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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., (© 2024 Association for Child and Adolescent Mental Health.)

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., Competing Interests: R.B.P. reports receiving research funding to his institution from SAGE Therapeutics and the Lundbeck Foundation., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

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.

Background: Antipsychotics carry a higher-risk profile than other psychotropic medications and may be prescribed for youth with conditions in which other first-line treatments are more appropriate. This study aimed to evaluate the population-level effect of the Safer Use of Antipsychotics in Youth (SUAY) trial, which aimed to reduce person-days of antipsychotic use among participants. Methods: We conducted an interrupted time series analysis using segmented regression to measure changes in prescribing trends of antipsychotic initiation rates pre-SUAY and post-SUAY trial at four U.S. health systems between 2013 and 2020. Results: In our overall model, adjusted for age and insurance type, antipsychotic initiation rates decreased by 0.73 (95% confidence interval [CI]: 0.30, 1.16, p = 0.002) prescriptions per 10,000 person-months before the SUAY trial. In the first quarter following the start of the trial, there was an immediate decrease in the rate of antipsychotic initiations of 6.57 (95% CI: 0.99, 12.15) prescriptions per 10,000 person-months. When comparing the posttrial period to the pretrial period, there was an increase of 1.09 (95% CI: 0.32, 1.85) prescriptions per 10,000 person-months, but the increasing rate in the posttrial period alone was not statistically significant (0.36 prescriptions per 10,000 person-months, 95% CI: -0.27, 0.99). Conclusion: The declining trend of antipsychotic initiation seen between 2013 and 2018 (pre-SUAY trial) may have naturally reached a level at which prescribing was clinically warranted and appropriate, resulting in a floor effect. The COVID-19 pandemic, which began in the final three quarters of the posttrial period, may also be related to increased antipsychotic medication initiation.

Objective: This study examined atypical antipsychotic prescribing by Food and Drug Administration (FDA) approved-use (on-label) status for adolescents before and during the COVID-19 pandemic., Methods: Retrospective data were collected from electronic health records (EHRs) of adolescents aged 10-17 years in Kaiser Permanente Northern California. New outpatient atypical antipsychotic prescription orders during 2013-2021 were evaluated. Prescriptions were categorized as on-label if linked in EHRs to autism, psychosis, bipolar disorder, or Tourette's diagnoses; otherwise, they were potentially off-label (herein, off-label). Trend analysis of monthly prescribing rates assessed slope change at pandemic onset for the cohort and by sex and age groups., Results: Among 5828 patients, 74.5% of new antipsychotic orders were off-label in 2021. Overall prescribing decreased significantly until early 2020 (slope = -0.045, P < .01) but then significantly increased through 2021 (post-March 2020 slope change = 0.211, P = .01). Off-label prescriptions increased at a similar rate during the COVID-19 time period, but on-label prescriptions did not change significantly. Males and younger adolescents (ages 10-14 years) showed significant decreases until early 2020, while females and older adolescents (ages 15-17 years) did not. Females and younger adolescents exhibited significant increases in overall and off-label prescribing rates following pandemic onset; older adolescents exhibited increases in overall prescriptions while males had no detectable changes., Conclusions: Antipsychotic prescribing declined slightly but then increased significantly following COVID-19 onset for overall and off-label prescriptions. Pandemic onset differentially impacted antipsychotic prescribing by sex and age, with overall and off-label prescribing driven by increases among female and younger adolescents., Competing Interests: Declaration of Competing Interest Dr. Costales reports grant support from the National Institute of Mental Health (T32MH125792) during the conduct of this study. Dr. Penfold reports receiving research funding to his institution from Janssen Research & Development, Otsuka Pharmaceuticals, and SAGE Therapeutics., (Copyright © 2024 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: The authors report no financial relationships with commercial interests.

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.

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)., (© 2023 National Rural Health Association.)

Introduction: People enrolled in Medicaid managed care who struggle with diabetes control often have complex medical, behavioral, and social needs. Here the authors report the results of a program designed to partner with primary care teams to address those needs., Methods: A nonprofit organization partnered with a Medicaid managed care plan and a Federally Qualified Health Center in California to enroll people with A1cs > 9% in a 12-month program. The program team included a community health worker, certified diabetes care and education specialist/registered dietitian, behavioral health counselor, and registered nurse. They developed patient-led action plans, connected patients to community resources, and supported behavior changes to improve diabetes control. Baseline assessments of behavioral health conditions and social needs were collected. Monthly A1c values were tracked for participants and a comparison group., Results: Of the 51 people enrolled, 83% had at least 1 behavioral health condition. More than 90% reported at least 1 unmet social need. The average monthly A1c among program participants was 0.699 lower than the comparison group post-enrollment ( P = .0008), and the disparity in A1c between Hispanic and non-Hispanic White participants at enrollment declined., Discussion: Participants had high levels of unmet medical, behavioral, and social needs. Addressing these needs resulted in a rapid and sustained improvement in A1c control compared to non-enrollees and a reduction in disparity of control among Hispanic participants., Conclusion: By partnering with a primary care team, a program external to Federally Qualified Health Center primary care can improve clinical outcomes for people with complex needs living with diabetes., Competing Interests: Conflicts of InterestDr Penfold reports receiving research funding to his institution from SAGE Therapeutics, Biogen, Janssen Research and Development, and The Lundbeck Foundation. Avni C Shah, MD, is the founder and CEO of Vayu Health. No conflicts of interest exist for Michael L Parchman, MD, MPH, Kelsey Stefanik-Guizlo, MPH, or Erika Holden, BA.

Importance: Telemedicine use was common during the COVID-19 pandemic, expanding many patients' approaches to accessing health care. Of concern is whether telemedicine access was poorer among higher-needs and disadvantaged populations., Objective: To assess patient characteristics associated with telemedicine use and telemedicine mode and describe telemedicine visit experiences by telemedicine mode., Design, Setting, and Participants: This cross-sectional study included data from the 2022 Health Information National Trends Survey and included US adults with a health care visit. Data were analyzed from May to September 2023., Exposure: Patient characteristics., Main Outcomes and Measures: Any telemedicine visits vs in-person visits only; telemedicine mode (video vs audio-only). Multivariable logistic models assessed patient characteristics associated with telemedicine visits and mode. Bivariate analyses compared telemedicine experiences by mode., Results: The study included 5437 adult patients (mean [SE] age, 49.4 [0.23] years; 3136 females [53.4%]; 1928 males [46.6%]). In 2022, 2384 patients (43%) had a telemedicine visit; 1565 (70%) had a video visit while 819 (30%) had an audio-only visit. In multivariable models, older age (≥75 years: adjusted odds ratio [aOR], 0.63; 95% CI, 0.42-0.94), no internet use (aOR, 0.62; 95% CI, 0.48-0.81), and living in the Midwest (aOR, 0.50; 95% CI, 0.35-0.70) were negatively associated with having telemedicine visits. Female sex (aOR, 1.43; 95% CI, 1.12-1.83), having chronic conditions (aOR, 2.13; 95% CI, 1.66-2.73), and multiple health care visits (2-4 visits: aOR, 1.77; 95% CI, 1.23-2.54; ≥5 visits: aOR, 3.29; 95% CI, 2.20-4.92) were positively associated. Among individuals who used telemedicine, older age (65-74 years: aOR, 2.13; 95% CI, 1.09-4.14; ≥75 years: aOR, 3.58; 95% CI, 1.60-8.00), no health insurance (aOR, 2.84; 95% CI, 1.42-5.67), and no internet use (aOR, 2.11; 95% CI, 1.18-3.78) were positively associated with having audio-only visits. We observed no significant differences in telemedicine use or mode by education, race and ethnicity, or income. Patients' experiences using telemedicine were generally similar for video and audio-only except more individuals who used audio-only had privacy concerns (20% vs 12%, P = .02)., Conclusions and Relevance: In this cross-sectional study of adults with health care visits, many patients, including those with the greatest care needs, chose telemedicine even after in-person visits were available. These findings support continuing this care delivery approach as an option valued by patients. Differences were not observed by most common measures of socioeconomic status. Continued monitoring of telemedicine use is needed to ensure equitable access to health care innovations.

