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Objective: The opioid intervention court (OIC) is an innovative, pre-plea treatment court to facilitate rapid linkage to medications for opioid use disorder (MOUD) for people at risk of overdose. This study compares participants in OIC and participants with opioid use problems in a traditional drug treatment court model on (i) initiation for any substance use (SU) treatment, (ii) initiation of MOUD, (iii) number of days to MOUD initiation, and (iv) retention in the OIC program/retention on MOUD., Methods: We used administrative court records from n = 389 OIC and n = 229 drug court participants in 2 counties in New York State. Differences in outcomes by court were assessed using logistic, multinomial, or linear regressions., Results: After adjusting for current charge severity, gender, race/ethnicity, age, and county, OIC participants were no more likely to initiate any SU treatment but were significantly more likely to initiate MOUD (81.2% OIC vs 45.9% drug court, P < 0.001) and were more quickly linked to any SU treatment (hazard ratio = 1.68, 95% confidence interval = 1.35-2.08) and MOUD (hazard ratio = 4.25, 95% confidence interval = 3.23-5.58) after starting the court. Retention in court/MOUD was higher among drug court participants and may speak to the immediate sanctions (eg, jail) for noncompliance with drug court directives as compared with opioid court, which does not carry such immediate sanctions for noncompliance., Conclusions: These analyses suggest that the new OIC model can more rapidly link participants to treatment, including MOUD, as compared with traditional drug court model, and may demonstrate improved ability to immediately stabilize and reduce overdose risk in court participants., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 American Society of Addiction Medicine.)

Importance: In coordinated specialty care (CSC) settings for people with a first episode of psychosis, the development of reliable, validated individual-level prediction tools for key outcomes may be informative for shared clinician and client decision-making., Objective: To develop an individual-level prediction tool using machine-learning methods that predicts a trajectory of education/work status or psychiatric hospitalization outcomes over a client's next year of quarterly follow-up assessments. Additionally, to visualize these predictions in a way that is informative to clinicians and clients., Design, Setting, and Participants: Individual-level data were collected for all patients enrolled in the OnTrackNY program at enrollment and at quarterly follow-ups using standardized forms. The OnTrackNY program, a network of CSC sites in New York State, provides person-centered, recovery-oriented, and evidence-based psychosocial and pharmaceutical interventions to individuals aged 16 to 30 years with recent-onset (<2 years) nonaffective psychosis. Although data collection is ongoing, data for this study were collected from October 2013 to December 2018, and the time frame for analysis was July 2020 to May 2021. Data were separated into a training/cross-validation set to perform internally validated model development and a separate holdout test set (~20% of the sample) for external validation. Random probability forest models were developed to predict individual-level trajectories of outcomes., Exposures: Forty-three individual-level demographic and clinical features collected at enrollment in OnTrackNY, 25 of which were time-varying and updated at quarterly follow-up assessments, and 13 site-level demographic and economic census variables., Main Outcomes and Measures: Individual-level education and/or employment status and psychiatric hospitalization trajectories at quarterly follow-up periods across the first 2 years of CSC., Results: The total study sample consists of 1298 individuals aged 16 to 30 years and included 341 women (26.3%), 949 men (73.1%), and 8 (<1%) with another gender. Prediction models performed well for 1-year trajectories of education/work across all validation sets, with areas under the receiver operating characteristic curve (AUCs) ranging from 0.68 (95% CI, 0.63-0.74) to 0.88 (95% CI, 0.81-0.96). Predictive accuracy for psychiatric hospitalization 3 months ahead reached AUC above 0.70; moreover, predictions of future psychiatric hospitalizations at 6 months and beyond were consistently poor, with AUCs below 0.60. Given the good externally validated performance for predicting education/work, a prototype interactive visualization tool displaying individual-level education/work trajectories and related features was developed., Conclusions and Relevance: This study suggests that accurate prediction tools can be developed for outcomes in people with first-episode psychosis, which may help inform shared clinician/client decision-making. Future work should study the effectiveness of its deployment, including proper communication to inform shared clinician/client decision-making in the context of a learning health care system. At present, more work is needed to develop better performing prediction models for future psychiatric hospitalizations before any tool is recommended for this outcome.

