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Objective: To understand how race and serious mental illness (SMI) interact for disruptive life events defined as financial (bankruptcy and judgement filings), and non-financial (arrests)., Methods: Patients were adults with schizophrenia (SCZ; N = 16,159) or bipolar I disorder (BPI; N = 30,008) matched 1:1 to patients without SMI (non-SMI) from health systems in Michigan and Southern California during 1/1/2007 through 12/31/2018. The main exposure was self-reported race, and the outcome was disruptive life events aggregated by Transunion. We hypothesized that Black patients with SCZ or BPI would be the most likely to experience a disruptive life event when compared to Black patients without SMI, and all White or Asian patients regardless of mental illness., Results: Black patients with SCZ had the least likelihood (37% lower) and Asian patients with BPI had the greatest likelihood (2.25 times higher) of experiencing a financial disruptive life event among all patients in the study. There was no interaction of race with either SCZ or BPI for experiencing an arrest. The findings did not support our hypotheses for patients with SCZ and partially supported them for patients with BPI., Conclusions: Clinical initiatives to assess social determinants of health should consider a focus on Asian patients with BPI., (Copyright © 2023 Elsevier Inc. All rights reserved.)

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.

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.)

Introduction: Knowledge of the factors affecting the adoption of new medications can enhance mental health care and guide quality improvement and policy development. Food and Drug Administration indications for treating bipolar disorder with several second-generation antipsychotics (SGAs) in the 2000s represent an opportunity to identify factors that impact the spread of a then-innovative treatment through a new population., Methods: Analysis of Department of Veterans Affairs administrative data identified the population of 170,811 veterans diagnosed with bipolar disorder from 2003 to 2010. We analyzed time trends and predictors of antimanic choice (SGA vs other) among the 40,512 outpatients with bipolar disorder who initiated their first VA outpatient antimanic prescription, using multinomial logistic regression in month-by-month analyses. We conducted classwise analyses and investigated prespecified predictors among specific agents., Results: In classwise analyses, SGAs supplanted lithium, valproate, and carbamazepine/oxcarbazepine as the most commonly initiated antimanics by 2007. Psychosis, but not other indices of severity, predicted SGA initiation. Demographic analyses did not identify substantial disparities in initiation of SGAs. Drug-specific analyses revealed some consideration of medical comorbidities in choosing among specific antimanic agents, although effect sizes were small. Most patients initiating an antimanic had received an antidepressant in the previous year., Discussion: Second-generation antipsychotics quickly became the frontline antimanic treatment for bipolar disorder, although antidepressants most commonly predated antimanic prescriptions. Second-generation antipsychotics were used for a broad range of patients rather than being restricted to a severely ill subpopulation. The modest association of antimanic choice with relevant medical comorbidities suggests that continued attention to quality prescribing practices is warranted.

Objectives: Studies of serious mental illnesses that use administrative databases have employed various criteria to establish diagnoses of interest. Several studies have assessed the validity of diagnostic inclusion criteria against research diagnoses. However, no studies have examined the effect of diagnostic inclusion criteria on prevalence and population characteristics across such groups., Methods: Administrative data for 2003-2010 from the Department of Veterans Affairs were used to calculate prevalence rates and assess effects of varying the diagnostic inclusion criteria on population composition for bipolar disorder, schizophrenia, and posttraumatic stress disorder (PTSD). Specifically, for each diagnosis, mutually exclusive subpopulations were compared on the basis of the following inclusion criteria for a given diagnosis: one treatment encounter, two outpatient encounters or one inpatient encounter, and any two encounters. For bipolar disorder and schizophrenia, effects of excluding individuals who had a competing diagnosis of, respectively, schizophrenia or bipolar disorder in the prior 12 months and since 2002 were also determined., Results: In 2010, moving from the broadest definitions of bipolar disorder (N=120,382), schizophrenia (N=91,977), and PTSD (N=554,028) to the most restrictive definitions reduced prevalence rates by, respectively, 28.7%, 34.9%, and 25.7%, with temporal trends for 2003-2010 paralleling results in 2010. Population composition changes with changing diagnostic inclusion criteria were variable, with predominantly small odds ratios., Conclusions: Population composition was relatively robust across common diagnostic inclusion criteria for each condition. Thus choice of criteria can focus on considerations of diagnostic validity and case-finding needs. Three mechanisms for the impact of diagnostic criteria on population composition in administrative data sets are discussed.