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., Competing Interests: Dr. Penfold reports receiving research funding to his institution from Sage Therapeutics and the Lundbeck Foundation. The other authors report no financial relationships with commercial interests.

Objective: Children with low income and minority race and ethnicity have worse hospital outcomes due partly to systemic and interpersonal racism causing communication and system barriers. We tested the feasibility and acceptability of a novel inpatient communication-focused navigation program., Methods: Multilingual design workshops with parents, providers, and staff created the Family Bridge Program. Delivered by a trained navigator, it included 1) hospital orientation; 2) social needs screening and response; 3) communication preference assessment; 4) communication coaching; 5) emotional support; and 6) a post-discharge phone call. We enrolled families of hospitalized children with public or no insurance, minority race or ethnicity, and preferred language of English, Spanish, or Somali in a single-arm trial. We surveyed parents at enrollment and 2 to 4 weeks post-discharge, and providers 2 to 3 days post-discharge. Survey measures were analyzed with paired t tests., Results: Of 60 families enrolled, 57 (95%) completed the follow-up survey. Most parents were born outside the United States (60%) with a high school degree or less (60%). Also, 63% preferred English, 33% Spanish, and 3% Somali. The program was feasible: families received an average of 5.3 of 6 components; all received >2. Most caregivers (92%) and providers (81% [30/37]) were "very satisfied." Parent-reported system navigation improved from enrollment to follow-up (+8.2 [95% confidence interval 2.9, 13.6], P = .003; scale 0-100). Spanish-speaking parents reported decreased skills-related barriers (-18.4 [95% confidence interval -1.8, -34.9], P = .03; scale 0-100)., Conclusions: The Family Bridge Program was feasible, acceptable, and may have potential for overcoming barriers for hospitalized children at risk for disparities., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships that may be considered as potential competing interests: K. Casey Lion reports financial support was provided by the National Institutes of Health., (Copyright © 2023 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

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., (© 2023 John Wiley & Sons Ltd.)

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., (Copyright © 2023 Elsevier Inc. All rights reserved.)

STAR-Caregivers Virtual Training and Follow-up (STAR-VTF) is an evidence-based intervention that teaches family caregivers how to manage behavioral and psychological symptoms of dementia. The study objective was to identify what adaptations to STAR-VTF are needed to improve cultural relevance for Latino caregivers. A qualitative research study was conducted that interviewed Spanish- and English-speaking caregivers of people with dementia who self-identify as Hispanic/Latino (N = 30) and healthcare and social service providers of older Latino clients and/or Latino family caregivers (N = 14). Thematic analysis methods were applied to code and analyze interview transcripts. The codebook was theory-driven, relying mainly on codes that directly represented components of the Cultural Treatment Adaptation Framework. Based on the content of the excerpts, the codes were sorted into themes that represented opportunities to culturally adapt STAR-VTF. Three themes were identified: (i) there was a need to increase awareness about dementia and decrease stigma; (ii) semantics mattered as certain words and phrases could be stigmatizing, offensive, or culturally inappropriate; and (iii) there was a need to incorporate into program materials the traditional family structure and nature of caregiving in Latino families. Based on findings, adaptations were performed on STAR-VTF that included expanding content to improve understanding of dementia, revising language that was viewed as problematic, and adding cultural examples to reflect the range of family involvement in caring for people living with dementia and multigenerational living. Findings from this qualitative research study advance understanding of the Latino caregiver experience and how to modify programs to better serve their needs., (© Society of Behavioral Medicine 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

To estimate the cost of implementing a clinical program designed to support safer use of antipsychotics in children and adolescents (youth) age 3-17 years at the time of initiating an antipsychotic medication. We calculate the costs of implementing a psychiatric consultation and navigation program for youth prescribed antipsychotic medications across 4 health systems, which included an electronic health record (EHR) decision support tool, consultation with a child and adolescent psychiatrist, and up to 6 months of behavioral health care navigation, as well as telemental health for patients (n = 348). Cost data were collected for both start-up and ongoing intervention phases and are estimated over a 1-year period. Data sources included study records and time-in-motion reports, analyzed from a health system perspective. Costs included both labor and nonlabor costs (2019 US dollars). The average total start-up and ongoing costs per health system were $34,007 and $185,174, respectively. The average total cost per patient was $2,128. The highest average ongoing labor cost components were telemental health ($901 per patient), followed by child and adolescent psychiatrist consultation ($659), and the lowest cost component was primary care/behavioral health provider time to review/respond to the EHR decision support tool and case consultation ($24). For health systems considering programs to promote safer and targeted use of antipsychotics among youth, this study provides estimates of the full start-up and ongoing costs of an EHR decision support tool, psychiatric consultation service, and psychotherapeutic services for patients and families.Trial registration: Clinicaltrials.gov, NCT03448575., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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.

Background: Rates of child maltreatment (CM) obtained from electronic health records are much lower than national child welfare prevalence rates indicate. There is a need to understand how CM is documented to improve reporting and surveillance., Objectives: To examine whether using natural language processing (NLP) in outpatient chart notes can identify cases of CM not documented by ICD diagnosis code, the overlap between the coding of child maltreatment by ICD and NLP, and any differences by age, gender, or race/ethnicity., Methods: Outpatient chart notes of children age 0-18 years old within Kaiser Permanente Washington (KPWA) 2018-2020 were used to examine a selected set of maltreatment-related terms categorized into concept unique identifiers (CUI). Manual review of text snippets for each CUI was completed to flag for validated cases and retrain the NLP algorithm., Results: The NLP results indicated a crude rate of 1.55 % to 2.36 % (2018-2020) of notes with reference to CM. The rate of CM identified by ICD code was 3.32 per 1000 children, whereas the rate identified by NLP was 37.38 per 1000 children. The groups that increased the most in identification of maltreatment from ICD to NLP were adolescents (13-18 yrs. old), females, Native American children, and those on Medicaid. Of note, all subgroups had substantially higher rates of maltreatment when using NLP., Conclusions: Use of NLP substantially increased the estimated number of children who have been impacted by CM. Accurately capturing this population will improve identification of vulnerable youth at high risk for mental health symptoms., Competing Interests: Declaration of competing interest The authors have no conflicts of interest relevant to this article to disclose., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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., (© 2023. The Author(s).)

