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Prognostic value of claims data for chronic kidney disease associated health risks
Insights
Claims data effectively predict chronic kidney disease (CKD) progression and outcomes like kidney failure, even without lab results. Incorporating CKD stage enhances prognostic accuracy for better patient risk assessment.
Area of Science:
- Nephrology
- Health Informatics
- Biostatistics
Background:
- Chronic kidney disease (CKD) poses significant risks for kidney failure and mortality.
- Prognostic models for CKD often rely on biochemical data, which may not always be available.
- This study explores the utility of administrative claims data for predicting outcomes in CKD patients.
Purpose of the Study:
- To evaluate the prognostic value of health insurance claims data for predicting renal replacement therapy (rRT), death, and hospital admissions in CKD patients.
- To assess the impact of incorporating CKD stage (CKDIII/IV) into prognostic models based on claims data.
- To determine if claims data can predict the prescription of CKD-related pharmacotherapies.
Main Methods:
- Analysis of claims data from 29,144 CKD patients (CKDIII/IV) from 2016 to 2022.
- Utilized billing codes to track rRT, death, hospital admissions (including acute kidney injury and heart failure), and diagnoses.
- Developed prognostic models using claims data, with and without CKD stage, to predict key outcomes.
Main Results:
- Claims data demonstrated significant prognostic capability for rRT (AUC 0.87), AKI (AUC 0.68), death (AUC 0.97), heart failure admissions (AUC 0.76), and ICU therapy (AUC 0.67).
- Inclusion of CKD stage significantly improved the predictive accuracy (AUC) of all models.
- Prescriptions of Renin-Angiotensin-system and SGLT2 inhibitors were associated with better renal and cardiovascular outcomes.
Conclusions:
- Health insurance claims data offer valuable prognostic information for renal and overall outcomes in CKD patients, irrespective of laboratory data.
- CKD stage is a crucial factor that enhances the predictive power of claims-based models.
- Further research should explore integrating additional data for individualized risk calibration in CKD management.
Background:
Chronic kidney disease (CKD) associates with kidney failure and overall health risks. We here investigated the prognostic value of claims data in the absence of biochemical data.
Methods:
29,144 persons insured at AOK Rhineland-Hamburg with a diagnosis of CKDIII or CKDIV in 2016 were included into analyses of renal replacement therapy (rRT), death, hospital admissions and diagnoses, and prescription of CKD-related therapies during the ensuing six-year period (2017-2022) using corresponding billing codes.
Results:
In 22,228 individuals diagnosed with CKDIII and 6,916 with CKDIV during the base year, rRT was prescribed in 3.8% and 14.3% during the observation period, 7.0% and 13.3% were admitted to the hospital for acute kidney injury (AKI). A combination of claims data significantly contributed to prognosis of rRT (AUC 0.87) and AKI (AUC 0.68) and overall outcomes death (AUC 0.97), hospital admission for heart failure (AUC 0.76) and intensive care unit (ICU) therapy (AUC 0.67). All AUC significantly improved after inclusion of CKD stage into the model. Outpatient prescriptions of Renin-Angiotensin-system and sodium-glucose cotransporter 2 (SGLT2) inhibitors associated with significantly better renal and cardiovascular outcomes. Prescription of CKD-related pharmacotherapy for calcium metabolism (AUC 0.74), hyperkalemia/hyperphosphatemia (AUC 0.83), metabolic acidosis (AUC 0.81), erythropoiesis stimulating agents (AUC 0.65), and hyperuricemia therapy (AUC 0.72) was prognosticated by claims data with significant contribution of CKD stage.
Summary And Conclusion:
Claims data provide prognostic information for renal and overall outcomes in CKDIII and CKDIV patients even in the absence of laboratory measurements. Inclusion of additional values should be evaluated in patients with and without CKD for individualized risk calibration.
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