Abstract
Abstract Background and Aims Anaemia is a common complication in patients with chronic kidney disease (CKD) and is associated with increased mortality, cardiovascular complications, reduced quality of life and increased use of healthcare resources. Mathematical modelling based on robust epidemiological and clinical data is a useful approach for predicting the future burden of disease and the impact of different intervention scenarios; this is important for health service planning. This analysis uses a microsimulation model, Inside ANEMIA of CKD, to predict the effects of a hypothetical intervention scenario that reduces the prevalence of anaemia of CKD on related healthcare costs in the USA from 2020 to 2025. Method A virtual cohort representing the US population was created within the Inside ANEMIA of CKD microsimulation model framework using demographics and epidemiological data drawn from the US Census Bureau, the Centers for Disease Control and Prevention, and the National Health and Nutrition Examination Survey. In the cohort, virtual individuals were ascribed an age–sex-stratified CKD status (defined by estimated glomerular filtration rate and albuminuria levels, as per international guidelines) and anaemia status (defined by haemoglobin level as mild, moderate or severe, as per WHO criteria) based on US prevalence data. Key comorbidities (type 2 diabetes, heart failure and hypertension) were also assigned, reflecting US-specific population statistics. Healthcare costs related to CKD and anaemia of CKD were taken from the published literature. The study modelled the effects on healthcare costs of a hypothetical intervention scenario in which the prevalence of moderate and severe anaemia is reduced by 20% per year from 2020 to 2025 compared with no intervention (baseline). In each scenario (i.e. intervention or baseline), the modelling analysis estimated healthcare costs related to CKD and anaemia (including inpatient, outpatient, pharmacy costs) for patients with moderate or severe anaemia of CKD. The model did not adjust for the potential costs of the intervention. Results Preliminary results predict that, with the hypothetical intervention, there could be 1.40 million fewer patients with moderate or severe anaemia of CKD in the USA in 2025 compared with no intervention (1.45 million versus 2.85 million). This represents a 49% reduction in cases of moderate or severe anaemia of CKD in 2025 with the intervention versus no intervention. The intervention is projected to lead to a reduction of approximately US$18 billion in annual direct healthcare costs in 2025 for patients with moderate or severe anaemia of CKD compared with no intervention (US$26 billion versus US$44 billion). Conclusion The Inside ANEMIA of CKD microsimulation model predicts that a hypothetical intervention which reduces the prevalence of moderate and severe anaemia of CKD would reduce direct healthcare costs. This suggests that interventions effective at reducing the prevalence of anaemia of CKD would help to reduce the economic burden on healthcare services.
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