OptiHealth: A Recommender Framework for Pareto Optimal Health Insurance Plans

Fernando Boccanera, Alexander Brodsky

2017

Abstract

Choosing a health insurance plan, even when the plans are standardized, is a daunting task. Research has shown that the complexity of the task leads consumers to make non-optimal choices most of the time. While a number of systems were introduced to assist the selection of health insurance plans, they fail to significantly reduce the main causes of poor decisions. To address this problem, this paper proposes OptiHealth, a recommender framework for Pareto optimal selection of health insurance plans. The proposed framework is based on (1) actuarial analysis of medical data and a method to accurately estimate the expected annual cost tailored to specific individuals, (2) finding and presenting a small number of diversified Pareto optimal plans based on key performance indicators, and (3) allowing decision makers to iteratively conduct a trade-off analysis.

Paper Citation

in Harvard Style

Boccanera F. and Brodsky A. (2017). OptiHealth: A Recommender Framework for Pareto Optimal Health Insurance Plans . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 599-609. DOI: 10.5220/0006334905990609

in Bibtex Style

@conference{iceis17,
author={Fernando Boccanera and Alexander Brodsky},
title={OptiHealth: A Recommender Framework for Pareto Optimal Health Insurance Plans},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={599-609},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006334905990609},
isbn={978-989-758-247-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - OptiHealth: A Recommender Framework for Pareto Optimal Health Insurance Plans
SN - 978-989-758-247-9
AU - Boccanera F.
AU - Brodsky A.
PY - 2017
SP - 599
EP - 609
DO - 10.5220/0006334905990609