Design of a payment decision support tool for Coordinated Specialty Care for Early Psychosis

Abstract

Strengthening evidence base and earmarked federal funding has spurred implementation of Coordinated Specialty Care (CSC) for people experiencing early psychosis. However, existing funding mechanisms are insufficient and unsustainable to support population deployment of CSC. This paper describes the design framework of an innovative payment model for CSC that includes a bundled case rate payment and an optional outcome-based payment. To assist CSC payer and provider organizations in designing payment systems tailored to local preferences and circumstances, the research team is developing a decision-support tool that allows users to define design choices and provide inputs. This paper documents the analytical algorithms underlying the tool and discusses ways by which the tool could be further developed or expanded for CSC and other behavioral health interventions that feature an interdisciplinary team of clinicians and non-clinical professionals, public education and outreach, patient-centeredness, and a recovery orientation.

Coordinated Specialty Care (CSC) consists of a set of evidence-based treatment practices for people experiencing early stages of psychosis (1). CSC is delivered by a multidisciplinary team of clinicians and non-clinical specialists, based on the principles of shared decision making, and aimed at maximizing recovery, including improving functioning and managing psychiatric symptoms. Community outreach is an integral component given the program’s emphasis on reaching individuals in the early phases of their illness. Implementation of CSC in the U.S. gained momentum following the research initiative at the National Institute of Mental Health known as RAISE (Recovery After an Initial Schizophrenia Episode). In particular, the RAISE-Early Treatment Program (ETP) study, a cluster-randomized trial involving 34 clinics in 21 states found CSC to be associated with greater improvement in quality of life and psychopathology, and, greater involvement in work and school by individuals experiencing first episode psychosis (2). The RAISE-Implementation and Evaluation Study (IES) (3), an implementation study, demonstrated feasibility of delivering CSC in community mental health center settings and developed tools and materials to support future implementation. Probably more importantly, CSC Implementation was also spurred by the earmarking of the Federal Mental Health Block Grant (MHBG) funding (“set-aside”) to states to implement intervention programs for individuals with early serious mental illness such as psychosis. Such set-aside funding amounted to 5% of MHBG in the initial rollout in 2014 and was doubled to 10% in 2015. By late 2017, an environmental scan conducted by the National Association of State Mental Health Program Directors (4) identified a total of 248 program sites of early intervention programs nation-wide that received MHBG funding.

Despite rapid dissemination of CSC, it has become apparent that existing funding mechanisms are not sufficient or sustainable for population deployment of CSC. Under the MHBG set-aside, state mental health authorities typically directed CSC provider organizations to bill Medicaid and commercial insurance for ongoing service delivery whenever possible. However, existing fee-for-service insurance billing opportunities are seriously misaligned with CSC in at least four ways. First, many services that are essential to the recovery orientation of CSC (e.g., supported employment and education and peer specialist services) are typically not covered by insurance (except through the Medicaid Home and Community Based Services provision in the Affordable Care Act) (5). Second, for CSC services with existing insurance coverage, e.g., medication management and psychotherapy, the prevailing payment rates are usually too low to support the intensive service needs of people receiving CSC. Third, activities that are not directed at individual clients but integral and essential to the operation of a CSC team (e.g., community outreach and education, team operation, staff supervision and training) are not billable (6). Fourth, fee-for-service billing, known to have strong incentives for volume rather than outcomes of care, may be especially detrimental to CSC because it discourages tailored and innovative service delivery (and thus increasing client dependence on the system rather than promoting independence). It also discourages investment in team building, public education and outreach, and client and family engagement, all of which are integral components of CSC.

