CKD impacts a large and diverse population in the United States, making provision of high-value CKD care both critical and inherently challenging. Value-based health care aims to provide high-quality care to individuals and populations while controlling costs. Value is often defined by quality as a function of cost. Value is greater if quality improves while costs remain unchanged or if quality remains unchanged while costs decrease. Current value-based care models incorporate these principles, measuring quality via performance metrics and calculating observed versus expected costs. These cost calculations, which comprise the denominator in the value equation, often are used in shared savings models, like the Kidney Care Choices (KCC) model Comprehensive Kidney Care Contracting options and, before that, the End-Stage Renal Disease Seamless Care Organizations (1). Importantly, the KCC model includes CKD stages 4 and 5 nondialysis populations, and thus, predicting costs for these individuals is critical to the valid implementation of shared savings. Additionally, valid assessment of risk is essential to identify successful interventions to delay progression of CKD to kidney failure.
Quality is the numerator in the value equation, and inherent in providing high-value care is determining what constitutes quality and how to measure it. The Centers for Medicare & Medicaid Services implemented the End-Stage Renal Disease Quality Incentive Program in 2012 as a value-based care program that seeks to incentivize high-value dialysis care through reimbursement penalties to facilities that do not perform adequately on a number of clinical and reporting quality measures. To date, however, no value-based program exists specifically for CKD despite the high prevalence of CKD, its high associated costs, and the risk of progression to kidney failure (2).
In this issue of CJASN, Prasad and colleagues evaluate the Kidney Failure Risk Equation (KFRE), a risk calculator for predicting the risk of dialysis, as an indicator of costs among individuals with CKD stages 3 and 4 in Saskatchewan, Canada (3). Prasad and colleagues posit that this methodology could be used to predict costs and resource utilization in the care of patients with moderate to severe CKD, thus informing efforts to provide high-value care to this population.
What Does This Study Show?
The authors utilize the KFRE to stratify risk among patients with CKD stage 3 (estimated GFR 30–59 ml/min per 1.73 m2) and CKD stage 4 (estimated GFR 15–29 ml/min per 1.73 m2) on the basis of the KFRE-determined risk of progression to dialysis. The KFRE is a prediction model introduced in 2011 and developed from two independent Canadian cohorts (4). It uses age, sex, region, estimated GFR, and urine albumin-to-creatinine ratio, with the option of also using serum albumin, phosphate, bicarbonate, and corrected calcium, to produce a risk estimate of initiating dialysis. It has been validated for use outside of Canada (5). The study population examined by Prasad and colleagues included 1003 adult patients treated in CKD clinics in Saskatchewan, Canada from 2004 to 2012 who were then followed for 5 additional years to evaluate health care cost and utilization. Patients with CKD were stratified as low, medium, and high risk for progression within each CKD stage. The primary outcome was costs associated with hospitalizations, physician visits, and medications. Patients (and associated costs) were censored at death and dialysis initiation.
The investigators show that, for patients with CKD stage 3, those at high risk for progression utilized approximately 50% more hospital-based and physician-based services relative to those in the low-risk group. There was no significant difference in drug utilization. Among patients with CKD stage 4, results were similar, with high-risk patients using significantly more hospital- and physician-based services. Total costs over 5 years were higher among high-risk compared with low-risk patients within both CKD stages. Among the CKD stage 3 group, cost differences were significant between low- and high-risk groups only for medications. Among the CKD stage 4 group, high-risk patients had significantly higher costs in all areas. These results provide insights into a potential strategy of using overall risk rather than eGFR-based CKD staging only for predicting high resource utilization.
A limitation of this study is generalizability. Utilization and costs were derived from kidney care provided in the context of multidisciplinary CKD clinics within the Canadian health care system. In contrast, care for nondialysis patients with CKD in the United States is provided across a range of payers such that care delivery is inherently variable, although Medicare remains the primary payer for a large proportion of older adults with CKD. Thus, although we would expect US patients at high risk for progression to also incur higher costs, cost and utilization likely vary more in the United States on the basis of insurance status and other socioeconomic factors. A second limitation is that the KFRE focuses on predicting risk of dialysis, not kidney failure, such that older individuals with otherwise identical risk factors have a lower KFRE score than younger individuals owing to a competing risk of death. This potentially may have led to lower costs due to death during follow-up and may further impact generalizability to the US population, where older individuals with kidney disease may be more likely to initiate kidney replacement therapy. Regardless, and consistent with the Kidney Disease Improving Global Outcomes (KDIGO) CKD Heat Map (6), a combination of estimated GFR and albuminuria appears to predict costs.
