Validation of a Multivariable Model to Predict Suicide Attempt in a Mental Health Intake Sample.

Importance: Given that suicide rates have been increasing over the past decade and the demand for mental health care is at an all-time high, targeted prevention efforts are needed to identify individuals seeking to initiate mental health outpatient services who are at high risk for suicide. Suicide prediction models have been developed using outpatient mental health encounters, but their performance among intake appointments has not been directly examined. Objective: To assess the performance of a predictive model of suicide attempts among individuals seeking to initiate an episode of outpatient mental health care. Design, Setting, and Participants: This prognostic study tested the performance of a previously developed machine learning model designed to predict suicide attempts within 90 days of any mental health outpatient visit. All mental health intake appointments scheduled between January 1, 2012, and April 1, 2022, at Kaiser Permanente Northern California, a large integrated health care delivery system serving over 4.5 million patients, were included. Data were extracted and analyzed from August 9, 2022, to July 31, 2023. Main Outcome and Measures: Suicide attempts (including completed suicides) within 90 days of the appointment, determined by diagnostic codes and government databases. All predictors were extracted from electronic health records. Results: The study included 1 623 232 scheduled appointments from 835 616 unique patients. There were 2800 scheduled appointments (0.17%) followed by a suicide attempt within 90 days. The mean (SD) age across appointments was 39.7 (15.8) years, and most appointments were for women (1 103 184 [68.0%]). The model had an area under the receiver operating characteristic curve of 0.77 (95% CI, 0.76-0.78), an area under the precision-recall curve of 0.02 (95% CI, 0.02-0.02), an expected calibration error of 0.0012 (95% CI, 0.0011-0.0013), and sensitivities of 37.2% (95% CI, 35.5%-38.9%) and 18.8% (95% CI, 17.3%-20.2%) at specificities of 95% and 99%, respectively. The 10% of appointments at the highest risk level accounted for 48.8% (95% CI, 47.0%-50.6%) of the appointments followed by a suicide attempt. Conclusions and Relevance: In this prognostic study involving mental health intakes, a previously developed machine learning model of suicide attempts showed good overall classification performance. Implementation research is needed to determine appropriate thresholds and interventions for applying the model in an intake setting to target high-risk cases in a manner that is acceptable to patients and clinicians.

Patient Perceptions of Prenatal Cannabis Use and Implications for Clinicians.

OBJECTIVE: To understand pregnant patients' reasons for prenatal cannabis use and perceptions of safety, desired and undesirable health care experiences, and desired information about prenatal cannabis use and secondarily to understand racial differences in these perceptions and preferences. METHODS: We conducted a qualitative study including 18 semi-structured, race-concordant virtual focus groups with pregnant individuals who self-reported cannabis use at prenatal care entry in a large integrated health care system in Northern California from November 2021 to December 2021. The focus groups included semi-structured questions that were recorded, transcribed, and coded by the research team. Thematic analysis was used to analyze the data. RESULTS: Overall, 53 participants were included; 30 self-identified, as White and 23 self-identified as Black. Participants averaged 30.3 years of age (SD 5.2 years) and were on average at 20.9 weeks of gestation at study enrollment; 69.8% reported daily cannabis use, 24.5% reported weekly cannabis use, and 5.7% reported monthly or less cannabis use at entrance to prenatal care. Although some participants quit cannabis use in early pregnancy because of concerns about potential health risks, many perceived a lack of scientific evidence or believed that prenatal cannabis use was safe. Many preferred cannabis to over-the-counter or prescription medications for treating mood, morning sickness, pain, and sleep. Participants valued open interactions with obstetricians that acknowledged their motivations for use, and they desired information about potential risks through conversations and educational materials. White and Black participants' perspectives were generally similar, but a few Black participants uniquely described concerns about racial bias related to their prenatal cannabis use. CONCLUSION: Pregnant patients used cannabis to manage mood and medical symptoms, and many believed that prenatal cannabis use was safer than the use of prescription medications. Obstetrician-initiated, patient-centered conversations around prenatal cannabis use, advice to discontinue cannabis use during pregnancy, and exploration of willingness to switch to medically recommended interventions for pregnancy-related symptoms may benefit patients.

Electroconvulsive Therapy Anesthetic Choice and Clinical Outcomes.

OBJECTIVE: Etomidate and methohexital are the 2 commonly used anesthetics for electroconvulsive therapy (ECT) in the United States. The objective of this study was to examine how anesthetic choice between etomidate and methohexital is associated with real-world clinical outcomes. METHODS: This naturalistic retrospective cohort study examined longitudinal electronic health records for 495 adult patients who received 2 or more ECT treatments from 2010 to 2019 in Kaiser Permanente North California, a large integrated health care system. Study outcomes included 12-month posttreatment depression remission as measured by the 9-item Patient Health Questionnaire, psychiatric and all-cause emergency department visits, and psychiatric and all-cause hospitalizations. RESULTS: Anesthetic choice was not significantly related to depression severity, emergency department visits, or psychiatric hospitalizations at 12 months after completing ECT. In exploratory analyses, we found that etomidate compared with methohexital was associated with higher rates of patient discomfort adverse effects-postictal agitation, phlebitis, and myoclonus (2.4% vs 0.4%; P < 0.001). CONCLUSIONS: We present the first large comparison of etomidate and methohexital as anesthetics for ECT and their associations with real-world outcomes. Our study showed no significant difference on depression remission, emergency department visits, or hospitalizations 12-months posttreatment. Thus, clinicians should focus on other patient or treatment characteristics when deciding on anesthetics for ECT. Further investigation is needed to confirm our exploratory findings that etomidate use was correlated with a higher rate of patient discomfort adverse effects relative to methohexital.

Evaluating Implementation and Outcomes of the Achieving Depression and Anxiety Patient-Centered Treatment Collaborative Care Program in a Large, Integrated Health Care System: A Mixed Methods Observational Study Protocol.

Background Collaborative care is an evidence-based multidisciplinary model shown to improve patient depression and anxiety outcomes. Although there is robust literature showing the effectiveness of collaborative care on depression and anxiety symptoms, there is little published on outcomes of collaborative care implementation or the efficacy of collaborative care compared with psychiatric referrals. Reported here is a study protocol examining a novel depression and anxiety collaborative care program in a large, integrated health care system. Methods This is a mixed methods study of the Achieving Depression and Anxiety Patient-Centered Treatment (ADAPT) program as compared to outpatient psychiatric care at Kaiser Permanente Northern California, a large, integrated health care delivery system. The ADAPT program was designed using collaborative care principles, including measurement-based care, accurate diagnosis, and population management. Eligible participants will be ≥ 18 years old with mild to moderate-severe depressive symptoms as measured by the Patient Health Questionnaire-9. Exclusion criteria include acute suicide risk and serious mental health comorbidities. Implementation is examined using the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework and interviews with program stakeholders. Results Pending. Conclusion Study data will help inform future collaborative care efforts while expanding the literature base. The Achieving Depression and Anxiety Patient-Centered Treatment program may improve patient outcomes and access to quality depression and/or anxiety care.

Opportunities to Integrate Mobile App-Based Interventions Into Mental Health and Substance Use Disorder Treatment Services in the Wake of COVID-19.

The COVID-19 pandemic has heightened concerns about the impact of depression, anxiety, alcohol, and drug use on public health. Mobile apps to address these problems were increasingly popular even before the pandemic, and may help reach people who otherwise have limited treatment access. In this review, we describe pandemic-related substance use and mental health problems, the growing evidence for mobile app efficacy, how health systems can integrate apps into patient care, and future research directions. If equity in access and effective implementation can be addressed, mobile apps are likely to play an important role in mental health and substance use disorder treatment.

Physical, Mental Health and Developmental Conditions, and Sociodemographic Characteristics Associated With Adverse Childhood Experiences Among Young Children in Pediatric Primary Care.