Although CSC teams around the country continue to employ a patchwork approach to financing, (6, 7) there is emerging consensus in support of a payment model that bundles and comprehensively covers the entire package of CSC services (6, 8). Of note, the Medicaid Accountable Care Organization of Marion County, Oregon established a per-member-per-month bundled case rate for CSC in 2016. Another more recent example are CSC programs in Philadelphia, which now receive a case-rate payment from the local coordinating organization of Medicaid behavioral health benefits. In addition, CSC programs in several states (e.g., Maine and Illinois) are in discussion with Medicaid and/or commercial payers for possible adoption of a case rate payment; at least two CSC programs in two different states (New York and Oregon) currently leverage the bundled, prospective payment of the federal Certified Community Behavioral Health Center (CCBHC) demonstration to cover the costs of their programs (9). CSC programs varied in terms of the specific treatment models adopted, services provided, and the credentials, time, and cost of time of professionals that make up the team (4), making it necessary that payers and provider organizations conduct local and collaborative decision-making regarding a case rate payment. CSC teams are overwhelmingly community-based behavioral health provider organizations and typically have limited resources or experience in payment contracting with insurance entities. On the other hand, since CSC is a new treatment approach, payers may need assistance determining the specific design of the payment including payment rates.

This study aims to develop an interactive tool to support collaborative decision-making by payers and CSC providers. We document below the design framework of our tool and the analytical algorithms developed to calculate payment rate(s) given user choices and inputs. We discuss ways in which the tool can be further developed or customized to support payment and financial planning needs for CSC. Finally, we discuss caveats users should bear in mind when interpreting results from the decision-making tool.

Methods

Design Framework

Frank et al. (2014) proposed a multi-part payment model for CSC that contains a bundled case rate payment (covering case identification, client engagement and retention), a per-service component (covering CSC services delivered to specific clients post-enrollment), and an outcome-based payment that is financed by withholding a portion of the per-service payment (to mitigate perverse incentives associated with the per-service payment) and rewards CSC provider teams for achieving pre-specified outcome targets.

To facilitate payment decision-making reflecting local preferences, existing payment mechanisms, and CSC service delivery, we adapted the Frank et al. framework in the following ways. First, we make the bundled case rate payment a “must-have” component but allow decision-makers to decide what types of CSC services should be bundled and covered under the case-rate payment. This design reflects the general consensus that a bundled payment is aligned with CSC implementation, but also affords the flexibility to local stakeholders to tap into existing payment mechanisms for selected CSC services (e.g., services delivered by licensed clinicians that are usually most readily reimbursable) if so desired. A common issue with CSC financing is that supported employment and education, peer specialist services, and other services provided by non-clinicians or non-licensed providers cannot be billed to insurance with existing payment mechanisms and rules. By allowing decision-makers to bundle these services into the case rate, our payment model may maximize the chances that these non-clinical services be covered in CSC (10).

Second, we make outcome-based payment an optional component, to allow for stakeholder flexibility in deciding whether and when to start holding provider organizations accountable for client outcomes. In the early stage of CSC implementation, priorities of many provider teams are team-building, community outreach to establish robust referral sources, and team workflow. It might make more sense to institute an outcome-based payment at a later phase. In addition, in our model, the outcome-based payment is financed by withholding a portion of the case rate payment (details below) and is paid out for each client that achieves a pre-specified outcome in a given reporting period. This is in contrast with the common “all-or-nothing” approach in which providers receive the incentive payment only if a measured outcome of the entire patient panel crosses a threshold (11). The “all-or-nothing” approach provides little incentives for incremental improvement for providers whose performance is either way below the threshold or above the threshold. In addition, with the small panel size in CSC (typically below 50), mean outcome measures of the panel have low reliability and therefore subject provider teams to substantial risks.

Third, our design framework lets the local payers and providers decide on sources of financing of services not covered under the bundled payment, thus making a hybrid model possible. A figure online in supplement 4 illustrates our framework.

