University of South Florida
Scholar Commons
Graduate Theses and Dissertations
Graduate School
July 2018
Developing the Evidence Base for Mental Health
Policy and Services: Inquiries into Epidemiology,
Cost-Benefits, and Utilization
Joseph L. Smith
University of South Florida, [email protected]
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Scholar Commons Citation
Smith, Joseph L., "Developing the Evidence Base for Mental Health Policy and Services: Inquiries into Epidemiology, Cost-Benefits, and Utilization" (2018).Graduate Theses and Dissertations.
Developing the Evidence Base for Mental Health Policy and Services: Inquiries into Epidemiology, Cost-Benefits, and Utilization
by
Joseph L. Smith
A dissertation submitted in partial fulfillment of the requirements of the degree of Doctor of Philosophy Public Health with a concentration in Health Services Research
Department of Health Policy and Management College of Public Health
University of South Florida
Major Professor: Troy C. Quast, Ph.D. Eric A. Storch, Ph.D.
Sean Gregory, Ph.D. Jacqueline Wiltshire, Ph.D.
Date of Approval: July 31, 2018
Keywords: Mental Illness, Injury, Obsessive-Compulsive Disorder, Cost-Sharing, Cost-Effectiveness Copyright © 2018, Joseph L. Smith
DEDICATION
To my parents, Richard and Katalin, who provided seemingly endless encouragement and support in all forms. My brother, Jon, for keeping me company in Florida. To Carl and Jo Dee Schultz, for being my surrogate family and providing respite from my studies. To Billy Oglesby for the unconditional support and accountability check-ins, past, present, and future. To Anna Ialynytchev for always looking out for me and making sure that I’m smiling.
ACKNOWLEDGMENTS
I thank my major professor, Troy Quast, for stepping up to increasingly greater responsibility on my committee. I also thank my other committee members, Eric Storch, Sean Gregory, and Jacqueline Wiltshire. I am thankful for others who have supported me Jay Wolfson, Sandy Potthoff, Roger Boothroyd, Ellen Daley, Donna Petersen, and John Petrila. I am grateful for financial support from the University of South Florida, College of Public Health, the Department of Health Policy and Management, The Rothman Center at All Children’s Hospital, and the Office of the Vice President of USF Health.
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TABLE OF CONTENTS
List of Tables ... iii
List of Figures ... v
Abstract ... vi
Chapter One: Introduction ... 1
Evidence-Based Practices ... 2
Behavioral Health Services Research Methods ... 3
Overview of Chapter 2: Epidemiology of Disorders ... 4
Overview of Chapter 3: Cost-Benefit Analysis ... 6
Overview of Chapter 4: Economic Analysis of Claims Data ... 8
Summary ... 12
References ... 13
Chapter Two:Prevalence of psychiatric disorders varies by cause of injury among adults presenting to the emergency department ... 22
Introduction ... 22
Methods ... 24
Data ... 24
Psychiatric Disorder Diagnoses ... 25
Cause of Injury ... 25 Covariates ... 26 Statistical Analyses... 26 Results ... 27 Discussion ... 31 Limitations ... 37 Conclusion ... 38 References ... 38
Chapter Three:Cost-benefit analysis of first-line treatment strategies for obsessive-compulsive disorder in children and adolescents ... 42
Introduction ... 42
Methods ... 44
Model Overview... 44
Parameters... 46
Treatment Effects and Benefits ... 46
Costs... 47
Interventions Assessed ... 47
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Probabilistic Sensitivity Analysis ... 50
Results ... 50
Benefits ... 50
Costs ... 51
Cost-Benefits... 50
Probabilistic Sensitivity Analysis ... 51
Discussion ... 53
Limitations ... 54
Conclusion ... 55
References ... 56
Chapter Four: The association between cost-sharing and psychotherapy and medication utilization among adults with OCD ... 60
Introduction ... 60 Methods ... 64 Data Source ... 64 Unit of Analysis ... 65 Inclusion Criteria ... 67 Dependent Variables ... 67
Psychotherapy Intensity and Dose ... 67
SRI Mediation Adherence ... 68
Independent Variable... 69
Covariates ... 70
Analytic Plan ... 71
Results ... 74
Psychotherapy Intensity and Dose ... 81
SRI Medication Adherence ... 84
Discussion ... 90
Limitations ... 92
Conclusion ... 93
References ... 94
Chapter Five: Conclusion ... 100
Summary ... 100
Chapter 2: Epidemiology of Disorders ... 100
Chapter 3: Cost-Benefit Analysis ... 102
