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The American Journal of Managed Care January 2016
Does Distance Modify the Effect of Self-Testing in Oral Anticoagulation?
Adam J. Rose, MD, MSc; Ciaran S. Phibbs, PhD; Lauren Uyeda, MA; Pon Su, MS; Robert Edson, MA; Mei-Chiung Shih, PhD; Alan Jacobson, MD; and David B. Matchar, MD
Improving Engagement in Employer-Sponsored Weight Management Programs
Bruce W. Sherman, MD, and Carol Addy, MD, MMSc
Impact of a Scalable Care Transitions Program for Readmission Avoidance
Brent Hamar, DDS, MPH; Elizabeth Y. Rula, PhD; Aaron R. Wells, PhD; Carter Coberley, PhD; James E. Pope, MD; and Daniel Varga, MD
Care Pathways in US Healthcare Settings: Current Successes and Limitations, and Future Challenges
Anita Chawla, PhD; Kimberly Westrich, MA; Susanna Matter, MBA, MA; Anna Kaltenboeck, MA; and Robert Dubois, MD, PhD
The Introduction of Generic Risperidone in Medicare Part D
Vicki Fung, PhD; Mary Price, MA; Alisa B. Busch, MD, MS; Mary Beth Landrum, PhD; Bruce Fireman, MA; Andrew A. Nierenberg, MD; Joseph P. Newhouse, PhD; and John Hsu, MD, MBA, MSCE
Effects of Continuity of Care on Emergency Department Utilization in Children With Asthma
Shu-Tzu Huang, MS; Shiao-Chi Wu, PhD; Yen-Ni Hung, PhD; and I-Po Lin, PhD
Outcomes Trends for Acute Myocardial Infarction, Congestive Heart Failure, and Pneumonia, 2005-2009
Chapy Venkatesan, MD; Alita Mishra, MD; Amanda Morgan, MD; Maria Stepanova, PhD; Linda Henry, PhD; and Zobair M. Younossi, MD
Factors Related to Continuing Care and Interruption of P4P Program Participation in Patients With Diabetes
Suh-May Yen, MD, PhD; Pei-Tseng Kung, ScD; Yi-Jing Sheen, MD, MHA, Li-Ting Chiu, MHA; Xing-Ci Xu, MHA; and Wen-Chen Tsai, DrPH
Oral Anticoagulant Discontinuation in Patients With Nonvalvular Atrial Fibrillation
Sumesh Kachroo, PhD; Melissa Hamilton, MPH; Xianchen Liu, MD, PhD; Xianying Pan, MS; Diana Brixner, PhD; Nassir Marrouche, MD; and Joseph Biskupiak, PhD, MBA
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Value-Based Insurance Designs in the Treatment of Mental Health Disorders
Alesia Ferguson, PhD; Christopher Yates, BA; and J. Mick Tilford, PhD

Value-Based Insurance Designs in the Treatment of Mental Health Disorders

Alesia Ferguson, PhD; Christopher Yates, BA; and J. Mick Tilford, PhD
This study examined the application of value-based insurance design to the treatment of mental health disorders and addresses any additional challenges.
Another study has shown that mental health disorders are responsible for 10% of children’s hospitalizations.29 Within the penal system, victim and societal external costs are substantial, and educational systems also are influenced by mental disorders. SAMSA reported in 2013 that 27.7% of adolescents who failed a grade were also diagnosed with a severe emotional disturbance.25 Poor performance in school can limit later success in entering college and attaining and keeping employment. Additional financial, physical, and emotional impacts for family members of those with a mental health disorder are difficult to assess30; they may result largely from a lack of social support.31-33

Applying V-BID to Mental Health

Because the costs of not adequately and effectively identifying and treating those with mental health disorders early are high, cost-effective, improved strategies to address the problem are needed. V-BIDs offer some promise. The application of V-BID to mental health disorders needs to include an understanding of the scope of mental illnesses and a thorough review of successful treatment programs, especially those that have produced improved outcomes (especially long-term outcomes) at relatively low cost. Patient adherence to medication that controls early signs of a mental health disorder and programs that address some of such disorders’ causes (eg, stress, physical illness), are areas of practical focus in a V-BID program, as are treatment methods that combine strategies of low drug usage with alternative treatment methods (ie, cognitive-behavioral strategies). Managing mental health disorders entirely with pharmaceuticals can potentially have negative consequences depending on the class of medication, age group, and individual response, ranging from cardiologic side effects, weight gain, and insomnia to loss of fertility and suicide.27,34-37

Consequences of overtreatment and misdiagnosis of mental health disorders are also quite severe, making it imperative to apply V-BID sensitively and in a clinically correct manner. Milder forms of depression, for example, seem to respond more effectively to self-help strategies (eg, physical exercise, family support and other social support, and other forms of cognitive behavioral therapy) than to pharmaceutical treatment.38 Conversely, the treatment of severe mental health disorders must not be trivialized; ineffective undertreatment with pharmaceuticals must be avoided.

