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International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749 . Open Access


Machine Learning for Prediction of Clinical Appointment No-Shows

Machine Learning for Prediction of Clinical Appointment No-Shows

Jeffin Joseph
Department of Management, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India.

S. Senith
Department of Management, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India.

A. Alfred Kirubaraj
Department of Electronics and Communication, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India.

S. R. Jino Ramson
Saveetha School of Engineering, Tamil Nadu, India.

DOI https://doi.org/10.33889/IJMEMS.2022.7.4.036

Received on December 16, 2021
  ;
Accepted on June 06, 2022

Abstract

A no-show occurs when patient misses his appointment for visiting doctor in an outpatient clinic. No-shows result in inefficiencies in scheduling, capacity wastage and discontinuity in care. The study aims to develop and compare different models for predicting appointment no-shows in a hospital. The no-show estimation was made using five algorithms including Logistic Regression, Decision Tree Classifier, Random Forest, Linear Support Vector Machine and Gradient Boosting. The performance of each model is measured in terms of accuracy, specificity, precision, recall and F measure. The receiver operating characteristic curve and the precision-recall curve are obtained as further performance indicators. The result shows gradient boosting is more evident in giving consistent performance. The categorical variables used for prediction are gender, mapped age, appointment type, previous no-shows, number of previous no-shows, appointment weekday, waiting interval days, scholarship, hypertension, diabetes, alcoholism, handicap and SMS received.

Keywords- Healthcare, Machine learning, Patient no-shows, Hospital management, Predictive analytics.

Citation

Joseph, J., Senith, S., Kirubaraj, A. A., & Ramson, S. R. J. (2022). Machine Learning for Prediction of Clinical Appointment No-Shows. International Journal of Mathematical, Engineering and Management Sciences, 7(4), 558-574. https://doi.org/10.33889/IJMEMS.2022.7.4.036.