Suicide Screening, Risk Assessment, and Lethal Means Counseling During Zero Suicide Implementation.

OBJECTIVE: The authors measured implementation of Zero Suicide (ZS) clinical practices that support identification of suicide risk and risk mitigation, including screening, risk assessment, and lethal means counseling, across mental health specialty and primary care settings. METHODS: Six health care systems in California, Colorado, Michigan, Oregon, and Washington participated. The sample included members ages ≥13 years from 2010 to 2019 (N=7,820,524 patients). The proportions of patients with suicidal ideation screening, suicide risk assessment, and lethal means counseling were estimated. RESULTS: In 2019, patients were screened for suicidal ideation in 27.1% (range 5.0%-85.0%) of mental health visits and 2.5% (range 0.1%-35.0%) of primary care visits among a racially and ethnically diverse sample (44.9% White, 27.2% Hispanic, 13.4% Asian, and 7.7% Black). More patients screened positive for suicidal ideation in the mental health setting (10.2%) than in the primary care setting (3.8%). Of the patients screening positive for suicidal ideation in the mental health setting, 76.8% received a risk assessment, and 82.4% of those identified as being at high risk received lethal means counseling, compared with 43.2% and 82.4%, respectively, in primary care. CONCLUSIONS: Six health systems that implemented ZS showed a high level of variation in the proportions of patients receiving suicide screening and risk assessment and lethal means counseling. Two opportunities emerged for further study to increase frequency of these practices: expanding screening beyond patients with regular health care visits and implementing risk assessment with lethal means counseling in the primary care setting directly after a positive suicidal ideation screening.

Adolescents Who Do Not Endorse Risk via the Patient Health Questionnaire Before Self-Harm or Suicide.

Importance: Given that the Patient Health Questionnaire (PHQ) item 9 is commonly used to screen for risk of self-harm and suicide, it is important that clinicians recognize circumstances when at-risk adolescents may go undetected. Objective: To understand characteristics of adolescents with a history of depression who do not endorse the PHQ item 9 before a near-term intentional self-harm event or suicide. Design, Setting, and Participants: This was a retrospective cohort study design using electronic health record and claims data from January 2009 through September 2017. Settings included primary care and mental health specialty clinics across 7 integrated US health care systems. Included in the study were adolescents aged 13 to 17 years with history of depression who completed the PHQ item 9 within 30 or 90 days before self-harm or suicide. Study data were analyzed September 2022 to April 2023. Exposures: Demographic, diagnostic, treatment, and health care utilization characteristics. Main Outcome(s) and Measure(s): Responded "not at all" (score = 0) to PHQ item 9 regarding thoughts of death or self-harm within 30 or 90 days before self-harm or suicide. Results: The study included 691 adolescents (mean [SD] age, 15.3 [1.3] years; 541 female [78.3%]) in the 30-day cohort and 1024 adolescents (mean [SD] age, 15.3 [1.3] years; 791 female [77.2%]) in the 90-day cohort. A total of 197 of 691 adolescents (29%) and 330 of 1024 adolescents (32%), respectively, scored 0 before self-harm or suicide on the PHQ item 9 in the 30- and 90-day cohorts. Adolescents seen in primary care (odds ratio [OR], 1.5; 95% CI, 1.0-2.1; P = .03) and older adolescents (OR, 1.2; 95% CI, 1.0-1.3; P = .02) had increased odds of scoring 0 within 90 days of a self-harm event or suicide, and adolescents with a history of inpatient hospitalization and a mental health diagnosis had twice the odds (OR, 2.0; 95% CI, 1.3-3.0; P = .001) of scoring 0 within 30 days. Conversely, adolescents with diagnoses of eating disorders were significantly less likely to score 0 on item 9 (OR, 0.4; 95% CI, 0.2-0.8; P = .007) within 90 days. Conclusions and Relevance: Study results suggest that older age, history of an inpatient mental health encounter, or being screened in primary care were associated with at-risk adolescents being less likely to endorse having thoughts of death and self-harm on the PHQ item 9 before a self-harm event or suicide death. As use of the PHQ becomes more widespread in practice, additional research is needed for understanding reasons why many at-risk adolescents do not endorse thoughts of death and self-harm.

