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Public health emergencies impact the well-being of people and communities. Long-term emotional distress is a pervasive and serious consequence of high levels of crisis exposure and low levels of access to mental health care. At highest risk for mental health trauma are historically medically underserved and socially marginalized populations and frontline health care workers (HCWs). Current public health emergency response efforts provide insufficient mental health services for these groups. The ongoing mental health crisis of the COVID-19 pandemic has implications for the resource-strained health care workforce. Public health has an important role in delivering psychosocial care and physical support in tandem with communities. Assessment of US and international public health strategies deployed during past public health emergencies can guide development of population-specific mental health care. The objectives of this topical review were (1) to examine scholarly and other literature on the mental health needs of HCWs and selected US and international policies to address them during the first 2 years of the pandemic and (2) to propose strategies for future responses. We reviewed 316 publications in 10 topic areas. Two-hundred fifty publications were excluded, leaving 66 for this topical review. Findings from our review indicate a need for flexible, tailored mental health outreach for HCWs after disasters. US and global research emphasizes the dearth of institutional mental health support for HCWs and of mental health providers who specialize in helping the health care workforce. Future public health disaster responses must address the mental health needs of HCWs to prevent lasting trauma.

The Affordable Care Act requires all insurance plans sold on health insurance marketplaces and individual and small-group plans to cover 10 Essential Health Benefits (EHB), including behavioral health services. Instead of applying a uniform EHB plan design, the Department of Health and Human Services let states define their own EHB plan. This approach was seen as the best balance between flexibility and comprehensiveness, and assumed there would be little state-to-state variation. Limited federal oversight runs the risk of variation in EHB coverage definitions and requirements, as well as potential divergence from standardized medical guidelines. We analyzed 112 EHB documents from all states for behavioral health coverage in effect from 2012 to 2017. We find wide variation among states in their EHB plan required-coverage, and divergence between medical-practice guidelines and EHB plans. These results emphasize consideration of federated regulation over health insurance coverage standards. Federal flexibility in states benefit design nods to state-specific policymaking-processes and population needs. However, flexibility becomes problematic if it leads to inadequate coverage that reduces access to critical health care services. The EHBs demonstrate an incomplete effort to establish appropriate minimum standards of coverage for behavioral health services.

There is international recognition of the high prevalence of depression and its associated disability. In countries where workers have been studied, major depressive disorders are the most prevalent chronic conditions in the prior year. Economic costs of depression include the costs related to screening, treatment, maintenance, and support of persons with depression. Costs also include those due to the effects of depression on absenteeism, presenteeism, and long-term disability costs. Workplaces offer high potential for preventing depression; recognizing early and advanced stages of depression; improving depression care off-site or on-site, in person or virtually; and improving outcomes of those efforts. Evidence-based programs for reducing depression costs exist. Innovations in technology and growing interest in financing novel programs for persons with depression offer promising outcomes clinically and economically.

Objective: Despite barriers, organizations with varying characteristics have achieved full integration of primary care services with providers and services that identify, treat, and manage those with mental health and substance use disorders. What are the key factors and common themes in stories of this success? Methods: A systematic literature review and snowball sampling technique was used to identify organizations. Site visits and key informant interviews were conducted with 6 organizations that had over time integrated behavioral health and primary care services. Case studies of each organization were independently coded to identify traits common to multiple organizations. Results: Common characteristics include prioritized vulnerable populations, extensive community collaboration, team approaches that included the patient and family, diversified funding streams, and data-driven approaches and practices. Conclusions: While significant barriers to integrating behavioral health and primary care services exist, case studies of organizations that have successfully overcome these barriers share certain common factors.

