Acceptability of linking individual credit, financial, and public records data to healthcare records for suicide risk machine learning models.

Objectives: Individual-level information about negative life events (NLE) such as bankruptcy, foreclosure, divorce, and criminal arrest might improve the accuracy of machine learning models for suicide risk prediction. Individual-level NLE data is routinely collected by vendors such as Equifax. However, little is known about the acceptability of linking this NLE data to healthcare data. Our objective was to assess preferences for linking external NLE data to healthcare records for suicide prevention. Materials and Methods: We conducted a discrete choice experiment (DCE) among Kaiser Permanente Washington (KPWA) members. Patient partners assisted in the design and pretesting of the DCE survey. The DCE included 12 choice tasks involving 4 data linking program attributes and 3 levels within each attribute. We estimated latent class conditional logit models to derive preference weights. Results: There were 743 participants. Willingness to link data varied by type of information to be linked, demographic characteristics, and experience with NLE. Overall, 65.1% of people were willing to link data and 34.9% were more private. Trust in KPWA to safeguard data was the strongest predictor of willingness to link data. Discussion: Most respondents supported linking NLE data for suicide prevention. Contrary to expectations, People of Color and people who reported experience with NLEs were more likely to be willing to link their data. Conclusions: A majority of participants were willing to have their credit and public records data linked to healthcare records provided that conditions are in place to protect privacy and autonomy.

Importance of variables from different time frames for predicting self-harm using health system data.

Objective: Self-harm risk prediction models developed using health system data (electronic health records and insurance claims information) often use patient information from up to several years prior to the index visit when the prediction is made. Measurements from some time periods may not be available for all patients. Using the framework of algorithm-agnostic variable importance, we study the predictive potential of variables corresponding to different time horizons prior to the index visit and demonstrate the application of variable importance techniques in the biomedical informatics setting. Materials and Methods: We use variable importance to quantify the potential of recent (up to three months before the index visit) and distant (more than one year before the index visit) patient mental health information for predicting self-harm risk using data from seven health systems. We quantify importance as the decrease in predictiveness when the variable set of interest is excluded from the prediction task. We define predictiveness using discriminative metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and positive predictive value. Results: Mental health predictors corresponding to the three months prior to the index visit show strong signal of importance; in one setting, excluding these variables decreased AUC from 0.85 to 0.77. Predictors corresponding to more distant information were less important. Discussion: Predictors from the months immediately preceding the index visit are highly important. Implementation of self-harm prediction models may be challenging in settings where recent data are not completely available (e.g., due to lags in insurance claims processing) at the time a prediction is made. Conclusion: Clinically derived variables from different time frames exhibit varying levels of importance for predicting self-harm. Variable importance analyses can inform whether and how to implement risk prediction models into clinical practice given real-world data limitations. These analyses be applied more broadly in biomedical informatics research to provide insight into general clinical risk prediction tasks.

Making Pragmatic Clinical Trials More Pragmatic.

This Viewpoint discusses pragmatic trials and their role in developing new knowledge that can be broadly applicable throughout the health care system.

Autism Diagnosis Among US Children and Adults, 2011-2022.