Chapter 4: Economic Analysis of Claims Data ... 103
Policy and Practice Implications... 104
Chapter 2 ... 104 Chapter 3 ... 104 Chapter 4 ... 105 Future Research ... 106 Conclusion ... 107 References ... 108 Appendix A ... 111
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LIST OF TABLES
Table 2.1: Sample count and weighted proportion of visits having each psychiatric disorder by
cause of injury for all ED visits. ... 27
Table 2.2: Sample counts and weighted proportion having a psychiatric disorder, or not by demographic, patient, and hospital-related for all ED patients. ... 29
Table 2.3: Main effects estimates from multivariable logistic regression models examining the odds of being diagnosed with each category of the psychiatric disorder relative to not being diagnosed with the same disorder reported as odds ratios (ORs) with 95% confidence intervals (95% CIs). ... 32
Table 2.4: Covariate estimates from multivariable logistic regression models examining the odds of being diagnosed with each category of the psychiatric disorder relative to not being diagnosed with the same disorder reported as odds ratios (ORs) with 95% confidence intervals (95% CIs). ... 33
Table 2.5: Estimate of effects as absolute risk (AR), relative risk (RR), and risk differences (RD) of any psychiatric disorder and by category of disorder controlling for regression results ... 34
Table 3.1: Probabilistic and deterministic parameters used in the models. ... 49
Table 3.2: Cost-benefit results. ... 52
Table 4.1: Sample size, analytic units, and data manipulation at each stage of sample construction. ... 67
Table 4.2: Psychotherapy code definitions and duration of encounters. ... 68
Table 4.3: Process for building-up zero-inflated negative binomial models for psychotherapy intensity and dose. ... 72
Table 4.4: Process for building-up logistic regression models for MPRm. ... 74
Table 4.5: Continuous and semi-continuous episode characteristics ... 78
Table 4.6: Frequencies and proportion by type of encounter. ... 79
Table 4.7: Frequencies and proportions of categorical variables. ... 80
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Table 4.9: Average marginal effects estimates of psychotherapy visit intensity based on
zero-inflated negative binomial regression estimates. ... 85 Table 4.10: Average marginal effects estimates of psychotherapy dose (in minutes) based on
zero-inflated negative binomial regression estimates. ... 86 Table 4.11: Average marginal effects estimates of SRI medication possession ratio-modified
based on logistic regression estimates. ... 88 Table A4.1: Zero-inflated negative binomial model estimates for psychotherapy intensity,
comparing null model to full model. ... 111 Table A4.2: Zero-inflated negative binomial model estimates for psychotherapy dose, comparing
null model to full model. ... 114 Table A4.3: Comparison of null model to full model Logistic regression model estimates for
probability of adherence, defined as MPRm ≥0.80. ... 117 Table A4.4: Sensitivity analysis of average marginal effects estimates of SRI medication
possession ratio-modified based on logistic regression estimates various MPRm
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LIST OF FIGURES
Figure 3.1: Decision tree used to model cost-benefit analysis. ... 45
Figure 3.2: Graph of cost-benefit analysis results. ... 51
Figure 3.3: Probabilistic sensitivity analysis scatterplot. ... 53
Figure 4.1: Histogram showing the number of episodes in the sample. ... 75
Figure 4.2: Histogram showing skewed distribution of all encounters per episode with mass at one. ... 76
Figure 4.3: Histogram showing the distribution of psychotherapy intensity with mass at zero... 76
Figure 4.4: Histogram showing the distribution of Medication Possession Ratio-modified, in which ratios > 1 were limited to 1. ... 77
Figure 4.5: Histogram showing cost-share as a percentage of total cost of care for OCD per episode. ... 77
Figure 4.6: Histogram showing cost-share as a dollar amount for OCD treatment during an episode. ... 78
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ABSTRACT
The overarching aim of this dissertation is to use health services research methods to address three problems in behavioral health services. This dissertation seeks to address the knowledge gaps in behavioral health services through the generation of evidence intended to support evidence-based practices (EBP).
