Economic evaluations of treatment of depressive disorders in adolescents: Protocol for a scoping review.

AIM: Depressive disorders in adolescents are common and impairing. Evidence-based treatments are available; however, at a cost. In the context of the COVID-19 pandemic, we anticipate increased demand for treatment services for adolescents with depression. We also anticipate that economic resources will be strained. Identifying cost-effective strategies to optimally treat depression in adolescents is imperative. This protocol for a scoping review aims to describe the literature with respect to economic evaluations of treatments for depression in adolescents. METHODS: We will conduct a scoping review using established methods and reporting guidelines. MEDLINE, Embase, PsyclNFO, Econlit, and the International HTA Database will be searched from inception to June 13, 2023, with an update closer to time of manuscript submission, while the NHS Economic Evaluation Database archives will be searched from inception to December 2014. Publications that contain economic evaluations, in the context of a clinical trial or a model-based study, testing a treatment of depression in adolescents will be selected for inclusion. Extracted data items will include: economic evaluation perspectives, health outcome variables and costs used in economic evaluations, types of analyses performed, as well as quality of reporting and methodology. RESULT: A narrative synthesis with summary tables will be used to describe our findings. CONCLUSION: Our findings will help identify gaps in the literature with respect to economic analyses for the treatment of depression such that these gaps can be filled with future research. Policy-makers, funders and administrators may also use our findings to inform their decisions around provision of various treatments for depression in adolescents. REGISTRATION: osf.io/5fteb (note that information on this link will be updated upon acceptance for publication based on reviewer comments).

Assessing the "healthy immigrant effect" in mental health: Intra- and inter-cohort trends in mood and/or anxiety disorders.

BACKGROUND: The healthy immigrant effect implies that, at the time of immigration, new immigrants are typically healthier than the Canadian-born population. Furthermore, this health advantage fades the longer cohorts of immigrants remain in the host country. METHODS: Most studies assessing the healthy immigrant effect rely on strong, untestable assumptions to extract unique effects for length of stay (LOS) (i.e., how long an immigrant has been in a host country), period (i.e., year of observation), and cohort (i.e., year of immigration). Rather than attempting to parse out separate effects for LOS, period, and cohort, we adopt a descriptive, cohort-centric approach to study immigrant mental health, which examines intra- and inter-cohort trends, that is, joint LOS-period and cohort-period parameters, respectively. While intra-cohort trends show how immigrants' mental health change with LOS across periods, inter-cohort trends reveal how the mental health of successive cohorts of immigrants differ across time periods. To provide a thorough assessment of the healthy immigrant effect, we use both survey and administrative data on cohorts of Canadian immigrants from 2003 to 2013. RESULTS: The survey data reveal that mental health declines steeply (i.e., there is an increase in mood and/or anxiety disorders) within and across immigrant cohorts, while the administrative data show little overall change in mental health care utilization within and across cohorts. The divergent results may reflect issues related to barriers in access to mental health services because the administrative data, which are based on health care utilization, do not the capture the increase in mental disorders seen in the survey data. CONCLUSION: This study highlights the benefit of a cohort-based approach to assess the healthy immigrant effect as it pertains to mental health as well as the importance of using different types of data, which may be measuring different aspects of immigrant mental health and health care utilization.

The PSY-SIM Model: Using Real-World Data to Inform Health Care Policy for Individuals With Chronic Psychotic Disorders.

BACKGROUND AND HYPOTHESIS: Few microsimulation models have been developed for chronic psychotic disorders, severe and disabling mental disorders associated with poor medical and psychiatric outcomes, and high costs of care. The objective of this work was to develop a microsimulation model for individuals with chronic psychotic disorders and to use the model to examine the impact of a smoking cessation initiative on patient outcomes. STUDY DESIGN: Using health records and survey data from Ontario, Canada, the PSY-SIM model was developed to simulate health and cost outcomes of individuals with chronic psychotic disorders. The model was then used to examine the impact of the Smoking Treatment for Ontario Patients (STOP) program from Ontario on the development of chronic conditions, life expectancy, quality of life, and lifetime health care costs. STUDY RESULTS: Individuals with chronic psychotic disorders had a lifetime risk of 63% for congestive heart failure and roughly 50% for respiratory disease, cancer and diabetes, and a life expectancy of 76 years. The model suggests the STOP program can reduce morbidity and lead to survival and quality of life gains with modest increases in health care costs. At a long-term quit rate of 4.4%, the incremental cost-effectiveness ratio of the STOP program was $41,936/QALY compared with status quo. CONCLUSIONS: Smoking cessation initiatives among individuals with chronic psychotic disorders can be cost-effective. These findings will be relevant for decision-makers and clinicians looking to improving health outcomes among this patient population.

