Simulated Effects of Policies to Reduce Diabetes Risk Among Adults With Schizophrenia Receiving Antipsychotics

Microsimulation Models on Mental Health: A Critical Review of the Literature

OBJECTIVES

To retrieve and synthesize the literature on existing mental health-specific microsimulation models or generic microsimulation models used to examine mental health, and to critically appraise them.

METHODS

All studies on microsimulation and mental health published in English in MEDLINE, Embase, PsycINFO, and EconLit between January 1, 2010, and September 30, 2022, were considered. Snowballing, Google searches, and searches on specific journal websites were also undertaken. Data extraction was done on all studies retrieved and the reporting quality of each model was assessed using the Quality Assessment Reporting for Microsimulation Models checklist, a checklist developed by the research team. A narrative synthesis approach was used to synthesize the evidence.

RESULTS

Among 227 potential hits, 19 studies were found to be relevant. Some studies covered existing economic-demographic models, which included a component on mental health and were used to answer mental-health-related research questions. Other studies were focused solely on mental health and included models that were developed to examine the impact of specific policies or interventions on specific mental disorders or both. Most models examined were of medium quality. The main limitations included the use of model inputs based on self-reported and/or cross-sectional data, small and/or nonrepresentative samples and simplifying assumptions, and lack of model validation.

CONCLUSIONS

This review found few high-quality microsimulation models on mental health. Microsimulation models developed specifically to examine mental health are important to guide healthcare delivery and service planning. Future research should focus on developing high-quality mental health-specific microsimulation models with wide applicability and multiple functionalities.

National trends in metabolic risk of psychiatric inpatients in the United States during the atypical antipsychotic era

Although the cardiometabolic effects of atypical antipsychotics have been well-described in clinical samples, less is known about the longer-term impacts of these treatments. We report rates of metabolic syndrome in a nationally representative sample of U.S. adult inpatients 1993-2018 admitted for schizophrenia-spectrum disorders (n = 1,785,314), any mental health disorder (n = 8,378,773), or neither (n = 14,458,616) during a period of widespread atypical antipsychotic use. Metabolic syndrome, derived from additional diagnoses, was defined as three or more of hypertension, dyslipidemia, type II diabetes, hyperglycemia, and overweight or obese. Using an ecological age and period design, a 4-level period variable was constructed to proxy for atypical antipsychotic exposure as the minimum of age minus 20 years or the calendar year minus 1997 in accord with the disease course for schizophrenia-spectrum illness and the market share of atypical antipsychotics in the U.S. Logistic regression models, adjusted for age, year, and exposure main effects, estimated odds ratios (ORs) of metabolic syndrome. Relative to other mental health or other discharges, schizophrenia-spectrum discharges had an elevated risk for metabolic syndrome regardless of potential atypical antipsychotic exposure (OR = 1.46; 95 % CI, 1.30-1.64). For schizophrenia-spectrum discharges, periods of potential atypical antipsychotic exposure conferred additional metabolic syndrome risk OR = 1.21; 95 % CI, 1.04-1.41 for exposures of 1-2 years, OR = 1.29; 95 % CI, 1.13-1.46 for 3-7 years, OR = 1.27; 95 % CI, 1.12-1.44 for 8-12 years, and OR = 1.10; 95 % CI 0.98-1.24 for >12 years. In summary, cardiometabolic disease and related risks were elevated among a nationally representative sample of adult inpatients with schizophrenia-spectrum disorders during a period of pervasive atypical antipsychotic use.

Receipt of Promotional Payments at the Individual and Physician Network Level Associated with Higher Branded Antipsychotic Prescribing Rates

Pharmaceutical promotion can lead to market size expansion, which is beneficial if previously untreated patients access treatment but deleterious if it leads to overuse, an area of concern for second generation antipsychotics (SGA). We contribute to a growing body of work suggesting that networks of social and professional relationships shape prescribing behavior. We examined 88,439 Medicare Part D prescribing physicians, finding that promotion is associated with SGA market size expansion (elasticity: 0.062) and that network-level promotional activity is associated with network members' branded product prescribing. Research on the effects of promotion should account for its effects in prescribers' networks.