CSC Payment Design Choices

As shown in the supplement 4 online, within each component of the payment model, we specify design choices that allow decision-makers to tailor their payment models to local preferences and circumstances. The only choice for the case-rate payment is the type or types of CSC services covered by this component. We followed a study conducted in New York State (12) and grouped all services into four categories: 1) clinical services directly involving a client (or his/her family members) in an individual or group setting and typically provided by licensed clinicians, 2) supported employment and education services and peer-specialist services directly involving or directed at a client and provided by non-clinician specialists, 3) care or case management services involving or tied to a specific client including care coordination with the client’s non-CSC providers, and, 4) administrative and team operational tasks, which may or may not be tied to specific clients and include scheduling, documentation, community outreach and education, staff training and supervision, and other ongoing tasks to support the operation of the team. This grouping reflects differential availability of existing payment mechanisms, with “clinical services” associated with greatest availability, two middle groups associated with rare but some emerging payment mechanisms (e.g., the Medicaid Home and Community Based Services (5) and Health Homes (13) provisions), and the “administrative and operational tasks” associated with almost no systematic, insurance-based payment. By allowing users to select among the four types of CSC services, we afford decision-makers the flexibility of combining existing payment mechanisms with the case rate payment to support CSC.

Under outcome-based payment, we provide two design choices. One is concerned with the outcome measures that CSC teams will report on and be held accountable for. The three outcomes indicated in the figure in the online supplement (supplement 4) reflect important recovery-oriented goals of CSC but are not exhaustive of all client outcomes that may be deemed important by local decision-makers, for example, achievement of independent living. The second design choice under outcome-based payment concerns the amount of funds available for outcome-based payment, operationalized as a % of the total case rate payment. This “withhold” approach arguably provides stronger incentives for achieving a given outcome target, a behavioral economics principle known as “loss aversion” (13). An additional advantage, from the perspective of the payer, is that it sets a cap on the total payment (case rate and outcome-based payment) and thus eases budget planning. However, CSC provider stakeholders will likely perceive such a design as penalizing since, as long as their performance is not perfect, they would receive a lower payment compared to if outcome-based payment were not adopted. To better align incentives, we incorporate a larger mark-up for the case rate payment if an outcome-based payment is selected, as detailed below.

Key Premise: Cost-based payment rate

A major premise underlying the payment design is: the case rate payment needs to reflect the costs of delivering evidence-based CSC. Thus, to estimate the case rate payment, the first step is to estimate the costs of CSC service delivery and team operation. Because the make-up of the CSC team (in terms of roles and professional credentials of personnel for each role) and the costs of staffing the team may vary significantly, the payment design tool needs to collect data on these local information to support tailored payment rate. Supplement 1 is a screenshot from our tool that solicits such information from the user. In addition, the tool collects data on the (average) fringe benefit rate and indirect cost rate that will be applied to the direct costs of staffing the team to derive total costs. Our tool then calculates the costs of delivering the CSC services to be covered by the case rate.

Analytical Algorithms

For each client engaged in a payment period (e.g., a month in a per-client-per-month or PCPM case rate), a fixed or flat case rate is calculated by first estimating the cost of operating/staffing the CSC team to deliver CSC services covered by the case rate, and then dividing by the number of clients receiving services (CSC team caseload):$PCPM=\frac{\left({\sum }_j{w}_j\ast FT{E}_j\right)\ast S\ast m}{CSC\hspace{0.33em}Caseload}$, where j indexes the types of professionals (by credential) that make up the team, and w_j is the wage rate of Credential j. S stands for the share of the total operating costs of the CSC team accounted for by the types of services to be covered under the case rate payment; S needs to be empirically estimated. Supplement 2 describes our data source and approaches undertaken to estimate the shares of total costs accounted for by different types of CSC services. m is a mark-up factor (e.g., 1.10) that we apply to the cost estimate to provide a small margin to account for CSC-related costs not captured by the estimated costs of staffing the team.