Evaluating the Prevalence of Four Recommended Practices for Suicide Prevention Following Hospital Discharge.

BACKGROUND: The Joint Commission's National Patient Safety Goal (NPSG) for suicide prevention (NPSG.15.01.01) requires that accredited hospitals maintain policies/procedures for follow-up care at discharge for patients identified as at risk for suicide. The proportion of hospitals meeting these requirements through use of recommended discharge practices is unknown. METHODS: This cross-sectional observational study explored the prevalence of suicide prevention activities among Joint Commission-accredited hospitals. A questionnaire was sent to 1,148 accredited hospitals. The authors calculated the percentage of hospitals reporting implementation of four recommended discharge practices for suicide prevention. RESULTS: Of 1,148 hospitals, 346 (30.1%) responded. The majority (n = 212 [61.3%]) of hospitals had implemented formal safety planning, but few of those (n = 41 [19.3%]) included all key components of safety planning. Approximately a third of hospitals provided a warm handoff to outpatient care (n = 128 [37.0%)] or made follow-up contact with patients (n = 105 [30.3%]), and approximately a quarter (n = 97 [28.0%]) developed a plan for lethal means safety. Very few (n = 14 [4.0%]) hospitals met full criteria for implementing recommended suicide prevention activities at time of discharge. CONCLUSION: The study revealed a significant gap in implementation of recommended practices related to prevention of suicide postdischarge. Additional research is needed to identify factors contributing to this implementation gap.

Characteristics of patients with non-cancer pain and long-term prescription opioid use who have used medical versus recreational marijuana.

OBJECTIVE: Marijuana use is increasingly common among patients with chronic non-cancer pain (CNCP) and long-term opioid therapy (LTOT). We determined if lifetime recreational and medical marijuana use were associated with more frequent and higher dose prescription opioid use. DESIGN: Cross-sectional SUBJECTS: Eligible patients (n=1,037), who had a new period of prescription opioid use lasting 30-90 days, were recruited from two midwestern health care systems to a study of long-term prescription opioid use and mental health outcomes. The present cross-sectional analyses uses baseline data from this on-going cohort study. METHODS: Primary exposures were participant reported lifetime recreational and medical marijuana use versus no lifetime marijuana use. Prescription opioid characteristics included daily versus non-daily opioid use and ≥50 morphine milligram equivalent (MME) dose per day vs. <50 MME. Multivariate, logistic regression models estimated the association between lifetime recreational and medical marijuana use vs. no use and odds of daily and higher dose prescription opioid use, before and after adjusting for confounding. RESULTS: The sample was an average of 54.9 (SD±11.3) years of age, 57.3% identified as female gender, 75.2% identified as White, and 22.5% identified as Black race. Among all participants, 44.4% were never marijuana users, 21.3% were recreational only, 7.7% medical only and 26.6% were both recreational and medical marijuana users. After controlling for all confounders, lifetime recreational marijuana use, as compared to no use, was significantly associated with increased odds of daily prescription opioid use (OR=1.61; 95%CI:1.02-2.54). There was no association between lifetime recreational or medical marijuana use and daily opioid dose. CONCLUSION: Lifetime medical marijuana use is not linked to current opioid dose, but lifetime recreational use is associated with more than a 60% odds of being a daily prescription opioid user. Screening for lifetime recreational marijuana use may identify patients with chronic pain who are vulnerable to daily opioid use which increases risk for adverse opioid outcomes. Prospective data is needed to determine how marijuana use influences the course of LTOT and vice versa.

Patient Perspectives on Mental Health and Pain Management Support Needed Versus Received During Opioid Deprescribing.