Importance: An improved understanding of autism spectrum disorder (ASD) prevalence over time and across the lifespan can inform health care service delivery for the growing population of autistic children and adults. Objective: To describe trends in the prevalence of ASD diagnoses using electronic records data from a large network of health systems in the US. Design, Setting, and Participants: This cross-sectional study examined annual diagnosis rates in health records of patients in US health systems from January 1, 2011, to December 31, 2022. Eligible individuals were included in the study sample for a given calendar year if they were enrolled in a participating health system for at least 10 months out of the year. Data were extracted from 12 sites participating in the Mental Health Research Network, a consortium of research centers embedded within large, diverse health care systems. Main Outcome and Measures: Diagnoses of ASD were ascertained using International Classification of Diseases, Ninth Revision (ICD-9) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) revision codes. Annual diagnosis rates were calculated as the number of unique members diagnosed, divided by the total members enrolled. Results: A total of 12 264 003 members were enrolled in 2022 (2 359 359 children aged 0 to 17 years [19.2%]; 6 400 222 female [52.2%]; 93 002 American Indian or Alaska Native [0.8%], 1 711 950 Asian [14.0%], 952 287 Black or African American [7.8%], 2 971 355 Hispanic [24.2%], 166 144 Native Hawaiian or Pacific Islander [1.4%], and 6 462 298 White [52.7%]). The ASD diagnosis rate was greatest among 5-to-8-year-olds throughout the study period and increased by 175% among the full sample, from 2.3 per 1000 in 2011 to 6.3 per 1000 in 2022. The greatest relative increase in diagnosis rate from 2011 to 2022 occurred among 26-to-34-year-olds (450%) and increases were greater for female vs male individuals among children (305% [estimated annual percentage change (EAPC), 13.62 percentage points; 95% CI, 12.49-14.75 percentage points] vs 185% [EAPC, 9.63 percentage points; 95% CI, 8.54-10.72 percentage points], respectively) and adults (315% [EAPC, 13.73 percentage points; 95% CI, 12.61-14.86 percentage points] vs 215% [EAPC, 10.33 percentage points; 95% CI, 9.24-11.43 percentage points]). Relative increases were greater in racial and ethnic minority groups compared with White individuals among children, but not adults. Conclusions and Relevance: In this cross-sectional study of children and adults in the US, ASD diagnosis rates increased substantially between 2011 and 2022, particularly among young adults, female children and adults, and children from some racial or ethnic minority groups. Diagnosis prevalence trends generated using health system data can inform the allocation of resources to meet the service needs of this growing, medically complex population.

Safer and targeted use of antipsychotics in youth: an embedded, pragmatic randomized trial.

BACKGROUND: Antipsychotic medications (AP) are inappropriately prescribed to young people. The goal of this pragmatic trial was to test a four-component approach to improved targeting of antipsychotic prescribing to people aged ≥3 and <18 years. METHODS: Clinicians in four health systems were cluster randomized by the number of previous AP orders and service line - specialty mental health and all others. Intervention arm clinicians received a best practice alert and child psychiatrist consultation and feedback. Families received system navigation and expedited access to psychotherapy. Primary outcomes were total days' supply of AP medication and proportion of youth with any AP supply at 6 months. We estimated the log-odds of AP use at 6 months and the relative rate of AP over 6 months. The Safer and Targeted Use of Antipsychotics in Youth (SUAY) trial took place between 3/2018 and 12/2020. RESULTS: The trial enrolled 733 patients. The odds ratio (OR) comparing use at 6 months was 0.75 (95% CI: 0.52, 1.09). The mean number of days using AP was 118.5 for intervention patients and 128.2 for control patients (relative risk [RR] = 0.92; 95% CI: 0.81-1.04). Exploratory heterogeneity of treatment effects (HTE) was not detected in groups defined by age, gender, provider specialty, and insurance type. HTE by race/ethnicity was present: among youth of color, mean days' supply was 103.2 for intervention arm and 131.2 for the control arm (RR 0.79, 95% CI: 0.67-0.93). Among secondary outcomes, only new psychotherapy referrals differed with 44.3% (n = 154) of intervention participants having a new order for psychotherapy compared to 33.5% (n = 129) in the control arm (OR 1.47: 95% CI: 1.01-2.14). CONCLUSIONS: This intervention did not result in less AP use at 6 months or a reduction in the days' supply of AP medication, although psychotherapy orders increased. The intervention may be effective for some subgroups.

Recorded Diagnosis of Gender Identity Disorder Is Strongly Associated with Suicide Mortality.