Objective: Trauma exposure is widely prevalent, with more than 60% of adolescents having experienced at least 1 traumatic event and a third of those at high risk to develop posttraumatic stress disorder (PTSD). Data are scarce and out of date on the services children and adolescents with PTSD receive, impeding efforts to improve care and outcomes. This study examines health service use for a large and diverse sample of children and adolescents with and without a diagnosis of PTSD., Method: Using a matched case-control study, we gathered information from 4 large health care systems participating in the Mental Health Research Network. Data from each site's electronic medical records on diagnoses, health care encounters, and demographics were analyzed. Nine hundred fifty-five 4- to 18-year-olds with a diagnosis of PTSD were identified and matched on a 1:5 ratio to 4770 controls. We compared cases with controls on frequency of service use in outpatient primary care, medical specialty care, acute care, and mental health care. We also assessed psychotropic medication use., Results: Children and adolescents diagnosed with PTSD used nearly all physical and mental health service categories at a higher rate than controls. However, one-third of children and adolescents did not receive even 1 outpatient mental health visit (36.86%) during the year-long sampling window., Conclusion: Our findings suggest that children and adolescents diagnosed with PTSD may have unmet mental health needs. They are high utilizers of health services overall, but lower utilizers of the sectors that may be most helpful in resolving their symptoms., Competing Interests: Disclosure: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Patients and their loved ones often report symptoms or complaints of cognitive decline that clinicians note in free clinical text, but no structured screening or diagnostic data are recorded. These symptoms/complaints may be signals that predict who will go on to be diagnosed with mild cognitive impairment (MCI) and ultimately develop Alzheimer's Disease or related dementias. Our objective was to develop a natural language processing system and prediction model for identification of MCI from clinical text in the absence of screening or other structured diagnostic information., Methods: There were two populations of patients: 1794 participants in the Adult Changes in Thought (ACT) study and 2391 patients in the general population of Kaiser Permanente Washington. All individuals had standardized cognitive assessment scores. We excluded patients with a diagnosis of Alzheimer's Disease, Dementia or use of donepezil. We manually annotated 10,391 clinic notes to train the NLP model. Standard Python code was used to extract phrases from notes and map each phrase to a cognitive functioning concept. Concepts derived from the NLP system were used to predict future MCI. The prediction model was trained on the ACT cohort and 60% of the general population cohort with 40% withheld for validation. We used a least absolute shrinkage and selection operator logistic regression approach (LASSO) to fit a prediction model with MCI as the prediction target. Using the predicted case status from the LASSO model and known MCI from standardized scores, we constructed receiver operating curves to measure model performance., Results: Chart abstraction identified 42 MCI concepts. Prediction model performance in the validation data set was modest with an area under the curve of 0.67. Setting the cutoff for correct classification at 0.60, the classifier yielded sensitivity of 1.7%, specificity of 99.7%, PPV of 70% and NPV of 70.5% in the validation cohort., Discussion and Conclusion: Although the sensitivity of the machine learning model was poor, negative predictive value was high, an important characteristic of models used for population-based screening. While an AUC of 0.67 is generally considered moderate performance, it is also comparable to several tests that are widely used in clinical practice., (© 2022. The Author(s).)

Introduction: With stressors that are often associated with suicide increasing during the coronavirus disease 2019 (COVID-19) pandemic, there has been concern that suicide mortality rates may also be increasing. Our objective was to determine whether suicide mortality rates increased during the COVID-19 pandemic., Methods: We conducted an interrupted time-series study using data from January 2019 through December 2020 from 2 large integrated health care systems. The population at risk included all patients or individuals enrolled in a health plan at HealthPartners in Minnesota or Henry Ford Health System in Michigan. The primary outcome was change in suicide mortality rates, expressed as annualized crude rates of suicide death per 100,000 people in 10 months following the start of the pandemic in March 2020 compared with the 14 months prior., Results: There were 6,434,675 people at risk in the sample, with 55% women and a diverse sample across ages, race/ethnicity, and insurance type. From January 2019 through February 2020, there was a slow increase in the suicide mortality rate, with rates then decreasing by 0.45 per 100,000 people per month from March 2020 through December 2020 (SE=0.19, P=0.03)., Conclusions: Overall suicide mortality rates did not increase with the pandemic, and in fact slightly declined from March to December 2020. Our findings should be confirmed across other settings and, when available, using final adjudicated state mortality data., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Importance: People at risk of self-harm or suicidal behavior can be accurately identified, but effective prevention will require effective scalable interventions., Objective: To compare 2 low-intensity outreach programs with usual care for prevention of suicidal behavior among outpatients who report recent frequent suicidal thoughts., Design, Setting, and Participants: Pragmatic randomized clinical trial including outpatients reporting frequent suicidal thoughts identified using routine Patient Health Questionnaire depression screening at 4 US integrated health systems. A total of 18 882 patients were randomized between March 2015 and September 2018, and ascertainment of outcomes continued through March 2020., Interventions: Patients were randomized to a care management intervention (n = 6230) that included systematic outreach and care, a skills training intervention (n = 6227) that introduced 4 dialectical behavior therapy skills (mindfulness, mindfulness of current emotion, opposite action, and paced breathing), or usual care (n = 6187). Interventions, lasting up to 12 months, were delivered primarily through electronic health record online messaging and were intended to supplement ongoing mental health care., Main Outcomes and Measures: The primary outcome was time to first nonfatal or fatal self-harm. Nonfatal self-harm was ascertained from health system records, and fatal self-harm was ascertained from state mortality data. Secondary outcomes included more severe self-harm (leading to death or hospitalization) and a broader definition of self-harm (selected injuries and poisonings not originally coded as self-harm)., Results: A total of 18 644 patients (9009 [48%] aged 45 years or older; 12 543 [67%] female; 9222 [50%] from mental health specialty clinics and the remainder from primary care) contributed at least 1 day of follow-up data and were included in analyses. Thirty-one percent of participants offered care management and 39% offered skills training actively engaged in intervention programs. A total of 540 participants had a self-harm event (including 45 deaths attributed to self-harm and 495 nonfatal self-harm events) over 18 months following randomization: 172 (3.27%) in care management, 206 (3.92%) in skills training, and 162 (3.27%) in usual care. Risk of fatal or nonfatal self-harm over 18 months did not differ significantly between the care management and usual care groups (hazard ratio [HR], 1.07; 97.5% CI, 0.84-1.37) but was significantly higher in the skills training group than in usual care (HR, 1.29; 97.5% CI, 1.02-1.64). For severe self-harm, care management vs usual care had an HR of 1.03 (97.5% CI, 0.71-1.51); skills training vs usual care had an HR of 1.34 (97.5% CI, 0.94-1.91). For the broader self-harm definition, care management vs usual care had an HR of 1.10 (97.5% CI, 0.92-1.33); skills training vs usual care had an HR of 1.17 (97.5% CI, 0.97-1.41)., Conclusions and Relevance: Among adult outpatients with frequent suicidal ideation, offering care management did not significantly reduce risk of self-harm, and offering brief dialectical behavior therapy skills training significantly increased risk of self-harm, compared with usual care. These findings do not support implementation of the programs tested in this study., Trial Registration: ClinicalTrials.gov Identifier: NCT02326883.