Importance: Intersecting factors of social position including ethnoracial background may provide meaningful ways to understand disparities in pathways to care for people with a first episode of psychosis., Objective: To examine differences in pathways to care by ethnoracial groups and by empirically derived clusters combining multiple factors of social and clinical context in an ethnoracially diverse multisite early-intervention service program for first-episode psychosis., Design, Setting, and Participants: This cohort study used data collected on individuals with recent-onset psychosis (<2 years) by clinicians with standardized forms from October 2013 to January 2020 from a network of 21 coordinated specialty care (CSC) programs in New York State providing recovery-oriented, evidence-based psychosocial interventions and medications to young people experiencing early psychosis., Exposures: Ethnoracial group and other factors of social position (eg, insurance status, living situation, English fluency, geographic region) intersecting with first-contact experiences (ie, type of first service, referral source, and symptoms at referral)., Main Outcomes and Measures: Outcome measures were time from onset to first contact, first contact to CSC, and onset to CSC., Results: The total study sample consists of 1726 individuals aged 16 to 30 years and included 452 women (26%), 1263 men (73%), and 11 (<1%) with another gender enrolled in the network of CSC programs. The total sample consisted of 153 Asian (9%), 599 Black (35%), 454 Latinx (26%), and 417 White individuals (24%). White individuals had a significantly shorter time from onset to first contact (median [IQR], 17 [0-80] days) than Asian (median [IQR], 34 [7-94] days) and Black (median [IQR], 30 [1-108] days) individuals but had the longest period from first contact to CSC (median [IQR], 102.5 [45-258] days). Five distinct clusters of individuals emerged that cut across ethnoracial groups. The more disadvantaged clusters in terms of both social position and first-contact experiences had the longest time from onset to first contact, which were longer than for any single ethnoracial group., Conclusions and Relevance: In this cohort study of individuals with recent-onset psychosis, time-to-treatment outcomes differed by ethnoracial group and by empirically derived clusters combining multiple factors of social and clinical context. The examination of disparities in durations to treatment through an intersectional, ethnoracial lens may improve understanding of the inequities resulting from the various intersecting factors that may compound delays in treatment initiation.

Individuals with serious mental illness are particularly vulnerable to COVID-19. The New York State (NYS) Office of Mental Health implemented patient and staff rapid testing, quarantining, and vaccination to limit COVID-19 spread in 23 state-operated psychiatric hospitals between November 2020 and February 2021. COVID-19 infection rates in inpatients and staff decreased by 96% and 71%, respectively, and the NYS population case rate decreased by 6%. Repeated COVID-19 testing and vaccination should be priority interventions for state-operated psychiatric hospitals. ( Am J Public Health . 2021;111(10):1780-1783. https://doi.org/10.2105/AJPH.2021.306444).

Objective: This study examined associations of patient, hospital, and service system factors with provision of discharge planning to individuals treated in hospital psychiatric units., Methods: This retrospective cohort analysis used 2012-2013 New York State Medicaid claims data of 18,185 patients ages <65 years who were treated in hospital psychiatric units and discharged to the community. The claims data were linked to data from managed behavioral health care organizations indicating whether inpatient staff scheduled a follow-up outpatient appointment with a mental health provider. Additional data regarding hospital and service system characteristics were obtained from the American Hospital Association Annual Survey, the Area Health Resource File, and other state administrative databases. Rates and adjusted odds ratios were assessed for the likelihood of inpatient staff scheduling a follow-up appointment., Results: Inpatient staff scheduled outpatient appointments for 79.8% of discharges. The adjusted odds of not having an outpatient appointment scheduled as part of the patient's discharge plan were significantly associated with several factors, including being homeless on admission, having a diagnosis of a co-occurring substance use disorder, having high levels of medical comorbid conditions, and not being engaged in psychiatric outpatient services in the month prior to admission., Conclusions: Patient characteristics were more strongly associated with failure to receive discharge planning than were hospital and service system characteristics.

