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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In addition to providing critical medical services to communities, hospitals are also forces of broader change when seen from the perspective of neighborhood development. Over the past few decades the obligation on the part of U.S. nonprofit hospitals to positively impact the communities in which they are located has become entrenched in both U.S. tax law and the practices of many hospitals. This article presents findings from a grounded theory qualitative study of the relationship between a non-profit children's hospital in Columbus, Ohio, and the neighborhood in which it is located. Based on in-depth interviews with local residents and community leaders, findings suggest that community members often interpret distance, safety, and transportation in different, and often counter-intuitive ways. Drawing upon literature from medical geography and sociology, the authors argue that hospitals may benefit from working closely with community members to determine how space is understood and constructed when planning community health interventions. [ABSTRACT FROM AUTHOR]

Background: While clinicians are expected to routinely assess and address suicide risk, existing data provide little guidance regarding the significance of visit-to-visit changes in suicidal ideation.Methods: Electronic health records from four large healthcare systems identified patients completing the Patient Health Questionnaire or PHQ9 at outpatient visits. For patients completing two questionnaires within 90 days, health system records and state vital records were used to identify nonfatal and fatal suicide attempts. Analyses examined how changes in PHQ9 item 9 responses between visits predicted suicide attempt or suicide death over 90 days following the second visit.Results: Analyses included 430,701 pairs of item 9 responses for 118,696 patients. Among patients reporting thoughts of death or self-harm "nearly every day" at the first visit, risk of suicide attempt after the second visit ranged from approximately 2.0% among those reporting continued thoughts "nearly every day" down to 0.5% among those reporting a decrease to "not at all." Among those reporting thoughts of death or self-harm "not at all" at the first visit, risk of suicide attempt following the second visit ranged from approximately 0.2% among those continuing to report such thoughts "not at all" up to 1.2% among those reporting an increase to "nearly every day".Conclusions: Resolution of suicidal ideation between visits does imply a clinically important reduction in short-term risk, but prior suicidal ideation still implies significant residual risk. Onset of suicidal ideation between visits does not imply any special elevation compared to ongoing suicidal ideation. Risk is actually highest for patients repeatedly reporting thoughts of death or self-harm. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

Objective To examine whether the effects of a nurse navigator intervention for cancer vary with baseline depressive symptoms. Method Participants were enrolled in a randomized controlled trial of a nurse navigation intervention for patients newly diagnosed with lung, breast or colorectal cancer ( N = 251). This exploratory analysis used linear regression models to estimate the effect of a nurse navigator intervention on patient experience of care. Models estimated differential effects by including interactions between randomization group and baseline depressive symptoms. Baseline scores on the 9-item Patient Health Questionnaire (PHQ) were categorized into 3 groups: no depression (PHQ=0–4, N = 138), mild symptoms of depression (PHQ=5–9, N = 76) and moderate to severe symptoms (PHQ=10 or greater, N = 34). Patient experience outcomes were measured by subscales of the Patient Assessment of Chronic Illness Care (PACIC) and subscales from an adaptation of the Picker Institute’s patient experience survey at 4-month follow-up. Results With the exception of the PACIC subscale of delivery system/practice design, interaction terms between randomization group and PHQ-9 scores were not statistically significant. Conclusions The intervention was broadly useful; we found that it was equally beneficial for both depressed patients and patients who were not significantly depressed in the first 4 months postdiagnosis. However, because of the small sample size, we cannot conclude with certainty that patients with depressive symptoms did not differentially benefit from the intervention. [ABSTRACT FROM AUTHOR]

Background The overlap of somatic symptoms of depression with symptoms of cancer treatment is widely acknowledged and studied. However, this literature provides little guidance for clinicians as to whether these items should be used in assessing depression. The current study examined the appropriateness of using somatic items for assessment of depression in people with cancer. Methods People with newly diagnosed breast, lung or colorectal cancer ( n =251) completed the Patient Health Questionnaire-9 (PHQ9) shortly after cancer diagnosis but before cancer treatment (baseline), 4 months later, typically during or shortly after treatment, and 12 months later. Pharmacy data was used to classify participants as having low somatic symptoms or high somatic symptoms. Differential item function (DIF) compared the functioning of the somatic items of the PHQ9 in the low vs. high symptom groups and the chemotherapy vs. no chemotherapy groups at the 4-month assessment. Results Significant DIF was not found on any of the four somatic items of the PHQ9 and differences in the item parameters of the somatic items were not consistent across the groups. However, fatigue and sleep indicated only mild depression. Only removing the fatigue item greatly affected the number screening positive for depression at 4 months (8.3%) but removing the other somatic items did not have as large an effect. Only one participant at baseline screened positive for depression by somatic symptoms alone (no psychological symptoms) and no participants screened positive by somatic symptoms alone at 4 months and 12 months. Limitations The sample size was small for DIF and consisted of mostly women with breast cancer. Conclusions Somatic symptoms of depression can continue to be administered to people with cancer, however the fatigue and sleep items should be used with caution. [ABSTRACT FROM AUTHOR]

