A Process Improvement Study on a Military System of Clinics to Manage Patient Demand and Resource Utilization Using Discrete-Event Simulation, Sensitivity Analysis, and Cost-Benefit Analysis

Abstract

Inefficiencies in the healthcare system are a growing concern. Long wait-times are a concern at military clinics because it takes servicemembers away from performing their duties. Managing wait-times are particularly challenging due to frequent relocations of servicemembers and variable patient demands that are less likely to be experienced by civilian clinics. Military clinics must be capable to meet increasing demand when servicemembers require a Deployment Health Assessment; it also needs to be capable of handling an instantaneous surge of walk-ins when a medical incident occurs in the local area. It must be able to meet these demands in a fiscally austere environment. Existing research primarily focuses on stand-alone clinics, whereas this research takes a novel approach of examining a system of clinics, in which some resources are shared. This research evaluates the impacts of variable staffing levels on total wait-time for the system of clinics at baseline demand and when demand increases, using discrete-event simulation, sensitivity analysis, and cost-benefit analysis. This research finds misallocated resources; the wait-time of alternative systems are sensitive to deployment and medical incident demands; and hiring an optometrist while removing an occupational medicine doctor provides the highest savings in baseline, deployment, and medical incident demand environments.

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Document Details

Document Type
Technical Report
Publication Date
Mar 12, 2015
Accession Number
ADA615410

Entities

People

  • Michael Q. Corpuz

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Air Force
  • Cost Benefit Analysis
  • Cost Effectiveness
  • Delivery Of Health Care
  • Health
  • Health Care
  • Health Services
  • Hospitals
  • Literature Surveys
  • Medical Personnel
  • Military Personnel
  • Occupational Medicine
  • Patient Care
  • Simulations
  • Statistical Analysis
  • Systems Engineering
  • United States

Readers

  • Computational Modeling and Simulation
  • Economics
  • Medical or Health Care Field.