Workforce Planning for Embedded Mental Health Care in the U.S. Navy

Abstract

Abstract Introduction Embedding mental health providers directly into operational units provides opportunities for holistic individual and population focused mental health support. To effectively provide clinical mental health care to a large number of Sailors and Marines while supporting the larger command, it is crucial to arrive at an optimal number of mental health (MH) care staff. In response to an increasing demand for MH care by operational units distributed globally, the U.S. Navy (USN) critically analyzed the current MH staffing levels, estimated future demand for MH care providers, and evaluated several staffing options. The following article illustrates a case study of workforce planning for the USN’s embedded MH delivery model. Materials and methods Several existing data sources were used to calculate current number of MH care staff across all USN platforms and to estimate demand for MH care. An open source Linear Programming application was used to estimate staffing solutions that meet business requirements in the most efficient manner possible. Results Results suggested different conclusions for embedded mental health staffing across USN communities. Depending on existing staffing levels and the number of Sailors or Marines anticipated to require care, the Linear Programming algorithm estimated needed staffing levels to address demand. Conclusion The current project represents the first systematic workforce planning initiative designed to help staff the USN’s global demand for community focused MH care. The results of this project have identified areas where additional embedded mental health resources should be made available. By systematically documenting all services and capabilities and carefully examining the operational demands of each community, the current solution was able to identify precisely what type of MH resources should be allocated to a given community.