Dynamic capacity allocation in a radiology service considering different types of patients, individual no-show probabilities, and overbooking.

ABSTRACT:

Background

We propose a mathematical model formulated as a finite-horizon Markov Decision Process (MDP) to allocate capacity in a radiology department that serves different types of patients. To the best of our knowledge, this is the first attempt at considering radiology resources with different capacities and individual no-show probabilities of ambulatory patients in an MDP model. To mitigate the negative impacts of no-show, overbooking rules are also investigated.

Methods

The model's main objective is to identify an optimal policy for allocating the available capacity such that waiting, overtime, and penalty costs are minimized. Optimization is carried out using traditional dynamic programming (DP). The model was applied to real data from a radiology department of a large

SUBMITTER: da Silva RBZ 

PROVIDER: S-EPMC8442351 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature