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A cloud based health insurance plan recommendation system: A user centered approach

Authors :
Samee U. Khan
Limin Zhang
Assad Abbas
Kashif Bilal
Source :
Future Generation Computer Systems. :99-109
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

The recent concept of "Health Insurance Marketplace" introduced to facilitate the purchase of health insurance by comparing different insurance plans in terms of price, coverage benefits, and quality designates a key role to the health insurance providers. Currently, the web based tools available to search for health insurance plans are deficient in offering personalized recommendations based on the coverage benefits and cost. Therefore, anticipating the users' needs we propose a cloud based framework that offers personalized recommendations about the health insurance plans. We use the Multi-attribute Utility Theory (MAUT) to help users compare different health insurance plans based on coverage and cost criteria, such as: (a) premium, (b) co-pay, (c) deductibles, (d) co-insurance, and (e) maximum benefit offered by a plan. To overcome the issues arising possibly due to the heterogeneous data formats and different plan representations across the providers, we present a standardized representation for the health insurance plans. The plan information of each of the providers is retrieved using the Data as a Service (DaaS). The framework is implemented as Software as a Service (SaaS) to offer customized recommendations by applying a ranking technique for the identified plans according to the user specified criteria. We present a cloud based health insurance plan recommendation system.We propose a standard ontological representation for all the health insurance plans.An algorithm to determine the similarities between the user requirements and plans is presented.We propose a ranking technique based on the Multi-attribute Utility Theory (MAUT).

Details

ISSN :
0167739X
Database :
OpenAIRE
Journal :
Future Generation Computer Systems
Accession number :
edsair.doi...........1a871426b981ef345402723a9f7c8ac1
Full Text :
https://doi.org/10.1016/j.future.2014.08.010