Collaborative-care management (CCM) is an evidence-based practice that involves a multidisciplinary depression care team (e.g
., primary care providers, nurse care managers, pharmacists, psychologists, psychiatrists) providing guideline-concordant depression treatment in the primary care setting. Numerous effectiveness studies have demonstrated that CCM improves outcomes for primary care patients treated for depression [1
]. The CCM model has been rolled out nationally in the United States by the Department of Veterans Affairs (VA) Medical Centers as part of the Primary Care/Mental Health Integration Initiative [11
More recently, the VA has encouraged the implementation of CCM in its Community Based Outpatient Clinics (CBOCs), where 64% of veterans receive their care [12
], and mandated implementation in those categorized as large (5,000-10,000 patients) and very large (> 10,000 patients). Veterans treated at CBOCs have similar demographic characteristics as veterans treated at VA Medical Centers (VAMCs) [13
]. All CBOCs provide primary care services, and most large and very large CBOCs also provide specialty mental health services. However, veterans treated in CBOCs have significantly fewer mental health visits than do veterans treated at VAMCs [14
]. Twenty-six percent of CBOCs are private clinical organizations contracting with the VA to provide primary care services to veterans [12
]. Veterans treated in contract CBOCs have significantly fewer mental health visits than do veterans treated in VA-staffed (i.e
., owned and operated) CBOCs [15
]. While CCM could potentially address this disparity, there are numerous barriers to implementing a complex clinical program like CCM in small contract CBOCs.
The organizational characteristics of contract CBOCs present added challenges to the implementation of CCM. For example, contract CBOCs receive capitated payments (a fixed amount per enrollee to cover a defined scope of services) from the VA and, thus, must consider the financial risk associated with depression quality-improvement efforts. As a result, contract CBOCs may be less willing to comply with VA quality-improvement initiatives compared to VA-staffed clinics, unless these initiatives are embedded into their legal contracts. In addition, the majority of contract CBOCs do not have on-site psychiatrists, and because half of contract CBOCs are located in rural areas, [16
] recruiting psychiatrists to small contract CBOCs is typically not feasible. A previous randomized trial documented that the CCM model can be adapted using telemedicine technologies to effectively improve outcomes for patients treated in CBOCs without on-site psychiatrists [17
]. While there is good evidence that telemedicine-based CCM improves outcomes in contract CBOCs, no implementation strategy is known to be effective for this type of organizational context.
The overall goal of our research was to facilitate the adoption of telemedicine-based CCM in contract CBOCs. The Promoting Action on Research in Health Services (PARiHS) framework proposes that successful adoption of an evidence-based practice depends on (1) evidence, (2) context, and (3) facilitation [18
]. Evidence includes results from randomized trials, as well as anecdotal evidence from clinical experience [19
]. Context includes both factors internal to the organization, such as culture, climate, and capacity, [21
] as well as external forces, such as mandates and performance measures. Facilitation typically involves an integrated set of implementation strategies to promote adoption. In this study, we used a facilitation method known as evidence-based quality improvement (EBQI). EBQI has been used successfully to implement CCM in VA Medical Centers [30
]. Our specific objective was to test the feasibility of EBQI as an implementation strategy for telemedicine-based CCM in contract CBOCs. Results should inform efforts to roll out complex evidence-based practices to small satellite clinics of integrated healthcare systems.
EBQI was developed by Rubenstein and colleagues based on the findings of the Mental Health Awareness Project, which compared two quality-improvement strategies for depression in primary care [31
]. Clinics were randomized to either a top-down centralized quality-improvement model or a bottom-up locally driven quality-improvement model [32
] The top-down approach involved centralized experts implementing depression evidence-based practices, with some input from local primary care staff. The bottom-up approach involved local clinical staff implementing depression evidence-based practices, with some input from experts. The bottom-up quality-improvement teams had both the best and worst outcomes in terms of fidelity to the evidence base [32
]. This finding suggests that the bottom-up approach has the best potential for quality improvement but is subject to substantial variation depending on local climate, culture, and capacity [32
]. These findings are consistent with two well-designed implementation studies that found that traditional continuous quality-improvement models do not improve depression outcomes [33
]. Qualitative analyses of the Mental Health Awareness Project also indicated that the top-down approach was more efficient, but the project failed to attain buy-in from local clinicians and administrators [35
]. In contrast, the bottom-up quality-improvement approach promoted customization and buy-in but was perceived to be overly time-consuming and inefficient (e.g
., reinventing the wheel) [35
]. Based on these findings, the EBQI model was developed, which involves both centralized strategic
decision making and local tactical
decision making [35
]. There is a growing consensus among implementation experts [36
] and frontline clinicians and managers [32
] that quality-improvement strategies that incorporate both top-down and bottom-up approaches hold the most promise for sustained implementation of evidence-based practices.
In EBQI, both researchers (clinical experts, implementation experts) and local staff participate fully in the quality-improvement process, with the researchers facilitating rather than dictating implementation efforts [32
]. Thus, EBQI is intended to foster a researcher/clinician partnership that promotes buy-in from leadership [40
]. Lack of support from leadership has been shown to be one of the most important barriers to the implementation of the CCM [42
]. While emphasizing the involvement of outside experts and empirical evidence, EBQI stresses that an organization's own healthcare professionals and staff are best positioned to improve their systems [40
]. Clinicians and administrators contribute the local knowledge needed to tailor the evidence-based practice for their own particular needs and organizational capabilities. Researchers contribute knowledge of the evidence base; ensure fidelity to the evidence base; and supply materials, procedures, and tools needed for successful implementation. In addition to providing expertise, researchers in the EBQI model also facilitate problem solving and provide ongoing technical support for developing data collection/analysis tools, informatics, and training materials. EBQI also emphasizes continuously revising the adapted evidence-based practice based on feedback during Plan-Do-Study-Act cycles and, thus, should lead to adapted evidence-based practices that are robust, user friendly, and feasible to deploy in real-world practice settings. The primary objective of this research was to test the feasibility of EBQI as a facilitation strategy for implementing telemedicine-based CCM in contract CBOCs.