioid prescriptions in 2016. For 8485 fills (0.6%), 1 or more family member met prescriber and pharmacy shopping criteria. For 44 547 fills (3.0%), the patient met criteria. For 6947 of the 8485 fills (81.9%) for which 1 or more family member met criteria, patients did not meet criteria. When criteria were 3 or more prescribers at 3 or more pharmacies, the proportion of fills for which 1 or more family member met criteria increased to 1.9%. Conclusions and Relevance: In this national study of US patients with private family insurance plans, 0.6% of opioid prescription fills occurred when at least 1 of the patient's family members met prescriber and pharmacy shopping criteria. For most of these fills, patients did not meet criteria. Findings suggest the potential for opioid diversion within families.

Predictors of alcohol use transitions among drug-using youth presenting to an urban emergency department.

BACKGROUND: Precipitants of alcohol use transitions can differ from generalized risk factors. We extend prior research by predicting transitions in alcohol use disorder (AUD) during adolescence and emerging adulthood. METHODS: From 12/2009-9/2011, research assistants recruited 599 drug-using youth age 14-24 from Level-1 Emergency Department in Flint, Michigan. Youth were assessed at baseline and four biannual follow-ups, including a MINI Neuropsychiatric interview to diagnose AUD (abuse/dependence). We modeled AUD transitions using continuous time Markov Chains with transition probabilities modulated by validated measures of demographics, anxiety/depression symptoms, cannabis use, peer drinking, parental drinking, and violence exposure. Separate models were fit for underage (<21) and those of legal drinking age. RESULTS: We observed 2,024 pairs of consecutive AUD states, including 264 transitions (119 No-AUD→AUD; 145 AUD→No-AUD); 194 (32.4%) individuals were diagnosed with AUD at ≥1 assessment. Among age 14-20, peer drinking increased AUD onset (No-AUD→AUD transition) rates (Hazard ratio-HR = 1.70; 95%CI: [1.13,2.54]), parental drinking lowered AUD remission (AUD→No-AUD transition) rates (HR = 0.53; 95%CI: [0.29,0.97]), and cannabis use severity both hastened AUD onset (HR = 1.18; 95%CI: [1.06,1.32]) and slowed AUD remission (HR = 0.85; 95%CI: [0.76,0.95]). Among age 21-24, anxiety/depression symptoms both increased AUD onset rates (HR = 1.35; 95%CI: [1.13,1.60]) and decreased AUD remission rates (HR = 0.74; 95%CI: [0.63,0.88]). Friend drinking hastened AUD onset (HR = 1.18, 95%CI: [1.05,1.33]), and slowed AUD remission (HR = 0.84; 95%CI: [0.75,0.95]). Community violence exposure slowed AUD remission (HR = 0.69, 95%CI: [0.48,0.99]). In both age groups, males had >2x the AUD onset rate of females, but there were no sex differences in AUD remission rates. Limitations, most notably that this study occurred at a single site, are discussed. CONCLUSIONS: Social influences broadly predicted AUD transitions in both age groups. Transitions among younger youth were predicted by cannabis use, while those among older youth were predicted more by internalizing symptoms and stress exposure (e.g., community violence). Our results suggest age-specific AUD etiology, and contrasts between prevention and treatment strategies.

Overdose and adverse drug event experiences among adult patients in the emergency department.

INTRODUCTION: Overdose is a leading cause of injury and death in the United States. Emergency Department (ED) patients have an elevated prevalence of substance use. This study describes overdose/adverse drug event experiences among adult ED patients to inform strategies to address overdose risk. METHODS: Patients seeking care at a large ED in the city of Flint, Michigan participated in a computerized self-assessment during 2011-2013 (n=4571). Overdose was assessed with a broad definition and included occurrences that could be considered adverse drug events. Among those with this type of experience, additional items assessed symptoms, outcomes, and intent. RESULTS: 12% reported an overdose history. Of participants' most serious overdoses, 74% were without clear intent for self-harm, although this was true of only 61% of overdoses involving opiates or sedatives, and 52% had symptoms present that indicated that it was life-threatening. Binge drinking on a monthly basis (ORs=1.4) was associated with a medically serious overdose compared to never having an overdose. Compared to no drug use in the last year, use of one drug was associated with an OR of 1.8, two drugs was associated with an OR of 5.8, three drugs was associated with an OR of 8.4, and four or more drugs was associated with an OR of 25.1 of having had a medically serious overdose (all p<0.05). CONCLUSIONS: Most overdose experiences among ED patients were without clear intent of self-harm. The ED may be an appropriate setting for efforts to reduce overdose risk, especially among polysubstance users.

New Persistent Opioid Use After Minor and Major Surgical Procedures in US Adults.

