Journal of Mental Health Policy and Economics最新文献

Background: The economic cost of perinatal mood and anxiety disorders (PMADs) is high and includes the cost of reduced maternal economic productivity, more preterm births, and increases in other maternal mental health expenditures. PMADs also substantially contribute the cost of maternal morbidity. This paper offers a discussion of the quality-of-care cascade model of PMADs, which outlines care pathways that people typically face as well as gaps and unmet needs that frequently happen along the way. The model uses the US health system as an example. A discussion of international implications follows.

Discussion: The quality-of-care cascade model outlines downward dips in quality of care along the perinatal mental health treatment continuum, including access (many Americans do not have access to affordable health insurance), enrollment (even when individuals are offered health insurance, some do not enroll), coverage (even if individuals have health insurance, some needed services or providers may not be covered), choice (even if services and providers are covered, patients may not be able to choose among plans, institutions, or clinicians), consistency (even if patients have a choice of plan or provider, a consistent source of care may not be accessible), referral (even if care is available and accessible, referral services may not be), quality (even if patients have access to both care and referral services, there may be gaps in the quality of care provided), adherence (even if patients receive high-quality care, they may not be adherent to treatment), barriers (societal forces that may influence people's choices and behaviors), and shocks (unanticipated events that could disrupt care pathways). In describing the quality-of-care cascade model, this paper uses the US healthcare system as the primary example. However, the model can extend to examine quality-of-care dips along the perinatal mental health treatment continuum within the international context. Although the US healthcare system may differ from other healthcare systems in many respects, shared commonalities lead to quality-of-care dips in countries with healthcare systems structured differently than in the US.

Implications for health policies: The global cost of PMADs remains substantial, and addressing the costs of these conditions could have a significant impact on overall cost and quality of care internationally. The quality-of-care cascade model presented in this paper could help identify, understand, and address the complex contributing factors that lead to dips in quality-of-care for perinatal mental health conditions across the world.

Dr. Esther Duflo, Nobel Laureate in Economics, and co-founder and co-director of the Abdul Latif Jameel Poverty Action Lab (J-PAL) sat down with Dr. Benjamin Cook for a "fireside chat" at the 12th National Institute of Mental Health Global Mental Health Research Without Borders Conference. Dr. Duflo discussed J-PAL's efforts to develop and test interventions for improving mental health and how cash transfer programs can be used to improve mental health. She also discussed the importance of using randomized control trials (RCTs) in shaping global mental health initiatives. Dr. Duflo shared insights from projects addressing loneliness among older individuals in India, secondary school scholarships in Ghana, and other studies that have informed social policies. Looking forward, she discusses climate change as a threat to the reductions in poverty realized in the last 30 years and encourages the expansion of networks of research and policy collaborations to improve global health.

Background: Aligning cost of mental health care with expected clinical and functional benefits of that care would incentivize the delivery of high value treatments and services. In turn, ineffective or untested care could still be offered but at costs high enough to offset the delivery of high value care.

Aims: The authors comment on Benson and Fendrick's paper on Value-Based Insurance Design (VBID) for mental health in the September 2023 special issue of this journal. The authors also present a preliminary framework of key ingredients needed to consider VBID for mental health treatments and services.

Methods: The authors briefly review current and past efforts to contain costs and improve quality of mental health care, which include (for example) use of carve-out and carve-in programs, evaluation of cost sharing models, impact of accountable care organizations, and studying other benefit designs and impact of federal and state policies.

Results: Using PTSD as an example, key ingredients of VBID for mental health services were identified and include the following: tools for case identification and monitoring progress over time at the population level; specific treatments and services with evidence of clinical effectiveness, cost-effectiveness, and health equity; and an approach to document the specific treatment or service was delivered (versus another treatment or service that may lack evidence).

Discussion: The inability to afford mental health care is a top barrier to treatment seeking. People who do elect to spend time and money on mental health care are further disadvantaged by accessing care that is not well regulated and the quality at best is questionable. VBID could be an important lever for increasing access to and use of high value mental health care. Partnerships among the research, practice, and policy communities can help ensure research solutions meet needs of these two communities.

Implications for health care: VBID holds promise to make high value mental health care more affordable while discouraging low value treatments and services.

Implications for health policies: While evidence gaps remain, these gaps can be filled concurrently with pursuit of VBID for mental health services.

Implications for future research: This paper identifies important research opportunities to help make VBID a reality for mental health care.

Background: The economic burden of chronic psychotic disorders is substantial. However, few studies have employed an incidence based approach to estimate the economic burden of chronic psychotic disorders. Furthermore, the existing work has mainly used models populated with data obtained from published literature, making several assumptions to estimate incidence-based costs.

Aims of the study: The objective of this study was to estimate the direct cumulative mean health care costs of chronic psychotic disorders, using an incidence-based, cost-of-illness approach and real-world data from a single-payer health care system.

