Produção Nacional
Revisado por pares
Application of Machine Learning Techniques to Predict a Patient’s No-Show in the Healthcare Sector
2021; Multidisciplinary Digital Publishing Institute; Volume: 14; Issue: 1 Linguagem: Inglês
10.3390/fi14010003
ISSN1999-5903
AutoresLuiz Henrique Salazar, Valderi Reis Quietinho Leithardt, Wemerson Delcio Parreira, Anita Maria da Rocha Fernandes, Jorge Luís Victória Barbosa, Sérgio D. Correia,
Tópico(s)Customer churn and segmentation
ResumoThe health sector faces a series of problems generated by patients who miss their scheduled appointments. The main challenge to this problem is to understand the patient’s profile and predict potential absences. The goal of this work is to explore the main causes that contribute to a patient’s no-show and develop a prediction model able to identify whether the patient will attend their scheduled appointment or not. The study was based on data from clinics that serve the Unified Health System (SUS) at the University of Vale do Itajaí in southern Brazil. The model obtained was tested on a real collected dataset with about 5000 samples. The best model result was performed by the Random Forest classifier. It had the best Recall Rate (0.91) and achieved an ROC curve rate of 0.969. This research was approved and authorized by the Ethics Committee of the University of Vale do Itajaí, under opinion 4270,234, contemplating the General Data Protection Law.
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