Objective: To develop a new approach to prescribing guidelines as part of a pragmatic trial, Safer Use of Antipsychotics in Youth (SUAY; ClinicalTrials.gov Identifier: NCT03448575), which supports prescribers in delivering high-quality mental health care to youths., Method: A nominal group technique was used to identify first- to nth-line treatments for target symptoms and potential diagnoses. The panel included US pediatricians, child and adolescent psychiatrists, and psychopharmacology experts. Meeting materials included information about Medicaid review programs, systematic reviews, prescribing guidelines, and a description of the pragmatic trial. Afterward, a series of 4 webinar discussions were held to achieve consensus on recommendations., Results: The panel unanimously agreed that the guideline should focus on target symptoms rather than diagnoses. Guidance included recommendations for first- to nth-line treatment of target mental health symptoms, environmental factors to be addressed, possible underlying diagnoses that should first be considered and ruled out, and general considerations for pharmacological and therapeutic treatments., Conclusion: Prescribing guidelines are often ignored because they do not incorporate the real-world availability of first-line psychosocial treatments, comorbid conditions, and clinical complexity. Our approach addresses some of these concerns. If the approach proves successful in our ongoing pragmatic trial, Safer Use of Antipsychotics in Youth (SUAY), it may serve as a model to state Medicaid programs and health systems to support clinicians in delivering high-quality mental health care to youths., Clinical Trial Registration Information: Safer Use of Antipsychotics in Youth; http://clinicaltrials.gov/; NCT03448575., (Copyright © 2021 American Academy of Child & Adolescent Psychiatry. All rights reserved.)

Background: Clinician perceptions before and after inviting patients to read office notes (open notes) are unknown., Objective: To describe changes in clinicians' attitudes about sharing notes with patients., Design, Participants, and Main Measure: Survey of outpatient primary and specialty care clinicians who were from a large group practice and had one or more patients who accessed notes. The main outcome was percent change (before vs. after implementation) in clinician perception that online visit notes are beneficial overall., Key Results: Of the 563 invited clinicians, 400 (71%) took the baseline survey; 295 were eligible for a follow-up survey with 192 (65%) responding (119 primary care, 47 medical specialties, 26 surgical specialties). Before implementation, 29% agreed or somewhat agreed that visit notes online are beneficial overall, increasing to 71% following implementation (p<0.001); 44% switched beliefs from bad to good idea; and 2% reported the opposite change (p<0.001). This post-implementation change was observed in all clinician categories. Compared to pre-implementation, fewer clinicians had concerns about office visits taking longer (47% pre vs. 15% post) or requiring more time for questions (71% vs. 16%), or producing notes (57% vs. 28%). Before and after implementation, most clinicians reported being less candid in documentation (65% vs. 52%) and that patients would have more control of their care (72% vs. 78%) and worry more (72% vs. 65%)., Conclusions: Following implementation, more primary and specialty care clinicians agreed that sharing notes with patients online was beneficial overall. Fewer had concerns about more time needed for office visits or documentation. Most thought patients would worry more and reported being less candid in documentation., (© 2021. Society of General Internal Medicine.)

Background: Few studies report on machine learning models for suicide risk prediction in adolescents and their utility in identifying those in need of further evaluation. This study examined whether a model trained and validated using data from all age groups works as well for adolescents or whether it could be improved., Methods: We used healthcare data for 1.4 million specialty mental health and primary care outpatient visits among 256,823 adolescents across 7 health systems. The prediction target was 90-day risk of suicide attempt following a visit. We used logistic regression with least absolute shrinkage and selection operator (LASSO) and generalized estimating equations (GEE) to predict risk. We compared performance of three models: an existing model, a recalibrated version of that model, and a newly-learned model. Models were compared using area under the receiver operating curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value., Results: The AUC produced by the existing model for specialty mental health visits estimated in adolescents alone (0.796; [0.789, 0.802]) was not significantly different than the AUC of the recalibrated existing model (0.794; [0.787, 0.80]) or the newly-learned model (0.795; [0.789, 0.801]). Predicted risk following primary care visits was also similar: existing (0.855; [0.844, 0.866]), recalibrated (0.85 [0.839, 0.862]), newly-learned (0.842, [0.829, 0.854])., Limitations: The models did not incorporate non-healthcare risk factors. The models relied on ICD9-CM codes for diagnoses and outcome measurement., Conclusions: Prediction models already in operational use by health systems can be reliably employed for identifying adolescents in need of further evaluation., (Copyright © 2021. Published by Elsevier B.V.)

Introduction: Previous studies report that item 9 of the Patient Health Questionnaire (PHQ9) is useful for stratifying risk of suicide attempt in adults. This study re-produced the utility of item 9 of PHQ9 in assessing risk of suicide attempt in adolescents., Materials and Methods: Individuals aged 13 to 17 years in 4 health systems with a diagnosis of depression and history of treatment were included. We estimated time to first observed fatal or non-fatal suicide attempt in the 2 years following completion of a PHQ9, stratified by response to item 9., Results: There were 51,807 PHQ9 questionnaires for 20,363 youth and 861 instances of suicide attempt. Cumulative probability of suicide attempt ranged from approximately 3.3% (95% CI, 3.0 to 3.5%) for those responding "not at all" on item 9 to 10.8% (95% CI, 9.2 to 12.4%) for those responding "nearly every day". These probabilities are more than 3 times higher than previously reported in adults., Conclusion: PHQ item 9 is useful for stratifying risk of suicide attempt in the 2 years following completion of the questionnaire. Monitoring PHQ item 9 over time for patients in treatment for depression can be useful for population health management of adolescents with depression., (© 2021 The American Association of Suicidology.)

Objective: Addressing firearm access is recommended when patients are identified as being at risk of suicide. However, the practice of assessing firearm access is controversial, and no national guidelines exist to inform practice. This study qualitatively explored patient perspectives on a routine question about firearm access to optimize the patient centeredness of this practice in the context of suicide risk., Methods: Electronic health record data were used to identify primary care patients reporting depressive symptoms, including suicidal thoughts, within 2 weeks of sampling. Participants completed a semistructured telephone interview (recorded and transcribed), which focused broadly on the experience of being screened for suicidality and included specific questions to elicit beliefs and opinions about being asked a standard firearm access question. Directive (deductive) and conventional (inductive) content analysis was used to analyze responses to the portion of the interview focused on firearm assessment and disclosure., Results: Thirty-seven patients in Washington State ages 20-95 completed the qualitative interview by phone. Organizing themes included apprehensions about disclosing access to firearms related to privacy, autonomy, and firearm ownership rights; perceptions regarding relevance of the firearm question, informed by experiences with suicidality and common beliefs and misconceptions about the inevitability of suicide; and suggestions for connecting questions about firearms and other lethal means to suicide risk., Conclusions: Clarifying the purpose and use of routine firearm access assessment, contextualizing firearm questions within injury prevention broadly, and addressing misconceptions about suicide prevention may help encourage disclosure of firearm access and increase the patient centeredness of this practice.

Objectives: Antipsychotic prescribing in children and adolescents increased sharply beginning in the 1990s, but recent reports among Medicaid enrollees suggest declining trends. However, few studies have included both commercially and publicly insured patients or focused on trends in new antipsychotic medications in children without documented psychotic disorders or other indicated conditions. The objective of the study was to report trends in new antipsychotic prescribing for pediatric patients (age 3-17 years) in a large children's health care system. Methods: Data were abstracted from electronic medical records (January 1, 2013 to December 31, 2017). New antipsychotic medication orders were defined as antipsychotic orders for patients without an order in the 180 days prior. Patients were excluded if the order was initiated in an emergency department or inpatient setting; they were diagnosed with psychotic disorder, mania, autism spectrum disorder, or intellectual disability; or the order was for prochlorperazine. The crude rate of new antipsychotic prescribing is reported quarterly with Poisson 95% confidence intervals in the total sample and by demographic subgroups (child vs. adolescent, female vs. male, public vs. private insurance, and white vs. nonwhite). Results: Antipsychotic orders decreased from 54.9 prescriptions per 10,000 person months in the first quarter of 2013 to 34.1 per 10,000 person months in the last quarter of 2017. Rates of antipsychotic prescribing were significantly higher for adolescents compared with children, patients who were commercially insured compared with Medicaid insured, and at most time points for white compared with non-white patients. However, prescribing rates did not differ significantly based on gender. Conclusions: Antipsychotic prescribing declined for both commercially and Medicaid-insured children in a pediatric hospital-based system, although white and commercially insured patients were more likely to be prescribed antipsychotics. More attention may be needed for reducing potentially avoidable prescribing of antipsychotics in previously understudied subgroups, such as commercially insured patients. Clinical Trial Registration Number: NCT03448575.

