Journal of Mental Health Policy and Economics最新文献

Background: People working in agriculture, fishing, and forestry have elevated risks of suicide. The suicide rates for the occupations of "agriculture, fishing, and forestry" are significantly higher than any other occupation.

Aims of study: This study evaluates whether the variability in socioeconomic and demographic factors and in climate as well as the support from mental health providers and social associations affected the suicide rates of farmers in the US.

Methods: We estimate Poisson count data regression and county level-fixed effects regressions using data from the National Center for Health Statistics complemented with relevant socio-economic, climate data and data on mental health providers from a variety of sources.

Results: The results show more suicides in counties with more farms and with higher share of population without health insurance, lower agricultural wages and, in non-rural counties higher poverty rate. Surprisingly, we find more suicides in counties with more social associations, while the availability of mental health providers is associated with fewer suicides in non-rural counties, and lower suicide rate in southern counties.

Discussion: These results highlight the need for innovative targeted policy interventions instead of relying on one-size-fits-all approach. Farmers and farm workers are yet to be reached with modern and effective tools to improve mental health and prevent suicide. At the same time, factors such as the weather and climate as well as some more traditional factors such as social associations or religious participation play a limited role.

Implications for health policies: Support mechanisms have a differential effect in rural and urban areas. It is important to identify the specific demographic, climate, and policy changes that serve as external stressors and affect farm workers' suicide and accidental death from on-farm injury.

Implication for further research: Ideally, individual level data on farmers would be best in a study that evaluates what factors cause suicides.

Background: Unemployment is associated with a high risk of experiencing mental illness. This can lead to stigmatisation, reduced quality of life, and long-term costs like increased healthcare expenditure and productivity losses for society as a whole. Previous research indicates evidence for an association between unemployment and higher mental health service costs, but there is insufficient information available for the German healthcare system.

Aim of the study: This study aims to identify costs and cost drivers for health and social service use among unemployed people with mental health problems in Germany.

Methods: A sample of 270 persons participated at baseline and six-month-follow-up. Healthcare and social service use was assessed using the Client Socio-Demographic and Service Receipt Inventory. Descriptive cost analysis was performed. Associations between costs and potential cost drivers were tested using structural equation modelling.

Results: Direct mean costs for 12 months range from EUR 1265.13 (somatic costs) to EUR 2206.38 (psychiatric costs) to EUR 3020.70 (total costs) per person. Path coefficients indicate direct positive effects from the latent variable mental health burden (MHB) on stigma stress, somatic symptoms, and sick leave.

Discussion: The hypothesis that unemployed people with mental health problems seek help for somatic symptoms rather than psychiatric symptoms was not supported. Associations between MHB and costs strongly mediated by sick leave indicate a central function of healthcare provision as being confirmation of the inability to work.

Implications for health policies: Targeted interventions to ensure early help-seeking and reduce stigma remain of key importance in reducing long-term societal costs.

Implications for further research: Future research should explore attitudes regarding effective treatment for the target group.

Background: SSRIs and SNRIs are antidepressants that have largely substituted old antidepressants like Monoamine Oxidase Inhibitors (MAOIs) and Tricyclic Antidepressants (TCAs). They have been widely used since 1987 when the FDA approved the first SSRI Fluoxetine and the first SNRI Venlafaxine in 1993. Since then, several new SSRIs and SNRIs have been approved and entered the market. Utilization, pricing, and spending trends of SSRIs and SNRIs have not been analyzed yet in Medicaid.

Aim: To assess the trends of drug expenditure, utilization, and price of SSRI and SNRI antidepressants in the US Medicaid program, and to highlight the market share of SSRIs and SNRIs and the effect of generic drug entry on Medicaid drug expenditure.

Methods: A retrospective descriptive data analysis was conducted for this study. National pharmacy summary data for study brand and generic drugs were retrieved from the Medicaid State Outpatient Drug Utilization Data. These data were collected by the US Centers for Medicare and Medicaid Services (CMS). The study period was between 1991 and 2018. Study drugs include 12 different SSRI and SNRI brands and their generics available in the market, such as citalopram, escitalopram, paroxetine, fluoxetine, sertraline, venlafaxine, desvenlafaxine, duloxetine, and levomilnacipran. Data were analyzed annually and categorized by total prescriptions (utilization), total reimbursement (spending), and cost per prescription as the proxy of the price for each drug.

Results: From 1991 to 2018, total prescriptions of SSRI and SNRI drugs rose by 3001%. Total Medicaid spending on SSRIs and SNRIs increased from USD 64.5 million to USD 2 billion in 2004, then decreased steadily until it reached USD 755 million in 2018. The SSRIs average utilization market share was 87% compared to 13% of the SNRIs utilization market share. About 72% of total Medicaid spending on the two groups goes to SSRIs, while the remaining 28% goes to SNRIs. Brand SSRIs and SNRIs prices increased over time. On the contrary, generic drugs prices steadily decreased over time.

Discussion: An increase in utilization and spending for both SSRI and SNRI drugs was observed. After each generic drug entered the market, utilization shifted from the brand name to the respective generic due to their lower price. These generic substitutions demonstrate a meaningful cost-containment policy for Medicaid programs.

Implications for health policies: Our findings show the overall view of Medicaid expenditure on one of the most commonly prescribed drug classes in the US. They also provide an important insight toward the antidepressant market and the importance of monitoring different drugs and their alternatives.

Introduction: The COVID-19 pandemic is a significant health and economic crisis around the world. The U.S. saw a rapid escalation in laboratory-confirmed cases of COVID-19 and related deaths in March, 2020. The financial consequences of a virtual economic shutdown to curb the spread of the coronavirus are widespread and debilitating, with over 30 million Americans (about 20% of the labor force) filing for unemployment benefits since mid-March. During these unprecedented times, it is important to understand the impact of the COVID-19 pandemic on psychological distress and overall fear associated with the virus.

Data: To gain an understanding of the overall levels and predictors of psychological distress experienced in the first month of the COVID-19 pandemic in the U.S., a survey was administered online to over 2,000 individuals residing in the country. The survey instrument was administered between March 22-26, 2020, during which time the country was suffering through a period of exponential growth in COVID-19 cases and fatalities. It was administered via MTurk, a popular crowdsourcing platform increasingly used by social scientists to procure large samples over a brief period of time. A short, valid screening instrument to measure psychological distress in individuals, the Kessler 10 scale was developed in the U.S. in the 1990s as an easy-to-administer symptom assessment. The first dependent variable is the respondents' summated Kessler 10 score. The second dependent variable is a 7-category measure of how afraid the subject is about the novel coronavirus. The final dependent variable is also a 7-category scale, this time measuring self-reported likelihood of contracting the coronavirus. A variety of socio-demographic variables and health status were collected to analyze factors associated with psychological distress and mental health.

Methods: Ordinary Least Squares (OLS) multiple regression was employed to analyze these data.

Results: We find that protective factors against psychological distress include age, gender (male), and physical health. Factors exacerbating psychological distress include Hispanic ethnicity and a previous mental illness diagnosis. Similar factors are significantly related to fear of the virus and self-assessed likelihood of contracting it.

Discussion: The COVID-19 pandemic is associated with high levels of psychological distress in the U.S. The Kessler 10 mean value in our sample is 21.12, which falls in the likely to experience mild mental illness category, yet is considerably higher compared to one of the largest and earliest benchmark studies validating the scale. Psychological distress is one element of overall mental health status that could be influenced by the COVID-10 pandemic. Other mental health conditions such as depression, anxiety, and substance use disorders could also be affected by the pandemic