Prescription opioid tapering has increased significantly over the last decade. Evidence suggests that tapering too quickly or without appropriate support may unintentionally harm patients. The aim of this analysis was to understand patients' experiences with opioid tapering, including support received or not received for pain control or mental health. Patients with evidence of opioid tapering from 6 health care systems participated in semi-structured, in-depth interviews; family members of suicide decedents with evidence of opioid tapering were also interviewed. Interviews were analyzed using thematic analysis. Participants included 176 patients and 16 family members. Results showed that 24% of the participants felt their clinicians checked in with them about their taper experiences while 41% reported their clinicians did not. A majority (68%) of individuals who experienced suicide behavior during tapering reported that clinicians did check in about mood and mental health changes specifically; however, 27% of that group reported no such check-in. More individuals reported negative experiences (than positive) with pain management clinics-where patients are often referred for tapering and pain management support. Patients reporting successful tapering experiences named shared decision-making and ability to adjust taper speed or pause tapering as helpful components of care. Fifty-six percent of patients reported needing more support during tapering, including more empathy and compassion (48%) and an individualized approach to tapering (41%). Patient-centered approaches to tapering include reaching out to monitor how patients are doing, involving patients in decision-making, supporting mental health changes, and allowing for flexibility in the tapering pace. PERSPECTIVE: Patients tapering prescription opioids desire more provider-initiated communication including checking in about pain, setting expectations for withdrawal and mental health-related changes, and providing support for mental health. Patients preferred opportunities to share decisions about taper speed and to have flexibility with pausing the taper as needed.

Predicting suicide death after emergency department visits with mental health or self-harm diagnoses.

OBJECTIVE: Use health records data to predict suicide death following emergency department visits. METHODS: Electronic health records and insurance claims from seven health systems were used to: identify emergency department visits with mental health or self-harm diagnoses by members aged 11 or older; extract approximately 2500 potential predictors including demographic, historical, and baseline clinical characteristics; and ascertain subsequent deaths by self-harm. Logistic regression with lasso and random forest models predicted self-harm death over 90 days after each visit. RESULTS: Records identified 2,069,170 eligible visits, 899 followed by suicide death within 90 days. The best-fitting logistic regression with lasso model yielded an area under the receiver operating curve of 0.823 (95% CI 0.810-0.836). Visits above the 95th percentile of predicted risk included 34.8% (95% CI 31.1-38.7) of subsequent suicide deaths and had a 0.303% (95% CI 0.261-0.346) suicide death rate over the following 90 days. Model performance was similar across subgroups defined by age, sex, race, and ethnicity. CONCLUSIONS: Machine learning models using coded data from health records have moderate performance in predicting suicide death following emergency department visits for mental health or self-harm diagnosis and could be used to identify patients needing more systematic follow-up.

Short report: Transition to International Classification of Diseases, 10th Revision and the prevalence of autism in a cohort of healthcare systems.

LAY ABSTRACT: Currently, the prevalence of autism spectrum disorder (henceforth "autism") is 1 in 36, an increasing trend from previous estimates. In 2015, the United States adopted a new version (International Classification of Diseases, 10th Revision) of the World Health Organization coding system, a standard for classifying medical conditions. Our goal was to examine how the transition to this new coding system impacted autism diagnoses in 10 healthcare systems. We obtained information from electronic medical records and insurance claims data from July 2014 through December 2016 for each healthcare system. We used member enrollment data for 30 consecutive months to observe changes 15 months before and after adoption of the new coding system. Overall, the rates of autism per 1000 enrolled members was increasing for 0- to 5-year-olds before transition to International Classification of Diseases, 10th Revision and did not substantively change after the new coding was in place. There was variation observed in autism diagnoses before and after transition to International Classification of Diseases, 10th Revision for other age groups. The change to the new coding system did not meaningfully affect autism rates at the participating healthcare systems. The increase observed among 0- to 5-year-olds is likely indicative of an ongoing trend related to increases in screening for autism rather than a shift associated with the new coding.

Psychotherapy Disruption Before and After the Transition to Virtual Mental Health Care Induced by the COVID-19 Pandemic.