We assessed the association between gender identity disorder (GID) diagnosis and suicide in a retrospective case-control study (N=300,364) from nine health care systems between 2000 and 2015. Adjusting for age and sex, the odds ratio for GID was 18.6 (95% confidence interval 7.0-49.5). Adjusting additionally for comorbid psychiatric diagnoses, the odds ratio was 4.75 (1.78-12.68), higher than depressive (3.96, 3.64-4.31), alcohol use (3.42, 3.04-3.84), bipolar (2.42, 2.10-2.80), and psychotic disorders (1.44, 1.22-1.70). These U.S. data support prior research demonstrating increased suicide risk among patients with diagnosed GID, who may benefit from targeted screening and intervention within health care systems.

Use of ICD-10-CM Codes for Adverse Social Determinants of Health Across Health Systems.

OBJECTIVE: This study investigated ICD-10-CM codes for adverse social determinants of health (SDoH) across 12 U.S. health systems by using data from multiple health care encounter types for diverse patients covered by multiple payers. METHODS: The authors described documentation of 11 SDoH ICD-10-CM code categories (e.g., educational problems or social environmental problems) between 2016 and 2021; assessed changes over time by using chi-square tests for trend in proportions; compared documentation in 2021 by gender, age, race-ethnicity, and site with chi-square tests; and compared all patients' mental health outcomes in 2021 with those of patients with documented SDoH ICD-10-CM codes by using exact binomial tests and one-proportion z tests. RESULTS: Documentation of any SDoH ICD-10-CM code significantly increased, from 1.7% of patients in 2016 to 2.7% in 2021, as did that for all SDoH categories except educational problems. Documentation was often more prevalent among female patients and those of other or unknown gender than among male patients and among American Indian or Alaska Native, Black or African American, and Hispanic individuals than among those belonging to other race-ethnicity categories. More educational problems were documented for younger patients, and more social environmental problems were documented for older patients. Psychiatric diagnoses and emergency department visits and hospitalizations related to mental health were more common among patients with documented SDoH codes. CONCLUSIONS: SDoH ICD-10-CM code documentation was infrequent and differed by population subgroup. Differences may reflect documentation practices or true SDoH prevalence variation. Standardized SDoH documentation methods are needed in health care settings.

Effectiveness of Integrating Suicide Care in Primary Care : Secondary Analysis of a Stepped-Wedge, Cluster Randomized Implementation Trial.

BACKGROUND: Primary care encounters are common among patients at risk for suicide. OBJECTIVE: To evaluate the effectiveness of implementing population-based suicide care (SC) in primary care for suicide attempt prevention. DESIGN: Secondary analysis of a stepped-wedge, cluster randomized implementation trial. (ClinicalTrials.gov: NCT02675777). SETTING: 19 primary care practices within a large health care system in Washington State, randomly assigned launch dates. PATIENTS: Adult patients (aged ≥18 years) with primary care visits from January 2015 to July 2018. INTERVENTION: Practice facilitators, electronic medical record (EMR) clinical decision support, and performance monitoring supported implementation of depression screening, suicide risk assessment, and safety planning. MEASUREMENTS: Clinical practice and patient measures relied on EMR and insurance claims data to compare usual care (UC) and SC periods. Primary outcomes included documented safety planning after population-based screening and suicide risk assessment and suicide attempts or deaths (with self-harm intent) within 90 days of a visit. Mixed-effects logistic models regressed binary outcome indicators on UC versus SC, adjusted for randomization stratification and calendar time, accounting for repeated outcomes from the same site. Monthly outcome rates (percentage per 10 000 patients) were estimated by applying marginal standardization. RESULTS: During UC, 255 789 patients made 953 402 primary care visits and 228 255 patients made 615 511 visits during the SC period. The rate of safety planning was higher in the SC group than in the UC group (38.3 vs. 32.8 per 10 000 patients; rate difference, 5.5 [95% CI, 2.3 to 8.7]). Suicide attempts within 90 days were lower in the SC group than in the UC group (4.5 vs. 6.0 per 10 000 patients; rate difference, -1.5 [CI, -2.6 to -0.4]). LIMITATION: Suicide care was implemented in combination with care for depression and substance use. CONCLUSION: Implementation of population-based SC concurrent with a substance use program resulted in a 25% reduction in the suicide attempt rate in the 90 days after primary care visits. PRIMARY FUNDING SOURCE: National Institute of Mental Health.