Previous work has examined epidemiology of behavioral health disorders in the ED, but they have not attempted to examine disorders by the cause of injury. Chapter 2 examines the epidemiology of psychiatric disorders among adults who seek care in the emergency department (ED) by cause of injury. Data from a national hospital discharge survey was analyzed using logistic and multinomial regression. Estimates are given as average marginal effects (AME) to simplify the interpretation and application. Intentionally-caused injury and undetermined cause of injury are significantly associated with psychiatric disorders. Patients with undetermined cause of injury were more likely to be diagnosed with anxiety disorders, depressed mood, and psychoses relative to patients with unintentional injuries
Since there are several treatment options for obsessive-compulsive disorder (OCD), including cognitive behavioral therapy (CBT), serotonin reuptake inhibitors (SRIs), and combinations of these, a comparison of treatment effects denominated in dollars is helpful when comparing risks and benefits. Chapter 3 builds on previous randomized control trials of treatments for OCD in children and adolescents by ranks the cost-benefits of first-line treatments. The analysis aggregates treatment effects from
published trials in meta-analytic framework and a Monte Carlo simulation of 100,000 hypothetic children and adolescents to derive ranked cost-benefit. Treatments strategies starting with CBT, but not CBT and SRIs concurrently, were the most cost-beneficial.
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The relationship between cost-sharing and utilization of behavioral health services has been studied in the aggregate, but there has been little work examining the relationship by disorder and treatment modality. The aim of Chapter 4 is to examine the association between cost-sharing and utilization of psychotherapy and adherence to pharmacotherapy among insured adults with OCD. This chapter utilizes the Truven MarketScan Commercial Claims and Encounters dataset to perform zero-inflated negative binomial regression and logistic regression analyses. Increased cost-sharing was significantly, negatively associated with psychotherapy intensity and dose, but not associated with SRI adherence.
This dissertation examined three different research questions to address gaps in the behavioral health services research. The findings of these chapters have implications for patients, clinicians, insurers, and policymakers. The results can be used to improve aspects of cost, quality, access, and efficiency of behavioral health services.
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CHAPTER ONE: INTRODUCTION
In the United States, healthcare spending accounts for 18% of the gross domestic product, or about $3.3 trillion annually.1 These costs have continued to rise despite the implementation of the Patient Protection and Affordable Care Act (PPACA) beginning in 2010. There is evidence, however, that the rate of increase in healthcare inflation has declined.2 Behavioral health disorders, collectively, accounted for the largest proportion of healthcare costs, totaling over 7% or $241.1 billion in medical costs alone3 and an additional $262.6 billion in lost wages4 (adjusted for 2017$). The huge monetary costs aside, behavioral health disorders are a significant source of impairment and mortality in the U.S. and beyond.5
Behavioral health disorders are one of the most common classes of disorders in the United States, affecting 18% of adults and 13% of children in a given year.6,7 These financial and human burdens
warrant behavioral health services research targeting cost, quality, and access.
Over the last decade, several important policy changes have increased access to behavioral health services. The Mental Health Parity and Addiction Equity Act of 2008 (MHPAEA) eliminated some managed care-imposed barriers such as treatment limits, differential cost-sharing requirements, and differential utilization management techniques relative to general medical care.8-10 The passage of the
PPACA in 2010 further decreased barriers by expanding the MHPAEA protections to individual plans, adding behavioral health services to the list of essential benefits, allowing states to expand Medicaid eligibility, requiring individuals to purchase insurance, and requiring coverage for dependents until age 26.9 These changes likely contributed to increased coverage for and utilization of behavioral health
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services,9,11-13 but they have not universally improved access, quality, or costs of services. Even among
the insured, access remains restricted due to the use of other utilization management techniques such as increased use of narrow and tiered networks.14 These policy changes have done little to improve the
quality of such services,14-16 or even the assessment of quality.17,18 Furthermore, patients with insurance coverage including behavioral health services still face financial barriers to accessing care.19 Additional
research is needed to determine how insurance benefit design affects how care is delivered to behavioral health patients.20 In light of these ongoing challenges, more research is needed on costs, quality, and access for the delivery of behavioral health services.