Objectives To assess the financial effect of the 2008 Hospital-Acquired Conditions Initiative (HACI) pressure ulcer payment changes on Medicare, other payers, and hospitals. Design Retrospective before-and-after study of all-payer statewide administrative data for more than 2.4 million annual adult discharges in 2007 and 2009 using the Healthcare Cost and Utilization Project State Inpatient Datasets for California. How often and by how much the 2008 payment changes for pressure ulcers affected hospital payment was assessed. Setting Nonfederal acute care California hospitals (N = 311). Participants Adults discharged from acute-care hospitals. Measurements Pressure ulcer rates and hospital payment changes. Results Hospital-acquired pressure ulcer rates were low in 2007 (0.28%) and 2009 (0.27%); present-on-admission pressure ulcer rates increased from 2.3% in 2007 to 3.0% in 2009. According to clinical stage of pressure ulcer (available in 2009), hospital-acquired Stage III and IV ulcers occurred in 603 discharges (0.02%); 60,244 discharges (2.42%) contained other pressure ulcer diagnoses. Payment removal for Stage III and IV hospital-acquired ulcers reduced payment in 75 (0.003%) discharges, for a statewide payment decrease of $310,444 (0.001%) for all payers and $199,238 (0.001%) for Medicare. For all other pressure ulcers, the Hospital-Acquired Conditions Initiative reduced hospital payment in 20,246 (0.81%) cases (including 18,953 cases with present-on-admission ulcers), reducing statewide payment by $62,538,586 (0.21%) for all payers and $47,237,984 (0.32%) for Medicare. Conclusion The total financial effect of the 2008 payment changes for pressure ulcers was negligible. Most payment decreases occurred by removal of comorbidity payments for present-on-admission pressure ulcers other than Stages III and IV. The removal of payment for hospital-acquired Stage III and IV ulcers by implementation of the HACI policy was 1/200th that of the removal of payment for other types of pressure ulcers that occurred in implementation of the Hospital-Acquired Conditions Initiative.

Assessing the value of clinical and translational research funding on accelerating the translation of scientific knowledge is a fundamental issue faced by the National Institutes of Health (NIH) and its Clinical and Translational Awards (CTSAs). To address this issue, the authors propose a model for measuring the return on investment (ROI) of one key CTSA program, the clinical research unit (CRU). By estimating the economic and social inputs and outputs of this program, this model produces multiple levels of ROI: investigator, program, and institutional estimates. A methodology, or evaluation protocol, is proposed to assess the value of this CTSA function, with specific objectives, methods, descriptions of the data to be collected, and how data are to be filtered, analyzed, and evaluated. This article provides an approach CTSAs could use to assess the economic and social returns on NIH and institutional investments in these critical activities.

We use 4 years of data from the retiree health benefits program of the University of Michigan to estimate the effect of price on the health plan choices of Medicare beneficiaries. During the period of our analysis, changes in the University's premium contribution rules led to substantial price changes. A key feature of this 'natural experiment' is that individuals who had retired before a certain date were exempted from having to pay any premium contributions. This 'grandfathering' creates quasi-experimental variation that is ideal for estimating the effect of price. Using regression discontinuity methods, we compare the plan choices of individuals who retired just after the grandfathering cutoff date and were therefore exposed to significant price changes to the choices of a 'control group' of individuals who retired just before that date and therefore did not experience the price changes. The results indicate a statistically significant effect of price, with a $10 increase in monthly premium contributions leading to a 2 to 3 percentage point decrease in a plan's market share.

We revisit the question of price elasticity of employer-sponsored insurance (ESI) take-up by directly examining changes in the take-up of ESI at a large firm in response to exogenous changes in employee premium contributions. We find that, on average, a 10% increase in the employee's out-of-pocket premium increases the probability of dropping coverage by approximately 1%. More importantly, we find heterogeneous impacts: married workers are much more price-sensitive than single employees, and lower-paid workers are disproportionately more likely to drop coverage than higher-paid workers. Elasticity estimates for employees below the 25th percentile of salary distribution in our sample are nearly twice the average.

Although mental illness treatment protocols exist, the organization and financing of screening and treatment services inhibit access. These challenges are compounded for refugees, immigrants, and other groups vulnerable due to their ethnicity, race, or culture. By creating a system-wide, collaborative, integrated model that recognizes and addresses critical clinical and economic aspects in the delivery of services, high quality, evidence-based care can be made available to groups susceptible to the burdens of mental illness. Clinically and financially aligning primary and specialty care offers a viable alternative for improving access and quality of mental health services to vulnerable populations.

