Development and validation of a code-based algorithm using in-hospital medical records to identify patients with pulmonary arterial hypertension in the French Healthcare Database
Clément Jambon-Barbara, Alex Hlavaty, Claire Bernardeau, Hélène Bouvaist, M. Chaumais, Marc Humbert, D. Montani, J. Cracowski, C. Khouri
{"title":"Development and validation of a code-based algorithm using in-hospital medical records to identify patients with pulmonary arterial hypertension in the French Healthcare Database","authors":"Clément Jambon-Barbara, Alex Hlavaty, Claire Bernardeau, Hélène Bouvaist, M. Chaumais, Marc Humbert, D. Montani, J. Cracowski, C. Khouri","doi":"10.1183/23120541.00109-2024","DOIUrl":null,"url":null,"abstract":"Pulmonary arterial hypertension (PAH) is a rare and severe disease for which most of the evidence about prognostic factors, evolution and treatment efficacy comes from cohorts, registries and clinical trials. We therefore aimed to develop and validate a new PAH identification algorithm that can be used in the French healthcare database (SNDS).We developed and validated the algorithm using the Grenoble Alpes University Hospital medical charts. We first identified PAH patients following a previously validated algorithm (Gillmeyeret al. algorithm), using in hospital ICD-10 codes, right heart catheterisation procedure and PAH specific treatment dispensing. Then, we refined the latter with the exclusion of chronic thromboembolic pulmonary hypertension procedures and treatment, the main misclassification factor. Secondly, we validated this algorithm using a gold standard review of in-hospital medical charts and calculated sensitivity, specificity, positive and negative predictive value (PPV and NPV) and accuracy. Finally, we applied this algorithm in the French healthcare database and described the characteristics of the identified patients.In the Grenoble University Hospital, we identified 252 unique patients meeting all the algorithm's criteria between 01/01/2010 and 30/06/2022, and reviewed all medical records. The sensitivity, specificity, PPV, NPV and accuracy were 91.0%, 74.3%, 67.9%, 93.3% and 80.6% respectively. Application of this algorithm to the SNDS yielded the identification of 9931 patients with consistent characteristics compared to PAH registries.Overall, we propose a new PAH identification algorithm developed and adapted to the French specificities, that can be used in future studies using the French healthcare database.","PeriodicalId":11739,"journal":{"name":"ERJ Open Research","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERJ Open Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1183/23120541.00109-2024","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0
Abstract
Pulmonary arterial hypertension (PAH) is a rare and severe disease for which most of the evidence about prognostic factors, evolution and treatment efficacy comes from cohorts, registries and clinical trials. We therefore aimed to develop and validate a new PAH identification algorithm that can be used in the French healthcare database (SNDS).We developed and validated the algorithm using the Grenoble Alpes University Hospital medical charts. We first identified PAH patients following a previously validated algorithm (Gillmeyeret al. algorithm), using in hospital ICD-10 codes, right heart catheterisation procedure and PAH specific treatment dispensing. Then, we refined the latter with the exclusion of chronic thromboembolic pulmonary hypertension procedures and treatment, the main misclassification factor. Secondly, we validated this algorithm using a gold standard review of in-hospital medical charts and calculated sensitivity, specificity, positive and negative predictive value (PPV and NPV) and accuracy. Finally, we applied this algorithm in the French healthcare database and described the characteristics of the identified patients.In the Grenoble University Hospital, we identified 252 unique patients meeting all the algorithm's criteria between 01/01/2010 and 30/06/2022, and reviewed all medical records. The sensitivity, specificity, PPV, NPV and accuracy were 91.0%, 74.3%, 67.9%, 93.3% and 80.6% respectively. Application of this algorithm to the SNDS yielded the identification of 9931 patients with consistent characteristics compared to PAH registries.Overall, we propose a new PAH identification algorithm developed and adapted to the French specificities, that can be used in future studies using the French healthcare database.
期刊介绍:
ERJ Open Research is a fully open access original research journal, published online by the European Respiratory Society. The journal aims to publish high-quality work in all fields of respiratory science and medicine, covering basic science, clinical translational science and clinical medicine. The journal was created to help fulfil the ERS objective to disseminate scientific and educational material to its members and to the medical community, but also to provide researchers with an affordable open access specialty journal in which to publish their work.