Evidence-Based Practices
There is an increasing focus on dissemination and implementation of evidence-based practice (EBP),21 which is the practice of health care services arising from the culmination of clinical expertise, patient preferences, and best-available research evidence.22,23 Clinical expertise is accumulated by practitioners through years of training and treating patients in clinical settings. Patient preferences are determined on a case-by-case basis taking into account factors that are important to patients such as effectiveness, invasiveness, side effects, costs, and prognosis.23 Empirical evidence is the foundation of EBP and is generated using a variety of methods from basic benchtop science to worldwide
epidemiological and economic studies.
Prior to the use of the term EBP beginning in 1992,24 clinical epidemiology referred to the
critical appraisal and application of research to the practice of medicine.25 Initially, clinical epidemiology/EBP researchers applied classical epidemiology principles and methods to medical problems through conducting epidemiological studies, systematically evaluating existing research, and translating studies of health care services and outcomes into practice settings.26,27 Ultimately, EBP
employed research methods to optimize costs, quality, and access of health services.
EBPs are disseminated primarily through peer-reviewed publications, clinical practice guidelines, meta-analyses, and systematic reviews.28 Despite relatively widespread dissemination of EBPs, there
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remains significant challenges to effectively implementing EBPs in the real-world. For example, one study found that penetration rates of EBPs among state mental health authorities was only 1-3%.21
Another study found substantial variation in the number of EBPs between urban and rural settings.29 Even
individuals with private insurance do not consistently receive EBP for treatment of depression,30-32 even though the EBPs improve outcomes, reduce missed work, and reduce overall costs.33,34 In response, some
insurers have pointed to the high cost of implementing and maintaining EBPs as a reason for low uptake,35 which necessitates new economic analyses to address these concerns. More work is needed to continue development and implementation of EBPs, while investigating their uptake and impact in the behavioral health system.
Behavioral Health Services Research Methods
Health services research (HSR) was formally established as a field of inquiry in the early 1960s with the goal of supporting the triple aim of reducing costs, improving quality, and enhancing access for health care services.36,37 The purpose of HSR is the generation and dissemination of reliable, valid data that informs the use of appropriate, effective, cost-effective, efficient, and acceptable care.38 To achieve this end, HSR practitioners utilize a variety of tools and techniques to answer questions a regarding how to best provide healthcare to populations or subpopulations.
Individuals with behavioral health problems are one of these subpopulations. As the top category of disease expenditure,39,40 behavioral health is ripe for systematic evaluation and improvement. There
have been significant improvements in financial access to care via the MHPAEA and ACA, yet
challenges remain in terms of costs and access to behavioral health services.12 This dissertation employs
three different methods for assessing cost, quality, and access of behavioral health services using secondary data analysis. The common thread within Chapters 2 through 4 is the use of HSR methods to generate evidence to be used to further improve structures, processes, and outcomes within mental health services.
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Chapter 2 examines the epidemiology of comorbid psychiatric disorders among adults presenting to the emergency department (ED) for injuries. The primary aim of Chapter 2 is to provide clinicians with evidence to narrow the subpopulation of injury patients that should be screened for specific classes of psychiatric disorders within time and resourced constrained EDs. Screening could provide additional opportunities to improve quality of care in the ED and access to behavioral health services for patients screening positive. Chapter 3 uses current EBPs for obsessive-compulsive disorder (OCD) in children and adolescents to perform a cost-benefit analysis. The aim of Chapter 3 is to provide clinicians, patients, parents, and payers an empirical comparison based on expected effectiveness and costs across options. Insurers and/or policymakers could utilize these results to incentivize the use of the most cost-beneficial treatments over less beneficial or more expensive options. Chapter 4 uses economic analyses to examine the relationship between cost-sharing and utilization of guideline-recommended psychotherapy and pharmacotherapy for treating OCD in adults. Recurring cost-sharing expenses may deter patients from fully realizing the recommended dose or duration of the EBPs. The aim of Chapter 4 is to quantify the relationship between sharing, visit intensity, and medication adherence to provide evidence that cost-sharing is a blunt instrument and may have unintentional effects of deterring high-value care. The
remainder of the Introduction provides an overview of the studies presented in Chapters 2 through 4.
