Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases

Cécile Couchoud (1, 2) , Maxime Raffray (3, 4, 5) , Mathilde Lassalle (1, 2) , Zhanibek Duisenbekov (1, 2) , Olivier Moranne (6, 7, 8) , Marie Erbault (9) , Helene Lazareth (10) , Cyrielle Parmentier (11) , Fitsum Guebre Egziabher (12, 13) , Aghilès Hamroun (14, 15, 16) , Marie Metzger (17) , Imene Mansouri (2) , Marcel Goldberg (18) , Marie Zins (18) , Sahar Bayat-Makoei (3, 4, 5) , Sofiane Kab (18)

1 CKD REIN - Chronic Kidney Disease - Réseau Epidémiologie et Information en Néphrologie
2 Agence de la biomédecine [Saint-Denis la Plaine]
3 EHESP - École des Hautes Études en Santé Publique [EHESP]
4 ARENES - Arènes: politique, santé publique, environnement, médias
5 RSMS - Recherche sur les services et le management en santé
6 UM - Université de Montpellier
7 CHU Nîmes - Hôpital Universitaire Carémeau [Nîmes]
8 IDESP - Institut Desbrest de santé publique
9 HAS - Haute Autorité de Santé [Saint-Denis La Plaine]
10 HEGP - Hôpital Européen Georges Pompidou [APHP]
11 CHU Trousseau [APHP]
12 Hôpital Edouard Herriot [CHU - HCL]
13 UCBL - Université Claude Bernard Lyon 1
14 Institut Pasteur de Lille
15 RID-AGE - Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167
16 CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]
17 CESP - Centre de recherche en épidémiologie et santé des populations
18 CONSTANCES - Cohortes épidémiologiques en population

Background Health policy-making require careful assessment of CKD epidemiology to develop efficient and cost-effective care strategies. The aim of the present study was to use the RENALGO-EXPERT algorithm to estimate the global prevalence of CKD in France. Methods An expert group developed the RENALGO-EXPERT algorithm based on healthcare consumption. This algorithm has been applied to the French National Health claims database (SNDS), where no biological test findings are available in order to estimate a national CKD prevalence for the years 2018–2021. The CONSTANCES cohort (+ 219 000 adults aged 18–69 with one CKD-EPI eGFR) was used to discuss the limit of using health claims data. Results Between 2018 and 2021, the estimated prevalence in the SNDS increased from 8.1% to 10.5%. The RENALGO-EXPERT algorithm identified 4.5% of the volunteers in the CONSTANCES as CKD. The RENALGO-EXPERT algorithm had a PPV of 6.2% and NPV of 99.1% to detect an eGFR<60 ml/min/1.73m². Half of 252 false positive cases (ALGO +, eGFR > 90) had been diagnosed with kidney disease during hospitalization, and the other half based on healthcare consumption suggestive of a ‘high-risk’ profile. 95% of the 1661 false negatives (ALGO -, eGFR < 60) had an eGFR between 45 and 60 ml/min, ½ had medication and 2/3 a biological exams possibly linked to CKD. Half of them had a hospital stay during the period but none had a diagnosis of kidney disease. Conclusions Our result is in accordance with other estimations of CKD prevalence in the general population. Analysis of diverging cases (FP and FN) suggests using health claims data has inherent limitations. Such algorithm is able to identify patients whose care pathway is close to the usual and specific CKD pathways. It does not identify patients who have not been diagnosed or whose care is inappropriate or at early stage with stable GFR.

Mots clés: CKD; diabetes; Epidemiology; health claims databases; hypertension

Domaines: Sciences du Vivant [q-bio]

Cécile Couchoud, Maxime Raffray, Mathilde Lassalle, Zhanibek Duisenbekov, Olivier Moranne, et al.. Prevalence of chronic kidney disease in France: methodological considerations and pitfalls with the use of Health claims databases. Clinical Kidney Journal, 2024, 14 (1), pp.sfae117. ⟨10.1093/ckj/sfae117⟩. ⟨hal-04576173⟩