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Authors: Ricardo Almeida 1 ; Nuno Silva 2 and André Vasconcelos 1

Affiliations: 1 INESC-ID, Instituto Superior Técnico, Lisbon, Portugal ; 2 Grupo Luz Saúde, Learning Health, Lisbon, Portugal

Keyword(s): No-show, Healthcare, Prediction Algorithms, Pre-processing, Machine Learning Techniques.

Abstract: A no-show is when a patient misses a previously scheduled appointment. No-shows cause an impact in the healthcare sector, decreasing efficiency. When a patient misses an appointment the clinic resource are wasted, postpones his or her chance to get treated for a medical condition and denies medical service to another patient. In this research, machine learning techniques are used to find patterns in healthcare data and make no-show predictions. A no-show prediction model is proposed to integrate machine learning techniques into a model that supports the testing of predictions on different datasets. The model is integrated into an online medical appointment booking platform to allow the models and predictions made, to be saved and integrated into a real-time system. Machine learning techniques are tested using three datasets with different characteristics. Through these tests, the model proposed can find the best features, which are similar in every dataset. The results obtained are c ompared to other prediction algorithms and techniques. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Almeida, R.; Silva, N. and Vasconcelos, A. (2021). A Machine Learning Approach for Real Time Prediction of Last Minute Medical Appointments No-shows. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF, ISBN 978-989-758-490-9; ISSN 2184-4305, pages 328-336. DOI: 10.5220/0010221903280336

@conference{healthinf21,
author={Ricardo Almeida. and Nuno Silva. and André Vasconcelos.},
title={A Machine Learning Approach for Real Time Prediction of Last Minute Medical Appointments No-shows},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF,},
year={2021},
pages={328-336},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010221903280336},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - HEALTHINF,
TI - A Machine Learning Approach for Real Time Prediction of Last Minute Medical Appointments No-shows
SN - 978-989-758-490-9
IS - 2184-4305
AU - Almeida, R.
AU - Silva, N.
AU - Vasconcelos, A.
PY - 2021
SP - 328
EP - 336
DO - 10.5220/0010221903280336