Background: Several second generation antipsychotics (SGAs) received FDA approval for bipolar disorder in the 2000s. Although efficacious, they have been costly and may cause significant side effects. Little is known about the factors associated with prescribers' decisions to initiate SGA prescriptions for this condition., Methods: We gathered administrative data from the Department of Veterans Affairs on 170,713 patients with bipolar disorder between fiscal years 2003-2010. Patients without a prior history of taking SGAs were considered eligible for SGA initiation during the study (n =126,556). Generalized estimating equations identified demographic, clinical, and comorbidity variables associated with initiation of an SGA prescription on a month-by-month basis., Results: While the number of patients with bipolar disorder using SGAs nearly doubled between 2003 and 2010, analyses controlling for patient characteristics and the rise in the bipolar population revealed a 1.2% annual decline in SGA initiation during this period. Most medical comorbidities were only modestly associated with overall SGA initiation, although significant differences emerged among individual SGAs. Several markers of patient severity predicted SGA initiation, including previous hospitalizations, psychotic features, and a history of other antimanic prescriptions; these severity markers became less firmly linked to SGA initiation over time. Providers in the South were somewhat more likely to initiate SGA treatment., Conclusions: The number of veterans with bipolar disorder prescribed SGAs is rising steadily, but this increase appears primarily driven by a corresponding increase in the bipolar population. Month-by-month analyses revealed that higher illness severity predicted SGA initiation, but that this association may be weakening over time.

Background: Evidence suggests that patients with bipolar disorder have an elevated risk for comorbid posttraumatic stress disorder (PTSD) compared to those without a bipolar diagnosis. Although bipolar disorder is associated with decreased health-related quality of life (HRQOL), it is unclear whether comorbid PTSD interacts to affect HRQOL., Method: Baseline data from a multi-site study of patients with bipolar disorder were analyzed. Patient surveys ascertained clinical and demographic information, including physical and mental HRQOL based on the SF-12, mood symptoms (PHQ-9, Internal State Scale), and self-reported co-occurring conditions including PTSD., Results: Overall (N=384), 44.9% of patients self-reported co-occurring PTSD. Patients with PTSD had lower physical and mental HRQOL scores compared to those without PTSD (mean (SD) for those with and without PTSD, respectively): Mental Component Scale score 30.51 (8.22) and 32.86 (8.35); Physical Component Scale score 35.56 (7.77) and 37.21 (7.20). After adjusting for demographic and clinical factors including mood symptoms, multiple linear regression analyses revealed that PTSD was no longer significantly associated with physical or mental HRQOL; however, depressive symptoms were independently associated with mental HRQOL (Beta -0.63, p<0.01)., Conclusion: Depressive symptoms may explain the association between PTSD and mental HRQOL. Clinicians working with these patients will want to emphasize treatment of depression as important towards improving HRQOL for this group., (Published by Elsevier B.V.)

Objectives: The objectives of this study were to ascertain the relative importance of scientific "approval" versus U.S. Food and Drug Administration (FDA) regulatory approval regarding changes in aripiprazole prescribing rates for treating bipolar disorder and to identify system-level covariates associated with faster regional uptake of aripiprazole., Methods: Medication use data for 2002–2009 were obtained from the Veterans Health Administration (VHA) National Psychosis Registry for 106,547 patients with diagnoses of bipolar disorder, aggregated at the level of the Veterans Integrated Service Network (VISN). VISN-level independent variables were obtained from several VHA organizational databases. Interrupted time-series analysis was used to examine changes in rates of prescribing aripiprazole, and logistic regression was used to model above- versus below-median growth in aripiprazole prescribing across VISNs., Results: Three inflections were observed, corresponding to the publication of two positive studies and FDA approval of aripiprazole for the treatment of bipolar mania. No significant VISN-level policy, administrative, or staffing predictors of the growth rate in aripiprazole prescribing were identified. Exploratory analyses showed that access to care may play a role in uptake, whereas competing demands, such as substance abuse treatment needs, may retard adoption., Conclusions: Early published evidence may have a strong impact on practice for low-barrier innovations, such as newly marketed medications or changes in indication for approved medications. Regional targeting of prescriber behavior interventions may maximize efficiency in efforts to change prescribing; further delineation of factors associated with regional heterogeneity in prescribing would support such efforts.