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An Efficient Source Selection Approach for Retrieving Electronic Health Records From Federated Clinical Repositories

An Efficient Source Selection Approach for Retrieving Electronic Health Records From Federated Clinical Repositories

Nidhi Gupta (Jaypee Institute of Information Technology, Noida, India) and Bharat Gupta (Jaypee Institute of Information Technology, Noida, India)
Copyright: © 2022 |Volume: 15 |Issue: 2 |Pages: 18
ISSN: 1935-570X|EISSN: 1935-5718|EISBN13: 9781683180296|DOI: 10.4018/IJITSA.307025
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MLA

Gupta, Nidhi, and Bharat Gupta. "An Efficient Source Selection Approach for Retrieving Electronic Health Records From Federated Clinical Repositories." IJITSA vol.15, no.2 2022: pp.1-18. https://doi.org/10.4018/IJITSA.307025

APA

Gupta, N. & Gupta, B. (2022). An Efficient Source Selection Approach for Retrieving Electronic Health Records From Federated Clinical Repositories. International Journal of Information Technologies and Systems Approach (IJITSA), 15(2), 1-18. https://doi.org/10.4018/IJITSA.307025

Chicago

Gupta, Nidhi, and Bharat Gupta. "An Efficient Source Selection Approach for Retrieving Electronic Health Records From Federated Clinical Repositories," International Journal of Information Technologies and Systems Approach (IJITSA) 15, no.2: 1-18. https://doi.org/10.4018/IJITSA.307025

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Abstract

The data retrieval and unification of patient electronic health records from distinct clinical repositories is essential for an effective health decision making. The scattering of patient data in many complementary but also overlapping sources poses a challenge in locating the desired records. Maintaining the patient master index also faced legal and privacy issues. Therefore, it is essential to locate the relevant records of the patient in federated clinical data sources. The research carried out proposed an efficient approach for relevant selection of patient records using semantic technologies. The approach uses both triple pattern-wise and join-aware source selection approaches for optimal selection of relevant data sources. The state-of-art federated engines are evaluated on the basis of source selection time and overall query execution time for different federated queries. The experimental results shows that the proposed approach selects the relevant data sources with reduced number of remote requests and significantly reduces the query execution time.

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