As described above, if the decision-makers choose to include an outcome-based payment, they also decide on a proportion of total case rate payment that is “withheld” and made available for outcome-based payment. For each client that achieves an outcome target (e.g., no psychiatric hospitalization or ED visit during a reporting period), the provider team is expected to receive the following payment:$R_O=\frac{Total\hspace{0.33em}outcome\hspace{0.33em}\$}{n_o\ast N_o}$, where n_o is the number of outcome targets selected and N_o is the number of clients eligible for outcome-based payment over a given reporting period. N_o is usually smaller than the team caseload because stakeholders may decide to exclude clients that are newly enrolled in the program (e.g., within the first 3 months) in determining outcome-based payment since the provider team have had limited time to influence the outcomes of these clients. Our tool then estimates the total outcome-based payment a provider team are expected to receive over a reporting period by generating a panel of simulated clients and their outcomes. Supplement 3 describes our data source and approaches to estimating total outcome-based payment received by a team over 12 months.

Supplement 4 presents two scenarios of payment design and estimates payments based on the analytical algorithms outlined above. The two scenarios differ in terms of the types of CSC services covered under the case rate payment but are identical otherwise. As shown, the PCPM payment rate was estimated to be $1,619/month if all four types of CSC services were covered under the case rate payment and $802/month if the case rate payment were to cover all but “clinical services”.

User testing

For our tool to support real-world payment decisions, it must be suited to the needs of the target user groups and perceived as intuitive and easy to use (14, 15). Therefore, as part of the development process, we have been conducting user-centered design sessions with key informants from the payer and provider communities, using a prototype of the tool. In several cases, these interviews have also informed important decisions about the algorithm. For example, interviews with CSC provider teams indicated that resource intensity in CSC service delivery often does not present the type of regularity as seen in collaborative care (16): once enrolled, it might take months to fully engage clients into CSC. In addition, as is typical in psychosis, clients may experience “ups and downs” throughout their tenure in the program and require changing intensity of services. This qualitative input helped us decide against a variable case rate reflecting a dichotomy between acute vs. maintenance phases of services. In the next phase of tool development, we plan to conduct user testing by engaging payer and provider partners in the same testing session to specifically assess the utility and feasibility of the tool to facilitate stakeholder collaboration.

Discussion

This paper describes the design framework of a payment model for Coordinated Specialty Care and documents the analytical algorithms underlying a decision-support tool for CSC payment design. This tool answers to the need to tailor payment design to local circumstances and preferences. Meanwhile, in this beta version of the tool, we deliberately limited the number of scenarios and options to facilitate user adoption. We thus anticipate tool development to be an ongoing and iterative process.

We propose several ways by which the payment design and the tool could be further developed. First, there might be a need for multiple case rate payments to fully support CSC. Before clients formally enroll in CSC, teams usually spend substantial staff time engaging prospective clients and families, suggesting a potential need for a one-time payment for the engagement phase of a client, who may or may not ultimately enroll in CSC (Personal communication with Vinod Srihari). In addition, there may be a need for a case rate payment for ongoing but often less intensive care after the initial 2-year CSC (often referred to as a “step-down” phase) as CSC teams and their clients develop rapport and a mutual desire to continue the clinical relationship. Another emerging need is regarding clients not yet diagnosed with psychosis but presenting signs and symptoms indicating high risk for psychosis, often referred to as the “clinical high risk” group. A number of teams around the country operate programs for the clinical high risk clients in parallel with their CSC programs and have relied on either insurance billing or grants (17) to support the program. The tool we have developed for CSC can be readily adapted to meet decision-making needs for these additional payments.

Second, depending on local preferences and feasibility of outcome measurement and reporting, our tool can be adjusted to incorporate a different choice set of CSC outcomes than proposed in the current tool, as long as data on the joint distributions of these outcomes exist to support the simulation. While the current tool divides total funding available for outcome-based payment equally among selected outcomes (thus effectively assigning the same weight to all outcomes), the tool can be adjusted to assign varying weights to outcomes based on consensus reached out of local stakeholder discussion.

Several features of the tool conveys fairness and transparency to facilitate shared decision-making. Examples include the cost-based approach of calculating the case rate and the upward adjustment of case rate payment when an outcome-based payment is included, thus subjecting provider teams to payment risks. On the other hand, we tried to limit risks to payers by adopting a withhold approach in defining the outcome-based payment. More importantly, the tool operationalizes the payment design around design choices and user inputs so that payer and provider partners could collaboratively alter design choices (e.g., outcomes to be incentivized) and/or inputs (e.g., make-up of the CSC team) and compare resulting payments. While the idea of conducting “what if” exercises presents strong face validity and is endorsed by (the small number of) payers and provider teams we spoke with, it remains to be empirically tested via user tests that simultaneously engage payer and provider partners.