Importance: Despite increased focus on reducing opioid prescribing for long-term pain, little is known regarding the incidence and risk factors for persistent opioid use after surgery. Objective: To determine the incidence of new persistent opioid use after minor and major surgical procedures. Design, Setting, and Participants: Using a nationwide insurance claims data set from 2013 to 2014, we identified US adults aged 18 to 64 years without opioid use in the year prior to surgery (ie, no opioid prescription fulfillments from 12 months to 1 month prior to the procedure). For patients filling a perioperative opioid prescription, we calculated the incidence of persistent opioid use for more than 90 days among opioid-naive patients after both minor surgical procedures (ie, varicose vein removal, laparoscopic cholecystectomy, laparoscopic appendectomy, hemorrhoidectomy, thyroidectomy, transurethral prostate surgery, parathyroidectomy, and carpal tunnel) and major surgical procedures (ie, ventral incisional hernia repair, colectomy, reflux surgery, bariatric surgery, and hysterectomy). We then assessed data for patient-level predictors of persistent opioid use. Main Outcomes and Measures: The primary outcome was defined a priori prior to data extraction. The primary outcome was new persistent opioid use, which was defined as an opioid prescription fulfillment between 90 and 180 days after the surgical procedure. Results: A total of 36 177 patients met the inclusion criteria, with 29 068 (80.3%) receiving minor surgical procedures and 7109 (19.7%) receiving major procedures. The cohort had a mean (SD) age of 44.6 (11.9) years and was predominately female (23 913 [66.1%]) and white (26 091 [72.1%]). The rates of new persistent opioid use were similar between the 2 groups, ranging from 5.9% to 6.5%. By comparison, the incidence in the nonoperative control cohort was only 0.4%. Risk factors independently associated with new persistent opioid use included preoperative tobacco use (adjusted odds ratio [aOR], 1.35; 95% CI, 1.21-1.49), alcohol and substance abuse disorders (aOR, 1.34; 95% CI, 1.05-1.72), mood disorders (aOR, 1.15; 95% CI, 1.01-1.30), anxiety (aOR, 1.25; 95% CI, 1.10-1.42), and preoperative pain disorders (back pain: aOR, 1.57; 95% CI, 1.42-1.75; neck pain: aOR, 1.22; 95% CI, 1.07-1.39; arthritis: aOR, 1.56; 95% CI, 1.40-1.73; and centralized pain: aOR, 1.39; 95% CI, 1.26-1.54). Conclusions and Relevance: New persistent opioid use after surgery is common and is not significantly different between minor and major surgical procedures but rather associated with behavioral and pain disorders. This suggests its use is not due to surgical pain but addressable patient-level predictors. New persistent opioid use represents a common but previously underappreciated surgical complication that warrants increased awareness.

Nonmedical use of pain medications in dental patients.

BACKGROUND: Substance use is overrepresented in dental clinics that provide affordable care and dental clinics provide potential access to opioid analgesics. Research is needed to better understand prescription opioid misuse in this population. OBJECTIVE: The purpose of this study was to assess the prevalence and correlates of the misuse of prescription opioids in adults seeking dental care from a low-cost dental training clinic. METHODS: Patients were recruited from a university school's dentistry patient emergency and admission services clinic. Patients (n = 369) within the waiting area of the clinic completed a self-report questionnaire about their nonmedical use of prescription pain medications, medication diversion and use of substances. RESULTS: Approximately 37.9% (140/369) of those who completed the study survey reported at least some nonmedical use of pain medications within the past 30 days. Use was associated with diversion of medication, and use of tobacco, marijuana, and sedatives. CONCLUSIONS: Within this sample from a dental clinic, nonmedical use of prescription pain medications was more common than in the general population. This suggests that dental clinics may be an appropriate setting for provider education and patient-based intervention strategies to reduce nonmedical use of pain medications.

Noncancer pain conditions and risk of suicide.

IMPORTANCE: There are limited data on the extent to which suicide mortality is associated with specific pain conditions. OBJECTIVE: To examine the associations between clinical diagnoses of noncancer pain conditions and suicide among individuals receiving services in the Department of Veterans Affairs Healthcare System. DESIGN: Retrospective data analysis. SETTING: Data were extracted from National Death Index and treatment records from the Department of Veterans Healthcare System. PARTICIPANTS: Individuals receiving services in fiscal year 2005 who remained alive at the start of fiscal year 2006 (N = 4 863 086). MAIN OUTCOMES AND MEASURES: Analyses examined the association between baseline clinical diagnoses of pain-related conditions (arthritis, back pain, migraine, neuropathy, headache or tension headache, fibromyalgia, and psychogenic pain) and subsequent suicide death (assessed in fiscal years 2006-2008). RESULTS: Controlling for demographic and contextual factors (age, sex, and Charlson score), elevated suicide risks were observed for each pain condition except arthritis and neuropathy (hazard ratios ranging from 1.33 [99% CI, 1.22-1.45] for back pain to 2.61 [1.82-3.74] for psychogenic pain). When analyses controlled for concomitant psychiatric conditions, the associations between pain conditions and suicide death were reduced; however, significant associations remained for back pain (hazard ratio, 1.13 [99% CI, 1.03-1.24]), migraine (1.34 [1.02-1.77]), and psychogenic pain (1.58 [1.11-2.26]). CONCLUSIONS AND RELEVANCE: There is a need for increased awareness of suicide risk in individuals with certain noncancer pain diagnoses, in particular back pain, migraine, and psychogenic pain.

