Cross-validation of comorbidity items in two national databases in a sample of patients with end-stage kidney disease

BMC Health Services Research

Research

Cécile Couchoud¹  Eric Cellarier²  Assia Hami³  Antoine Rachas⁴  Philippe Tuppin⁴  Panayotis Constantinou⁴  Isabella Vanorio-Vega⁵ 

[1] Agence de La Biomédecine, 1 Avenue du Stade de France, 93212, Saint-Denis, France;Centre Hospitalier Universitaire Clermont-Ferrand, Hôpital Gabriel Montpied Département d’Information Médicale, 63003, Clermont-Ferrand, France;Centre Hospitalier Universitaire de Nantes. PHU1-Institut de Transplantation Urologie Néphrologie (ITUN), Centre d’Hemodialyse Chronique- Aile Nord-Zone Administrative RCB, Nantes, France;Direction de La Stratégie Des Études Et Des Statistiques, Caisse Nationale de L’assurance Maladie (CNAM), 75986, Paris, Cedex 20, France;Direction de La Stratégie Des Études Et Des Statistiques, Caisse Nationale de L’assurance Maladie (CNAM), 75986, Paris, Cedex 20, France;Agence de La Biomédecine, 1 Avenue du Stade de France, 93212, Saint-Denis, France;

关键词: Medico-administrative databases;    Algorithm validation;    Comorbidities;   

DOI  :  10.1186/s12913-023-10145-y

 received in 2023-04-11, accepted in 2023-10-14,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThe use of national medico-administrative databases for epidemiological studies has increased in the last decades. In France, the Healthcare Expenditures and Conditions Mapping (HECM) algorithm has been developed to analyse and monitor the morbidity and economic burden of 58 diseases. We aimed to assess the performance of the HECM in identifying different conditions in patients with end-stage kidney disease (ESKD) using data from the REIN registry (the French National Registry for patients with ESKD).MethodsWe included all patients over 18 years of age who started renal replacement therapy in France in 2018. Five conditions with a similar definition in both databases were included (ESKD, diabetes, human immunodeficiency virus [HIV], coronary insufficiency, and cancer). The performance of each SNDS algorithm was assessed using sensitivity, specificity, positive predictive values (PPVs), negative predictive values (NPVs), and Cohen’s kappa coefficient.ResultsIn total 5,971 patients were included. Among them, 81% were identified as having ESKD in both databases. Diabetes was the condition with the best performance, with a sensitivity, specificity, PPV, NPV, and Kappa coefficient all over 80%. Cancer had the lowest level of agreement with a Kappa coefficient of 51% and a high specificity and high NPV (94% and 95%). The conditions for which the definition in the HECM included disease-specific medications performed better in our study.ConclusionThe HECM showed good to very good concordance with the REIN database information overall, with the exception of cancer. Further validation of the HECM tool in other populations should be performed.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

【 图 表 】

Fig. 3