Our tool does not support all aspects of the decision to design and operationalize a payment model. Specifically, conditions by which provider teams receive the case rate payments are left undefined and out of the scope of this tool. These conditions may include program certification and structural requirements, e.g., provision of key components of CSC, and, client-level requirements, e.g., eligibility criteria for enrollment and continued services (8) and a clear and operational definition of engagement in CSC in a given month to receive the PCPM case rate. They may also include ongoing program fidelity and patient outcome monitoring, and, in the case that an outcome-based payment is adopted, operational definitions of outcome targets (in terms of denominator, numerator, reporting period, etc.) and processes of reporting. The tool also does not make any assumption about how the CSC team should be staffed but rather assumes that would be an outcome of discussion among key stakeholders such as CSC payers, providers, and regulating and credentialing agencies. Given the low incidence of early psychosis relative to other common mental health conditions and the intensive resource requirements of CSC, policy-makers and mental health administrators need to conduct planning to determine the number and geographic distribution of CSC teams. Existing tools can be tapped to support such decisions (18).

There are several limitations pertaining to the underlying algorithms of the tool. First, several key parameters, namely, allocation of total team operation costs to different types of CSC services and the joint distributions of CSC outcomes, were derived based on data from New York State’s CSC implementation known as OnTrackNY (www.ontrackny.org) (Supplements 2 and 3). Systematic and coordinated efforts in New York ensured high quality of the OnTrackNY data, which reflect the experience of a large number of teams (23 as of January, 2020) with diverse geographic locations and patient populations. Nevertheless, they may not generalize to experience of CSC programs in other parts of the country. To the extent that data reflecting local CSC experience are available, they can be integrated into the current tool to better support local decision-making. Second, although our algorithms tried to take into account staff time on community outreach and team operation that is not tied to a specific client (Supplement 2), lack of empirical data in this area may have led to underestimation of the proportion of total costs devoted to these activities. More systematic data collection on those costs will inform future refinement of the tool.

To sustain implementation of CSC in the context of competing priorities of mental health programs, many critical questions remain, including the ultimate effectiveness of CSC models, the scope of services necessary to achieve an impact, and funding sources to support its ongoing implementation. The tool and approach outlined in this report do not directly answer these questions but are meant to support decisions in allocating limited resources.

Implications of our work may go far beyond payment for CSC. Many behavioral health interventions are team-based, require substantial public education and outreach, employ patient centeredness and therefore tailored interventions, and are recovery-oriented. The design framework and the analytical approaches we describe here can be readily adapted to support payment innovations for these programs. Furthermore, with its flexibility and expandability, our payment design framework points to a future research agenda: payment designs with different design choices (e.g., a case rate covering all vs. some of the services) or with varying complexity (e.g., two case rate payments to cover two phases of treatment vs. a single case rate) can be tested in experimental or quasi-experimental set-ups. Process- (e.g., intervention fidelity) and patient outcomes can be compared across different designs to provide inferences.

Figure 1.

Components and design choices of the CSC payment system

Highlights:

• Existing funding mechanisms are insufficient and unsustainable to support population deployment of Coordinated Specialty Care (CSC) and misaligned with its interdisciplinary approach, emphasis on public education and outreach, patient-centeredness, and recovery orientation.

• A framework proposed for CSC payment design includes a bundled case rate payment to cover the costs of all or selected types of CSC services and an optional outcome-based payment that provides incentives for and encourages innovation for achieving CSC outcomes.

• A decision support tool under development operationalizes CSC payment design with design choices and user inputs, thus enabling collaboration of payer and provider organizations and tailoring of payment design to local circumstances.