Clozapine Use Among People With Psychotic Disorders Who Experience Specific Indications for Clozapine.

Objective: To examine rates of clozapine use among people with psychotic disorders who experience specific indications for clozapine.Methods: Records data from 11 integrated health systems identified patients aged 18 years or older with recorded International Classification of Diseases, Tenth Revision, Clinical Modification, diagnoses of schizophrenia, schizoaffective disorder, or other psychotic disorder who experienced any of the 3 events between January 1, 2019, and December 31, 2019, suggesting indications for clozapine: a diagnosis of self-harm injury or poisoning, suicidal ideation diagnosed or in response to standardized assessments, and hospitalization or emergency department (ED) care for psychotic disorder despite treatment with 2 or more antipsychotic medications. Prescription dispensing data identified all clozapine use prior to or in the 12 months following each indication event. Analyses were conducted with aggregate data from each health system; no individual data were shared.Results: A total of 7,648 patients with psychotic disorder diagnoses experienced at least 1 indication event. Among 1,097 experiencing a self-harm event, 32 (2.9%) had any prior clozapine use, and 10 (0.9%) initiated clozapine during the following 12 months. Among 6,396 with significant suicidal ideation, 238 (3.7%) had any prior clozapine use, and 70 (1.1%) initiated clozapine over 12 months. Among 881 with hospitalization or ED visit despite pharmacotherapy, 77 (8.7%) had any prior clozapine treatment, and 41 (4.7%) initiated clozapine over 12 months. Among those with significant suicidal ideation, rates of both prior clozapine treatment and subsequent initiation varied significantly by race and ethnicity, with rates among Hispanic and non-Hispanic Black patients lower than among non Hispanic White patients.Conclusions: Initiating clozapine treatment is uncommon among people with psychotic disorders who experience events suggesting clozapine is indicated, with even lower rates among Black and Hispanic patients.

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.

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.

LiveWell, a smartphone-based self-management intervention for bipolar disorder: Intervention participation and usability analysis.

BACKGROUND: Understanding how individuals utilize and perceive digital mental health interventions may improve engagement and effectiveness. To support intervention improvement, participant feedback was obtained and app use patterns were examined for a randomized clinical trial evaluating a smartphone-based intervention for individuals with bipolar disorder. METHODS: App use and coaching engagement were examined (n = 124). Feedback was obtained via exit questionnaires (week 16, n = 81) and exit interviews (week 48, n = 17). RESULTS: On average, over 48 weeks, participants used the app for 4.4 h and engaged with the coach for 3.9 h. Participants spent the most time monitoring target behaviors and receiving adaptive feedback and the least time viewing self-assessments and skills. Participants reported that the daily check in helped increase awareness of target behaviors but expressed frustration with repetitiveness of monitoring and feedback content. Participants liked personalizing their wellness plan, but its use did not facilitate skills practice. App use declined over time which participants attributed to clinical stability, content mastery, and time commitment. Participants found the coaching supportive and motivating for app use. LIMITATIONS: App engagement based on viewing time may overestimate engagement. The delay between intervention delivery and the exit interviews and low exit interview participation may introduce bias. CONCLUSION: Utilization patterns and feedback suggest that digital mental health engagement and efficacy may benefit from adaptive personalization of targets monitored combined with adaptive monitoring and feedback to support skills practice and development. Increasing engagement with supports may also be beneficial.

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.

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.

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.

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).

Beyond clinical outcomes: Case control study of the role of race in disruptive life events for people with serious mental illness.

OBJECTIVE: To understand how race and serious mental illness (SMI) interact for disruptive life events defined as financial (bankruptcy and judgement filings), and non-financial (arrests). METHODS: Patients were adults with schizophrenia (SCZ; N = 16,159) or bipolar I disorder (BPI; N = 30,008) matched 1:1 to patients without SMI (non-SMI) from health systems in Michigan and Southern California during 1/1/2007 through 12/31/2018. The main exposure was self-reported race, and the outcome was disruptive life events aggregated by Transunion. We hypothesized that Black patients with SCZ or BPI would be the most likely to experience a disruptive life event when compared to Black patients without SMI, and all White or Asian patients regardless of mental illness. RESULTS: Black patients with SCZ had the least likelihood (37% lower) and Asian patients with BPI had the greatest likelihood (2.25 times higher) of experiencing a financial disruptive life event among all patients in the study. There was no interaction of race with either SCZ or BPI for experiencing an arrest. The findings did not support our hypotheses for patients with SCZ and partially supported them for patients with BPI. CONCLUSIONS: Clinical initiatives to assess social determinants of health should consider a focus on Asian patients with BPI.

Suicide attempts after bariatric surgery: comparison to a nonsurgical cohort of individuals with severe obesity.

