Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Application of Disease Pattern Analysis with Lifestyle Risk Factor for Healthcare Promotion Service

Version 1 : Received: 5 April 2019 / Approved: 8 April 2019 / Online: 8 April 2019 (12:52:38 CEST)
Version 2 : Received: 11 April 2019 / Approved: 12 April 2019 / Online: 12 April 2019 (20:53:16 CEST)

How to cite: Cho, Y.S.; Jeong, S. Application of Disease Pattern Analysis with Lifestyle Risk Factor for Healthcare Promotion Service. Preprints 2019, 2019040095. https://doi.org/10.20944/preprints201904.0095.v2 Cho, Y.S.; Jeong, S. Application of Disease Pattern Analysis with Lifestyle Risk Factor for Healthcare Promotion Service. Preprints 2019, 2019040095. https://doi.org/10.20944/preprints201904.0095.v2

Abstract

Lately, the Critical Pathway(CP) of Electronic Medical Record(EMR) is used to the guideline for a treatment in the public hospital. We propose a healthcare promotion service using disease pattern with lifestyle risk factors. We classify a medical historical patient data with disease codes with lifestyle risk factors (hypertension, diabetes, smoking, overweight, excessive alcohol intake, and low physical activity) to make the lifestyle risk factors through the classification. We finally make the clusters of disease code with lifestyle risk factors using the medical historical data based on EMR's electronic discharge summary data. As the result of that, we do a healthcare recommending service based on the disease pattern with lifestyle risk. We can build a medical help desk of a public hospital to support people as we check into the public hospital; how to get the procedure of curing, the desired curing clinical method for the healthcare promotion service by each disease code, and how to be better our healthcare. We evaluate the performance of the proposed system by experimenting with the datasets collected at the medical center to measure performance and report some experimental results.

Keywords

EMR; SVM; Classification; Clustering

Subject

Computer Science and Mathematics, Information Systems

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