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dc.contributor.authorSánchez-de-Madariaga, Ricardo 
dc.contributor.authorMuñoz Carrero, Adolfo 
dc.contributor.authorCastro, Antonio L 
dc.contributor.authorMoreno, Oscar 
dc.contributor.authorPascual-Carrasco, Mario
dc.identifier.citationJ Vis Exp. 2018 Mar 19;(133):57439.es_ES
dc.description.abstractThis research shows a protocol to assess the computational complexity of querying relational and non-relational (NoSQL (not only Structured Query Language)) standardized electronic health record (EHR) medical information database systems (DBMS). It uses a set of three doubling-sized databases, i.e. databases storing 5000, 10,000 and 20,000 realistic standardized EHR extracts, in three different database management systems (DBMS): relational MySQL object-relational mapping (ORM), document-based NoSQL MongoDB, and native extensible markup language (XML) NoSQL eXist. The average response times to six complexity-increasing queries were computed, and the results showed a linear behavior in the NoSQL cases. In the NoSQL field, MongoDB presents a much flatter linear slope than eXist. NoSQL systems may also be more appropriate to maintain standardized medical information systems due to the special nature of the updating policies of medical information, which should not affect the consistency and efficiency of the data stored in NoSQL databases. One limitation of this protocol is the lack of direct results of improved relational systems such as archetype relational mapping (ARM) with the same data. However, the interpolation of doubling-size database results to those presented in the literature and other published results suggests that NoSQL systems might be more appropriate in many specific scenarios and problems to be solved. For example, NoSQL may be appropriate for document-based tasks such as EHR extracts used in clinical practice, or edition and visualization, or situations where the aim is not only to query medical information, but also to restore the EHR in exactly its original form.es_ES
dc.description.sponsorshipThis work was supported by Instituto de Salud Carlos III [grant numbers PI15/00321, PI15/00003, PI1500831, PI15CIII/00010 and RD16CIII].es_ES
dc.publisherJoVE es_ES
dc.subjectRelational Databasees_ES
dc.subjectNoSQL Databasees_ES
dc.subjectStandardized Medical Informationes_ES
dc.subjectISO/EN 13606 Standardes_ES
dc.subjectElectronicHealth Record Extractes_ES
dc.subjectAlgorithmic Complexityes_ES
dc.subjectResponse Timees_ES
dc.subjectReference Modeles_ES
dc.subjectDual Modeles_ES
dc.subjectClinical Practicees_ES
dc.subjectResearch Usees_ES
dc.subject.meshHumans es_ES
dc.subject.meshInformation Storage and Retrieval es_ES
dc.subject.meshDatabase Management Systems es_ES
dc.subject.meshElectronic Health Records es_ES
dc.titleExecuting Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databaseses_ES
dc.typejournal articlees_ES
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.contributor.funderInstituto de Salud Carlos III 
dc.identifier.journalJournal of visualized experiments : JoVEes_ES
dc.repisalud.centroISCIII::Unidad de Investigación en Telemedicina y eSaludes_ES
dc.rights.accessRightsopen accesses_ES
dc.relation.projectFISinfo:fis/Instituto de Salud Carlos III/null/null/Subprograma de proyectos de investigacion en salud (AES 2015). Modalidad proyectos en salud. (2015)/PI15/00321
dc.relation.projectFISinfo:fis/Instituto de Salud Carlos III/null/null/Subprograma de proyectos de investigacion en salud (AES 2015). Modalidad proyectos en salud. (2015)/PI15/00831

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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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