BACKGROUND: The rate of suicide is higher among individuals following bariatric surgery compared with the general population; however, it is not clear whether risk is associated with bariatric surgery beyond having severe obesity. OBJECTIVE: To compare the risk of a suicide attempt among those who had bariatric surgery versus a nonsurgical cohort with severe obesity. SETTING: Aggregate count data were collected from 5 healthcare systems. METHODS: Individuals were identified in the surgical cohort if they underwent bariatric surgery between 2009 and 2017 (n = 35,522) and then were compared with a cohort of individuals with severe obesity who never had bariatric surgery (n = 691,752). Suicide attempts were identified after study enrollment date using International Classification of Diseases, Ninth and Tenth Editions (ICD-9 and ICD-10) diagnosis codes from 2009 to 2021. RESULTS: The relative risk of a suicide attempt was 64% higher in the cohort with bariatric surgery than that of the nonsurgical cohort (2.2% versus 1.3%; relative risk = 1.64; 95% CI, 1.53-1.76). Within the cohort with bariatric surgery, suicide attempts were more common among the 18- to 39-year age group (P < .001), women (P = .002), Hawaiian-Pacific Islanders (P < .001), those with Medicaid insurance (P < .001), and those with a documented mental health condition at baseline (in the previous 2 years; P < .001). CONCLUSIONS: The relative risk of suicide attempts was higher among those who underwent bariatric surgery compared with a nonsurgical cohort, though absolute risk remained low. Providers should be aware of this increased risk. Screening for suicide risk after bariatric surgery may be useful to identify high-risk individuals.

Association Between Adverse Social Determinants of Health and Suicide Death.

OBJECTIVE: The aim of this study was to identify adverse social determinants of health (SDoH) International Statistical Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code prevalence among individuals who died by suicide and to examine associations between documented adverse SDoH and suicide. RESEARCH DESIGN: A case-control study using linked medical record, insurance claim, and mortality data from 2000 to 2015 obtained from 9 Mental Health Research Network-affiliated health systems. We included 3330 individuals who died by suicide and 333,000 randomly selected controls matched on index year and health system location. All individuals in the study (cases and controls) had at least 10 months of enrollment before the study index date. The index date for the study for each case and their matched controls was the suicide date for that given case. RESULTS: Adverse SDoH documentation was low; only 6.6% of cases had ≥1 documented adverse SDoH in the year before suicide. Any documented SDoH and several specific adverse SDoH categories were more frequent among cases than controls. Any documented adverse SDoH was associated with higher suicide odds [adjusted odds ratio (aOR)=2.76; 95% CI: 2.38-3.20], as was family alcoholism/drug addiction (aOR=18.23; 95% CI: 8.54-38.92), being an abuse victim/perpetrator (aOR=2.53; 95% CI: 1.99-3.21), other primary support group problems (aOR=1.91; 95% CI: 1.32-2.75), employment/occupational maladjustment problems (aOR=8.83; 95% CI: 5.62-13.87), housing/economic problems (aOR: 6.41; 95% CI: 4.47-9.19), legal problems (aOR=27.30; 95% CI: 12.35-60.33), and other psychosocial problems (aOR=2.58; 95% CI: 1.98-3.36). CONCLUSIONS: Although documented SDoH prevalence was low, several adverse SDoH were associated with increased suicide odds, supporting calls to increase SDoH documentation in medical records. This will improve understanding of SDoH prevalence and assist in identification and intervention among individuals at high suicide risk.

Differential Effects of an Intervention to Reduce Cardiovascular Risk for Patients With Bipolar Disorder, Schizoaffective Disorder, or Schizophrenia: A Randomized Clinical Trial.

Objective: To measure the impact of a clinical decision support (CDS) tool on total modifiable cardiovascular risk at 12 months separately for outpatients with 3 subtypes of serious mental illness (SMI) identified via ICD-9 and ICD-10 codes: bipolar disorder, schizoaffective disorder, and schizophrenia.Methods: This cluster-randomized pragmatic clinical trial was active from March 2016 to September 2018; data were analyzed from April 2021 to September 2022. Clinicians and patients from 78 primary care clinics participated. All 8,922 adult patients aged 18-75 years with diagnosed SMI, at least 1 cardiovascular risk factor not at goal, and an index and follow-up visit during the study period were included. The CDS tool provided a summary of modifiable cardiovascular risk and personalized treatment recommendations.Results: Intervention patients had 4% relative reduction in total modifiable cardiovascular risk at 12 months compared to controls (relative risk ratio = 0.96; 95% CI, 0.94 to 0.98), with similar intervention benefits for all 3 SMI subtypes. At index, 10-year cardiovascular risk was higher for patients with schizophrenia (mean [SD] = 11.3% [9.2%]) than for patients with bipolar disorder (8.5% [8.9%]) or schizoaffective disorder (9.4% [8.1%]), while 30-year cardiovascular risk was highest for patients with schizoaffective disorder (44% with 2 or more major cardiovascular risk factors, compared to 40% for patients with schizophrenia and 37% for patients with bipolar disorder). Smoking was highly prevalent (47%), and mean (SD) BMI was 32.7 (7.9).Conclusions: This CDS intervention produced a clinically and statistically significant 4% relative reduction in total modifiable cardiovascular risk for intervention patients versus controls at 12 months, an effect observed across all 3 SMI subtypes and attributable to the aggregate impact of small changes in multiple cardiovascular risk factors.Trial Registration: ClinicalTrials.gov Identifier: NCT02451670.