Overview of Chapter 2: Epidemiology of Disorders
Chapter 2 is an examination of the association between injuries treated in the ED and comorbid psychiatric disorders. This chapter highlights issues of access and quality of behavioral health services in the ED. Improved access to behavioral health services may be achieved through selective screening at-risk patients for disorders and linking identified patients to necessary follow-up care. Each ED encounter without screening represent a missed opportunity to direct patients into necessary behavioral health services. Moreover, since untreated psychiatric disorders can exacerbate somatic health problems though disruption in prescribed care.41-44Interventions that identify barriers to optimal care may improve overall
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Patients presenting in the ED commonly have diagnosed and undiagnosed comorbid psychiatric disorders. One study found that one quarter of ED patients without psychiatric complaints, met the diagnostic criteria for major depression.45 Others have found that over 40% of patients presenting to the
ED for a minor injury had a comorbid psychiatric disorder.46 Furthermore, there is robust association between chronic psychiatric disorders and injuries, generally.47
Each year, there are an estimated 141.4 million visits to EDs nationwide, of which 40 million are for an injury.48 Injuries are classified by mechanism (e.g., cut, fall, poisoning, traffic accident) and cause (i.e., unintentional, intentional self-harm, intentional assault, and undetermined). The largest proportion of injuries are unintentional, followed by undetermined, intentional assault, and intentional self-harm.48
The relationship between the cause of injury and psychiatric disorders is not well-understood. There is some evidence that psychiatric disorders may moderate risk aversion behavior,49-54 thus
increasing or decreasing probability of injuries. While the relationships are not well-understood, research has demonstrated that psychiatric disorders are positively correlated with injury rates and recidivism.
47,55-57
Moreover, patients presenting to the ED with injuries and comorbid psychiatric disorders have more complications, longer lengths of stay, and higher mortality compared to patients without comorbid psychiatric disorders.58
Injuries are generally easy to observe and diagnose in the ED,59,60 while psychiatric disorders are substantially more difficult to observe.61,62 Previous research has shown that ED clinicians have difficulty
diagnosing patients with anxiety,61 depression,45 and other disorders.61-63 For example, attending ED
physicians diagnosed just 2% of patients who presented with a diagnosable psychiatric disorder.62 In light low identification rates, ED clinicians and patients might benefit from new tools or protocols that enhance their ability to diagnose latent comorbidities.
The purpose of the study was to examine the association between cause of injury and psychiatric disorders among patients presenting to the ED with injuries, to provide clinicians with actionable
guidance regarding psychiatric disorder screening. A large, national discharge dataset was utilized to answer this research question. The study addressed three hypotheses: 1) patients with injuries are more
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likely to have a comorbid psychiatric disorder relative to ED patients without injuries; 2) intentional injuries, self-inflicted, and assault-related, are strongly, positively correlated with psychiatric disorders; and 3) undetermined cause of injury is positively associated with psychiatric disorders.
There are several significant implications for the examination of the relationship between cause of injury and comorbid psychiatric disorders in the ED. First, quantifying the relationship between cause of injury and psychiatric disorders increases our understanding of the epidemiology of psychiatric disorders in the ED. A robust association would indicate that additional screenings are needed to identify comorbid psychiatric disorders in the ED. Second, patients who are appropriately identified, can be referred to inpatient or community-based care. Early detection of behavioral health disorders may lead to earlier interventions, which can reduce the likelihood of additional impairments due to disorders and/or could improve treatment outcomes.58 In addition, treated psychiatric disorders may reduce ED costs and utilization associated with ED recidivism. Third, if the associations are found to be positive and robust, the results may help ED clinicians narrow the subpopulation that would benefit most from the additional psychiatric screening. Evidence from this study can be used to introduce efficient screening protocols that improve access and quality of care.