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.

Purpose: The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making., Methods: In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives., Results: We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed., Conclusions: Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system., (© 2024 John Wiley & Sons Ltd.)

Objective: To understand the impact of the transition to telehealth during COVID-19 on psychotherapy visits for patients with dementia. Method: Retrospective study of older adults with dementia who had at least one psychotherapy visit in the 9 months before and after the onset of COVID-19 at 3 U.S. health systems. Care disruptions were gaps of 45+ days. Descriptive statistics and logistic mixed-effects models examined factors associated with care disruption. Results: 4953 patients with dementia made 19,902 psychotherapy visits. Gaps in psychotherapy were less frequent during COVID-19 (29.4%) than before (48.9%), with the odds of a patient experiencing a care disruption during COVID-19 0.54 times the odds prior to COVID-19 (95% CI: 0.50-0.59). Almost all patient subgroups had lower adjusted odds of care disruption during COVID-19. Discussion: There were fewer disruptions in psychotherapy care following the rapid shift to virtual care. Telehealth may be a viable option for patients with dementia., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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.

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.)

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.)

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.

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.)

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: 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.)

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.)

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.

Objective: To compare patterns of health care utilization associated with first presentation of psychosis among different racial and ethnic groups of patients., Design: The study was a retrospective observational design., Setting: The study was conducted in five health care systems in the western United States. All sites were also part of the National Institute of Mental Health-funded Mental Health Research Network (MHRN)., Participants: Patients (n = 852) were aged 15 - 59 years (average 26.9 ± 12.2 years), 45% women, and primarily non-Hispanic White (53%), with 16% Hispanic, 10% non-Hispanic Black, 6% Asian, 1% Native Hawaiian/Pacific Islander, 1% Native American/ Alaskan Native, and 12% unknown race/ethnicity., Main Outcome Measures: Variables examined were patterns of health care utilization, type of comorbid mental health condition, and type of treatment received in the three years before first presentation of psychosis., Methods: Data abstracted from electronic medical records and insurance claims data were organized into a research virtual data warehouse (VDW) and used for analysis., Results: Compared with non-Hispanic Whites, Asian patients (16% vs 34%; P=.007) and non-Hispanic Black patients (20% vs 34%; P=.009) were less likely to have a visit with specialty mental health care before their first presentation of psychosis., Conclusions: Early detection of first episode psychosis should start with wider screening for symptoms outside of any indicators for mental health conditions for non-Hispanic Black and Asian patients., Competing Interests: Competing Interests: None declared., (Copyright © 2019, Ethnicity & Disease, 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: 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.

Objective: To identify space-time clusters of changes in prescribing aripiprazole for bipolar disorder among providers in the VA., Data Sources: VA administrative data from 2002 to 2010 were used to identify prescriptions of aripiprazole for bipolar disorder. Prescriber characteristics were obtained using the Personnel and Accounting Integrated Database., Study Design: We conducted a retrospective space-time cluster analysis using the space-time permutation statistic., Data Extraction Methods: All VA service users with a diagnosis of bipolar disorder were included in the patient population. Individuals with any schizophrenia spectrum diagnoses were excluded. We also identified all clinicians who wrote a prescription for any bipolar disorder medication., Principal Findings: The study population included 32,630 prescribers. Of these, 8,643 wrote qualifying prescriptions. We identified three clusters of aripiprazole prescribing centered in Massachusetts, Ohio, and the Pacific Northwest. Clusters were associated with prescribing by VA-employed (vs. contracted) prescribers. Nurses with prescribing privileges were more likely to make a prescription for aripiprazole in cluster locations compared with psychiatrists. Primary care physicians were less likely., Conclusions: Early prescribing of aripiprazole for bipolar disorder clustered geographically and was associated with prescriber subgroups. These methods support prospective surveillance of practice changes and identification of associated health system characteristics., (© Health Research and Educational Trust.)

