Models Predicting Length of Stay among Government Officials

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Duangkamol Buajumrus
Arnond Sakworawich


This research aimed to study the model predicting length of stay among government officials’ patients with medical benefits by using negative binomial regression. The results found that patient characteristics factors such as age and medical history factors such as length of stay, surgery, medical expenses, hospital level, health and mental health, and comorbidities and complications were related to the length of stay. This model enables hospitals to manage resources and services more efficiently. By using negative binomial regression, the hospitals will be able to predict length of stay based on patient characteristics and medical history to guide the planning of appropriate patient care and discharge. Calculating bed occupancy rate enables hospitals to determine bed capacity for critical care, emergency case and epidemic outbreak as well as to estimate medical expenses. Moreover, the research provides the factors that influence patients’ length of stay.


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