A Predictive Approach for Healthcare Expenditure Using Ensemble Techniques

Syed Musharaf, Sripathi Srujan Kumar, B Maruthi Reddy, Bidyutlata Sahoo

2025

Abstract

Accurate estimates of healthcare expenses are necessary due to the rising cost of healthcare brought on by the advent of new viruses and other health issues. These forecasts are essential for individuals and insurance providers to make educated decisions and plan for future medical requirements. Because of the exponential expansion of data and the complexity of computations involved, traditional methods of evaluating health insurance prices have become increasingly insufficient and frequently inaccurate. The objectives of this research are to determine the most accurate ensemble technique for forecasting changes in healthcare spending, assess the effectiveness of ensemble approaches in comparison to traditional models, and help prospective purchasers of medical insurance choose plans that best suit their individual requirements.Through rigorous experimentation and analysis, several regression algorithms, including KNN Regressor, Linear Regressor, Random Forest, Decision Tree, and XGB Regressor, were assessed for their predictive performance. Among these, the most successful performance was XGB Regressor, with an astounding accuracy of 89.7%. This result highlights the algorithm's robustness and effectiveness in handling the complexity inherent in healthcare expenditure prediction.

Paper Citation

in Harvard Style

Musharaf S., Kumar S., Reddy B. and Sahoo B. (2025). A Predictive Approach for Healthcare Expenditure Using Ensemble Techniques. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 41-48. DOI: 10.5220/0013586300004664

in Bibtex Style

@conference{incoft25,
author={Syed Musharaf and Sripathi Srujan Kumar and B Maruthi Reddy and Bidyutlata Sahoo},
title={A Predictive Approach for Healthcare Expenditure Using Ensemble Techniques},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={41-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013586300004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - A Predictive Approach for Healthcare Expenditure Using Ensemble Techniques
SN - 978-989-758-763-4
AU - Musharaf S.
AU - Kumar S.
AU - Reddy B.
AU - Sahoo B.
PY - 2025
SP - 41
EP - 48
DO - 10.5220/0013586300004664
PB - SciTePress