A Predictive and Scalable Capital Investment Risk Model (CIRM) for the Department of Veterans Affairs

Authors

  • James Schreiner
  • Montrel Jackson
  • Michael Ruggieri
  • Christian Sarlitto
  • John Szalankiewicz

DOI:

https://doi.org/10.37266/ISER.2025v12i2.pp95-100

Keywords:

Risk Priority Number, ArcGIS, Risk Criteria

Abstract

The Department of Veterans Affairs (VA), Office of Construction and Facilities Management, is working towards providing a data-driven, risk-informed, capital investment information model to aid VA stakeholders in the allocation of funds and resources across the VA medical facility portfolio. The novel research methodology presented uses ArcGIS to provide a layered risk visual of the country using a unique multi-criteria additive risk model and compares the risk score against veteran satisfaction and facility condition assessments to understand the investment trade space. This output is the distinctive Capital Investment Risk Model (CIRM). Three main risk factors behind a county specific risk priority number metric include environmental risk, veteran demand, and resource allocations. The findings include insights into how the VA enterprise, and regional VA leaders might consider the next fiscal investment, understand its sensitivity, and predict future trends in the risk profile of each healthcare provider’s ability to serve its veterans.

References

Amaral, Ernesto F. L., Pollard, Michael S., Mendelsohn, Johnson, & Cefalu, Matthew. (2018) “Current and Future Demographics of the Veteran Population, 2014–2024.” Population Review, vol. 57, no. 1, https://doi.org/10.1353/prv.2018.0002.

Cowper, D. C., Longino, C. F., Kubal, J. D., Manheim, L. M., Dienstfrey, S. J., & Palmer, J. M. (2000). The retirement migration of U.S. veterans, 1960, 1970, 1980, and 1990. Journal of Applied Gerontology, 19(2), 123–137. https://doi.org/10.1177/073346480001900201

ChatGPT. Assistance given to the author, AI. ChatGPT aided in review to make sure it was clear and concise and was not repetitive, making sure it was in a scholarly tone. All content and analysis is original. West Point, NY, 11OCT2024.

Driscoll, P. J., Parnell, G. S., & Henderson, D. L. (2022). Decision Making in Systems Engineering and Management . Wiley.

McDonough, Denis. “United States Department of Veteran’s Affairs Climate Action Plan; August 2021.” U.S. Department of Veterans Affairs. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.sustainability.gov/pdfs/va-2021-cap.pdf.

U.S. Department of Veterans Affairs. About the department - U.S. Department of Veterans Affairs. https://department.va.gov/about/.

Published

2025-05-12

How to Cite

Schreiner, J., Jackson, M., Ruggieri, M., Sarlitto, C., & Szalankiewicz, J. (2025). A Predictive and Scalable Capital Investment Risk Model (CIRM) for the Department of Veterans Affairs. Industrial and Systems Engineering Review, 12(2), 95-100. https://doi.org/10.37266/ISER.2025v12i2.pp95-100