Optimization of Diagnosis and Treatment of Chronic Diseases Based on Association Analysis Under the Background of Regional Integration

In order to improve medical quality, shorten hospital stays, and reduce redundant treatment, an optimization of diagnosis and treatment of chronic diseases based on association analysis under the background of regional integration in the paper was proposed, which was to expand the scope of applicati...

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Bibliographic Details
Published in:Journal of medical systems Vol. 43; no. 3; pp. 46 - 8
Main Authors: Xia, Kaijian, Zhong, Xiaowei, Zhang, Li, Wang, Jianqiang
Format: Journal Article
Language:English
Published: New York Springer US 01.03.2019
Springer Nature B.V
Subjects:
Association analysis
Chronic illnesses
Correlation analysis
Data processing
Diagnosis
Distributed Analytics and Deep Learning in Health Care
Health Informatics
Health Sciences
Integration
Medical diagnosis
Medical treatment
Medicine
Medicine & Public Health
Optimization
Regional analysis
Statistics for Life Sciences
Systems-Level Quality Improvement
Chronic diseases
Regional medical integration
Diagnosis and treatment
Medical quality
FP-growth algorithm
ISSN:0148-5598, 1573-689X, 1573-689X
Online Access:Get full text
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Summary:In order to improve medical quality, shorten hospital stays, and reduce redundant treatment, an optimization of diagnosis and treatment of chronic diseases based on association analysis under the background of regional integration in the paper was proposed, which was to expand the scope of application of the clinical pathway standard diagnosis and treatment program in the context of regional medical integration and mass medical data, so that it had a larger group of patients within the region. In the context of regional medical integration, owing to the types of medical data were diverse, the preprocessing requirements and process specifications for diagnosis and treatment data were firstly proposed. At the stage of diagnosis and treatment unit optimization, the correlation between clinical behaviors was analyzed by using association rules of the FP-growth and Apriori algorithm. Through the optimization and combination of diagnosis and treatment units, the optimized clinical pathway was finally achieved. Experiments showed that after the optimization strategy by the paper proposed, the clinical path diagnosis and treatment achieved obvious improvement in medical quality under the condition that the medical cost was basically flat.
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ISSN:0148-5598
1573-689X
1573-689X
DOI:10.1007/s10916-019-1169-9