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: Many individuals with serious mental illness (SMI) are capable of employment in regular jobs (i.e. jobs paying at least minimum wage, not set aside for persons with disabilities, and not obtained with assistance from mental health services), but they may need job accommodations to be successful. The extant literature focuses almost exclusively on accommodations for workers with SMI who are receiving employment support, so we know almost nothing about the nature or frequency of accommodations needed by workers who are independently employed.
Aims: Drawing on survey data from a sample of workers with diagnoses of SMI who are capable of regular, mainstream employment, we aim to: (i) describe the nature and frequency of job accommodations workers requested from their employer or initiated on their own; and (ii) identify individual- and work-related factors associated with the probabilities of requesting or initiating accommodations.
Methods: The analysis sample includes 731 workers with diagnoses of schizophrenia, bipolar disorder, or major depressive disorder, who were employed in regular jobs post-onset of SMI. Workers identified any job accommodations requested from their employer, or initiated on their own. Summary statistics describe the nature and frequency of accommodations in four categories: scheduling, workspace, supervision, job modification. Logistic regression models estimate the relationship between workers' health- and job-related characteristics and the probabilities of requesting or self-initiating accommodations.
Results: Whereas 84% of workers in our sample self-initiated accommodations, only 25% requested accommodations from their employer. The most frequent accommodations of either type involved flexibility in scheduling (63% self-initiated, 24% requested), or modifications to the workspace (58%, 19%). Factors significantly correlated with the probability of requesting accommodations include: supportive workplace culture, longer job tenure, more severe cognitive/social limitations. Factors significantly correlated with the probability of self-initiating accommodations include: younger age, more severe social limitations, greater job autonomy.
Discussion: This is the first study of job accommodations among a cohort of persons with SMI independently employed in regular jobs. We identify a type of accommodation, self-initiated by the worker, that has not been studied before. These self-initiated accommodations are far more prevalent than employer-provided accommodations in our sample. Key factors associated with the probabilities of requesting/initiating accommodations reflect need (e.g. compromised health) and feasibility of implementation in a particular job. Limitations of the study include the cross-sectional design which limits our ability to identify causal relationships.
Implications for he
Background: In the US, much of the research into new intervention and delivery models for behavioral health care is funded by research institutes and foundations, typically through grants to develop and test the new interventions. The original grant funding is typically time-limited. This implies that eventually communities, clinicians, and others must find resources to replace the grant funding -otherwise the innovation will not be adopted. Diffusion is challenged by the continued dominance in the US of fee-for-service reimbursement, especially for behavioral health care.
Aims: To understand the financial challenges to disseminating innovative behavioral health delivery models posed by fee-for-service reimbursement, and to explore alternative payment models that promise to accelerate adoption by better addressing need for flexibility and sustainability.
Methods: We review US experience with three specific novel delivery models that emerged in recent years. The models are: collaborative care model for depression (CoCM), outpatient based opioid treatment (OBOT), and the certified community behavioral health clinic (CCBHC) model. These examples were selected as illustrating some common themes and some different issues affecting diffusion. For each model, we discuss its core components; evidence on its effectiveness and cost-effectiveness; how its dissemination was funded; how providers are paid; and what has been the uptake so far.
Results: The collaborative care model has existed for longest, but has been slow to disseminate, due in part to a lack of billing codes for key components until recently. The OBOT model faced that problem, and also (until recently) a regulatory requirement requiring physicians to obtain federal waivers in order to prescribe buprenorphine. Similarly, the CCBHC model includes previously nonbillable services, but it appears to be diffusing more successfully than some other innovations, due in part to the approach taken by funders.
Discussion: A common challenge for all three models has been their inclusion of services that were not (initially) reimbursable in a fee-for-service system. However, even establishing new procedure codes may not be enough to give providers the flexibility needed to implement these models, unless payers also implement alternative payment models.
Implications for health care provision and use: For providers who receive time-limited grant funding to implement these novel delivery models, one key lesson is the need to start early on planning how services will be sustained after the grant ends.
Implications for health policy: For research funders (e.g., federal agencies), it is clearly important to speed up the process of obtaining coverage for each novel delivery model, including the development of new billable service codes, and to plan for this
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.
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