Methods: Using health records from Ontario, Canada, all individuals with a valid health card number, residing in the province, and diagnosed with a chronic psychotic disorder between the ages of 16 and 45 from April 1st, 2006, to March 31st, 2021, were included in the analysis. Using a mix of bottom-up and top-down methodologies and a robust cost estimator, cumulative mean health care costs were estimated from diagnosis to death or the end of observation period. Cumulative mean health care costs, and respective 95% confidence intervals (CIs), were estimated for the 1-year period (i.e., first year post-diagnosis), overall, by sex, age groups and health service, and for the 5-, 10- and 15-periods, overall and by sex.

Results: One-, 5-, 10- and 15-year total discounted cumulative mean health care costs were estimated at USD 24,441.16, 95% CI (USD 24,166.13, USD 24,716.19), USD 70,754.69, 95% CI (USD 69,827.48-USD 71,681.89), USD 117,136.88, 95% CI (USD 115,370.40-USD 118,903.35), and USD 157,829.01 95% CI (USD 155,599.32.-USD 160,058.70), respectively. Total mean 1-year costs post-diagnosis were higher for younger individuals. Although females had higher 1-year costs, males had higher 5-, 10- and 15-year costs. Psychiatric hospitalisations made up the largest component of total costs across all cost estimates.

Discussion: These results suggest that the costs of chronic psychotic disorders are high in the year of diagnosis and then increase at a decreasing rate thereafter. Compared to previous work, the cost estimates from the present study suggest that the use of real-world data produces lower estimates of cumulative costs, albeit likely more accurate ones. However, these estimates do not account for costs of care provided in community-based agencies.

Implications for health policies: These estimates will serve as important inputs for policymakers looking to make decisions around resource allocation.

Implications for future research: Future research should seek to follow incident cases in administrative data over a longer time period to obtain cumulative costs of longer duration.

Background: The COVID-19 pandemic has been widely reported to have increased symptoms of anxiety, depression, and other mental health issues. It may also have significantly disrupted continuity of treatment for existing patients and made access for those newly seeking care more difficult at a time when treatment needs are higher.

Aims of the study: This study seeks to examine the impact of the COVID-19 pandemic on mental health status and mental health treatment among adults residing in the U.S. civilian, non-institutionalized population.

Methods: The data are drawn from the 2019-2020 Medical Expenditure Panel Survey (MEPS), a nationally representative household survey of the U.S. civilian non-institutionalized population conducted annually since 1996 and used extensively to study mental health treatment in the U.S. I examine unadjusted and regression-adjusted differences between 2019 and 2020 in perceived mental health status (excellent, very good, good, fair, poor) and in the K6 general psychological distress, the PHQ-2 depression screener, and the VR-12 mental component summary score. Similarly, using the detailed MEPS data on health care encounters and prescription drug fills, I examine differences in mental health use treatment between 2019 and 2020. I focus specifically on changes in continuity of treatment among those already in treatment in January and February, before the pandemic fully struck, as well differences in the initiation of new episodes of treatment after the pandemic began.

Results: All four mental health scales included in the MEPS show statistically significant declines in mental health between 2019 and 2020, particularly among younger adults. On balance, the percentage of US adults receiving mental health treatment did not change significantly. Continuity of treatment increased slightly in 2020, with 87.1% of adults in treatment January or February still receiving care in the second quarter, an increase of 2.5 percentage points (p=.025). However, there were significant declines in the initiation of new episodes of treatment, especially in the second quarter of 2020.

Discussion: While the continuity of treatment among adults already in care when the COVID pandemic first led to nationwide disruptions is welcome news, the decline in new episodes of mental health treatment among those not previously treated is of great concern. In a time of heightened need, the gap between need and treatment likely grew larger. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE, AND IMPLICATIONS FOR HEALTH POLICIES: Continued long-term monitoring of the mental health needs and treatment gaps will be important, especially as many emergency measures designed to mitigate the effects of the pandemic on access to mental health treatment expire.

Background: While consumer cost-sharing is a widely used strategy to mitigate health care spending, numerous studies have demonstrated that even modest levels of out-of-pocket cost are associated with lower use of medical care, including clinically necessary, high-value services. Within mental health care, increases in cost-sharing are associated with reductions in use of mental health care and psychotropic medication use. Further, these reductions in mental health services and treatments can lead to downstream consequences including worsening of psychiatric illness and increased need for acute care and psychiatric hospitalization. Thus, there is a need for clinically informed solutions that explicitly balance the need for appropriate access to essential mental health services and treatments with growing fiscal pressures faced by public and private payers. Value-Based Insurance Design (VBID) describes a model where consumer cost-sharing is based on the potential clinical benefit rather than the price of a specific health care service or treatment.

Aims of the study: Describe value-based insurance design and applications in mental health care.

Results, discussion and implications for health policies: For over two decades, clinically nuanced VBID programs have been implemented in an effort to optimize the use of high-value health services and enhance equity through reduced consumer cost-sharing. Overall, the evidence suggests that VBID has demonstrated success in reducing consumer out-of-pocket costs associated with specific, high value services. By reducing financial barriers to essential clinical services and medications, VBID has potential to enhance equity. However, the impact of VBID on overall mental health care spending and clinical outcomes remains uncertain.