Background: Behavioral and psychological symptoms of dementia (BPSD) are associated with increased stress, burden, and depression among family caregivers of people with dementia. STAR-Caregivers Virtual Training and Follow-up (STAR-VTF) is adapted from an evidence-based, in-person program that trains family caregivers to manage BPSD. We used a human-centered design approach to obtain feedback from family caregivers about STAR-VTF. The program will be evaluated using a pragmatic randomized trial., Objective: The objective of the study was to understand the needs of family caregivers for improving BPSD management and the extent to which caregivers perceived that STAR-VTF could address those needs., Methods: Between July and September 2019, we conducted 15 semistructured interviews with family caregivers of people with dementia who receive care at Kaiser Permanente Washington in the Seattle metropolitan area. We identified participants from electronic health records, primarily based on a prescription for antipsychotic medication for the person with dementia (a proxy for caregivers dealing with BPSD). We showed caregivers low-fidelity prototypes of STAR-VTF online self-directed materials and verbally described potential design elements. We obtained caregiver feedback on these elements, focusing on their needs and preferences and perceived barriers to using STAR-VTF. We used a hybrid approach of inductive and deductive coding and aggregated codes to develop themes., Results: The idea of a virtual training program for learning to manage BPSD appealed to caregivers. They said health care providers did not provide adequate education in the early disease stages about the personality and behavior symptoms that can affect people with dementia. Caregivers found it unexpected and frustrating when the person with dementia began experiencing BPSD, symptoms they felt unprepared to manage. Accordingly, caregivers expressed a strong desire for the health care organization to offer programs such as STAR-VTF much sooner. Caregivers had already put considerable effort into problem solving challenging behaviors. They anticipated deriving less value from STAR-VTF at that point. Nonetheless, many were interested in the virtual aspect of the training due to the convenience of receiving help from home and the perception that help from a virtual program would be timelier than traditional service modalities (eg, face to face). Given caregivers' limited time, they suggested dividing the STAR-VTF content into chunks to review as time permitted. Caregivers were interested in having a STAR-VTF provider for additional support in managing challenging behaviors. Caregivers reported a preference for having the same coach for the program duration., Conclusions: Caregivers we interviewed would likely accept a virtual training program such as STAR-VTF to obtain information about BPSD and receive help managing it. Family caregivers anticipated deriving more value if STAR-VTF was offered earlier in the disease course., (©Magaly Ramirez, Miriana C Duran, Chester J Pabiniak, Kelly E Hansen, Ann Kelley, James D Ralston, Susan M McCurry, Linda Teri, Robert B Penfold. Originally published in JMIR Aging (http://aging.jmir.org), 10.02.2021.)

Introduction: There are no published procedural or safety guidelines for home-based telemental health (TMH) therapy with youth, despite the unique challenges and risks of providing services to this population outside of a traditional clinic setting. We developed clinical, logistical, and safety procedures for home-based TMH with youth in the context of a large clinical trial., Methods: A Targeted Approach to Safer Use of Antipsychotics in Youth (SUAY) study identifies youth ages 3-17 who are prescribed second-generation antipsychotic medication for non-psychotic disorders within large healthcare systems. Prescribing physicians receive psychopharmacology consultation. Patients receive a "navigator" to coordinate treatments and access to TMH if they do not have a local therapist. We optimized access by allowing TMH sessions to take place in the family's home, while providing guidelines for privacy, safety, and in-session crises., Results: Clinical issues included providing flexibility in the treatment modality and engaging families. Logistical issues included remote consenting for treatment and troubleshooting technological problems. Safety issues included crisis and safety planning with the youth and family before and during treatment., Discussion: The provision of home-based TMH therapy for youth requires adaptations to existing TMH procedural and safety guidelines to optimize clinical care, technology coordination, and safety. Trial registration number and trial register: Clinicaltrials.gov: NCT03448575.

Background: Programs such as the Pediatric Access Line in Washington state have shown decreases in antipsychotic medication use by youth with non-psychotic disorders. Program outcomes have been studied with observational designs. This manuscript describes the protocol for Targeted and Safer Use of Antipsychotics in Youth (SUAY), a randomized controlled trial of psychiatrist review of prescriptions and facilitated access to psychosocial care. The aim of the intervention is to reduce the number of person-days of antipsychotic use among participants., Methods: Recruitment occurs at 4 health systems. Targeted enrollment is 800 youth aged 3-17 years. Clinicians are block randomized to intervention versus usual care prior to the study. Youth are nested within the arm of the prescribing clinician. Clinicians in the intervention group receive an EHR-based best practice alert with options to expedite access to psychosocial care and all medication orders are reviewed by a child and adolescent psychiatrist with feedback provided to the prescriber. The primary outcome is person-days of antipsychotic medication use in the 6 months following the initial order. All randomized individuals contribute data regardless of their level of participation (including declining all services)., Discussion: The trial has been approved by the institutional review boards at each of the 4 sites. The intervention has 4 novel design features including automated recruitment using a best practice alert, psychiatrist medication order review and consultation, telephone navigation to psychosocial care, and telemental health visits. Recruitment began in March of 2018 and will be completed in June 2020. Follow-up will be completed December 31, 2020., Trial Registration: Clinicaltrials.gov, NCT03448575., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: To characterize the US national level healthcare utilization patterns of patients with commercial insurance plans before and after a psychiatric hospitalization admitted through the emergency department (ED) using insurance claims data., Method: We identified 34,250 patients from multiple commercial health insurance providers across the US who meet our eligibility criteria. We summarized their healthcare encounters and used logistic regression models to study the patterns of healthcare utilization including prior visits, outpatient follow-ups, and hospital- or ED-readmissions., Results: Suicidal ideation was highly prevalent at the time of the index event (29.88%). Almost half of the patients (48.28%) had healthcare encounters with the same primary diagnosis one year before admission, about 5% had outpatient follow-ups or were readmitted to the hospital or ED 7 days post discharge. The post 30-day follow-ups and readmission rates were slightly higher. In general, older patients were less likely to have prior visits, follow-ups, or readmissions, and patients with SUDs, specifically alcohol dependence, opioid dependence/abuse, and stimulant dependence, were more likely to have outpatient follow-ups., Conclusion: Patterns of patients' prior visits, follow-ups, and readmissions varied by demographics and psychiatric comorbidity. Additional studies are needed to further explain the spatial variations of utilization patterns., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: Studies show decreased depression diagnosis, psychotherapy, and medications and increased suicide attempts following US Food and Drug Administration antidepressant warnings regarding suicidality risk among youth. Effects on care spilled over to older adults. This study investigated whether suicide deaths increased following the warnings and declines in depression care., Methods: We conducted an interrupted time series study of validated death data (1990-2017) to estimate changes in trends of US suicide deaths per 100,000 adolescents (ages 10-19) and young adults (ages 20-24) after the warnings, controlling for baseline trends., Results: Before the warnings (1990-2002), suicide deaths decreased markedly. After the warnings (2005-2017) and abrupt declines in treatment, this downward trend reversed. There was an immediate increase of 0.49 suicides per 100,000 adolescents, 95% confidence interval [CI]: 0.12, 0.86) and a trend increase of 0.03 suicides per 100,000 adolescents per year (95% CI: 0.026, 0.031). Similarly, there was an immediate increase of 2.07 suicides per 100,000 young adults (95% CI: 1.04, 3.10) and a trend increase of 0.05 suicides per 100,000 young adults per year (95% CI: 0.04, 0.06). Assuming baseline trends continued, there may have been 5958 excess suicides nationally by 2010 among yearly cohorts of 43 million adolescents and 21 million young adults., Conclusions: We observed increases in suicide deaths among youth following the warnings and declines in depression care. Alternative explanations were explored, including substance use, economic recessions, smart phone use, and unintentional injury deaths. Additional factors may have contributed to continued increases in youth suicide during the last decade. Combined with previous research on declining treatment, these results call for re-evaluation of the antidepressant warnings., (© 2020 The Authors. Psychiatric Research and Clinical Practice published by Wiley Periodicals LLC. on behalf of the American Psychiatric Association.)