Characteristics of adults seeking medical marijuana certification.

BACKGROUND: Very little is known about medical marijuana users. The present study provides descriptive information on adults seeking medical marijuana and compares individuals seeking medical marijuana for the first time with those renewing their medical marijuana card on measures of substance use, pain and functioning. METHODS: Research staff approached patients (n=348) in the waiting area of a medical marijuana certification clinic. Chi-square and Wilcoxon signed rank tests were used to compare participants who reported that they were seeking medical marijuana for the first time (n=195) and those who were seeking to renew their access to medical marijuana (n=153). RESULTS: Returning medical marijuana patients reported a higher prevalence of lifetime cocaine, amphetamine, inhalant and hallucinogen use than first time patients. Rates of recent alcohol misuse and drug use were relatively similar between first time patients and returning patients with the exception of nonmedical use of prescription sedatives and marijuana use. Nonmedical prescription sedative use was more common among first time visitors compared to those seeking renewal (p<0.05). The frequency of recent marijuana use was higher in returning patients than first time patients (p<0.0001). Compared to first time patients, returning patients reported somewhat lower current pain level and slightly higher mental health and physical functioning. CONCLUSIONS: Study results indicate that differences exist between first time and returning medical marijuana patients. Longitudinal data are needed to characterize trajectories of substance use and functioning in these two groups.

Cause-specific mortality among Veterans with serious mental illness lost to follow-up.

OBJECTIVE: Although reduced care engagement has been linked to increased mortality for persons with serious mental illness (SMI), there have been limited investigations into specific mortality causes for this group. This study evaluates the effects of care disengagement on mortality cause and time until death in Veterans with SMI. METHOD: A total of 3300 Veterans with SMI lost to Veterans Affairs care for more than 1 year were contacted by providers who attempted treatment reengagement. Fisher's Exact Tests evaluated associations between mortality cause and reengagement status, and a Cox proportional hazard model evaluated the association between reengagement and survival. RESULTS: During the study, 146 (4.6%) patients died. A lack of reengagement was associated with increased noninjury death [odds ratio (OR)=1.64], increased cancer-based mortality (OR=4.76) and an average of 97.4 fewer days of life. CONCLUSIONS: Care reengagement may support medical care management and reduce preventable medical mortality for Veterans with SMI.

Association between opioid prescribing patterns and opioid overdose-related deaths.

CONTEXT: The rate of prescription opioid-related overdose death increased substantially in the United States over the past decade. Patterns of opioid prescribing may be related to risk of overdose mortality. OBJECTIVE: To examine the association of maximum prescribed daily opioid dose and dosing schedule ("as needed," regularly scheduled, or both) with risk of opioid overdose death among patients with cancer, chronic pain, acute pain, and substance use disorders. DESIGN: Case-cohort study. SETTING: Veterans Health Administration (VHA), 2004 through 2008. PARTICIPANTS: All unintentional prescription opioid overdose decedents (n = 750) and a random sample of patients (n = 154,684) among those individuals who used medical services in 2004 or 2005 and received opioid therapy for pain. Main Outcome Measure Associations of opioid regimens (dose and schedule) with death by unintentional prescription opioid overdose in subgroups defined by clinical diagnoses, adjusting for age group, sex, race, ethnicity, and comorbid conditions. RESULTS: The frequency of fatal overdose over the study period among individuals treated with opioids was estimated to be 0.04%.The risk of overdose death was directly related to the maximum prescribed daily dose of opioid medication. The adjusted hazard ratios (HRs) associated with a maximum prescribed dose of 100 mg/d or more, compared with the dose category 1 mg/d to less than 20 mg/d, were as follows: among those with substance use disorders, adjusted HR = 4.54 (95% confidence interval [CI], 2.46-8.37; absolute risk difference approximation [ARDA] = 0.14%); among those with chronic pain, adjusted HR = 7.18 (95% CI, 4.85-10.65; ARDA = 0.25%); among those with acute pain, adjusted HR = 6.64 (95% CI, 3.31-13.31; ARDA = 0.23%); and among those with cancer, adjusted HR = 11.99 (95% CI, 4.42-32.56; ARDA = 0.45%). Receiving both as-needed and regularly scheduled doses was not associated with overdose risk after adjustment. CONCLUSION: Among patients receiving opioid prescriptions for pain, higher opioid doses were associated with increased risk of opioid overdose death.