Analysis of Unmet Healthcare Needs in Ireland: A Data Mining Approach
Anatoli Nachev
Dr. Anatoli Nachev*, Lecturer, Business Information Systems, J. E. Cairnes School of Business & Economics, National University of Ireland, Galway, Ireland.
Manuscript received on February 08, 2021. | Revised Manuscript received on February 15, 2021. | Manuscript published on February 28, 2021. | PP: 81-86 | Volume-10 Issue-3, February 2021. | Retrieval Number: 100.1/ijeat.C22320210321 | DOI: 10.35940/ijeat.C2232.0210321
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study explores data form the Survey of Income and Living Condition (SILC), related to factors contributing to unmet healthcare needs in Ireland. We analysed predisposing, enabling and needs factors by building predictive models and measured the predictor importance by sensitivity analysis. Results show that critical factors for meeting the healthcare needs include financial status, degree of urbanization, indicators of social exclusion and deprivations, and self-perceived general health condition. Identifying and quantifying those factors form raw data may facilitate decision making in the domain.
Keywords: Unmet healthcare, data mining, classification, logistic regression.
Scope of the Article: Data Mining