Objective: This study examined a cohort of 15,520 inpatient psychiatric discharges to determine associations between scheduling an outpatient mental health appointment as part of discharge planning and attending outpatient care following discharge after control for patient, hospital, and system characteristics., Methods: 2012-2013 New York State Medicaid and other administrative databases were used to examine patients who were aged under 65 years, admitted to an inpatient psychiatric unit, and discharged to the community. Outcomes included attending an outpatient mental health service within 7 and 30 days following inpatient discharge. Scheduling a mental health outpatient appointment as part of the discharge plan was the primary predictor variable, and potentially confounding covariates were addressed by adjusting for propensity scores estimating the likelihood of having an outpatient appointment scheduled., Results: Among 15,520 discharged patients, 11,945 (77%) had an outpatient appointment scheduled with a mental health provider as part of their discharge planning. After adjustment for propensity scores, patients who had an outpatient appointment scheduled were significantly more likely to attend an outpatient mental health service within 7 (OR = 1.69; 95% CI, 1.48-1.94) and 30 days (OR = 1.65; 95% CI, 1.42-1.93) compared to patients who did not have an appointment scheduled. Even among those with a low propensity to have an appointment scheduled, scheduling an outpatient appointment was associated with attending outpatient services., Conclusions: Scheduling an outpatient mental health appointment is an effective and low-resource discharge planning practice that should be an important target for inpatient psychiatric clinical quality measurement and improvement., (© Copyright 2020 Physicians Postgraduate Press, Inc.)

Objective: Shortened life expectancy of people with mental disorders has been attributed to medical comorbidities, yet these conditions remain under-recognized and under-treated. This study characterizes the medical demands placed on inpatient psychiatric units to help guide medical assessment and management practices in these settings., Methods: Medicaid claims records and clinician data were linked with hospital and regional data for individuals with a principal diagnosis of any mental disorder admitted to psychiatric inpatient units in New York State from 2012 to 2013. A modified Elixhauser Comorbidity Index (ECI) score was calculated for each unique individual (n = 14,458). Adjusted odds ratios (AORs) of having a medical comorbidity were calculated using logistic regression analyses., Results: 74.9% of psychiatric inpatients had at least one medical comorbidity, including 57.5% of people ages 18-24. Higher rates of medical comorbidity were associated with older age, female gender, non-schizophrenia diagnoses, and engagement in care prior to hospitalization. Patients with medical comorbidities had lower odds (AOR 0.54; 99% CI 0.35-0.83) of being treated in hospitals with 100 or more total beds compared to smaller hospitals., Conclusions: A high prevalence of common medical diagnoses among psychiatric inpatients underscores the importance of adequate detection and medical treatment of medical comorbidities in psychiatric inpatient settings., (Copyright © 2020 Elsevier Inc. All rights reserved.)

To adapt and validate a scale for measuring interprofessional collaboration in HIV prevention and care (IPC-HIV), primary survey data were collected (2012-2017) from 577 HIV service providers in 60 organizations in New York, New Jersey, and Michigan. Cross-sectional training data were used to develop the IPC-HIV scale. The model was validated by fitting the five-factor confirmatory factor-analysis model to a 30-item set. The scale measures five domains with reliable alpha coefficients: Interdependence, Professional Activities, Flexibility, Collective Ownership, and Reflection on Process. Correlations between subscales were significant ( p < .05). The strongest correlation was between Reflection on Process and Collective Ownership subscale scores. Mean scores ranged lfrom 4.070 to 4.880, with the highest score for Flexibility across all locations. IPC-HIV is valid and reliable among HIV-prevention and care workers, and is recommended for examining the effect of IPC on patient access to HIV testing and primary care.