Objective: To evaluate the association between patterns of alcohol use and short-term risk of suicide attempt among patients with and without reported suicidal ideation., Methods: Kaiser Permanente Washington electronic health record data were used to identify mental health visits (1/1/2010-6/30/2015) with documented assessments for unhealthy alcohol use (AUDIT-C) and suicidal ideation (PHQ-9 ninth question). Logistic regression fit using generalized estimating equations were used to conduct visit-level analyses, accounting for correlation between individuals' assessments. Separate models evaluated the association between (1) level of alcohol consumption and (2) frequency of heavy episodic drinking (HED), in combination with suicidal ideation (any vs none), with suicide attempt within 90 days following each visit. Primary models adjusted for age, gender, race/ethnicity and visit year., Results: Of 59,705 visits (43,706 unique patients), 372 (0.62%) were followed by a suicide attempt within 90 days. The risk of suicide attempt was significantly higher for patients reporting suicidal ideation across all levels of alcohol consumption compared to patients reporting low-level alcohol use and no suicidal ideation, particularly high-level use (OR 9.77, 95% CI, 6.23-15.34). Similarly, risk of suicide attempt was higher for patients reporting suicidal ideation across all levels of HED relative to those reporting no HED or suicidal ideation, particularly HED monthly or more (OR 6.80, 95% CI 4.77-9.72). Among patients reporting no suicidal ideation, no associations were observed., Conclusions: Findings underscore the potential value of offering alcohol-related care to patient reporting suicidal ideation. Additional strategies are needed to identify suicide risk among those reporting no suicidal ideation.

Purpose: To assess whether primary care practices with and without support from a larger organization differ in their ability to produce timely reports on cardiovascular disease quality measures., Background: Although many primary care practices are now part of larger organizations, it is not clear whether such a shift will improve the ability of those who work in these primary care settings to easily access and use their own data for improvement., Methods: Smaller primary care practices were enrolled in a trial of external practice support to build quality improvement (QI) capacity. A request for clinical quality measure (eCQM) data were sent to each practice and study outcomes were defined based on the date on which practices first submitted valid data for at least 1 of the 3 measures. A practice survey completed by a clinic manager captured practice characteristics, including the presence of QI support from a larger organization., Results: Of the 209 enrolled practices, 205 had complete data for analysis. Practices without central QI support had higher rates of eCQM submission at 30 days (38% vs 20%) and 60 days, (63% vs 48%) than practices with central QI support. Practices with central QI support took longer to submit data (median, 57 days) compared with practices without centralized support (median, 40 days) although this difference was not significant., Conclusion: The ability of smaller practices without centralized QI support to report their eCQMs more quickly may have implications for their subsequent ability to improve these measures., Competing Interests: Conflicting and Competing Interests: None., (© Copyright 2020 by the American Board of Family Medicine.)

Background: Children from socially disadvantaged families experience worse hospital outcomes compared with other children. We sought to identify modifiable barriers to care to target for intervention., Methods: We conducted a prospective cohort study of hospitalized children over 15 months. Caregivers completed a survey within 3 days of admission and 2 to 8 weeks after discharge to assess 10 reported barriers to care related to their interactions within the health care system (eg, not feeling like they have sufficient skills to navigate the system and experiencing marginalization). Associations between barriers and outcomes (30-day readmissions and length of stay) were assessed by using multivariable regression. Barriers associated with worse outcomes were then tested for associations with a cumulative social disadvantage score based on 5 family sociodemographic characteristics (eg, low income)., Results: Of eligible families, 61% ( n = 3651) completed the admission survey; of those, 48% ( n = 1734) completed follow-up. Nine of 10 barriers were associated with at least 1 worse hospital outcome. Of those, 4 were also positively associated with cumulative social disadvantage: perceiving the system as a barrier (adjusted β = 1.66; 95% confidence interval [CI] 1.02 to 2.30), skill barriers (β = 3.82; 95% CI 3.22 to 4.43), cultural distance (β = 1.75; 95% CI 1.36 to 2.15), and marginalization (β = .71; 95% CI 0.30 to 1.11). Low income had the most consistently strong association with reported barriers., Conclusions: System barriers, skill barriers, cultural distance, and marginalization were significantly associated with both worse hospital outcomes and social disadvantage, suggesting these are promising targets for intervention to decrease disparities for hospitalized children., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2020 by the American Academy of Pediatrics.)

Objective: To evaluate the association between alcohol use routinely reported during outpatient mental healthcare visits and short-term risk of subsequent suicide attempt., Methods: Using a longitudinal retrospective-cohort design, electronic health records identified adult outpatient visits to a mental health provider (1/1/2010-6/30/2015) at Kaiser Permanente Washington with a documented Alcohol Use Disorders Identification Test-Consumption [AUDIT-C]. Suicide attempts within 90 days of AUDIT-C documentation were defined using death certificate cause-of-death and diagnosis codes (non-lethal). Visit-level analyses used generalized estimating equations to account for correlation between multiple AUDIT-Cs for individuals. Separate models evaluated the association between (1) level of consumption and (2) frequency of heavy drinking episodes and suicide attempts, adjusted for visit year, demographics, depressive symptom, and suicidal ideation., Results: Of 59,382 patient visits, 0.62% (N = 371) were followed by a suicide attempt within 90 days. Patients reporting high-level alcohol use were 1.77 times (95% CI, 1.22-2.57) more likely to attempt suicide than those reporting low-level use. Patients reporting daily or almost daily heavy drinking episodes were 2.33 times (95% CI, 1.38-3.93) more likely to attempt suicide than those reporting none., Conclusions and Relevance: The AUDIT-C is a valuable tool for assessing patterns of patient-reported alcohol use associated with subsequent suicide attempt., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: All clinical trial investigators have ethical and regulatory obligations to monitor participant safety and trial integrity. Specific procedures for meeting these obligations, however, may differ substantially between pragmatic trials and traditional explanatory clinical trials., Methods/results: Appropriate monitoring of clinical trials typically includes assessing rate of recruitment or enrollment; monitoring safe and effective delivery of study treatments; assuring that study staff act to minimize risks; monitoring quality and timeliness of study data; and considering interim analyses for early detection of benefit, harm, or futility. Each of these responsibilities applies to pragmatic clinical trials. Just as design of pragmatic trials typically involves specific and necessary departures from methods of explanatory clinical trials, appropriate monitoring of pragmatic trials typically requires specific departures from monitoring procedures used in explanatory clinical trials. We discuss how specific aspects of pragmatic trial design and operations influence selection of monitoring procedures and illustrate those choices using examples from three ongoing pragmatic trials conducted by the Mental Health Research Network., Conclusions: Pragmatic trial investigators should not routinely adopt monitoring procedures used in explanatory clinical trials. Instead, investigators should consider core principles of trial monitoring and design monitoring procedures appropriate for each pragmatic trial.

