Abstract
Length of stay of hospitalized patients is generally considered to be a significant and critical factor for healthcare policy planning which consequently affects the hospital management plan and resources. Its reliable prediction in the preadmission stage could further assist in identifying abnormality or potential medical risks to trigger additional attention for individual cases. Recently, data mining and machine learning constitute significant tools in the healthcare domain. In this work, we introduce a new decision support software for the accurate prediction of hospitalized patients’ length of stay which incorporates a novel two-level classification algorithm. Our numerical experiments indicate that the proposed algorithm exhibits better classification performance than any examined single learning algorithm. The proposed software was developed to provide assistance to the hospital management and strengthen the service system by offering customized assistance according to patients’ predicted hospitalization time.
Highlights
Nowadays, every healthcare system faces constant pressures to lower operating costs by improving the use of resources while maintaining and even enhancing the quality of service.Successful healthcare resource management is especially indispensable for addressing these seemingly contradictory pressures
We report a series of experiments to evaluate the performance of the proposed two-level classification algorithm against some of the most popular and commonly used classification algorithms
Based on the above discussion, we can conclude that the proposed two-level scheme performs significantly better than any presented single classifier for this specific imbalanced dataset for patients which stayed in the hospital for one and two days; while it exhibits considerably better classification performance for patients who hospitalized for more than two days
Summary
Every healthcare system faces constant pressures to lower operating costs by improving the use of resources while maintaining and even enhancing the quality of service. Successful healthcare resource management is especially indispensable for addressing these seemingly contradictory pressures. The main objective of hospital managers is the administration of facilities, equipment, and labor resources for the establishment of an appropriate planning and organizational structure while at the same time they anticipate expenditure reduction. To this end, several methodologies and techniques have been presented and developed. The major component in these techniques is the accurate prediction of patients’ hospitalization time and the identification of the factors which influence it. Length of Stay (LoS) is usually defined as the duration of a patient hospitalization and is calculated as the difference between the timestamp of a patient discharge and the timestamp of its admission
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