While early growth in preferred provider organizations (PPOs) coincided with growth of managed care generally, recent expansion has come primarily at the expense of other managed care plans. Little is known about the micro behavior underlying these trends. In 2005, University of Michigan employees were offered PPOs for the first time by vendors who also offered other plans. PPOs helped the offering vendors maintain or increase their total enrollment share. PPOs were most attractive to workers who previously had chosen less managed plans. Because PPOs drew few enrollees from health maintenance organizations (HMOs), there was little evidence of a backlash against managed care in the context of the University of Michigan employee group.

Objective:This study evaluated utilization of mental health and substance use services among enrollees at a large employee health plan following changes to benefit limits after passage in 2008 of federal mental health parity legislation.Methods:This study used a pre-post design. Benefits and claims data for 43,855 enrollees in the health plan in 2009 and 2010 were analyzed for utilization and costs after removal of a 30-visit cap on the number of covered mental health visits.Results:There was a large increase in the proportion of health plan enrollees with more than 30 outpatient visits after the cap’s removal, an increase of 255% among subscribers and 176% among dependents (p

As veterans age, chronic physical and psychiatric conditions increasingly challenge the Veterans Health Administration. We examine influences of age and diagnosis on health care utilization, within the context of the 1995 deinstitutionalization policy of the Veterans Health Administration. Veterans were hospitalized repeatedly over 5 years with diagnoses of schizophrenia, bipolar disorder, depression, or alcohol dependence (N = 7,719). Inpatient days decreased 14% from baseline while outpatient (OP) visits increased 63%, consistent with deinstitutionalization. In adjusted models, OP utilization greatly increased with age, but psychiatric visits-notably alcohol treatment--dropped sharply. Emergency visits rose after 1997, particularly for ethnic minorities. Individuals ages 35-49 and 50-64 years were the greatest consumers of OP care; these large, aging cohorts will continue to require additional services, taxing a burdened system. Utilization patterns evolve across the life course, requiring foresight to address changing demographic demands. Careful attention to mental health utilization patterns may help policy makers and providers understand psychiatric needs in older patients.

A goal of the Robert Wood Johnson Depression and Primary Care Initiative at the University of Michigan is to create and implement the clinical care and financial systems necessary to enable links between primary care and mental health specialty depression care. This paper describes the economic issues related to resources required, the mechanisms to distribute those resources, and the support that must be garnered from stakeholders. By systematic measurement and application, we assess the cost, price and selected consequences of these efforts. The study illustrates the need for both centralized and distributed capacity and support for innovative models of care.

This paper briefly reviews the recent history of psychosocial treatment for adults with severe mental illnesses in the United States. It examines the current sources and financing of such care, revealing the planned and unplanned reclassification of entitled beneficiaries and eligible patients, appropriate treatment, acceptable outcomes, and levels and sources of payment. One illustration of this phenomenon is seen in current efforts to identify and deliver only those public services that are covered by Medicaid, so as to allocate state resources only when they can be matched by federal monies. Another is the reliance on private health insurance, tied in the U.S. almost exclusively to employment, for medical care delivered under an acute, rather than a chronic care model. These analyses conclude with a discussion of the implicit and explicit mechanisms used to ration access to psychosocial treatment in the United States. The implications for individuals with serious mental illnesses, their families, and the general public are placed in historical and current policy contexts, recognizing the economic, social, and clinical variables that can moderate outcomes.