Overview of Chapter 3: Cost-Benefit Analysis
The aim of Chapter 3 is to determine the ranked efficiency of first-line treatments for obsessive-compulsive disorder (OCD) in children and adolescents. Chapter 3 provides evidence that supports decision-making when selecting the most appropriate treatment. In the face of limited time and financial resources, clinicians, patients, parents, and payers need to understand how treatments compare in terms of effectiveness, costs, time, and adverse effects.64 The comparison of costs and benefits of treatments
directly addresses areas of costs and quality of care. Access is indirectly considered since some patients may not be able to participate in the most effective treatments due to geographic, temporal, or financial barriers. Ranking alternatives allows patients and parents to make informed treatment decisions.
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There are few studies of cost analyses of behavioral health treatments, especially targeting children and adolescents.65,66 Moreover, cost-analyses need updated as new psychotherapy interventions, new medications, and alternative treatments are approved and disseminated. A review of the literature found that 67 economic studies in child and adolescent behavioral health were published between 2005 and 2012.66 Of these 67 studies, most were clustered around a handful of broadly-classified disorders
including autism, anxiety and depression, attention-deficit hyper-activity disorder, and conduct disorder.66 Further research is needed for specific disorders66 in which there are well-defined diagnoses and
treatments. One such disorder is OCD.
OCD affects between 1% and 2% of children and adolescents in the United States.67 Individuals with OCD exhibit obsessions and/or compulsions. Obsessions are recurrent, persistent, and intrusive thought, impulses, or images that cause significant distress and/or anxiety.68 Compulsions are repetitive behaviors, or mental processes that are carried out in response to the aforementioned obsession, to reduce anxiety, or in accordance with a rules system.68 The symptoms vary from mild to severely impairing,69 which can lead to reductions in quality of life.70 Most children and adolescents who do not receive the recommended treatments will continue to exhibit symptoms into adulthood.71,72
The current clinical guidelines for OCD endorse cognitive-behavioral therapy (CBT) and/or antidepressant medication (ADM) pharmacotherapy.73 The current evidence base suggests that CBT is both safe and effective for the treatment of OCD with superior effects compared to ADMs.74-76 The
evidence also supports the use of ADMs and CBT in combination,74,76-78 especially for patients that have
more severe symptoms.73,77,79 For some patients, ADMs are the recommended first-line treatment. For instance, some patients are unable to participate in CBT due to disease severity or due to concerns about CBT availability, time and distance barriers, and cost-barriers.73 Recent research suggests that adult
patients with at least moderate OCD symptoms prefer differing treatment modalities based on personal characteristics, but favor augmenting SRI therapy with CBT over augmenting with antipsychotics.80
Currently, there is only one cost analysis of OCD focusing on children and adolescents, but there are some issues with applying the findings to the U.S. healthcare system. The sole cost-effectiveness
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study was conducted in the United Kingdom, using assumptions surrounding their health system and extrapolating from adult research.81 The researchers also separately analyzed behavioral therapy (BT) and cognitive therapy (CT) from CBT, which does not follow accepted terminology in the U.S. and may be misleading.81 Therefore, Chapter 3 seeks to advance the field by conducting a cost-benefit analysis of first line treatments for OCD in children and adolescents.
The purpose of the study was to compare benefits, costs, and incremental cost-benefits for recommended treatments for OCD in children and adolescents. The study examined and ranked three initial strategies: 1) CBT monotherapy, 2) ADM monotherapy, 3) concurrent ADM+CBT and four augmentation strategies for treatment resistant cases: 1) more CBT after initial CBT monotherapy, 2) more CBT after initial ADM monotherapy, 3) more ADM after initial ADM monotherapy, and 4) adding ADM to CBT monotherapy. Based on the lone cost-effectiveness analysis, it was hypothesized that CBT monotherapy would be the most cost-beneficial strategy.
This study makes several contributions to the field of behavioral health services research. First, it is the first cost analysis of OCD treatments for children and adolescents in the U.S. This is important for selecting the most cost-beneficial (i.e., efficient) treatment option given the totality of the evidence and patient considerations. Patients must choose how to allocate their limited income and time in the face of several treatment options and require information from cost-analyses to identify the best option. Second, it aggregates existing research studies using a meta-analytic framework to allow for comparison of treatment effects despite not having primary data. Third, this study also improves upon generalizability because it minimizes heterogeneity of study participants, protocols, and practitioners between studies through the meta-analytic methodology.
