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Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years

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Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years

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dc.contributor.author Perez-Benito, Francisco Javier es_ES
dc.contributor.author Sáez Silvestre, Carlos es_ES
dc.contributor.author Conejero, J. Alberto es_ES
dc.contributor.author Tortajada, Salvador es_ES
dc.contributor.author Valdivieso, Bernardo es_ES
dc.contributor.author Garcia-Gomez, Juan M es_ES
dc.date.accessioned 2021-01-28T04:31:38Z
dc.date.available 2021-01-28T04:31:38Z
dc.date.issued 2019-08-07 es_ES
dc.identifier.issn 1932-6203 es_ES
dc.identifier.uri http://hdl.handle.net/10251/160077
dc.description.abstract [EN] Objective To evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years. Materials and methods Temporal Variability Assessment (TVA) based on probabilistic data quality assessment was applied to the historic monthly-batched admission data of Hospital La Fe Valencia, Spain from 2010 to 2016. Routine healthcare data with a complete EHR was expanded by processed variables such as the Charlson Comorbidity Index. Results Four Process-Reengineering interventions were detected by quantifiable effects on the EHR: (1) the hospital relocation in 2011 involved progressive reduction of admissions during the next four months, (2) the hospital services re-configuration incremented the number of inter-services transfers, (3) the care-services re-distribution led to transfers between facilities (4) the assignment to the hospital of a new area with 80,000 patients in 2015 inspired the discharge to home for follow up and the update of the pre-surgery planned admissions protocol that produced a significant decrease of the patient length of stay. Discussion TVA provides an indicator of the effect of process re-engineering interventions on healthcare practice. Evaluating the effect of facilities¿ relocation and increment of citizens (findings 1, 3¿4), the impact of strategies (findings 2¿3), and gradual changes in protocols (finding 4) may help on the hospital management by optimizing interventions based on their effect on EHRs or on data reuse. Conclusions The effects on hospitals EHR due to process re-engineering interventions can be evaluated using the TVA methodology. Being aware of conditioned variations in EHR is of the utmost importance for the reliable reuse of routine hospitalization data. es_ES
dc.description.sponsorship F.J.P.B, C.S., J.M.G.G. and J.A.C. were funded Universitat Politecnica de Valencia, project "ANALISIS DE LA CALIDAD Y VARIABILIDAD DE DATOS MEDICOS". www.upv.es. J.M.G.G.is also partially supported by: Ministerio de Economia y Competitividad of Spain through MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R); and European Commission projects H2020-SC1-2016-CNECT Project (No. 727560) and H2020-SC1-BHC-2018-2020 (No. 825750). The funders did not play any role in the study design, data collection and analysis, decision to publish, nor preparation of the manuscript. es_ES
dc.language Inglés es_ES
dc.publisher Public Library of Science es_ES
dc.relation.ispartof PLoS ONE es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.title Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1371/journal.pone.0220369 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/727560/EU/Collective wisdom driving public health policies/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2016-80054-R/ES/BIOMARCADORES DINAMICOS BASADOS EN FIRMAS TISULARES MULTIPARAMETRICAS PARA EL SEGUIMIENTO Y EVALUACION DE LA RESPUESTA A TRATAMIENTO DE PACIENTES CON GLIOBLASTOMA Y CANCER DE PRÓSTATA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825750/EU/Patient-centred pathways of early palliative care, supportive ecosystems and appraisal standard/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada es_ES
dc.description.bibliographicCitation Perez-Benito, FJ.; Sáez Silvestre, C.; Conejero, JA.; Tortajada, S.; Valdivieso, B.; Garcia-Gomez, JM. (2019). Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years. PLoS ONE. 14(8):1-19. https://doi.org/10.1371/journal.pone.0220369 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1371/journal.pone.0220369 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 8 es_ES
dc.identifier.pmid 31390350 es_ES
dc.identifier.pmcid PMC6685618 es_ES
dc.relation.pasarela S\393366 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
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dc.subject.ods 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades es_ES


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