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Letter to the Editor
Chronic Obstructive Pulmonary Disease and Big Data
Sobre la enfermedad pulmonar obstructiva crónica y el big data
Joan B. Sorianoa,b,
Corresponding author
jbsoriano2@gmail.com

Corresponding author.
, Borja G. Cosíob,c, José Luís López-Camposb,d, Juan José Soler-Cataluñab,e, Julio Ancocheaa,b, en nombre del Comité Científico Big COPData 1
a Hospital Universitario de la Princesa, Instituto de Investigación Sanitaria Princesa (IP), Universidad Autónoma de Madrid, Madrid, Spain
b Centro de Investigación en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
c Hospital Universitario Son Espases, Instituto de Investigación Sanitaria de Baleares (IdISBa), Palma, Mallorca, Spain
d Unidad Médico-Quirúrgica de Enfermedades Respiratorias, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/Universidad de Sevilla, Sevilla, Spain
e Servicio de Neumología, Hospital Arnau de Vilanova, Valencia, Spain
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            "entidad" => "Unidad M&#233;dico-Quir&#250;rgica de Enfermedades Respiratorias&#44; Instituto de Biomedicina de Sevilla &#40;IBiS&#41;&#44; Hospital Universitario Virgen del Roc&#237;o&#47;Universidad de Sevilla&#44; Sevilla&#44; Spain"
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            "entidad" => "Servicio de Neumolog&#237;a&#44; Hospital Arnau de Vilanova&#44; Valencia&#44; Spain"
            "etiqueta" => "e"
            "identificador" => "aff0025"
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        ]
        "correspondencia" => array:1 [
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    "titulosAlternativos" => array:1 [
      "es" => array:1 [
        "titulo" => "Sobre la enfermedad pulmonar obstructiva cr&#243;nica y el <span class="elsevierStyleItalic">big data</span>"
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    ]
    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">We have read with interest the novel study carried out by Prof&#46; Izquierdo et al&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Its results in the population with chronic obstructive pulmonary disease &#40;COPD&#41; in Castilla-La Mancha indicate that 10 years after the introduction of the National Strategy for COPD&#44; important gaps unfortunately still exist in the diagnosis and management of these patients&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Previous clinical audits on the management of COPD in Spain were based on tedious surveys that depended on the varying interest and response of individual researchers&#46;<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3&#44;4</span></a> The use and correct interpretation of big data should now provide almost real-time information on how and who is diagnosed and treated with COPD in Spain&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">A huge amount of health information is already being digitalized and stored in administrative databases&#44; but the text of the electronic medical record was considered unanalyzable&#46; Big data now makes it possible to exploit this information&#44; which should improve understanding of care processes and identify bottlenecks in order to correct errors and modify behaviors&#44; thus improving health outcomes&#46; One of the orphan areas of COPD is the study of severe exacerbations and the risk of readmissions&#44; areas of interest due to their impact on disease prognosis at an individual level&#44; on the health system in general&#44; and on the costs of both&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">The BIG COPData study&#44;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> led by SEPAR and Savana&#174; &#40;<a href="https://savanamed.com/es/">https&#58;&#47;&#47;savanamed&#46;com&#47;es&#47;</a>&#41; is currently underway&#44; with the participation of France&#44; Germany&#44; the UK&#44; Canada&#44; USA&#44; U&#46;S&#46;&#44; and other countries &#40;ClinicalTrials&#46;gov No&#46; NCT04206098&#41;&#46; Its objective is to identify factors associated with hospital readmissions in patients with COPD&#46; Big COPData aims to developing a predictive model of readmissions&#44; using Natural Language Processing &#40;NLP&#41; techniques and big data&#46; This new methodology should allow for a better diagnosis of the entire healthcare process and its impact on the lives of COPD patients&#46;</p></span>"
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    "fechaRecibido" => "2020-03-08"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0010">The members of the Big COPData Scientific Committee are&#58; Julio Ancochea&#44; Alberto Fern&#225;ndez-Villar&#44; Borja G&#46; Cosio&#44; Jos&#233; Luis Izquierdo&#44; Jos&#233; Luis L&#243;pez-Campos&#44; Marc Miravitlles&#44; Jos&#233; Miguel Rodr&#237;guez&#44; Juan Jos&#233; Soler-Catalu&#241;a and Joan B&#46; Soriano&#46;</p>"
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      1 => array:2 [
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Soriano JB&#44; Cos&#237;o BG&#44; L&#243;pez-Campos JL&#44; Soler-Catalu&#241;a JJ&#44; Ancochea J&#46; Sobre la enfermedad pulmonar obstructiva cr&#243;nica y el <span class="elsevierStyleItalic">big data</span>&#46; Arch Bronconeumol&#46; 2021&#59;57&#58;144&#46;</p>"
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                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Clinical Management of COPD in a Real-World Setting&#46; A Big Data Analysis &#91;Article in English&#44; Spanish&#93;"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "J&#46;L&#46; Izquierdo"
                            1 => "D&#46; Morena"
                            2 => "Y&#46; Gonzalez"
                            3 => "J&#46;M&#46; Paredero"
                            4 => "B&#46; Perez"
                            5 => "D&#46; Graziani"
                          ]
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                      "doi" => "10.1016/j.arbres"
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              "identificador" => "bib0010"
              "etiqueta" => "2"
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                0 => array:2 [
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                          "etal" => false
                          "autores" => array:2 [
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                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "J&#46;L&#46; Lopez-Campos"
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                            3 => "Project 3E"
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                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1111/crj.12208"
                      "Revista" => array:6 [
                        "tituloSerie" => "Clin Respir J&#46;"
                        "fecha" => "2016"
                        "volumen" => "10"
                        "paginaInicial" => "217"
                        "paginaFinal" => "222"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/25185741"
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                  "contribucion" => array:1 [
                    0 => array:2 [
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                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "M&#46; Abad-Arranz"
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                            2 => "E&#46; Mascaros Balaguer"
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                            4 => "L&#46; Abad Polo"
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                  ]
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                    0 => array:2 [
                      "doi" => "10.1186/s12874-018-0528-4"
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                        "tituloSerie" => "BMC Med Res Methodol&#46;"
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                        "volumen" => "18"
                        "paginaInicial" => "68"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29970023"
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                  "referenciaCompleta" => "Big COPData &#91;Accessed 3 March 2020&#93; Available from&#58; <a target="_blank" href="https://bigcopdata.savanamed.com">https&#58;&#47;&#47;bigcopdata&#46;savanamed&#46;com</a> European Union Horizon2020 Identifier&#58; 829654&#46;"
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Article information
ISSN: 15792129
Original language: English
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