IMPROVING THE NAVY NURSE CORPS’ WARTIME SURGE FORCE PLANNING BY IMPLEMENTING A MARKOV MODEL

Abstract

One of the key components of Navy Medicine is the Navy Nurse Corps (NC). The commitment by the NC to be in sync with the Chief of Naval Operations’ and Commandant of the Marine Corps’ operational plans requires the Nurse Corps community to allocate subspecialties according to the needs of the Navy with the mindset of operational readiness. Under the current system of accession, the NC is meeting its targeted end strength (E/S). At the same time, however, the NC suffers from an imbalance in the management of its quality, the subspecialties (SSP): critical wartime subspecialties are understaffed, while the specialties fulfilling non-operational requirements are overstaffed. This accession practice results in an undersupply of critical SSPs should a contingency arise. This thesis therefore proposes a Markov model to optimize the surge force planning for the NC to maximize the probability that enough personnel will be available in critical SSPs to meet operational needs during a contingency. This model is designed to forecast future E/S and operational surge forces to assess whether they will meet the operational readiness goals from the National Defense Strategy. Based on hypothetical target E/S and beginning inventory, the model demonstrates reliable forecasting capabilities as it satisfied all three assumptions required to build a Markov model, demonstrating an almost identical behavior both by the fixed inventory accession and by the steady state method.