Vhance Valencia

Simulation-Based Evaluation of the Effects of Patient Load on Mental Workload of Healthcare Staff

Introduction In parts of Ohio, Veterans Affairs Medical Centers are working to handle patient load issues by sending patient overflows to the Wright-Patterson Medical Center. The Wright-Patterson Medical Center will benefit from the increase in patients; however, there are concerns that the patient quality of care may suffer. If the increase in patients results in the healthcare staff experiencing high mental workload levels, staff performance could be reduced. The objective of this research is to evaluate the influence of patient load on the mental workload of staff in an inpatient unit at the Wright-Patterson Medical Center. Methods This research uses discrete-event simulation to quantitatively model the mental workload of healthcare staff in an inpatient unit of the Wright-Patterson Medical Center. The model was used to find the idle time, average workload, and overload time of healthcare staff under current and future patient loads. In addition, the performance of individual tasks was evaluated. Results The results of this research find a linear relationship between patient load and three workload metrics (idle time, average workload, and overload time) with each worsening as patient load increases. Nurses and technicians experience the greatest negative impacts to mental workload as patient load increases with those staff members who have the most workload at the baseline condition experiencing greater increase in workload as patient load increases. In addition, the time spent in an overload state increases disproportionately with patient load increases, with overload time increases being worse for urgent tasks than for nonurgent tasks. Conclusions Based on this study, the researchers found that the modeled inpatient unit can safely handle the expected patient load increases. The study provides the unit with information to proactively prepare and reduce healthcare staff overloading.

Infrastructure Decay Modeling With the Input-Output Inoperability Model

Asset management and infrastructure interdependency concepts are found to be useful in the study of infrastructure decay. As such, infrastructure decay is modeled with the input-output inoperabilit...

Medical readiness: evaluating the robustness of medical clinic staffing solutions

Medical readiness requires Department of Defense medical clinics to be robust to changes in patient demand. Minor fluctuations in patient demand occur on a regular basis, but major increases can also occur. Major demand increases can result from a number of occurrences, including mass military deployments, medical incidents, outbreaks, and overflow from Veterans’ Affairs clinics. This research evaluates a system of clinics at Wright-Patterson Air Force Base in order to determine its ability to handle a 200% surge in patient demand. In addition, this study evaluates the relative effectiveness of six different staffing mix options to minimize patient wait times, also under the surge demand conditions. This evaluation is conducted using discrete-event simulation to estimate patient wait times and includes a sensitivity analysis of the increased patient demand, as well as a cost–benefit analysis to determine the most cost-effective alternative scenario. The study finds that adjustments to staffing mix enable cost savings while meeting current demands. In addition, the study finds that adjusting the staffing mix will not have a negative impact on patient wait time in the surge conditions, relative to the current staffing mix.

Probabilistic Assessment of Failure for United States Air Force Building Systems

AbstractDeteriorating and failing federal facilities represent a significant cost to the U.S. government. In maintaining these assets, the United States Air Force currently uses a facility data sys...

User-Centered Design Applied to USAF Civil Engineering Explosive Ordnance Disposal Tools and Jigs

This research employed a user-centered design process to examine the application of additive manufacturing (AM) to fabricate tools and jigs in USAF civil engineering (CE) operations. Within this research, numerous parts were designed and printed for use within CE operations, rapidly evolving the design based upon user feedback. The results of the part testing and the resultant surveys indicate that AM can impact the daily operations of a CE unit, improving operational effectiveness. Further, the research determined that AM has reached a point that the integration of AM into strategically coordinated units, along with proper education and training, can be beneficial for the CE career field. However, this research raises questions regarding the dissemination and rapid adoption of successful designs across DoD operations, without creating burdensome evaluation methods or proliferating an overwhelming number of less than ideal designs.