Clifford A. Smith

Background: An adequate supply of mental health (MH) professionals is necessary to provide timely access to MH services. Veterans Health Administration (VHA) continues to prioritize the expansion of the MH workforce to meet increasing demand for services. Objective: Validated staffing models are essential to ensure timely access to care, to plan for future demand, to ensure delivery of high-quality care, and to balance the demands of fiscal responsibility and strategic priorities. Design: Longitudinal retrospective cohort of VHA outpatient psychiatry, fiscal years 2016–2021. Participants: Outpatient VHA psychiatrists. Main Measures: Quarterly outpatient staff-to-patient ratios (SPRs), defined as the number of full-time equivalent clinically assigned providers per 1000 veterans receiving outpatient MH care, were calculated. Longitudinal recursive partitioning models were created to identify optimal cut-offs for the outpatient psychiatry SPR associated with success on VHA’s measures of quality, access, and satisfaction. Key Results: Among outpatient psychiatry staff, the root node identified an outpatient SPR of 1.09 for overall performance (p < 0.001). For metrics associated with Population Coverage, a root node identified an SPR of 1.36 (p < 0.001). Metrics associated with continuity of care and satisfaction were associated with a root node of 1.10 and 1.07 (p < 0.001), respectively. In all analyses, the lowest SPRs were associated with the lowest group performance on VHA MH metrics of interest. Conclusions: Establishing validated staffing models associated with high-quality MH care is critical given the national psychiatry shortage and increasing demand for services. Analyses support VHA’s current recommended minimum outpatient psychiatry-specific SPR of 1.22 as a reasonable target to provide high-quality care, access, and satisfaction.

Veterans Health Administration (VHA) continues to expand the mental health (MH) workforce to meet increasing demand for services. In the present study, longitudinal unbiased recursive partitioning models (conditional inference trees) were created to identify optimal cutoffs for outpatient staffing ratios associated with success on VHA's measures of quality, access, and satisfaction. Quarterly Staff-to-Patient Ratios (SPRs), defined as the number of full-time equivalent providers per 1,000 veterans receiving outpatient mental health care, were calculated for 12 quarters from fiscal years 2016-2018. Associations between VHA metrics associated with quality, access, and satisfaction were evaluated in relation to the overall outpatient SPR. The root node identified an overall outpatient SPR of 7.39 as the split for optimal MH performance. Root nodes associated with metrics addressing population coverage, continuity of care, and experience of care identified SPRs of 7.87, 6.81, and 7.42, respectively. In all analyses, the lowest SPRs were associated with the lowest performance on VHA MH metrics, while the highest SPRs were associated with the highest performance. Analyses support VHA's current recommended minimum outpatient SPR of 7.72 as a reasonable target to provide high-quality care, access, and satisfaction. Impact Statement Determination of appropriate mental health staffing is critical to meet quality, cost, and satisfaction expectations. Since 2012, Veterans Health Administration has advocated for a recommended minimum outpatient staffing level. The present study supports ongoing prioritization of mental health staffing to meet ongoing demand increases.

Achieving quality outcomes and cost efficiency within mental health are overarching objectives of the Veterans Health Administration (VHA). The mental health care workforce has long been oriented toward the goal of high quality outcomes; however, cost efficiency has only recently been elevated into this important value equation. With increased demand for access to mental health services within the VHA, leadership sought to advance methods of determining and improving mental health provider productivity. Monitoring of productivity data may also provide data signaling the potential need for additional staffing to keep up with demand for services. This article outlines VHA's development and specification of mental health productivity policy, implementation strategies, and a discussion of challenges and lessons learned for other systems to consider in implementing productivity monitoring.

With the expansion of integrated primary care and the increased focus on fiscal sustainability, it is critical for clinical managers of these innovative systems to have practical methods for measuring administrative outcomes. Administrative outcomes will assist leadership in the development of efficient, streamlined clinics to provide services to the primary care population. Additionally, administrative measures can be utilized to provide information to assist in guiding resource utilization and management decisions. Several administrative outcomes are suggested for integrated primary care managers to consider for application, including: clinic utilization measures, integrated care administrative measures, wait time and access metrics, and productivity monitors. Effective utilization of these measures can help office managers and clinic leadership not only to maximize patient care, but also to enhance essential business operations, which increase the long-term sustainability of integrated primary care programs.