COSTS OF HEALTHCARE RESOURCE UTILIZATION IN INCIDENT CASES OF CHRONIC KIDNEY DISEASE IN PRIMARY CARE: THE REDIC STUDY
Author(s)
Martí Blasco, MSc1, José Romano, MD2, Natalia Jimenez, BPharm1, Ariadna Arbiol Roca, PhD3, Sílvia Cobo, MD4, Betlem Salvador González, PhD5.
1Boehringer Ingelheim España, S.A., Sant Cugat del Vallès, Spain, 2Gerència d’Atenció Primària i a la Comunitat Delta, Institut Català de la Salut, L’Hospitalet de Llobregat, Spain, 3Laboratori Territorial Metropolitana Sud, Institut Català de la Salut, l'Hospital Universitari de Bellvitge, Barcelona, Spain, 4Gerència d’Atenció Primària i a la Comunitat Baix Llobregat, Institut Català de la Salut, Cornellà de Llobregat, Spain, 5Unitat de Suport a la Recerca Metropolitana Sud-Penedès, Institut d’Investigació en Atenció Primària de Salut Jordi Gol (IDIAPJGol), El Prat de Llobregat, Spain.
1Boehringer Ingelheim España, S.A., Sant Cugat del Vallès, Spain, 2Gerència d’Atenció Primària i a la Comunitat Delta, Institut Català de la Salut, L’Hospitalet de Llobregat, Spain, 3Laboratori Territorial Metropolitana Sud, Institut Català de la Salut, l'Hospital Universitari de Bellvitge, Barcelona, Spain, 4Gerència d’Atenció Primària i a la Comunitat Baix Llobregat, Institut Català de la Salut, Cornellà de Llobregat, Spain, 5Unitat de Suport a la Recerca Metropolitana Sud-Penedès, Institut d’Investigació en Atenció Primària de Salut Jordi Gol (IDIAPJGol), El Prat de Llobregat, Spain.
OBJECTIVES: To assess healthcare resource utilization (HCRU) costs in incident chronic kidney disease (CKD) according to KDIGO risk stage and diagnostic coding status at identification in primary care (PC).
METHODS: This retrospective cohort study used electronic health records from the SIDIAP database (Catalonia, Spain) and included adults with incident CKD identified in PC between 2012 and 2021, either by coded diagnosis or laboratory confirmation. Cases were classified into KDIGO risk stages (moderate, high, very high, other). Codification was considered at <6 months after identification.
HCRU costs included hospitalizations (all-cause, cardiovascular [CV], renal), visits (PC physician/nurse, PC and hospital emergency), referrals (nephrology, endocrinology, internal medicine, cardiology, geriatrics), CKD laboratory tests, ultrasound, cardio-renal-metabolic treatments, sick leave, and renal replacement therapy (RRT). Costs were estimated per 1,000 person-years and updated to 2022 euros.
RESULTS: A total of 447,202 patients were included (53.8% women; median age 77 years). KDIGO stage was classifiable in 95.6%. Among diagnosed patients: 64.7% moderate, 25.4% high, 10.0% very high risk; among undiagnosed: 77.1%, 18.8%, and 4.1%.
Across stages, undiagnosed individuals were older, more often female, and had higher prevalence of type 2 diabetes and cardiovascular disease (except heart failure in moderate/high risk). They also more frequently received RAASi (except high risk) and lipid-lowering therapy.
Costs per 1,000 person-years were higher in undiagnosed vs diagnosed in moderate (€3.7M vs €3.4M) and high risk (€5.2M vs €5.0M), but not in very high risk (€8.4M vs €10.0M). All-cause and CV hospitalization costs were higher in undiagnosed, whereas CKD-related hospitalization costs were higher in diagnosed. Most other HCRU components were also higher in undiagnosed.
CONCLUSIONS: HCRU costs increased with KDIGO risk stage. In moderate and high risk, costs were higher in undiagnosed patients. Further studies should clarify whether differences are driven by baseline characteristics or diagnosis.
METHODS: This retrospective cohort study used electronic health records from the SIDIAP database (Catalonia, Spain) and included adults with incident CKD identified in PC between 2012 and 2021, either by coded diagnosis or laboratory confirmation. Cases were classified into KDIGO risk stages (moderate, high, very high, other). Codification was considered at <6 months after identification.
HCRU costs included hospitalizations (all-cause, cardiovascular [CV], renal), visits (PC physician/nurse, PC and hospital emergency), referrals (nephrology, endocrinology, internal medicine, cardiology, geriatrics), CKD laboratory tests, ultrasound, cardio-renal-metabolic treatments, sick leave, and renal replacement therapy (RRT). Costs were estimated per 1,000 person-years and updated to 2022 euros.
RESULTS: A total of 447,202 patients were included (53.8% women; median age 77 years). KDIGO stage was classifiable in 95.6%. Among diagnosed patients: 64.7% moderate, 25.4% high, 10.0% very high risk; among undiagnosed: 77.1%, 18.8%, and 4.1%.
Across stages, undiagnosed individuals were older, more often female, and had higher prevalence of type 2 diabetes and cardiovascular disease (except heart failure in moderate/high risk). They also more frequently received RAASi (except high risk) and lipid-lowering therapy.
Costs per 1,000 person-years were higher in undiagnosed vs diagnosed in moderate (€3.7M vs €3.4M) and high risk (€5.2M vs €5.0M), but not in very high risk (€8.4M vs €10.0M). All-cause and CV hospitalization costs were higher in undiagnosed, whereas CKD-related hospitalization costs were higher in diagnosed. Most other HCRU components were also higher in undiagnosed.
CONCLUSIONS: HCRU costs increased with KDIGO risk stage. In moderate and high risk, costs were higher in undiagnosed patients. Further studies should clarify whether differences are driven by baseline characteristics or diagnosis.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE279
Topic
Economic Evaluation
Topic Subcategory
Cost/Cost of Illness/Resource Use Studies
Disease
Urinary/Kidney Disorders