Background: Routine population-based screening for depression is an essential part of evolving health care models integrating care for mental health in primary care. Depression instruments often include questions about suicidal thoughts, but how patients experience these questions in primary care is not known and may have implications for accurate identification of patients at risk., Objectives: To explore the patient experience of routine population-based depression screening/assessment followed, for some, by suicide risk assessment and discussions with providers., Design: Qualitative, interview-based study., Participants: Thirty-seven patients from Kaiser Permanente Washington who had recently screened positive for depression on the 2-item Patient Health Questionnaire [PHQ] and completed the full PHQ-9., Approach: Criterion sampling identified patients who had recently completed the PHQ-9 ninth question which asks about the frequency of thoughts about self-harm. Patients completed semi-structured interviews by phone, which were recorded and transcribed. Directive and conventional content analyses were used to apply knowledge from prior research and elucidate new information from interviews; thematic analysis was used to organize key content overall and across groups based on endorsement of suicide ideation., Key Results: Four main organizing themes emerged from analyses: (1) Participants believed being asked about suicidality was contextually appropriate and valuable, (2) some participants described a mismatch between their lived experience and the PHQ-9 ninth question, (3) suicidality disclosures involved weighing hope for help against fears of negative consequences, and (4) provider relationships and acts of listening and caring facilitated discussions about suicidality., Conclusions: All participants believed being asked questions about suicidal thoughts was appropriate, though some who disclosed suicidal thoughts described experiencing stigma and sometimes distanced themselves from suicidality. Direct communication with trusted providers, who listened and expressed empathy, bolstered comfort with disclosure. Future research should consider strategies for reducing stigma and encouraging fearless disclosure among primary care patients experiencing suicidality.

Objective: Guidelines recommend against prescribing antipsychotics without an indication, yet prescription rates remain undesirably high for youths. Information technology can facilitate guideline-based prescribing, but little is known about providers' needs. The Safer Use of Antipsychotics in Youth project is implementing an algorithm-based workflow for peer consultation, care navigation, and expedited psychotherapy access. To optimize workflow for a multisite trial, we engaged providers for input., Methods: Guided by human-centered design, we interviewed 15 providers from Kaiser Permanente Washington and Nationwide Children's Hospital about their prescribing barriers and workflow preferences. We identified qualitative themes on barriers affecting implementation and design opportunities to optimize workflow., Results: Providers expressed two major barriers: potential disruptions to clinical practice and threats to professional autonomy. Three design opportunities emerged: à la carte orders, passive review of orders, and consultation self-acknowledgment., Conclusions: Human-centered design offers an innovative approach to improve guideline-based prescribing with optimizations that are grounded in providers' needs.

Purpose: We conducted a randomized controlled trial to compare the effectiveness of adding various forms of enhanced external support to practice facilitation on primary care practices' clinical quality measure (CQM) performance., Methods: Primary care practices across Washington, Oregon, and Idaho were eligible if they had fewer than 10 full-time clinicians. Practices were randomized to practice facilitation only, practice facilitation and shared learning, practice facilitation and educational outreach visits, or practice facilitation and both shared learning and educational outreach visits. All practices received up to 15 months of support. The primary outcome was the CQM for blood pressure control. Secondary outcomes were CQMs for appropriate aspirin therapy and smoking screening and cessation. Analyses followed an intention-to-treat approach., Results: Of 259 practices recruited, 209 agreed to be randomized. Only 42% of those offered educational outreach visits and 27% offered shared learning participated in these enhanced supports. CQM performance improved within each study arm for all 3 cardiovascular disease CQMs. After adjusting for differences between study arms, CQM improvements in the 3 enhanced practice support arms of the study did not differ significantly from those seen in practices that received practice facilitation alone (omnibus P = .40 for blood pressure CQM). Practices randomized to receive both educational outreach visits and shared learning, however, were more likely to achieve a blood pressure performance goal in 70% of patients compared with those randomized to practice facilitation alone (relative risk = 2.09; 95% CI, 1.16-3.76)., Conclusions: Although we found no significant differences in CQM performance across study arms, the ability of a practice to reach a target level of performance may be enhanced by adding both educational outreach visits and shared learning to practice facilitation., (© 2019 Annals of Family Medicine, Inc.)

Purpose: Six key elements of opioid medication management redesign in primary care have been previously identified. Here, we examine the effect of implementing these Six Building Blocks on opioid-prescribing practices., Methods: Six rural-serving organizations with 20 clinic locations received support for 15 months during the period October 2015 to May 2017 to implement the Six Building Blocks. Patients undergoing long-term opioid therapy (LtOT) at these study sites were compared with patients undergoing LtOT enrolled in a regional health plan who did not receive care at the study sites but who resided in the same primary care service areas (control group). Outcomes were monthly trend in the proportion of patients undergoing LtOT prescribed a ≥100 morphine equivalent dose (MED) of opioids daily and the total number of patients receiving an opioid prescription. An interrupted time series using difference-indifference analysis was used for tests of significance., Results: The proportion of patients prescribed a ≥100 MED of opioids daily decreased 2.2% (11.8% to 9.6%) among patients at the intervention clinics and 1.3% (14.0% to 12.7%) among patients in the control group. The rate of decrease was significantly greater among study patients than among patients in the control group ( P = .018). The rate of decrease in the number of patients on LtOT at intervention clinics increased during the intervention period compared with the preintervention period ( P <.001)., Conclusions: Efforts to redesign opioid medication management in primary care resulted in a significant decrease in opioid prescribing. Future research is needed to determine if these results are generalizable to other settings and to assess implications for patient-reported outcomes., (© 2019 Annals of Family Medicine, Inc.)

Background: Sharing of research data derived from health system records supports the rigor and reproducibility of primary research and can accelerate research progress through secondary use. But public sharing of such data can create risk of re-identifying individuals, exposing sensitive health information., Method: We describe a framework for assessing re-identification risk that includes: identifying data elements in a research dataset that overlap with external data sources, identifying small classes of records defined by unique combinations of those data elements, and considering the pattern of population overlap between the research dataset and an external source. We also describe alternative strategies for mitigating risk when the external data source can or cannot be directly examined., Results: We illustrate this framework using the example of a large database used to develop and validate models predicting suicidal behavior after an outpatient visit. We identify elements in the research dataset that might create risk and propose a specific risk mitigation strategy: deleting indicators for health system (a proxy for state of residence) and visit year., Discussion: Researchers holding health system data must balance the public health value of data sharing against the duty to protect the privacy of health system members. Specific steps can provide a useful estimate of re-identification risk and point to effective risk mitigation strategies., Competing Interests: The authors have no competing interests to declare.

