Improving resource allocation in the precision medicine Era: a simulation-based approach using R

Abstract

The application of personalized medicine in developing countries is a major challenge, especially for those with poor economic status. A critical factor in improving the application of personalized medicine is the efficient allocation of resources. In healthcare systems, optimizing resource allocation without compromising patient care is paramount. This tutorial employs a simulation-based approach to evaluate the efficiency of bed allocation within a hospital setting. Utilizing a patient arrival model with an exponential distribution, we simulated patient trajectories to examine system bottlenecks, particularly focusing on waiting times. Initial simulations painted a scenario of an ‘unstable’ system, where waiting times and queue lengths surged due to the limited number of available beds. This research offers insights for hospital management on resource optimization leading to improved patient care.

Summary points

• The authors employ a simulation-based approach to evaluate the efficiency of bed allocation within a hospital setting.

• They use a patient arrival model with a customizable distribution to simulate patient trajectories and examine system bottlenecks, focusing particularly on waiting times and queues.

• The initial simulations depict an ‘unstable’ system where waiting times and queue lengths surge due to the limited number of available beds. Then stabilized system is demonstrated after optimizing resource allocation.

• The authors present a hypothetical scenario that simulates the addition of beds in a constrained facility, elucidating how small changes can greatly affect patient waiting times and overall system stability.

• The article provides insights for hospital management on resource optimization leading to improved patient care.

• It highlights the use of discrete event simulation (DES) as a potent tool for conducting thorough process simulations, allowing for a sophisticated representation of complex systems.

• The article emphasizes the fundamental advantage of employing DESs in healthcare decision-making, particularly for understanding, predicting and optimizing complex systems such as patient queues in healthcare facilities.

• It proposes the use of DES as a valuable tool for healthcare decision-makers. DES allows for the creation of computer models that mimic real-world systems, enabling the exploration of various scenarios and their potential outcomes.

• The study demonstrates the utility of DES in analyzing the impact of resource constraints on patient queuing within a healthcare facility.

• This ‘what-if’ scenario analysis empowers hospital administrators to make informed choices based on data-driven insights rather than intuition.

Keywords: :

• Computer Simulation
• Decision Analytic models
• Healthcare Process Improvement
• Precision Medicine
• R Model

Financial disclosure

The authors have no financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.