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A Healthcare Quality Assessment Model Based on Outlier Detection Algorithm

Authors :
Nawaf Alharbe
Mohamed Ali Rakrouki
Abeer Aljohani
Source :
Processes; Volume 10; Issue 6; Pages: 1199
Publication Year :
2022
Publisher :
Multidisciplinary Digital Publishing Institute, 2022.

Abstract

With the extremely rapid growth of data in various industries, big data is gradually recognized and valued by people. Medical big data, which can best reflect the significance of big data value, has also received attention from various parties. In Saudi Arabia, healthcare quality assessment is mostly based on human experience and basic statistical methods. In this paper, we proposed a healthcare quality assessment model based on medical big data in a region of Saudi Arabia, which integrated traditional evaluation methods and machine learning based techniques. Healthcare data has been accurate and effective after noise processing, and the outliers could reflect certain medical quality information. An improved k-nearest neighbors (KNN) algorithm has been proposed and its time complexity have been reduced to be more suitable for big data processing. An outlier indicator has been established based on statistical methods and the improved KNN algorithm. Experimental results showed that the proposed approach has good potential for detecting hospitals with financial fraud and poor-quality medical care.

Details

Language :
English
ISSN :
22279717
Database :
OpenAIRE
Journal :
Processes; Volume 10; Issue 6; Pages: 1199
Accession number :
edsair.doi.dedup.....81ead5538710a28fe4d3dda8c1a7b0c2
Full Text :
https://doi.org/10.3390/pr10061199