Objective: The authors sought to develop and validate models using electronic health records to predict suicide attempt and suicide death following an outpatient visit., Method: Across seven health systems, 2,960,929 patients age 13 or older (mean age, 46 years; 62% female) made 10,275,853 specialty mental health visits and 9,685,206 primary care visits with mental health diagnoses between Jan. 1, 2009, and June 30, 2015. Health system records and state death certificate data identified suicide attempts (N=24,133) and suicide deaths (N=1,240) over 90 days following each visit. Potential predictors included 313 demographic and clinical characteristics extracted from records for up to 5 years before each visit: prior suicide attempts, mental health and substance use diagnoses, medical diagnoses, psychiatric medications dispensed, inpatient or emergency department care, and routinely administered depression questionnaires. Logistic regression models predicting suicide attempt and death were developed using penalized LASSO (least absolute shrinkage and selection operator) variable selection in a random sample of 65% of the visits and validated in the remaining 35%., Results: Mental health specialty visits with risk scores in the top 5% accounted for 43% of subsequent suicide attempts and 48% of suicide deaths. Of patients scoring in the top 5%, 5.4% attempted suicide and 0.26% died by suicide within 90 days. C-statistics (equivalent to area under the curve) for prediction of suicide attempt and suicide death were 0.851 (95% CI=0.848, 0.853) and 0.861 (95% CI=0.848, 0.875), respectively. Primary care visits with scores in the top 5% accounted for 48% of subsequent suicide attempts and 43% of suicide deaths. C-statistics for prediction of suicide attempt and suicide death were 0.853 (95% CI=0.849, 0.857) and 0.833 (95% CI=0.813, 0.853), respectively., Conclusions: Prediction models incorporating both health record data and responses to self-report questionnaires substantially outperform existing suicide risk prediction tools.

Objective: The authors sought to describe patterns of health care use prior to first diagnosis of a psychotic disorder in a population-based sample., Method: Electronic health records and insurance claims from five large integrated health systems were used to identify 624 patients 15-29 years old who received a first diagnosis of a psychotic disorder in any care setting and to record health services received, diagnoses assigned, and medications dispensed during the previous 36 months. Patterns of utilization were compared between patients receiving a first diagnosis of a psychotic disorder and matched samples of general health system members and members receiving a first diagnosis of unipolar depression., Results: During the year before a first psychotic disorder diagnosis, 29% of patients had mental health specialty outpatient care, 8% had mental health inpatient care, 24% had emergency department mental health care, 29% made a primary care visit with a mental health diagnosis, and 60% received at least one mental health diagnosis (including substance use disorders). Compared with patients receiving a first diagnosis of unipolar depression, those with a first diagnosis of a psychotic disorder were modestly more likely to use all types of health services and were specifically more likely to use mental health inpatient care (odds ratio=2.96, 95% CI=1.97-4.43) and mental health emergency department care (rate ratio=3.74, 95% CI=3.39-4.53)., Conclusions: Most patients receiving a first diagnosis of a psychotic disorder had some indication of mental health care need during the previous year. General use of primary care or mental health services, however, does not clearly distinguish people who later receive a diagnosis of a psychotic disorder from those who later receive a diagnosis of unipolar depression. Use of inpatient or emergency department mental health care is a more specific indicator of risk.

Background: New health policies may have intended and unintended consequences. Active surveillance of population-level data may provide initial signals of policy effects for further rigorous evaluation soon after policy implementation., Objective: This study evaluated the utility of sequential analysis for prospectively assessing signals of health policy impacts. As a policy example, we studied the consequences of the widely publicized Food and Drug Administration's warnings cautioning that antidepressant use could increase suicidal risk in youth., Method: This was a retrospective, longitudinal study, modeling prospective surveillance, using the maximized sequential probability ratio test. We used historical data (2000-2010) from 11 health systems in the US Mental Health Research Network. The study cohort included adolescents (ages 10-17 y) and young adults (ages 18-29 y), who were targeted by the warnings, and adults (ages 30-64 y) as a comparison group. Outcome measures were observed and expected events of 2 possible unintended policy outcomes: psychotropic drug poisonings (as a proxy for suicide attempts) and completed suicides., Results: We detected statistically significant (P<0.05) signals of excess risk for suicidal behavior in adolescents and young adults within 5-7 quarters of the warnings. The excess risk in psychotropic drug poisonings was consistent with results from a previous, more rigorous interrupted time series analysis but use of the maximized sequential probability ratio test method allows timely detection. While we also detected signals of increased risk of completed suicide in these younger age groups, on its own it should not be taken as conclusive evidence that the policy caused the signal. A statistical signal indicates the need for further scrutiny using rigorous quasi-experimental studies to investigate the possibility of a cause-and-effect relationship., Conclusions: This was a proof-of-concept study. Prospective, periodic evaluation of administrative health care data using sequential analysis can provide timely population-based signals of effects of health policies. This method may be useful to use as new policies are introduced.

Importance: Individuals with psychotic disorders have increased mortality, and recent research suggests a marked increase shortly after diagnosis., Objective: To use population-based data to examine overall and cause-specific mortality after first diagnosis of a psychotic disorder., Design, Setting, and Participants: This cohort study used records from 5 integrated health systems that serve more than 8 million members in 5 states. Members aged 16 through 30 years who received a first lifetime diagnosis of a psychotic disorder from September 30, 2009, through September 30, 2015, and 2 comparison groups matched for age, sex, health system, and year of diagnosis were selected from all members making an outpatient visit (general outpatient group) and from all receiving a first diagnosis of unipolar depression (unipolar depression group)., Exposures: First recorded diagnosis of schizophrenia, schizoaffective disorder, mood disorder with psychotic symptoms, or other psychotic disorder in any outpatient, emergency department, or inpatient setting., Main Outcomes and Measures: Death within 3 years after the index diagnosis or visit date, ascertained from health system electronic health records, insurance claims, and state mortality records., Results: A total of 11 713 members with first diagnosis of a psychotic disorder (6976 [59.6%] men and 4737 [40.4%] women; 2368 [20.2%] aged 16-17 and 9345 [79.8%] aged 18-30 years) were matched to 35 576 outpatient service users and 23 415 members with a first diagnosis of unipolar depression. During the year after the first diagnosis, all-cause mortality was 54.6 (95% CI, 41.3-68.0) per 10 000 in the psychotic disorder group compared with 20.5 (95% CI, 14.7-26.3) per 10 000 in the unipolar depression group and 6.7 (95% CI, 4.0-9.4) per 10 000 in the general outpatient group. After adjustment for race, ethnicity, and preexisting chronic medical conditions, the relative hazard of death in the psychotic disorder group compared with the general outpatient group was 34.93 (95% CI, 8.19-149.10) for self-inflicted injury or poisoning and 4.67 (95% CI, 2.01-10.86) for other type of injury or poisoning. Risk of death due to heart disease or diabetes did not differ significantly between the psychotic disorder and the general outpatient groups (hazard ratio, 0.78; 95% CI, 0.15-3.96). Between the first and third years after diagnosis, all-cause mortality in the psychotic disorder group decreased from 54.6 to 27.1 per 10 000 persons and injury and poisoning mortality decreased from 30.6 to 15.1 per 10 000 persons. Both rates, however, remained 3 times as high as in the general outpatient group (9.0 per 10 000 for all causes; 4.8 per 10 000 for injury or poisoning)., Conclusions and Relevance: Increases in early mortality underscore the importance of systematic intervention for young persons experiencing the first onset of psychosis. Clinicians should attend to the elevated suicide risk after the first diagnosis a psychotic disorder.