Abstract

Under the background of the unbalanced supply and demand of medical diagnostic equipment and rising health care costs, this study aims to optimize the service scheduling for medical diagnostic equipment so as to improve patient satisfaction by ensuring the equipment utilization rate and hospital revenue. The finite horizon Markov Decision Process (MDP) was adopted to solve this problem. On the basis of field research, we divided patients into four categories: emergency patients, inpatients, appointed outpatients, and the randomly arrived outpatients according to the severity of illness and appointment situations. In the construction of the MDP model, we considered the possibility of cancellation (no-show patients) in scheduling optimization. Combined with the benefits and costs related to patient satisfaction, based on the value iteration algorithm, we took patient satisfaction and hospital revenue as the objective functions. Results indicated that, compared with the current scheduling strategy, the integrated strategy proposed in this study has a better performance, which could maintain the sustainable usage rate of large medical resources and patient satisfaction.

Highlights

  • In recent years, large-scale medical equipment has become an increasingly important tool for hospitals to provide high quality medical services

  • Under the target pursuit of patient satisfaction, according to the Markov Decision Process (MDP) result, we suggest that the optimal strategy of the hospital should be strictly based on the cost of patient satisfaction, and the selection of decision-making actions should be determined according to the sequence of various types of patient satisfaction costs

  • Combined with the actual situations, depending on the classification of patients based on their emergency degrees, according to four different types of patients and the examination facility of magnetic resonance imaging (MRI), a limited time MDP model is put forward for dynamic scheduling

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Summary

Introduction

Large-scale medical equipment has become an increasingly important tool for hospitals to provide high quality medical services. Large-scale medical examination facilities such as positron emission computed tomography (PET-CT), digital subtraction angiography (DSA), nuclear medicine single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI) are important medical resources. The diagnosis and the treatment of the most common illnesses are based on large medical equipment. The purchase and maintenance costs of medical equipment are quite high. Combined with the purchase quota of large medical equipment, it is difficult to meet the patients’ demand in densely populated Shanghai hospitals.

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