INTRODUCTION: To examine associations between patient characteristics and adverse childhood experiences (ACEs) in a population-based sample of pediatric primary care patients, using electronic health records and clinical, administrative data. METHOD: An observational study was conducted in an integrated health care delivery system. Children ages 1-5 years (N = 13,370) were screened for ACEs at routine well-child visits between September 1, 2018 and May 31, 2019 in three pediatrics clinics. Multivariate models examined associations between patient characteristics (age, gender, race/ethnicity, insurance type, neighborhood income and education level, physical, mental health and developmental diagnoses, weight status) and any ACEs, and ≥ 3 ACEs exposure. RESULTS: Prevalence and severity of ACE exposure varied by race/ethnicity. Older age, Medicaid insurance, epilepsy/seizure disorder, sleeping disorders, adjustment disorders, and feeding disorders were associated with higher odds of ACEs exposure, higher-income with lower odds. DISCUSSION: Understanding relationships between ACEs and patient features can provide information to clinicians for early detection and appropriate interventions.

Premature mortality associated with severe mental illness or substance use disorder in an integrated health care system.

OBJECTIVE: Research has reported shortened lifespans (by 15-30 years) for those with severe mental illness (SMI) or substance use disorder (SUD), particularly among public mental health treatment consumers. We assessed SMI- and SUD-associated mortality in the understudied setting of a large, nonprofit integrated health care system. METHOD: This retrospective cohort study examined 2010-2017 health system and death records for 564,592 adult patients. Half had SMI/SUD diagnosis; half were a demographically matched comparison group without SMI, other mental health, or SUD diagnoses. We estimated mortality risks, adjusting for demographic and physical health factors. RESULTS: Having SMI or SUD was associated with higher odds of death (adjusted odds ratio = 1.87) and an average 6.3 years of earlier death relative to comparison individuals. Co-occurring SMI and SUD conferred higher mortality risk from major natural and unnatural causes than did SMI with no SUD. CONCLUSIONS: Some indicators of premature mortality were lower than those reported for U.S. public mental health consumers, but risk level varied widely by diagnosis. While patients' having insurance and broad access to care may lower risk, access to care may be insufficient to overcome the many patient-, provider-, and system-level factors contributing to poor physical health in SMI and SUD.

Association of Anxiety With High-Cost Health Care Use Among Individuals With Type 2 Diabetes.

OBJECTIVE: People with type 2 diabetes vary greatly in their use of high-cost health care resources. We examined the association of anxiety with high-cost use after accounting for depression and medical comorbidity. RESEARCH DESIGN AND METHODS: Using electronic health record data, we assessed past anxiety diagnosis, health care use and costs, demographics, comorbidities, and diabetes control status and complications during 2008-2012 for 143,573 adult members of an integrated health care system with type 2 diabetes. Multivariable regression models estimated associations between anxiety and emergency department (ED) use, total hospitalization costs, and high-cost status (i.e., incurring total health care costs in the top 20% among all system members). RESULTS: During 2008-2011, 12.9% of participants received a diagnosis of anxiety, of whom 52.9% also had received a depression diagnosis. After adjustment for covariates including depression, anxiety was positively related to the number of ED visits in 2012 (incidence rate ratio 1.27; 95% CI 1.21, 1.34), the likelihood of visiting the ED on a chronic, frequent basis during 2010-2012 (odds ratio 2.55; 95% CI 1.90, 3.44), and high-cost status in 2012 (odds ratio 1.29; 95% CI 1.23, 1.36), but anxiety was not related to total hospitalization costs in 2012 (relative cost ratio 1.06; 95% CI 0.94, 1.21; P = 0.33). CONCLUSIONS: Anxiety is highly comorbid with depression among individuals with type 2 diabetes and is independently associated with high-cost resource use. Strategies to improve anxiety management among people with diabetes hold the potential to also reduce health care costs.