Objective: Involving family in the care of inpatients with serious mental illness is known to be beneficial. This study examined frequencies of involvement by family in the care and discharge planning for 179 psychiatric inpatients., Methods: Involvement by family in care and discharge planning was assessed from randomly selected medical records of inpatients with Medicaid and severe mental illness at two New York hospitals from 2012 to 2013. "Family" also included anyone close to the patient who provided support. Medicaid claims were reviewed for patient demographic and clinical characteristics and for postdischarge outpatient attendance data. Multiple regression models were used to test whether involvement by family was associated with comprehensive discharge planning (contacting outpatient providers, scheduling follow-up appointments, and forwarding a discharge summary to a provider) and initiation of outpatient treatment., Results: Inpatient staff contacted a family member for 134 (75%) patients. Sixty-seven (37%) patients received comprehensive discharge planning, and 96 (53%) and 139 (78%) attended an outpatient appointment within 7 and 30 days of discharge, respectively. Inpatient staff contacting family, communicating about the patient's health and/or mental health, and communicating about the discharge plan were significantly associated with entry into follow-up care by 7 and 30 days postdischarge. Family phone calls and/or visits with patients, attendance at family therapy sessions, and communication with inpatient staff about services available to families were significantly associated with patients receiving comprehensive discharge planning. When analyses controlled for demographic and clinical factors, having any involvement between family members and inpatient staff was significantly associated with patients' attending an outpatient appointment by 7 days (odds ratio [OR]=2.79, 95% confidence interval [CI]=1.28-6.08) or 30 days (OR=3.07, 95% CI=1.29-7.32) after discharge., Conclusions: The association of family involvement with comprehensive discharge planning and prompt entry into outpatient care underscores the importance of family contact and communication with staff during inpatient hospitalizations.

Background: The authors developed a practical and clinically useful model to predict the risk of psychosis that utilizes clinical characteristics empirically demonstrated to be strong predictors of conversion to psychosis in clinical high-risk (CHR) individuals. The model is based upon the Structured Interview for Psychosis Risk Syndromes (SIPS) and accompanying clinical interview, and yields scores indicating one's risk of conversion., Methods: Baseline data, including demographic and clinical characteristics measured by the SIPS, were obtained on 199 CHR individuals seeking evaluation in the early detection and intervention for mental disorders program at the New York State Psychiatric Institute at Columbia University Medical Center. Each patient was followed for up to 2 years or until they developed a syndromal DSM-4 disorder. A LASSO logistic fitting procedure was used to construct a model for conversion specifically to a psychotic disorder., Results: At 2 years, 64 patients (32.2%) converted to a psychotic disorder. The top five variables with relatively large standardized effect sizes included SIPS subscales of visual perceptual abnormalities, dysphoric mood, unusual thought content, disorganized communication, and violent ideation. The concordance index (c-index) was 0.73, indicating a moderately strong ability to discriminate between converters and non-converters., Conclusions: The prediction model performed well in classifying converters and non-converters and revealed SIPS measures that are relatively strong predictors of conversion, comparable with the risk calculator published by NAPLS (c-index = 0.71), but requiring only a structured clinical interview. Future work will seek to externally validate the model and enhance its performance with the incorporation of relevant biomarkers.

Objective: This study prospectively evaluated outcomes of OnTrackNY, a statewide coordinated specialty care (CSC) program for treatment of early psychosis in community settings, as well as predictors of outcomes., Methods: The sample included 325 individuals ages 16-30 with recent-onset nonaffective psychosis who were enrolled in OnTrackNY and who had at least one three-month follow-up. Clinicians provided data at baseline and quarterly up to one year. Domains assessed included demographic and clinical characteristics, social and occupational functioning, medications, suicidality and violence, hospitalization, and time to intervention. Primary outcomes included the symptoms, occupational functioning, and social functioning scales of the Global Assessment of Functioning (GAF), as adapted by the U.S. Department of Veterans Affairs Mental Illness Research, Education and Clinical Center; education and employment status; and psychiatric hospitalization rate., Results: Education and employment rates increased from 40% to 80% by six months, hospitalization rates decreased from 70% to 10% by three months, and improvement in GAF scores continued for 12 months. Female gender, non-Hispanic white race-ethnicity, and more education at baseline predicted better education and employment status at follow-up., Conclusions: Individuals with early psychosis receiving CSC achieved significant improvements in education and employment and experienced a decrease in hospitalization rate. Demographic variables and baseline education predicted education and employment outcomes. CSC teams should make particular effort to support the occupational goals of individuals at increased risk of not engaging in work or school, including male participants and participants from racial and ethnic minority groups.