Background: Unnecessary care contributes to high costs and places patients at risk of harm. While most providers support reducing low-value care, changing established practice patterns is difficult and requires active engagement in sustained behavioral, organizational, and cultural change. Here we describe an action-planning framework to engage providers in reducing overused services., Methods: The framework is informed by a comprehensive review of social science theory and literature, published reports of successful and unsuccessful efforts to reduce low-value care, and interviews with innovators of value-based care initiatives in twenty-three health care organizations across the United States. A multi-stakeholder advisory committee provided feedback on the framework and guidance on optimizing it for use in practice., Results: The framework describes four conditions necessary for change: prioritize addressing low-value care; build a culture of trust, innovation and improvement; establish shared language and purpose; and commit resources to measurements. These conditions foster productive sense-making conversations between providers, between providers and patients, and among members of the health care team about the potential for harm from overuse and reflection on current frequency of use. Through these conversations providers, patients and team members think together as a group, learn how to coordinate individual behaviors, and jointly develop possibilities for coordinated action around specific areas of overuse., Conclusions: Organizational efforts to engage providers in value-based care focused on creating conditions for productive sense-making conversations that lead to change., Implications: Organizations can use this framework to enhance and strengthen provider engagement efforts to do less of what potentially harms and more of what truly helps patients., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: To learn if a quality of care Medicaid child psychiatric consultation service implemented in three different steps was linked to changes in statewide child antipsychotic utilization., Data Sources/study Setting: Washington State child psychiatry consultation program primary data and Medicaid pharmacy division antipsychotic utilization secondary data from July 1, 2006, through December 31, 2013., Study Design: Observational study in which consult program data were analyzed with a time series analysis of statewide antipsychotic utilization., Data Collection/extraction Methods: All consultation program database information involving antipsychotics was compared to Medicaid pharmacy division database information involving antipsychotic utilization., Principal Findings: Washington State's total child Medicaid antipsychotic utilization fell from 0.51 to 0.25 percent. The monthly prevalence of use fell by a mean of 0.022 per thousand per month following the initiation of elective consults (p = .004), by 0.065 following the initiation of age/dose triggered mandatory reviews (p < .001), then by another 0.022 following the initiation of two or more concurrent antipsychotic mandatory reviews (p = .001). High-dose antipsychotic use fell by 57.8 percent in children 6- to 12-year old and fell by 52.1 percent in teens., Conclusions: Statewide antipsychotic prescribing for Medicaid clients fell significantly at different rates following each implementation step of a multilevel consultation and best-practice education service., (© Health Research and Educational Trust.)

Background: There is concern about the prevalence of prescribing antidepressant medications to youth without appropriate diagnoses or who have subthreshold (mild) depression., Methods: Electronic records data from 3 large healthcare systems identified youth aged ≤21 years starting a new episode of antidepressant treatment between January 1, 2009, and December 31, 2013. For those with a diagnosis of depression, Patient Health Questionnaire (PHQ9) scores at the time of treatment initiation were used to examine the distribution of symptom severity and patients' demographic and clinical characteristics., Results: Of the 15,460 episodes of treatment, a depression diagnosis was recorded in 95% of the cases. PHQ9 scores were available for 4,329 youth with a diagnosis of depression. Younger age, sex, previous treatment, co-occurring anxiety, treatment setting, concurrent psychotherapy, and site were significant predictors of completing a PHQ9. Among youth with a baseline score, 87% reported moderate or severe symptoms (PHQ9 score ≥ 10) and 13% reported mild or minimal symptoms (PHQ9 < 10). The proportion reporting PHQ9 < 10 when starting treatment decreased with age, ranging from 19% in those aged 13-14 years and 12% in those aged 18-21 years. Patients treated by psychiatrists were 1.54 times (95% Confidence Interval [CI], 1.21-1.97) more likely to have PHQ9 scores < 10 compared with primary care physicians. Patients with prior treatment history (odds ratio = 1.76; 95% CI, 1.45-2.13) and concurrent psychotherapy (odds ratio = 1.24; 95% CI, 1.02-1.52) were more likely to have PHQ9 < 10., Conclusions: In these health systems, prescribing of antidepressant medication to adolescents for minimal or mild depression is much less common than previous reported.