OBJECTIVE: This study aimed to examine population-level disruption in psychotherapy before and after the rapid shift to virtual mental health care induced by the onset of the COVID-19 pandemic in the United States. METHODS: This retrospective study used electronic health record and insurance claims data from three U.S. health systems. The sample included 110,089 patients with mental health conditions who were members of the health systems' affiliated health plans and attended at least two psychotherapy visits from June 14, 2019, through December 15, 2020. Data were subdivided into two 9-month periods (before vs. after COVID-19 onset, defined in this study as March 14, 2020). Psychotherapy visits were measured via health records and categorized as in person or virtual. Disruption was defined as a gap of >45 days between visits. RESULTS: Visits in the preonset period were almost exclusively in person (97%), whereas over half of visits in the postonset period were virtual (52%). Approximately 35% of psychotherapy visits were followed by a disruption in the preonset period, compared with 18% in the postonset period. Disruption continued to be less common (adjusted OR=0.45) during the postonset period after adjustment for visit, mental health, and sociodemographic factors. The magnitude of the difference in disruption between periods was homogeneous across sociodemographic characteristics but heterogeneous across psychiatric diagnoses. CONCLUSIONS: This study found fewer population-level disruptions in psychotherapy receipt after rapid transition to virtual mental health care following COVID-19 onset. These data support the continued availability of virtual psychotherapy.

Stability of Suicide Risk Prediction Models During Changes in Health Care Delivery.

OBJECTIVE: The authors aimed to use health records data to examine how the accuracy of statistical models predicting self-harm or suicide changed between 2015 and 2019, as health systems implemented suicide prevention programs. METHODS: Data from four large health systems were used to identify specialty mental health visits by patients ages ≥11 years, assess 311 potential predictors of self-harm (including demographic characteristics, historical risk factors, and index visit characteristics), and ascertain fatal or nonfatal self-harm events over 90 days after each visit. New prediction models were developed with logistic regression with LASSO (least absolute shrinkage and selection operator) in random samples of visits (65%) from each calendar year and were validated in the remaining portion of the sample (35%). RESULTS: A model developed for visits from 2009 to mid-2015 showed similar classification performance and calibration accuracy in a new sample of about 13.1 million visits from late 2015 to 2019. Area under the receiver operating characteristic curve (AUC) ranged from 0.840 to 0.849 in the new sample, compared with 0.851 in the original sample. New models developed for each year for 2015-2019 had classification performance (AUC range 0.790-0.853), sensitivity, and positive predictive value similar to those of the previously developed model. Models selected similar predictors from 2015 to 2019, except for more frequent selection of depression questionnaire data in later years, when questionnaires were more frequently recorded. CONCLUSIONS: A self-harm prediction model developed with 2009-2015 visit data performed similarly when applied to 2015-2019 visits. New models did not yield superior performance or identify different predictors.

Factors Associated With Interest in Engaging in Psychological Interventions for Pain Management.

OBJECTIVE: Engagement in evidence-based psychological interventions for pain management is low. Identifying characteristics associated with interest in interventions can inform approaches to increase uptake and engagement. The purpose of this study was to examine factors associated with interest in psychological interventions among persons with chronic noncancer pain receiving prescription opioids. METHODS: Participants with chronic noncancer pain and a new 30 to 90 day opioid prescription were recruited from 2 health systems. Participants (N=845) completed measures regarding pain, opioid use, psychiatric symptoms, emotional support, and interest in psychological interventions for pain management. RESULTS: There were 245 (29.0%) participants who reported a high interest in psychological interventions for pain management. In bivariate analyses, variables associated with interest included younger age, female sex, greater pain severity, greater pain interference, greater number of pain sites, lower emotional support, depression, anxiety, and post-traumatic stress disorder ( P <0.05). In a multivariate model, greater pain severity (odds ratio [OR]=1.17; CI: 1.04-1.32), depression (OR=2.10; CI: 1.39-3.16), post-traumatic stress disorder (OR=1.85; CI: 1.19-2.95), and lower emotional support (OR=0.69; CI: 0.5-0.97) remained statistically significant. DISCUSSION: The rate of interest in psychological interventions for pain management was low, which may indicate that patients initiating opioid treatment of chronic noncancer pain have low interest in psychological interventions. Greater pain severity and psychiatric distress were related to interest, and patients with these characteristics may especially benefit from psychological interventions. Providers may want to refer to psychological interventions before or when opioids are initiated. Additional work is needed to determine whether this would reduce long-term opioid use.