Overview of Chapter 4: Economic Analysis of Claims Data
Chapter 4 presents an economic analysis of the association between patient cost-sharing and behavioral health services utilization and medication adherence among adults with OCD. This chapter follows in the same line of research as the seminal work in the Rand Health Insurance Experiment (HIE),
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which has been replicated using observational data from health insurance claims.82-101 This chapter
utilizes a large, national commercial health insurance claims database to examine the relationship between cost-sharing and utilization of psychotherapy and pharmacotherapy for adults with OCD.
Health insurers have long struggled with the best method(s) for limiting the use of low value care, or care that does little to improve health but has high associated costs.102 Moral hazard occurs when
insured patients use more health care services than they would otherwise, because the patient only pays a portion or none of the true cost of care.103,104 One of the means by which insurers have sought to control moral hazard is through increased patient cost-sharing. Cost-sharing can include copayment, coinsurance, and/or deductible.
The demand for health care services has been shown to be responsive to varying levels of cost-sharing. The Rand HIE was conducted from 1974-1982 across six sites in the U.S.105 The study remains the largest, most expensive randomized control trial of health insurance in the U.S.105 The price elasticity of demand across all health care services was -0.20.106 This implies that for every 10% increase in patients’ price, patients reduced healthcare spending by 2%. However, grouping all health services together is problematic because the estimates of price sensitivity for behavioral health services has been found to vary more than somatic health service estimates.101,107-114
Reported estimates of price elasticity of demand for behavioral health services have shown variation based on sample selection, methodology, types of services assessed, and types of providers seen. Some have found that demand for behavioral health services is the same as somatic health services (i.e., about -0.20),108,115 while the majority have reported that behavioral health services are more sensitive to price relative to somatic health services (i.e.,< -0.20).107,110,113,114,116,117 Interpreting these findings are
complicated by additional variation in response to price conditional on the type of services provided (e.g.,, outpatient, inpatient, medications).107,110,113,116,118-123 Inpatient services are less sensitive to
cost-sharing relative to outpatient services, with most studies finding no significant change in utilization of inpatient service following increases in cost-sharing.124 Estimates of price elasticity of demand for
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to 6% decrease in spending for each 10% increase in cost-sharing.125 There is no significant association
between provider type and cost-sharing, although non-psychiatrist and psychiatrists are likely substitutes.119-121
The two primary treatments for adult OCD are psychotherapy and/or serotonin-reuptake
inhibitors (SRI).126-128 Both of these treatments are widely available in the U.S., although specialty care is
less available in rural areas.29,129,130 The decision as to which treatment to undertake is guided primarily by clinical necessity and secondarily by patient preferences.131 Patients have expressed that one of their chief concerns regarding treatment decisions is the cost of treatment.132-134 Despite this, little work has
examined the association between patient cost-sharing and the decisions to initiate and continue treatments.
Among the more recent research examining the association between cost-sharing and psychotherapy there is mixed evidence regarding cost-sharing. For example, Lu et al.108 found that deductibles had no effect on demand for behavioral health services, but the odds of service use for
decreased by over 3% for every 1% increase in coinsurance rates. On the contrary, Fishman et al.135 found that having an unmet deductible between $100 and $500 was associated with 15% lower odds of initiating psychotherapy for depression, but copayment had no effect on initiation or continuation. Considering these mixed findings, additional confirmatory work is needed.
The research examining the association between cost-sharing and medication adherence has shown that adherence decreases as price increases. In a review of over 100 articles, Goldman, Joyce and Zheng125 found that spending on prescription drugs decreases by 2% to 6% for every 10% increase in cost-sharing, with variation by drug class and disorder. Increases in medication cost-sharing was associated with decreases in adherence of 10% to 27% for <$50 and ≥$50 cost-sharing levels for
antipsychotic medications, respectively.85 Similarly, the odds of adherence decrease by 15% for every $10
increase in the price of antidepressant medications.82
Despite the numerous studies examining cost-sharing and utilization of behavioral health
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behavioral health disorders. The have been limited studies of depression,82,100,136-140 schizophrenia, 85,90,141-145
and substance abuse,101,146-148 while other disorders, despite relatively high lifetime prevalence, have been largely neglected, such as panic disorder (4.7%), specific phobias (12.5%), social phobia (12.1%), generalized anxiety disorder (5.7%), PTSD (6.8%), OCD (2.3%), bipolar disorder (4.4%), impulse control disorders (25%).149 This study seeks to address the gap through the investigation of cost-sharing and
treatment utilization among adults with OCD.
