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Measuring the quality of data in electronic health records aggregators
dc.contributor.author | Molina, Carlos | |
dc.contributor.author | Prados-Suárez, Belén | |
dc.date.accessioned | 2025-01-31T08:07:28Z | |
dc.date.available | 2025-01-31T08:07:28Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://hdl.handle.net/10481/101448 | |
dc.description.abstract | There is an increasing work to integrate health related data for health care services and research purposes. Most of the current proposals adapt the schemas of the data sources to extract automatically the information, but they do not measure the quality of the resulted data. Even more, smart personal devices gather health related data into private non-standard compliant databases. Although these sources could be useful for health care systems and research, to consider the quality of the information they offer is essential. Electronic Health Records Aggregators (EHRagg ) are a new concept to integrate this kind of information, that considers the quality of the data. In this paper we present several factors that affect the quality (intrinsic to the data and related to the later use of it) and proposed a fuzzy quality measure to be used inside the EHRagg systems. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | IEEE | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | EHR | es_ES |
dc.subject | Data integration | es_ES |
dc.subject | Data quality | es_ES |
dc.subject | Aggregation | es_ES |
dc.title | Measuring the quality of data in electronic health records aggregators | es_ES |
dc.type | conference output | es_ES |
dc.relation.projectID | PGC2018-096156-B-I00 | es_ES |
dc.rights.accessRights | embargoed access | es_ES |
dc.identifier.doi | https://doi.org/10.1109/FUZZ48607.2020.9177606 | |
dc.type.hasVersion | AM | es_ES |