Managed care plans in the United States are increasingly using paid claims records to monitor and judge the physicians who provide services to plan members. The motivation for economic, or “practice efficiency,” profiling, as this is termed, is primarily financial—physicians identified as being inefficient are considered to be wasteful of health plan resources, and these physicians can be encouraged to change their practice styles or they can be dropped from the plan's provider network (Sandy 1999; Nickerson and Rutledge 1999; Litton, Sisk, and Akins 2000). Vendors and clients (primarily health plans) of profiling systems consider a physician to be efficient if total claims costs of services provided to managed patients are no greater than costs expected for those patients, given the patients' demographic characteristics and health conditions. “Inefficient” physicians are those for whom actual claims costs exceed the expected amounts.1 When several physicians are involved in providing care to a patient, it is often quite difficult to determine from claims records which of the physicians ordered a particular service, prescribed a particular drug, or even admitted the patient to a hospital. Because of this attribution problem, economic profiling appears to be used most frequently in managed care plans that require primary care physicians (PCPs) to serve as gatekeepers. In these plans, the PCPs are assumed responsible for all costs incurred on behalf of the patients they manage, regardless of whether they themselves performed or even ordered the services. And with this assumption, attribution of responsibility is not an analytic problem. Even though dozens of firms offer profiling software and services to health plans, there are relatively few methodologies that can be used for risk-adjusting physician profiles, that is, for estimating patients' expected costs. And nearly all profiling vendors use one or more of these established methodologies. In the project reported here, our purposes were to determine whether some risk-adjustment methodologies used for physician profiling are more accurate than others, and whether risk-adjustment differences lead to different judgments about PCP practice efficiency. Our findings on accuracy of risk-adjustment methodologies are presented in Thomas, Grazier, and Ward (2002). Here, we describe findings related to levels of agreement among PCP practice efficiency rankings when, for a common set of PCPs, patients' expected costs are estimated using different risk-adjustment methodologies and two different measures of practice efficiency. For our analyses, we used the membership and claims databases of an independent practice association HMO that serves the five counties of Southeast Michigan. Six profiling system vendors/developers agreed to work with us on the project, to either make their risk-adjustment software available, or to process our data through their software and return the risk-adjusted results to us. A detailed description of each of the participating methodologies is provided in our project report (Thomas, Grazier, and Ward 2002). The methodologies are: Adjusted Clinical Groups (ACGs Version 4.5, 2000) from Johns Hopkins University. Adjusted clinical groups cluster health plan members having similar comorbidities into groups that have similar resource requirements and clinical characteristics. The ACG Case-Mix System then uses a branching algorithm to place each patient into one of 82 discrete, mutually exclusive categories based on the mix of clinical groups experienced during the time period under study (Johns Hopkins University 2000). Burden of Illness Score (BOI Version PRS 4.6, 2001) from MEDecision, Inc. This system is based on MEDecision's Practice Review System (PRS), which partitions care into episodes of illness and assigns services, severity levels, and medications to these episodes. The BOI Score is a linear-scaled measure that indicates relative health care cost risks associated with the particular mix of episodes experienced by a patient during a defined time period (Anderson and Gilbert 2002). Clinical Complexity Index (CCI Version 3.6, 1997) from Solucient, Inc. The CCI methodology considers age, severity, comorbidity, hospital admissions, and categories of diagnoses (acute, chronic, mental health, and pregnancy) to assign patients into mutually exclusive CCI risk categories. Although the system provides for 1,418 different categories, 95 percent of patients fall into just 45 of these (Solucient 1999). Diagnostic Cost Groups (DCGs Version 5.1, 2000) from DxCG, Inc. The DCG system includes a whole family of multiple linear regression models. For this study, we utilized the all encounter, hierarchical model (DCG/HCC) for a commercial population, which uses data on age, sex, and all diagnoses—inpatient and outpatient—to explain patients' health care expenditures for the period under study. In our analyses, we used the DCG retrospective risk measure, together with patients' age/sex categories (DxCG Inc. 2002). Episode Risk Groups (ERGs Version 4.2, 2001) from Symmetry Health Systems, Inc. Like BOI Score, ERGs are episode-based. The episodes underlying ERGs are created using Symmetry's Episode Treatment Groups (ETG™) methodology, a basic illness classification system that uses a series of clinical and statistical algorithms to combine related services into more than 600 mutually exclusive and exhaustive categories. For a given patient, episodes experienced during a time period are mapped into 119 Episode Risk Groups, and then a risk score is determined based on age, gender, and mix of ERGs. For our analyses, we used the ERG retrospective risk score (Symmetry Health Data Systems 2001). General Diagnostic Groups (GDGs Version 1.0, 2000) from Allegiance LLC. General Diagnostic Groups were developed using the Agency for Health Care Policy and Research's Clinical Classification Software (CCS). CCS aggregates individual ICD-9-CM codes identified on health care claims into 260 broad diagnosis categories for statistical analysis and reporting. The GDG system then lumps together CCS categories considered to be clinically similar and to have similar associated per-patient charges into 57 diagnostic categories. These 57 diagnostic categories are used as dummy variables in a multiple regression model for predicting health care costs (Cowen et al. 1998). Although CCI and the two episode-based methodologies include utilization data as independent predictors of risk, our analyses (not reported here) found that these systems were not different from the other three systems in terms of accuracy of member cost predictions (Thomas, Grazier, and Ward forthcoming).