Health Reporting from Different Data Sources: Does it Matter for Mental Health?

BACKGROUND: Mental disorders are typically stigmatized conditions associated with negative stereotypes, which may lead individuals to underreport them. Thus, survey data may be subject to biases. Although administrative data has some limitations, it is an alternative data source that may be considered more objective. AIMS OF THE STUDY: This study aimed to identify the degree of agreement between survey and administrative health care data for mental health conditions, factors affecting underreporting, and whether underreporting also occurs for physical health conditions. METHODS: We used Ontario data from the Canadian Community Health Survey linked to health records to examine the presence of mental health conditions (i.e., schizophrenia and mood disorders) and select physical health conditions (i.e., diabetes and cancer). Using administrative data as the reference standard, we created four categories for each health condition based on the level of agreement between the two data sources: consistent cases and non-cases (i.e. individuals with concordant data based on their reported health condition), and people who were found to underreport and overreport a condition (i.e. where the condition was present in the administrative data, but not in the survey data and vice-versa, respectively). The overall level of agreement was assessed using Cohen's kappa statistic. Probit regressions were estimated to determine the factors affecting underreporting. RESULTS: The Kappa statistics for mood disorder was fair (k= 0.26) and moderate for schizophrenia (k = 0.49). Physical health conditions had higher kappa values (diabetes, k = 0.81; ever having cancer, k = 0.68), with the exception of currently having cancer (k = 0.24). Underreporting was highest for the most stigmatizing condition, schizophrenia (63%), followed by mood disorders (39%) and cancer (39%), and lowest for diabetes (25%). Older age, being born in Africa and Asia, and being employed all increased the probability of underreporting among individuals identified in the administrative data; the opposite held for social assistance. DISCUSSION: We extended previous work on mental health reporting by combining survey data with administrative data to examine the level of agreement between respondents' self-reported mental health and administrative records. The data include some mental disorders not studied previously. We examined the entire adult population; this is important because prevalence of schizophrenia may be less common among older population groups due to higher mortality among this patient population. Additionally, there may be potential age-related differences in stigma and mental health conditions. The administrative health data captured only health services covered by the public provincial health insurance plan and thus did not capture medical care provided by psychologists, social workers, and nurses. While this would affect Kappa statistic values, it does not directly affect the underreporting analyses. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: Our results suggest that disclosure of mental health conditions may differ by the level of stigma, which has implications for obtaining accurate estimates of mental health prevalence from self-reported data sources.

Evaluating the Impact of a Critical Time Intervention Adaptation on Health Care Utilization among Homeless Adults with Mental Health Needs in a Large Urban Center.

OBJECTIVE: This study evaluated the impact of a critical time intervention (CTI) adaptation on health care utilization outcomes among adults experiencing homelessness and mental health needs in a large urban center. METHODS: Provincial population-based administrative data from Ontario, Canada, were used in a pre-post design for a cohort of 197 individuals who received the intervention between January 2013 and May 2014 and were matched to a cohort of adults experiencing homelessness who did not receive the intervention over the same time period. Changes in health care utilization outcomes in the year pre- and postintervention were evaluated using generalized estimating equations, and post hoc analyses evaluated differences between groups. RESULTS: Pre-post analyses revealed statistically significant changes in health care utilization patterns among intervention recipients, including reduced inpatient service use and increased outpatient service use in the year following the intervention compared to the year prior. However, the matched cohort analysis found nonsignificant differences in health service use changes between a subgroup of intervention recipients and their matched counterparts. CONCLUSIONS: An adapted CTI model was associated with changes in health care utilization among people experiencing homelessness and mental health needs. However, changes were not different from those observed in a matched cohort. Rigorous study designs with adequate samples are needed to examine the effectiveness of CTI and local adaptations in diverse health care contexts.