Assessment of Disruptive Life Events for Individuals Diagnosed With Schizophrenia or Bipolar I Disorder Using Data From a Consumer Credit Reporting Agency.

Importance: There is a dearth of population-level data on major disruptive life events (defined here as arrests by a legal authority, address changes, bankruptcy, lien, and judgment filings) for patients with bipolar I disorder (BPI) or schizophrenia, which has limited studies on mental health and treatment outcomes. Objective: To conduct a population-level study on disruptive life events by using publicly available data on disruptive life events, aggregated by a consumer credit reporting agency in conjunction with electronic health record (EHR) data. Design, Setting, and Participants: This study used EHR data from 2 large, integrated health care systems, Kaiser Permanente Southern California and Henry Ford Health. Cohorts of patients diagnosed from 2007 to 2019 with BPI or schizophrenia were matched 1:1 by age at analysis, age at diagnosis (if applicable), sex, race and ethnicity, and Medicaid status to (1) an active comparison group with diagnoses of major depressive disorder (MDD) and (2) a general health (GH) cohort without diagnoses of BPI, schizophrenia, or MDD. Patients with diagnoses of BPI or schizophrenia and their respective comparison cohorts were matched to public records data aggregated by a consumer credit reporting agency (98% match rate). Analysis took place between November 2020 and December 2022. Main Outcomes and Measures: The differences in the occurrence of disruptive life events among patients with BPI or schizophrenia and their comparison groups. Results: Of 46 167 patients, 30 008 (65%) had BPI (mean [SD] age, 42.6 [14.2] years) and 16 159 (35%) had schizophrenia (mean [SD], 41.4 [15.1] years). The majoriy of patients were White (30 167 [65%]). In addition, 18 500 patients with BPI (62%) and 6552 patients with schizophrenia (41%) were female. Patients with BPI were more likely to change addresses than patients in either comparison cohort (with the incidence ratio being as high as 1.25 [95% CI, 1.23-1.28]) when compared with GH cohort. Patients with BPI were also more likely to experience any of the financial disruptive life events with odds ratio ranging from 1.15 [95% CI, 1.07-1.24] to 1.50 [95% CI, 1.42-1.58]). The largest differences in disruptive life events were seen in arrests of patients with either BPI or schizophrenia compared with GH peers (3.27 [95% CI, 2.84-3.78] and 3.04 [95% CI, 2.57-3.59], respectively). Patients with schizophrenia had fewer address changes and were less likely to experience a financial event than their matched comparison cohorts. Conclusions and Relevance: This study demonstrated that data aggregated by a consumer credit reporting agency can support population-level studies on disruptive life events among patients with BPI or schizophrenia.

Diagnosed Posttraumatic Stress Disorder and Other Trauma-Associated Stress Disorders and Risk for Suicide Mortality.

OBJECTIVE: Strong evidence exists for posttraumatic stress disorder (PTSD) as a risk factor for suicidal thoughts and behaviors across diverse populations. However, few empirical studies have examined PTSD and other trauma-associated stress disorders as risk factors for suicide mortality among health system populations. This study aimed to assess trauma-associated stress diagnoses as risk factors for suicide mortality in a U.S. health system population. METHODS: This case-control, matched-design study examined individuals who died by suicide between 2000 and 2015 and had received care from nine U.S. health systems affiliated with the Mental Health Research Network (N=3,330). Individuals who died by suicide were matched with individuals from the general health system population (N=333,000): 120 individuals with PTSD who died by suicide were matched with 1,592 control group members, 84 with acute reaction to stress were matched with 2,218 control individuals, and 331 with other stress reactions were matched with 8,174 control individuals. RESULTS: After analyses were adjusted for age and sex, individuals with any trauma-associated stress condition were more likely to have died by suicide. Risk was highest among individuals with PTSD (adjusted OR [AOR]=10.10, 95% CI=8.31-12.27), followed by those with other stress reactions (AOR=5.38, 95% CI=4.78-6.06) and those with acute reaction to stress (AOR=4.49, 95% CI=3.58-5.62). Patterns of risk remained the same when the analyses were adjusted for any comorbid psychiatric condition. CONCLUSIONS: All trauma-associated stress disorders are risk factors for suicide mortality, highlighting the importance of health system suicide prevention protocols that consider the full spectrum of traumatic stress diagnoses.

