Two posters presented at ASN Kidney Week 2023 analyze the economic burden that chronic kidney disease (CKD) can place on U.S. patients and the health care system, including commercial, Medicare Advantage, and Medicaid populations. We evaluated the effectiveness of the Klinsk prediction model in the population.
The economic burden of CKD in the United States
More than 35 million people in the United States have CKD. The economic impact of managing this disease is significant, as Medicare costs for these patients rose to more than $87 billion in 2019. To fully understand the economic burden of CKD on the U.S. health care system and payers, and the sources of that burden, researchers need a systematic approach to analyze the extent of the direct medical costs of this disease. A literature review was conducted.
Doctor with piggy bank | Photo Doctor with piggy bank Image credit: Andy Dean – Stock.adobe.com
MEDLINE and Embase were used to identify relevant studies examining direct medical costs for CKD across the United States. Researchers characterizing these reports also sought to assess the economic burden associated with CKD stage, comorbidities, and insurance type. The analysis considered conference proceedings from 2020 to 2022 and papers published from January 2017 to July 2022. These studies are both broad-based (including overall CKD data not limited to stage or current comorbidities) and CKD-specific (presenting CKD statistics limited to stage or current comorbidities). It was classified as crab. All summarized costs are converted to 2022 United States Dollar (USD) rates and expressed as average annual costs per person.
A total of 52 citations were included in 39 district studies. Their sample sizes ranged from 52 people to over 7 million people. Additionally, direct medical costs ranged from $6,592 to $280,727, with higher medical costs associated with more severe CKD, or the presence of cardiovascular disease (CVD) or diabetes.
The largest factor influencing overall CKD patients is hospitalization costs (ranging from $2,331 to $116,30), followed by outpatient costs. Additionally, dialysis costs for these patients can reach $13,248, and prescription drug costs can rise to his $10,066.
In CKD-specific studies, outpatient costs accounted for the highest economic burden. Annual costs for patients with stage 3 CKD are reported to be $6,593, while annual costs for patients with end-stage renal disease can reach $143,745. Comorbidity of type 2 diabetes (T2D) and cardiovascular disease (CVD) resulted in costs of $280,727 and $70,742.
Utilization of clean risk model
Kidney function is measured by estimated glomerular filtration rate (eGFR), and CKD is often not diagnosed until these levels indicate a significant loss of function. The Klinrisk machine learning model has proven its ability to accurately predict a patient’s CKD progression by collecting routine laboratory data. Early detection of CKD can help clinicians identify high-risk individuals, initiate therapeutic intervention sooner, and dramatically improve patient outcomes. With this in mind, researchers set out to test the effectiveness of the ClinRisk model across U.S. commercial, Medicare Advantage, and Medicaid populations.
The ClinRisk model analyzes factors such as age, gender, complete blood count, metabolic panel, urinalysis, and chemistry panel to predict progressive CKD (identified by renal failure or a 40% drop in eGFR). Masu. The authors of this study analyzed the results of the study with and without urinalysis results (including albumin-t-creatinine ratio, protein-to-creatinine ratio) at 2 and 5 years post-index (as the patient’s first available serum creatinine result). The performance of the model was evaluated. , and semi-quantitative dipsticks.
A total of 4,410,131 patients were included in the analysis. The Medicare Advantage and Medicaid populations consisted of 341,666 and 93,056 people, respectively. Clin risk performance was measured using discrimination (area under the receiver operating characteristic curve). [AUC]), calibration plots, and Brier scores. The authors noted that identification results were very good overall, regardless of whether the payer had urine test results. Across all cohorts, AUC ranged from 0.80 to 0.83 at 2 years and 0.78 to 0.83 at 5 years. When urinalysis data were available, these ranges at 2 and 5 years were 0.81 to 0.87 and 0.80 to 0.87. For each combination of insurance company type and urine test coverage, Brier scores ranged from 0.068 to 0.075.
For these populations, the validity of the Klinsk model for predicting progressive CKD was further validated. The ability to identify adults who are at risk for CKD or who already have CKD could have significant benefits for patients. Among these benefits, the authors conclude by highlighting the potential for earlier intervention, slowing disease progression, and even reducing healthcare costs by utilizing the Klinsk model. .
reference
1. Rochon H, Osenenko KM, Chatterjee S, Donato BM. A systematic literature review of the economic burden of CKD in the United States. Poster presented at ASN Kidney Week 2023. From November 2nd to 5th. Philadelphia, Pennsylvania.
2. Tangri N, Ferguson TW, Bamforth RJ. Permanent validation of the ClinRisk model in U.S. commercial, Medicare Advantage, and Medicaid populations. Poster presented at ASN Kidney Week 2023. From November 2nd to 5th. Philadelphia, Pennsylvania.