Racial-Ethnic Differences in Receipt of Past-Year Health Care Services Among Suicide Decedents: A Case-Control Study.

OBJECTIVE: Suicide remains an urgent public health crisis. Although some sociodemographic characteristics are associated with greater suicide risk in the general population, it is unclear whether individuals utilizing health care in the United States have similar suicide incidence patterns. The authors examined whether race-ethnicity is associated with suicide death among patients seeking health care and investigated health care utilization patterns. METHODS: Data were collected from electronic health records and government mortality records for patients seeking health care across nine health care systems in the United States. Patients who died by suicide (N=1,935) were matched with patients in a control group (N=19,350) within each health care system. RESULTS: Patients who died by suicide were significantly more likely to be White, older, male, living in low-education areas, living in rural areas, or diagnosed as having mental health conditions or were significantly less likely to have commercial insurance (p<0.05). Among most racial-ethnic groups, those who died by suicide had a higher number of past-year mental health, primary care, and total health care visits; for American Indian/Alaska Native patients, the number of health care visits tended to be lower among suicide decedents. CONCLUSIONS: These findings suggest that higher past-year health care utilization was associated with increased likelihood of suicide death across several racial-ethnic groups. This observation underscores the need for identifying and managing suicide risk in health care settings, including outside of mental health visits, among most racial-ethnic groups.

Predicting risk of suicidal behavior from insurance claims data vs. linked data from insurance claims and electronic health records.

PURPOSE: Observational studies assessing effects of medical products on suicidal behavior often rely on health record data to account for pre-existing risk. We assess whether high-dimensional models predicting suicide risk using data derived from insurance claims and electronic health records (EHRs) are superior to models using data from insurance claims alone. METHODS: Data were from seven large health systems identified outpatient mental health visits by patients aged 11 or older between 1/1/2009 and 9/30/2017. Data for the 5 years prior to each visit identified potential predictors of suicidal behavior typically available from insurance claims (e.g., mental health diagnoses, procedure codes, medication dispensings) and additional potential predictors available from EHRs (self-reported race and ethnicity, responses to Patient Health Questionnaire or PHQ-9 depression questionnaires). Nonfatal self-harm events following each visit were identified from insurance claims data and fatal self-harm events were identified by linkage to state mortality records. Random forest models predicting nonfatal or fatal self-harm over 90 days following each visit were developed in a 70% random sample of visits and validated in a held-out sample of 30%. Performance of models using linked claims and EHR data was compared to models using claims data only. RESULTS: Among 15 845 047 encounters by 1 574 612 patients, 99 098 (0.6%) were followed by a self-harm event within 90 days. Overall classification performance did not differ between the best-fitting model using all data (area under the receiver operating curve or AUC = 0.846, 95% CI 0.839-0.854) and the best-fitting model limited to data available from insurance claims (AUC = 0.846, 95% CI 0.838-0.853). Competing models showed similar classification performance across a range of cut-points and similar calibration performance across a range of risk strata. Results were similar when the sample was limited to health systems and time periods where PHQ-9 depression questionnaires were recorded more frequently. CONCLUSION: Investigators using health record data to account for pre-existing risk in observational studies of suicidal behavior need not limit that research to databases including linked EHR data.

Association of initial opioid prescription duration and an opioid refill by pain diagnosis: Evidence from outpatient settings in ten US health systems.

OBJECTIVE: The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription. METHODS: We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription. RESULTS: Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3-4 days' supply). CONCLUSIONS: Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined.

The rapid shift to virtual mental health care: Examining psychotherapy disruption by rurality status.