Influenza and COVID-19 Vaccine Uptake Among Individuals With Versus Without Diagnosed Psychiatric Disorders.

OBJECTIVE: The authors sought to examine influenza and COVID-19 vaccine uptake among individuals diagnosed as having psychiatric disorders compared with those without such diagnoses and to examine variations in vaccine uptake by sociodemographic and clinical characteristics. METHODS: The study was conducted in the Kaiser Permanente Georgia, Washington, and Southern California health care systems. Individuals with psychiatric conditions had at least one diagnosis of any psychiatric disorder during a 12-month study period; individuals in the control group had no psychiatric disorder diagnoses during this period, and the two groups were matched on age and sex. Bivariate analyses were conducted with Pearson chi-square tests; multivariate analyses were used to calculate the odds of receiving an influenza vaccine (N=1,307,202 individuals) or COVID-19 vaccine (N=1,380,894 individuals) and were controlled for selected covariates. RESULTS: After controlling for relevant confounders, the authors found that having a diagnosis of any psychiatric illness was associated with significantly increased odds of receiving an influenza vaccine (OR=1.18; 95% CI=1.17-1.19, p<0.001), compared with no diagnosis of a psychiatric disorder. Having any psychiatric illness was associated with decreased odds of receiving a COVID-19 vaccine (OR=0.97; 95% CI=0.96-0.98, p<0.001), after the analysis was controlled for the same covariates. CONCLUSIONS: The findings provide evidence that people with mental health conditions were more likely to receive an influenza vaccine but were less likely to receive a COVID-19 vaccine, compared with individuals without such conditions. However, the vaccination rates observed for individuals with and without diagnosed psychiatric conditions were below national benchmarks, suggesting room for improving vaccine uptake in both patient populations.

Development and Validation of Electronic Health Record Measures of Safety Planning Practices as Part of Zero Suicide Implementation.

OBJECTIVE: Safety planning for suicide prevention is an important quality metric for Zero Suicide implementation. We describe the development, validation, and application of electronic health record (EHR) programs to measure uptake of safety planning practices across six integrated healthcare systems as part of a Zero Suicide evaluation study. METHODS: Safety planning was documented in narrative notes and structured EHR templates using the Stanley Brown Safety Planning Intervention (SBSPI) in response to a high-risk cutoff score on the Columbia Suicide Severity Rating Scale (CSSRS). Natural Language Processing (NLP) metrics were developed and validated using chart review to characterize practices documented in narrative notes. We applied NLP to measure frequency of documentation in the narrative text and standard programming methods to examine structured SBSPI templates from 2010-2022. RESULTS: Chart reviews found three safety planning practices documented in narrative notes that were delivered to at least half of patients at risk: professional contacts, lethal means counseling for firearms, and lethal means counseling for medication access/storage. NLP methods were developed to identify these practices in clinical text with high levels of accuracy (Sensitivity, Specificity, & PPV ≥ 82%). Among visits with a high-risk CSSRS, 40% (Range 2-73% by health system) had an SBSPI template within 1 year of implementation. CONCLUSIONS: This is one of the first reports describing development of measures that leverage electronic health records to track use of suicide prevention safety plans. There are opportunities to use the methods developed here in future evaluations of safety planning.

Measuring safety planning delivery in real-world systems to understand quality of suicide prevention care is challenging.Natural Language Processing (NLP) methods effectively identified some safety planning practices in electronic health records (EHR) from all notes ensuring a comprehensive measurement, but NLP will require updates/testing for local documentation practices.Structured safety planning templates in the EHR using the Stanley Brown Safety Planning Intervention improve ease and accuracy of measurement but may be less comprehensive than NLP for capturing all instances of safety planning documentation.

Psychotherapy Engagement Before and After a Rapid Transition to Telehealth During COVID-19 for Older Adults With Dementia.