Other innovative strategies exist. Blonk and colleagues (2006) found that a combination of workplace interventions (eg, adjustments to workplace environment) and individual-focused techniques (eg, conflict management) among self-employed individuals on sick leave due to work-related psychological issues was more effective at helping them return earlier (on average, by 200 days) than cognitive-behavioral therapy alone.39

In any early implementation of V-BID for mental health disorders, the focus should be on the most common ailments and those with the most potential for cost savings. In the United States in 2010 for example, 7,977,606 Medicaid beneficiaries had a mental disorder, with the largest category (4,070,153 beneficiaries) being mood disorders (ie, bipolar disorders and depressive disorders) costing more than $4 billion a year to treat25—a good place for V-BID pilot programs to begin. Treatment for mood disorders varies significantly, and includes numerous pharmacological and psychological therapies.40 Effectiveness of these treatments, alone or in combination, is highly dependent on cultural variations in acceptance and implementation; age appropriateness is also a consideration. Many mental health disorders, for example, peak around the age of 14 years and again around age 24 to 25 years.25 Interventions for these age groups to increase adherence and success are likely to vary (ie, insurance coverage for counseling visits and pharmacy costs to encourage parents to seek earlier treatment).

Reviews of the cost-effectiveness of various interventions in the treatment of mental health disorders indicate significant uncertainty and a need for further systematic research, in which patients’ long-term outcomes/end points are addressed in ways others than physician opinion.36,41-43 Rodgers and colleagues reviewed 17 studies on the clinical effectiveness and cost-effectiveness of low-intensity interventions for the prevention of relapse after a depression event, and found inadequate evidence of success and inconsistencies across studies.42 Similarly, in 2006, Marshall and Rathbone evaluated 7 studies that met their criteria for early intervention for schizophrenia (and/or people with prodromal systems), and found that there were insufficient trials to establish best practices; they suggested international collaborative work on interventions for these disorders.43 A review in 2011 by the same authors found most studies to still be small, diverse, and inconclusive; however, some interventions showed signs of promise, such as phase-specific and early intervention studies.44 More recently, Bee and colleagues completed a systematic review of community-based interventions that aimed to improve the quality of life for children of parents with serious mental disorders and found high-quality cost data to be lacking.45

The Recovery After an Initial Schizophrenia Episode (RAISE) multimodal, multidisciplinary early treatment program for first-episode psychosis is a large, prospective, randomized, controlled study that completed enrollment of 404 subjects in 2012; they were followed for 2 years. The results should offer some answers on the clinical and cost-effectiveness of the program's intervention compared with other current prevailing treatment approaches.46 RAISE will look at successful outcomes for patients in a real-world community setting using current funding mechanisms. Large systematic projects such as RAISE could provide needed cost-effectiveness end points to inform implementation of V-BID in the treatment of some mental health disorders.

Limited literature exists on V-BID cost-effectiveness applied specifically to mental health disorders. A computer simulation model focused on V-BID application across several diseases showed that V-BID, for the management of antidepressant medications, showed initial promise with the cost per quality-adjusted life-year of less than $30,000.47 V-BID effects on DALYs should also be studied as another extended measure of reduction in burden.

Many V-BID programs are demand-driven, meaning they primarily rely on changes in individual behavior (eg, reduced co-pays for medicines to encourage maintenance of disease treatment or increased co-pays to serve as disincentives for low-value services).48 V-BID programs can also be supplier-driven to incentivize physicians to provide higher-quality care at reduced costs. Encouraging primary care physicians to recognize early signs of mental health disorders while treating physical ailments, and to recommend effective programs or use of appropriate care through a psychiatrist, psychologist, clinical social worker, or other qualified therapist or counselor, could save money in the long term and reduce other chronic health outcomes. Therefore, designing some incentive to be given to the physician for identifying and following up with a patient’s mental health care through an appropriate specialist could become one aspect of V-BID for mental health treatment. However, this would be difficult without concerted efforts to train primary care physicians to better understand the signs and symptoms of mental health illnesses. Nevertheless, both demand-side and supply-side incentives within V-BID need consideration for the treatment of mental health disorders.

Other Challenges in Applying V-BID to Mental Health

V-BID is challenging regarding the treatment of all illnesses, including mental health disorders, and the latter present additional challenges. For example, privacy concerns (among other sensitivity issues) is important when implementing a workplace V-BID program. An initial strategy in a V-BID program offered through a large employer gathers information on all employees and tailors a health insurance plan or healthcare program for each individual. This is often done through a personal assessment form,49 but mental health disorder and substance abuse information—private and sensitive data for an employee—may prove difficult to gather in this manner. The employee may be inclined to not be entirely truthful about such information; if shared at all (and if the issue is even identified), they are likely to divulge it only to their primary care physician or psychiatrist.

Without an assessment of the extent of occurrence of mental health disorders and associated variables in the workplace, an employer may not have the ability to construct a V-BID program to directly address mental health disorders, much less tailor a program to each employee. However, employers could strategically design programs for some mental health disorders within the context of a broader program that also addresses physical disease (ie, incentivized exercise and stress management programs) and employees could be incentivized to visit a counselor when experiencing stress-related or substance abuse problems. Still, the treatment of mental health disorders also involves family members or caregivers, which poses additional complications. Strategic ideas can involve and engage the family and community at large through schools, church, and various family-centered settings—but these strategies may lie outside the scope of V-BID plans. However, innovative programs should consider any overlapping ideas to reach and incentivize family involvement, resolve access needs, and appeal to varying populations.

The literature on behavioral models of healthcare use demonstrate that the likelihood of a person receiving care for a mental health disorder is highly dependent on sociodemographic characteristics (eg, education, sex, race), access to services (eg, health insurance coverage), and the underlying disorder (eg, specific type, perceived need)50,51—all of which new V-BID programs for the treatment of mental health disorders must consider. In a study of 2258 adults aged 19 to 32 years, Vanheusden and colleagues found that only 34.6% of adults with psychopathology made use of any mental health services. Although the study did not find differences in sociodemographic characteristics in individuals seeking primary services, those seeking specialty services were likely to be female and economically inactive and to have a lower level of education.52

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