BACKGROUND: Given the low usage of virtual health care prior to the COVID-19 pandemic, it was unclear whether those living in rural locations would benefit from increased availability of virtual mental health care. The rapid transition to virtual services during the COVID-19 pandemic allowed for a unique opportunity to examine how the transition to virtual mental health care impacted psychotherapy disruption (i.e., 45+ days between appointments) among individuals living in rural locations compared with those living in nonrural locations. METHODS: Electronic health record and insurance claims data were collected from three health care systems in the United States including rurality status and psychotherapy disruption. Psychotherapy disruption was measured before and after the COVID-19 pandemic onset. RESULTS: Both the nonrural and rural cohorts had significant decreases in the rates of psychotherapy disruption from pre- to post-COVID-19 onset (32.5-16.0% and 44.7-24.8%, respectively, p < 0.001). The nonrural cohort had a greater reduction of in-person visits compared with the rural cohort (96.6-45.0 vs. 98.0-66.2%, respectively, p < 0.001). Among the rural cohort, those who were younger and those with lower education had greater reductions in psychotherapy disruption rates from pre- to post-COVID-19 onset. Several mental health disorders were associated with experiencing psychotherapy disruption. CONCLUSIONS: Though the rapid transition to virtual mental health care decreased the rate of psychotherapy disruption for those living in rural locations, the reduction was less compared with nonrural locations. Other strategies are needed to improve psychotherapy disruption, especially among rural locations (i.e., telephone visits).

Managed care updates of subscriber jail release to prompt community suicide prevention: clinical trial protocol.

BACKGROUND: Recent jail detention is a marker for trait and state suicide risk in community-based populations. However, healthcare providers are typically unaware that their client was in jail and few post-release suicide prevention efforts exist. This protocol paper describes an effectiveness-implementation trial evaluating community suicide prevention practices triggered by advances in informatics that alert CareSource, a large managed care organization (MCO), when a subscriber is released from jail. METHODS: This randomized controlled trial investigates two evidence-based suicide prevention practices triggered by CareSource's jail detention/release notifications, in a partial factorial design. The first phase randomizes ~ 43,000 CareSource subscribers who pass through any Ohio jail to receive Caring Contact letters sent by CareSource or to Usual Care after jail release. The second phase (running simultaneously) involves a subset of ~ 6,000 of the 43,000 subscribers passing through jail who have been seen in one of 12 contracted behavioral health agencies in the 6 months prior to incarceration in a stepped-wedge design. Agencies will receive: (a) notifications of the client's jail detention/release, (b) instructions for re-engaging these clients, and (c) training in suicide risk assessment and the Safety Planning Intervention for use at re-engagement. We will track suicide-related and service linkage outcomes 6 months following jail release using claims data. CONCLUSIONS: This design allows us to rigorously test two intervention main effects and their interaction. It also provides valuable information on the effects of system-level change and the scalability of interventions using big data from a MCO to flag jail release and suicide risk. TRIAL REGISTRATION: The trial is registered at clinicaltrials.gov (NCT05579600). Registered 27 June, 2023.

Impact of Opioid Dose Reductions on Patient-Reported Mental Health and Suicide-Related Behavior and Relationship to Patient Choice in Tapering Decisions.

Mental health and suicide-related harms resulting from prescription opioid tapering are poorly documented and understood. Six health systems contributed opioid prescribing data from January 2016 to April 2020. Patients 18 to 70 years old with evidence of opioid tapering participated in semi-structured interviews. Individuals who experienced suicide attempts were oversampled. Family members of suicide decedents who had experienced opioid tapering were also interviewed. Interviews were analyzed using thematic analysis. The study participants included 176 patients and 16 family members. Patients were 68% female, 80% White, and 15% Hispanic, mean age 58. All family members were female spouses of White, non-Hispanic male decedents. Among the subgroup (n = 60) who experienced a documented suicide attempt, reported experiencing suicidal ideation during tapering, or were family members of suicide decedents, 40% reported that opioid tapering exacerbated previously recognized mental health issues, and 25% reported that tapering triggered new-onset mental health concerns. Among participants with suicide behavior, 47% directly attributed it to opioid tapering. Common precipitants included increased pain, reduced life engagement, sleep problems, withdrawal, relationship dissolution, and negative consequences of opioid substitution with other substances for pain relief. Most respondents reporting suicide behavior felt that the decision to taper was made by the health care system or a clinician (67%) whereas patients not reporting suicide behavior were more likely to report it was their own decision (42%). This study describes patient-reported mental health deterioration or suicide behavior while tapering prescription opioids. Clinicians should screen for, monitor, and treat suicide behavior while assisting patients in tapering opioids. PERSPECTIVE: This work describes changes in patient-reported mental health and suicide behavior while tapering prescription opioids. Recommendations for improving care include mental health and suicide risk screening during and following opioid tapering.