Assessing the differential item functioning of PHQ-9 items for diverse racial and ethnic adults with mental health and/or substance use disorder diagnoses: A retrospective cohort study.

BACKGROUND: Improving health equity in depression care and suicide screening requires that measures like the Patient Health Questionnaire 9 (PHQ-9) function similarly for diverse racial and ethnic groups. We evaluated PHQ-9 differential item functioning (DIF) between racial/ethnic groups in a retrospective cohort study of secondary electronic health record (EHR) data from eight healthcare systems. METHODS: The population (n = 755,156) included patients aged 18-64 with mental health and/or substance use disorder (SUD) diagnoses who had a PHQ-9 with no missing item data in the EHR for primary care or mental health visits between 1/1/2009-9/30/2017. We drew two random samples of 1000 from the following racial/ethnic groups originally recorded in EHRs (n = 14,000): Hispanic, and non-Hispanic White, Black, Asian, American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, multiracial. We assessed DIF using iterative hybrid ordinal logistic regression and item response theory with p < 0.01 and 1000 Monte Carlo simulations, where change in model R2 > 0.01 represented non-negligible (e.g., clinically meaningful) DIF. RESULTS: All PHQ-9 items displayed statistically significant, but negligible (e.g., clinically unmeaningful) DIF between compared groups. The negligible DIF varied between random samples, although six items showed negligible DIF between the same comparison groups in both random samples. LIMITATIONS: Our findings may not generalize to disaggregated racial/ethnic groups or persons without mental health and/or SUD diagnoses. CONCLUSIONS: We found the PHQ-9 had clinically unmeaningful cross-cultural DIF for adult patients with mental health and/or SUD diagnoses. Future research could disaggregate race/ethnicity to discern if within-group identification impacts PHQ-9 DIF.

Complex modeling with detailed temporal predictors does not improve health records-based suicide risk prediction.

Suicide risk prediction models can identify individuals for targeted intervention. Discussions of transparency, explainability, and transportability in machine learning presume complex prediction models with many variables outperform simpler models. We compared random forest, artificial neural network, and ensemble models with 1500 temporally defined predictors to logistic regression models. Data from 25,800,888 mental health visits made by 3,081,420 individuals in 7 health systems were used to train and evaluate suicidal behavior prediction models. Model performance was compared across several measures. All models performed well (area under the receiver operating curve [AUC]: 0.794-0.858). Ensemble models performed best, but improvements over a regression model with 100 predictors were minimal (AUC improvements: 0.006-0.020). Results are consistent across performance metrics and subgroups defined by race, ethnicity, and sex. Our results suggest simpler parametric models, which are easier to implement as part of routine clinical practice, perform comparably to more complex machine learning methods.

A randomized controlled trial of an intervention to reduce stigma toward people with opioid use disorder among primary care clinicians.

BACKGROUND: Many primary care clinicians (PCCs) hold stigma toward people with opioid use disorder (OUD), which may be a barrier to care. Few interventions exist to address PCC stigma toward people with OUD. This study examined whether an online training incorporating patient narratives reduced PCCs' stigma toward people with OUD (primary) and increased intentions to treat people with OUD compared to an attention-control training (secondary). METHODS: PCCs from 15 primary care clinics were invited to complete a 30 min online training for an electronic health record-embedded clinical decision support (CDS) tool that alerts PCCs to screen, diagnose, and treat people with OUD. PCCs were randomized to receive a stigma-reduction version of the training with patient narrative videos or a control training without patient narratives and were blinded to group assignment. Immediately after the training, PCCs completed surveys of stigma towards people with OUD and intentions and willingness to treat OUD. CDS tool use was monitored for 6 months. Analyses included independent samples t-tests, Pearson correlations, and logistic regression. RESULTS: A total of 162 PCCs were randomized; 88 PCCs (58% female; 68% white) completed the training (Stigma = 48; Control = 40) and were included in analyses. There was no significant difference between intervention and control groups for stigma (t = - 0.48, p = .64, Cohen's d = - 0.11), intention to get waivered (t = 1.11, p = .27, d = 0.26), or intention to prescribe buprenorphine if a waiver were no longer required (t = 0.90, p = 0.37, d = 0.21). PCCs who reported greater stigma reported lower intentions both to get waivered (r = - 0.25, p = 0.03) and to prescribe buprenorphine with no waiver (r = - 0.25, p = 0.03). Intervention group and self-reported stigma were not significantly related to CDS tool use. CONCLUSIONS: Stigma toward people with OUD may require more robust intervention than this brief training was able to accomplish. However, stigma was related to lower intentions to treat people with OUD, suggesting stigma acts as a barrier to care. Future work should identify effective interventions to reduce stigma among PCCs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04867382. Registered 30 April 2021-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04867382.