Approximately 1-2% of U.S. adults are living with OCD, 150,151 which can reduce quality of life,
152-154
and have detrimental impacts on social and emotional well-being.155,156 As previously discussed in the context of children and adolescents, OCD is characterized by the presence of obsessions and/or compulsions that cause significant distress. The recommended first-line treatment for adults with OCD is also the same as in children and adolescents, which includes CBT and/or SRIs.79,157-161 In light of the existence of effective treatments for adults with OCD, identifying barriers to care, such as financial barriers (i.e., costs of care) is an important factor in ensuring that EBPs are disseminated, implemented, and accessible.
The results of Chapter 4 have several implications for insurance design regarding behavioral health services. First, this study provides evidence of a negative association between cost-sharing and psychotherapy intensity and dose among adults with OCD, which is comparable to prior research
examining cost-sharing and behavioral health disorders. Second, this research shows that cost-sharing is a blunt instrument as previously described124,162 since it is associated with reductions in utilization. This
chapter shows that increased cost-sharing is associated with lower utilization of psychotherapy (a major EBP recommendation) as outlined in treatment guidelines. In contrast, cost-sharing is not associated with adherence to SRI medications; however, caution should be used when evaluating these findings due to uncertainty in the model. Insurers and policymakers can use these findings, and other information, when determining appropriate cost-sharing mechanisms and levels for different treatment modalities by disorder to ensure access to high-quality treatments. The findings have implications for clinicians and researchers since most patients do not achieve the therapeutic dose or duration as recommended by the
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treatment guidelines, regardless of cost-sharing. Treatment decisions should take note of this and clinicians should address barriers in the course of treatment. Finally, researchers will need to develop novel ways of delivering treatments that better fit real-world utilization patterns.
Summary
The overarching aim of this dissertation is the contribution evidence to the scientific literature that can be directly incorporated into EBPs for the purposes of improving cost, quality, and access of behavioral health services. In each of the chapters, there is focus on ways to optimize care through at least two of the triple aims. One cannot optimize only one domain without some negative impact or concession in another domain. For example, in Chapter 2, increasing quality (via identifying comorbid disorders) for patients with injuries in the ED, would require increasing costs due to additional trainings and policy implementation, staff time needed to conduct screenings, physician time to diagnose and refer patients, and resources to treat patients with unstable behavioral health problems. In addition, ensuring patients have access to care via referrals requires establishing business relationships with outpatient behavioral health providers (if not done within the same system), providing additional beds, and potentially
providing free care to indigent patients. While it is relatively simple to maximize one domain, balancing the other two domains requires reliable, valid data.
There is no one correct or best method to generate the research basis for EBPs, hence this dissertation uses a variety of data sources and methods, and in the process demonstrates proficiency in health services research methods. Chapter 2 used a nationally, representative survey of ED records and epidemiological methods to address the research question, what is the relationship between injury and psychiatric disorders among patients seen in the ED? Chapter 3, utilized data from peer-reviewed randomized controlled trials and probability simulations to examine and rank the cost-benefits of recommended treatments to address the research question, what is the most efficient/ highest quality treatment for OCD in children and adolescents? Chapter 4 exploited a large insurance claims database and regression analyses to examine the relationship between cost-sharing and behavioral health service use for
13
adults with OCD. In doing so, it addressed the research question, how do financial barriers affect access to and quality of health care services?
While the methodology is important, the application of findings to practice and policy are equally important. Each chapter provides evidence that can be incorporated in the EBPs and/or used to support the dissemination, implementation, and access to EBPs for patients with behavioral health disorders. The audience for these chapters range from patients, to clinicians, to payer and policymakers. These
stakeholders all require reliable, valid information to make informed decisions, and in the case of the clinicians, implement EBPs. In our healthcare system with increasingly limited resources, it is necessary to identify the EBPs to maximize the return on time and monetary investments in health.
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