Prescription Opioid Dose Reductions and Potential Adverse Events: a Multi-site Observational Cohort Study in Diverse US Health Systems.

BACKGROUND: In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events. OBJECTIVE: Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality). DESIGN: This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of  ≥ 50 during six consecutive months. PATIENTS: We identified 60,040 non-cancer patients with  ≥ one 2-month dose reduction period (600,234 unique dose reduction periods). MAIN MEASURES: Analyses examined associations between dose reduction levels (1- < 15%, 15- < 30%, 30- < 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics. KEY RESULTS: Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1- < 15%, dose reductions of 30- < 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09-1.81), and all-cause mortality (OR 1.39, 95% CI 1.16-1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81-0.85). Dose reductions of 15- < 30%, compared to 1- < 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05-1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92-0.95), but were not associated with opioid overdose and all-cause mortality. CONCLUSIONS: Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored.

Baseline Characteristics From a New Longitudinal Cohort of Patients With Noncancer Pain and Chronic Opioid Use in the United States.

Retrospective cohort studies have consistently observed that long-term prescription opioid use is a risk factor for new major depressive episodes. However, prospective studies are needed to confirm these findings and establish evidence for causation. The Prescription Opioids and Depression Pathways cohort study is designed for this purpose. The present report describes the baseline sample and associations between participant characteristics and odds of daily versus nondaily opioid use. Second, we report associations between participant characteristics and odds of depression, dysthymia, anhedonia, and vital exhaustion. Patients with noncancer pain were eligible if they started a new period of prescription opioid use lasting 30 to 90 days. Participants were 54.8 (standard deviation ± 11.3) years of age, 57.3% female and 73% White race. Less than college education was more common among daily versus nondaily opioid users (32.4% vs 27.3%; P = .0008), as was back pain (64.2% vs 51.3%; P < .0001), any nonopioid substance use disorder (12.8% vs 4.8%; P < .0001), and current smoking (30.7% vs 18.4% P < .0001). High pain interference (50.9% vs 28.4%; P < .0001) was significantly associated with depression, as was having more pain sites (6.9 ± 3.6 vs 5.7 ± 3.6; P < .0001), and benzodiazepine comedication (38.2% vs 23.4%; P < .0001). High pain interference was significantly more common among those with anhedonia (46.8% vs 27.4%; P < .0001), and more pain sites (7.0 ± 3.7 vs 5.6 ± 3.6; P < .0001) were associated with anhedonia. Having more pain sites (7.9 ± 3.6 vs 5.5 ± 3.50; P < .0001) was associated with vital exhaustion, as was back pain (71.9% vs 56.8%; P = .0001) and benzodiazepine comedication (42.8% vs 22.8%; P < .0001). Patients using prescription opioids for noncancer pain have complex pain, psychiatric, and substance use disorder comorbidities. Longitudinal data will reveal whether long-term opioid therapy leads to depression or other mood disturbances such as anhedonia and vital exhaustion. PERSPECTIVE: This study reports baseline characteristics of a new prospective, noncancer pain cohort study. Risk factors for adverse opioid outcomes were most common in those with depression and vital exhaustion and less common in dysthymia and anhedonia. Baseline data highlight the complexity of patients receiving long-term opioid therapy for noncancer pain.