Background: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) carry a high mortality risk. While identifying clinical and genetic risk factors for these conditions has been hindered by their rarity, large electronic health databases hold promise for identifying large numbers of cases for study, especially with the introduction in 2008 of ICD-9 codes more specific for these conditions., Objective: The objective of this study is to estimate the validity of ICD-9 codes for ascertaining SJS/TEN in 12 collaborating research units in the USA, covering almost 60 million lives., Methods: From the electronic databases at each site, we ascertained potential cases of SJS/TEN using ICD-9 codes. At five sites, a subset of medical records was abstracted and standardized criteria applied by board-certified dermatologists to adjudicate diagnoses. Multivariate logistic regression was used to identify factors independently associated with validated SJS/TEN cases., Results: A total of 56 591 potential cases of SJS/TEN were identified. A subset of 276 charts was selected for adjudication and 39 (of the 276) were confirmed as SJS/TEN. Patients with the ICD-9 codes introduced after 2008 were more likely to be confirmed as cases (OR 3.32; 95%CI 0.82, 13.47) than those identified in earlier years. Likelihood of case status increased with length of hospitalization. Applying the probability of case status to the 56 591 potential cases, we estimated 475-875 to be valid SJS/TEN cases., Conclusion: Newer ICD-9 codes, along with length of hospitalization, identified patients with a high likelihood of SJS/TEN. This is important for identification of subjects for future pharmacogenomics studies., (Copyright © 2015 John Wiley & Sons, Ltd.)

The central idea observes a recursive mapping of [Formula: see text]-body intramolecular interactions to [Formula: see text]-body terms that is consistent with the molecular topology. Iterative application of the line graph transformation is identified as a natural and elegant tool to accomplish the recursion. The procedure readily generalizes to arbitrary [Formula: see text]-body potentials. In particular, the method yields a complete characterization of [Formula: see text]-body interactions. The hierarchical structure of atomic index lists for each interaction order [Formula: see text] is compactly expressed as a directed acyclic graph. A pseudo-code description of the generating algorithm is given. With suitable data structures (e.g., edge lists or adjacency matrices), automatic enumeration and indexing of [Formula: see text]-body interactions can be implemented straightforwardly to handle large bio-molecular systems. Explicit examples are discussed, including a chemically relevant effective potential model of taurocholate bile salt.

Background: Recommendations for annual seasonal influenza vaccination have expanded to now include >300 million children and adults each year. Community settings have become increasingly important venues for influenza vaccination. We sought to identify barriers to and solutions for expanding influenza vaccination in community settings., Methods: Semi-structured telephone interviews were conducted from 01/09 to 06/10 with a range of stakeholders involved in influenza vaccination, including health plans, medical services firms, retail based clinics, pharmacies, schools, and state and local public health immunization programs. Participants (n=65) were asked about barriers and feasible solutions to influenza vaccine delivery to children and adults in community settings. Key themes were identified through iterative coding using a grounded theory approach., Results: Stakeholders identified specific financial barriers to influenza vaccine delivery in 3 major areas: purchase and distribution, delivery, and reimbursement. Limited purchasing power, the uncertain nature of public demand, and unpredictable timing of influenza vaccine supply were important barriers to enhance delivery in community settings. Barriers to delivery included complexities in running off-site clinics, especially in school settings, the need to manage publicly vs. privately purchased vaccines separately, and state-to-state variability in requirements for credentialing, physician oversight, and reporting. Reimbursement barriers included a protracted credentialing process, the need to determine insurance eligibility at point-of-service, and lack of a billing infrastructure in off-site clinics. Opportunities to mitigate financial barriers to influenza vaccine delivery in community settings focused on coordination across providers and the role of public health as a "trusted broker" to overcome existing challenges., Conclusions: Financial and systems barriers hamper the optimal use of community settings to effectively deliver influenza vaccines. Public health partners at the federal, state, and local levels are well-positioned to facilitate the engagement of all stakeholders in this important and complex vaccine delivery system., (Copyright © 2011 Elsevier Ltd. All rights reserved.)