Objective: To understand the impact of the transition to telehealth during COVID-19 on psychotherapy visits for patients with dementia. Method: Retrospective study of older adults with dementia who had at least one psychotherapy visit in the 9 months before and after the onset of COVID-19 at 3 U.S. health systems. Care disruptions were gaps of 45+ days. Descriptive statistics and logistic mixed-effects models examined factors associated with care disruption. Results: 4953 patients with dementia made 19,902 psychotherapy visits. Gaps in psychotherapy were less frequent during COVID-19 (29.4%) than before (48.9%), with the odds of a patient experiencing a care disruption during COVID-19 0.54 times the odds prior to COVID-19 (95% CI: 0.50-0.59). Almost all patient subgroups had lower adjusted odds of care disruption during COVID-19. Discussion: There were fewer disruptions in psychotherapy care following the rapid shift to virtual care. Telehealth may be a viable option for patients with dementia.

Management of Depression in Adults: A Review.

Importance: Approximately 9% of US adults experience major depression each year, with a lifetime prevalence of approximately 17% for men and 30% for women. Observations: Major depression is defined by depressed mood, loss of interest in activities, and associated psychological and somatic symptoms lasting at least 2 weeks. Evaluation should include structured assessment of severity as well as risk of self-harm, suspected bipolar disorder, psychotic symptoms, substance use, and co-occurring anxiety disorder. First-line treatments include specific psychotherapies and antidepressant medications. A network meta-analysis of randomized clinical trials reported cognitive therapy, behavioral activation, problem-solving therapy, interpersonal therapy, brief psychodynamic therapy, and mindfulness-based psychotherapy all had at least medium-sized effects in symptom improvement over usual care without psychotherapy (standardized mean difference [SMD] ranging from 0.50 [95% CI, 0.20-0.81] to 0.73 [95% CI, 0.52-0.95]). A network meta-analysis of randomized clinical trials reported 21 antidepressant medications all had small- to medium-sized effects in symptom improvement over placebo (SMD ranging from 0.23 [95% CI, 0.19-0.28] for fluoxetine to 0.48 [95% CI, 0.41-0.55] for amitriptyline). Psychotherapy combined with antidepressant medication may be preferred, especially for more severe or chronic depression. A network meta-analysis of randomized clinical trials reported greater symptom improvement with combined treatment than with psychotherapy alone (SMD, 0.30 [95% CI, 0.14-0.45]) or medication alone (SMD, 0.33 [95% CI, 0.20-0.47]). When initial antidepressant medication is not effective, second-line medication treatment includes changing antidepressant medication, adding a second antidepressant, or augmenting with a nonantidepressant medication, which have approximately equal likelihood of success based on a network meta-analysis. Collaborative care programs, including systematic follow-up and outcome assessment, improve treatment effectiveness, with 1 meta-analysis reporting significantly greater symptom improvement compared with usual care (SMD, 0.42 [95% CI, 0.23-0.61]). Conclusions and Relevance: Effective first-line depression treatments include specific forms of psychotherapy and more than 20 antidepressant medications. Close monitoring significantly improves the likelihood of treatment success.

Variation in completeness of coding external cause of injuries under ICD-10-CM.

INTRODUCTION: Information about causes of injury is key for injury prevention efforts. Historically, cause-of-injury coding in clinical practice has been incomplete due to the need for extra diagnosis codes in the International Classification of Diseases-Ninth Revision-Clinical Modification (ICD-9-CM) coding. The transition to ICD-10-CM and increased use of clinical support software for diagnosis coding is expected to improve completeness of cause-of-injury coding. This paper assesses the recording of external cause-of-injury codes specifically for those diagnoses where an additional code is still required. METHODS: We used electronic health record and claims data from 10 health systems from October 2015 to December 2021 to identify all inpatient and emergency encounters with a primary diagnosis of injury. The proportion of encounters that also included a valid external cause-of-injury code is presented. RESULTS: Most health systems had high rates of cause-of-injury coding: over 85% in emergency departments and over 75% in inpatient encounters with primary injury diagnoses. However, several sites had lower rates in both settings. State mandates were associated with consistently high external cause recording. CONCLUSIONS: Completeness of cause-of-injury coding improved since the adoption of ICD-10-CM coding and increased slightly over the study period at most sites. However, significant variation remained, and completeness of cause-of-injury coding in any diagnosis data used for injury prevention planning should be empirically determined.

Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings.

OBJECTIVES: To evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiology reports of Emergency Department patients. To assess appropriateness of artificial intelligence (AI)-generated, patient-facing summaries of these findings. MATERIALS AND METHODS: Radiology reports extracted from the electronic health record of a large academic medical center were manually reviewed to identify non-emergent, incidental findings with high likelihood of requiring follow-up, further sub-stratified as "definitely actionable" (DA) or "possibly actionable-clinical correlation" (PA-CC). Instruction prompts to GPT-4 were developed and iteratively optimized using a validation set of 50 reports. The optimized prompt was then applied to a test set of 430 unseen reports. GPT-4 performance was primarily graded on accuracy identifying either DA or PA-CC findings, then secondarily for DA findings alone. Outputs were reviewed for hallucinations. AI-generated patient-facing summaries were assessed for appropriateness via Likert scale. RESULTS: For the primary outcome (DA or PA-CC), GPT-4 achieved 99.3% recall, 73.6% precision, and 84.5% F-1. For the secondary outcome (DA only), GPT-4 demonstrated 95.2% recall, 77.3% precision, and 85.3% F-1. No findings were "hallucinated" outright. However, 2.8% of cases included generated text about recommendations that were inferred without specific reference. The majority of True Positive AI-generated summaries required no or minor revision. CONCLUSION: GPT-4 demonstrates proficiency in detecting actionable, incidental findings after refined instruction prompting. AI-generated patient instructions were most often appropriate, but rarely included inferred recommendations. While this technology shows promise to augment diagnostics, active clinician oversight via "human-in-the-loop" workflows remains critical for clinical implementation.

Patient perspectives for improving treatment initiation for new episodes of depression in historically minoritized racial and ethnic groups.

OBJECTIVE: Depression is one of the costliest and most prevalent health conditions in the U.S. with 21 million adults having experienced at least one major depressive episode. Despite the availability of evidence-based treatments for depression, a large proportion of people with new diagnoses fail to initiate formal mental health treatment. Although individuals across all racial and ethnic groups fail to initiate treatment for depression, historically minoritized racial/ethnic groups are at even greater risk. METHOD: Thirty-four participants representing historically underserved racial and ethnic populations from two large health care systems in the U.S. participated in qualitative interviews or focus group to identify factors that impede and facilitate depression treatment initiation in primary care settings. RESULTS: Participants identified individual and systemic barriers and facilitators of treatment initiation for depression and suggested several ideas for increasing treatment engagement (i.e., increased communication and education from providers, community events, information on social media). CONCLUSION: Novel interventions are needed to improve treatment initiation following initial diagnosis of depression in primary care settings. Findings from this study offer suggestions for improving treatment initiation in traditionally underserved communities.

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.

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.

Sulcal pits of the superior temporal sulcus in schizophrenia patients with auditory verbal hallucinations.

Auditory verbal hallucinations (AVHs) are among the most common and disabling symptoms of schizophrenia. They involve the superior temporal sulcus (STS), which is associated with language processing; specific STS patterns may reflect vulnerability to auditory hallucinations in schizophrenia. STS sulcal pits are the deepest points of the folds in this region and were investigated here as an anatomical landmark of AVHs. This study included 53 patients diagnosed with schizophrenia and past or present AVHs, as well as 100 healthy control volunteers. All participants underwent a 3-T magnetic resonance imaging T1 brain scan, and sulcal pit differences were compared between the two groups. Compared with controls, patients with AVHs had a significantly different distributions for the number of sulcal pits in the left STS, indicating a less complex morphological pattern. The association of STS sulcal morphology with AVH suggests an early neurodevelopmental process in the pathophysiology of schizophrenia with AVHs.

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.