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

Importance: An improved understanding of autism spectrum disorder (ASD) prevalence over time and across the lifespan can inform health care service delivery for the growing population of autistic children and adults.

Objective: To describe trends in the prevalence of ASD diagnoses using electronic records data from a large network of health systems in the US.

Design, Setting, And Participants: This cross-sectional study examined annual diagnosis rates in health records of patients in US health systems from January 1, 2011, to December 31, 2022.

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

Background: Antipsychotic medications (AP) are inappropriately prescribed to young people. The goal of this pragmatic trial was to test a four-component approach to improved targeting of antipsychotic prescribing to people aged ≥3 and <18 years.

Methods: Clinicians in four health systems were cluster randomized by the number of previous AP orders and service line - specialty mental health and all others.

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

To understand the impact of the transition to telehealth during COVID-19 on psychotherapy visits for patients with dementia. 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.

Evaluation of the Safer Use of Antipsychotics in Youth Study on Population Level Antipsychotic Initiation: An Interrupted Time Series Analysis.

Antipsychotics carry a higher-risk profile than other psychotropic medications and may be prescribed for youth with conditions in which other first-line treatments are more appropriate. This study aimed to evaluate the population-level effect of the Safer Use of Antipsychotics in Youth (SUAY) trial, which aimed to reduce person-days of antipsychotic use among participants. We conducted an interrupted time series analysis using segmented regression to measure changes in prescribing trends of antipsychotic initiation rates pre-SUAY and post-SUAY trial at four U.

Patient Characteristics and Telemedicine Use in the US, 2022.

Importance: Telemedicine use was common during the COVID-19 pandemic, expanding many patients' approaches to accessing health care. Of concern is whether telemedicine access was poorer among higher-needs and disadvantaged populations.

Objective: To assess patient characteristics associated with telemedicine use and telemedicine mode and describe telemedicine visit experiences by telemedicine mode.

On- and Off-Label Atypical Antipsychotic Prescription Trends Across a Nine-Year Period Among Adolescents Pre- to Post-COVID-19.

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.

Short report: Transition to International Classification of Diseases, 10th Revision and the prevalence of autism in a cohort of healthcare systems.

Currently, the prevalence of autism spectrum disorder (henceforth "autism") is 1 in 36, an increasing trend from previous estimates. In 2015, the United States adopted a new version (International Classification of Diseases, 10th Revision) of the World Health Organization coding system, a standard for classifying medical conditions. Our goal was to examine how the transition to this new coding system impacted autism diagnoses in 10 healthcare systems.

The rapid shift to virtual mental health care: Examining psychotherapy disruption by rurality status.

Background: Given the low usage of virtual health care prior to the COVID-19 pandemic, it was unclear whether those living in rural locations would benefit from increased availability of virtual mental health care. The rapid transition to virtual services during the COVID-19 pandemic allowed for a unique opportunity to examine how the transition to virtual mental health care impacted psychotherapy disruption (i.e.

Improving Diabetes Control in a Medicaid Managed Care Population With Complex Needs.

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.

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

Objective: To understand how race and serious mental illness (SMI) interact for disruptive life events defined as financial (bankruptcy and judgement filings), and non-financial (arrests).

Methods: Patients were adults with schizophrenia (SCZ; N = 16,159) or bipolar I disorder (BPI; N = 30,008) matched 1:1 to patients without SMI (non-SMI) from health systems in Michigan and Southern California during 1/1/2007 through 12/31/2018. The main exposure was self-reported race, and the outcome was disruptive life events aggregated by Transunion.

Psychotherapy Disruption Before and After the Transition to Virtual Mental Health Care Induced by the COVID-19 Pandemic.

Objective: This study aimed to examine population-level disruption in psychotherapy before and after the rapid shift to virtual mental health care induced by the onset of the COVID-19 pandemic in the United States.

Methods: This retrospective study used electronic health record and insurance claims data from three U.S.

Pilot Evaluation of the Family Bridge Program: A Communication- and Culture-Focused Inpatient Patient Navigation Program.

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.

Cost of Implementing an Evidence-Based Intervention to Support Safer Use of Antipsychotics in Youth.

To estimate the cost of implementing a clinical program designed to support safer use of antipsychotics in children and adolescents (youth) age 3-17 years at the time of initiating an antipsychotic medication. We calculate the costs of implementing a psychiatric consultation and navigation program for youth prescribed antipsychotic medications across 4 health systems, which included an electronic health record (EHR) decision support tool, consultation with a child and adolescent psychiatrist, and up to 6 months of behavioral health care navigation, as well as telemental health for patients (n = 348). Cost data were collected for both start-up and ongoing intervention phases and are estimated over a 1-year period.

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

Importance: There is a dearth of population-level data on major disruptive life events (defined here as arrests by a legal authority, address changes, bankruptcy, lien, and judgment filings) for patients with bipolar I disorder (BPI) or schizophrenia, which has limited studies on mental health and treatment outcomes.

Objective: To conduct a population-level study on disruptive life events by using publicly available data on disruptive life events, aggregated by a consumer credit reporting agency in conjunction with electronic health record (EHR) data.

Design, Setting, And Participants: This study used EHR data from 2 large, integrated health care systems, Kaiser Permanente Southern California and Henry Ford Health.

STAR-Caregivers Virtual Training and Follow-up: a cultural adaptation for Latino caregivers of people with dementia.

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).

Using natural language processing to identify child maltreatment in health systems.

Background: Rates of child maltreatment (CM) obtained from electronic health records are much lower than national child welfare prevalence rates indicate. There is a need to understand how CM is documented to improve reporting and surveillance.

Objectives: To examine whether using natural language processing (NLP) in outpatient chart notes can identify cases of CM not documented by ICD diagnosis code, the overlap between the coding of child maltreatment by ICD and NLP, and any differences by age, gender, or race/ethnicity.

Development of a machine learning model to predict mild cognitive impairment using natural language processing in the absence of screening.

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.