This paper examines the relative accuracy of risk-adjustment methodologies used to profile primary care physician practice efficiency. Claims and membership data from an independent practice association health maintenance organization (HMO) were processed through risk-adjustment software of six different profiling methodologies. The Group R2 statistic was used to measure, for simulated panels of HMO members, how closely each methodology's cost predictions matched the panel's actual costs. All but one methodology explained at least 50% of panel cost variance with panels as small as 25 patients. Group R2 performance tended to be better when high-cost cases were included rather than excluded from the analyses.

This article documents a unique organizational, legal, and financial partnership between a state, a university, a Medicaid managed health care plan, and a county to provide integrated mental health, substance abuse, and primary and specialty health care services to Medicaid, low-income, and indigent consumers in Washtenaw county, Michigan. Major regulatory, financial, and clinical changes were required within and among the various partners in the Washtenaw County Integrated Health Care Project. A new entity—the Washtenaw Community Health Organization—was created to implement the project. By sharing resources as well as financial risks, the state, the county, and the university have been able to provide ongoing integrated care to a vulnerable population of patients. Although resource intensive in conceptualization and implementation, the project can be viewed as a model for other states that face growing needy populations and decreasing Medicaid budgets.

Managed behavioral health care is increasingly being used in public mental health systems. While supporters cite potential benefits, critics describe dire consequences for individuals with serious, long-term mental illness. The situation has parallels with the major changes resulting from deinstitutionalization some four decades ago. Believing that analyzing history may prevent repeating some of its mistakes, the authors compare the antecedents, benefits, and negative effects of deinstitutionalization with those of the public-sector managed behavioral health care systems being developed today. Lessons learned from the earlier era include the need for careful general and technical planning; for assignment of responsibility, including monitoring, to the public sector; and for a focus on clients and the special needs generated by severe mental illnesses.

Healthcare providers have increased the use of quality improvement (QI) techniques, but organizational variables that affect QI uptake and implementation warrant further exploration. This study investigates organizational characteristics associated with clinics that enroll and participate over time in QI. The Network for the Improvement of Addiction Treatment (NIATx) conducted a large cluster-randomized trial of outpatient addiction treatment clinics, called NIATx 200, which randomized clinics to one of four QI implementation strategies: (1) interest circle calls, (2) coaching, (3) learning sessions, and (4) the combination of all three components. Data on organizational culture and structure were collected before, after randomization, and during the 18-month intervention. Using univariate descriptive analyses and regression techniques, the study identified two significant differences between clinics that enrolled in the QI study (n = 201) versus those that did not (n = 447). Larger programs were more likely to enroll and clinics serving more African Americans were less likely to enroll. Once enrolled, higher rates of QI participation were associated with clinics' not having a hospital affiliation, being privately owned, and having staff who perceived management support for QI. The study discusses lessons for the field and future research needs.

To control the rise in expenditures and to increase access to mental health and substance abuse (MH/SA) services, a growing number of employers and states are implementing a “carve-out.” Under this arrangement, the sponsor separates insurance benefits by disease or condition, service category, or population and contracts separately for the management of care and/or associated risks. A carve-out allows a unique set of managed care techniques to be applied to a subset of particularly costly or complex benefits. This article describes various carve-out models, discusses the potential advantages and disadvantages of a full carve-out, and summarizes recent public and private sector research regarding the strategy’s effects on access and use, cost savings and shifting, and quality of care. It concludes by discussing approaches to the assessment and monitoring of the processes and outcomes associated with a MH/SA carve-out.