Examining equity in the utilisation of psychiatric inpatient care among patients with severe mental illness (SMI) in Ontario, Canada.

BACKGROUND: Severe mental illness (SMI) comprises a range of chronic and disabling conditions, such as schizophrenia, bipolar disorder and other psychoses. Despite affecting a small percentage of the population, these disorders are associated with poor outcomes, further compounded by disparities in access, utilisation, and quality of care. Previous research indicates there is pro-poor inequality in the utilisation of SMI-related psychiatric inpatient care in England (in other words, individuals in more deprived areas have higher utilisation of inpatient care than those in less deprived areas). Our objective was to determine whether there is pro-poor inequality in SMI-related psychiatric admissions in Ontario, and understand whether these inequalities have changed over time. METHODS: We selected all adult psychiatric admissions from April 2006 to March 2011. We identified changes in socio-economic equity over time across deprivation groups and geographic units by modeling, through ordinary least squares, annual need-expected standardised utilisation as a function of material deprivation and other relevant variables. We also tested for changes in socio-economic equity of utilisation over years, where the number of SMI-related psychiatric admissions for each geographic unit was modeled using a negative binomial model. RESULTS: We found pro-poor inequality in SMI-related psychiatric admissions in Ontario. For every one unit increase in deprivation, psychiatric admissions increased by about 8.1%. Pro-poor inequality was particularly present in very urban areas, where many patients with SMI reside, and very rural areas, where access to care is problematic. Our main findings did not change with our sensitivity analyses. Furthermore, this inequality did not change over time. CONCLUSIONS: Individuals with SMI living in more deprived areas of Ontario had higher psychiatric admissions than those living in less deprived areas. Moreover, our findings suggest this inequality has remained unchanged over time. Despite the debate around whether to make more or less use of inpatient versus other care, policy makers should seek to address suboptimal supply of primary, community or social care for SMI patients. This may potentially be achieved through the elimination of barriers to access psychiatrist care and the implementation of universal coverage of psychotherapy.

Characteristics of patients with mental illness and persistent high-cost status: a population-based analysis.

BACKGROUND: Most of the literature on high-cost users of health care has evaluated this population as a whole, but few studies have focused on high-cost patients with mental illness and whether they persist in the high-cost state. We sought to analyze this patient population in depth and determine predictors of persistency in the high-cost state. METHODS: We used 8 years of longitudinal patient-level population data (2010-2017) from Ontario to follow high-cost patients (those in and above the 90th percentile of the cost distribution) with mental illness. We classified high-cost status, based on the proportion of the study period that patients spent in the high-cost state, as persistent (6-8 yr), sporadic (1-2 yr) or moderate (3-5 yr). We compared characteristics between groups and determined predictors of being a patient with mental illness and persistent high-cost status. RESULTS: Among 52 638 patients with mental illness and high-cost status, 18 149 (34.5%) were considered persistent high cost. These patients had higher mean annual costs of care ($44 714, 95% confidence interval [CI] $43 724-$45 703) than patients with sporadic ($23 205, 95% CI $22 741-$23 668) and moderate ($31 055, 95% CI $30 359-31 751) status, largely owing to psychiatric hospital admissions. Patients with mental illness and persistent high-cost status were more likely to be female, older, long-term residents of Ontario (information ascertained from the Immigrants, Refugees and Citizenship Canada Database), living in low-income or urban areas, or to have comorbidities. The strongest predictors of persistent (v. sporadic) high-cost status were HIV (relative risk ratio [RRR] 4.32, 95% CI 3.08-6.06), psychosis (RRR 3.41, 95% CI 3.25-3.58) and dementia (RRR 3.21, 95% CI 2.81-3.68). INTERPRETATION: Among patients with mental illness and high-cost status, persistence in the high-cost state was determined mainly by psychosis and other comorbidities. Quality-of-care interventions directed at managing psychosis and multimorbidity, as well as preventive interventions to target patients with mental illness before they enter the persistent high-cost state, are needed.