CKD and Value-Based Care in the United States
Data from the National Health and Nutrition Examination Survey (2015–2018) show that approximately 15% of the US adult population has CKD, as defined by either low eGFR or albuminuria (2). Care for patients with CKD varies widely, and a substantial portion of patients with CKD are unaware of their diagnosis of kidney disease (7). Despite its importance in predicting progression of kidney disease and risks of cardiovascular, and mortality outcomes in people with CKD, albuminuria is not routinely measured. Only 38% of Medicare enrollees aged 66 years or older with low eGFR had urine protein testing in 2018 (2). Recently, Ahmed and colleagues performed a retrospective analysis of data from a major regional health care system using the KFRE to examine the association between “high-” and “low”-risk patients with CKD and various clinical quality metrics (8). Notably, 70% of their potential sample was excluded from analyses due to missing data on albuminuria, preventing calculation of a KFRE score.
Literature examining models of value-based care for patients with CKD is limited. Brady and colleagues used private preferred-provider organization claims data to identify qualities of high-value nephrology practices on the basis of total cost of care as well as a composite measure of quality of care for patients with nondialysis CKD and for patients receiving dialysis (9). They found that high-value practices had lower costs, with risk-adjusted per capita monthly spending approximately 24% lower than for average-value practices. In addition, they identified qualities of high-value practices, including the use of multidisciplinary, highly responsive care teams to provide accessible care to patients with the goal of preventing unnecessary hospitalization and emergency department visits, patient education programs to empower self-care, preparations to increase the efficiency of office visits, use of clinical decision tools and protocols to guide decision making regarding high-cost services, and investment in infrastructure to support high-value care. This analysis suggests that transitioning from average to high-value care likely requires upfront investment to implement teams to provide targeted, individualized care to the highest risk patients.
Innovations for CKD Care Provision in the United States
The Kidney Care Choices model, beginning on January 1, 2022, is an opportunity to improve the value and quality of care provided to patients with CKD in the United States. The model, which includes patients with CKD stages 4 and 5 as well as patients receiving dialysis, offers four voluntary payment options for participating providers, including the Kidney Care First (KCF) option and three Comprehensive Kidney Care Contracting options. Within the KCF option, participating nephrology practices will receive payment adjustments on the basis of quality indicators as well as costs and utilization among patients with late-stage CKD and those receiving dialysis. The Comprehensive Kidney Care Contracting options allow Kidney Contracting Entities (for which nephrologists are required whereas dialysis facilities are optional) to assume varying degrees of risk for Medicare part A and B costs, with the potential reward of cost savings commensurate with the degree of risk. Initial quality metrics for the Kidney Care Choices model include depression remission and patient activation as well as optimal dialysis starts and, for the KCF only, a cost measure (1). Similar to the End-Stage Renal Disease Quality Incentive Program, participating practices must reach a certain quality performance or improvement thresholds in these measures to avoid a potentially substantial financial penalty.
Given the inclusion of advanced CKD in these models, it is critical, both for resource allocation for model participants and for expected cost calculations for shared savings options, to assess accurately which patients are at high risk for adverse outcomes. The KFRE provides one option for this, as does the existing CKD Heat Map. Critically, both of these instruments incorporate albuminuria, a measure that all too often is missing from clinical and administrative data sources. On November 1, 2021, the New York Times published an article titled: “Are too many older adults told they have kidney disease?” (10). Although this article recognized that risk is heterogeneous among individuals with low GFR, it critically failed to highlight that the key piece of data to help identify this heterogeneity, albuminuria assessment, is readily obtainable but too often not assessed. A recipe for successful provision of high-value care for patients with CKD exists, but it will not succeed without first ensuring we have the key ingredients—both eGFR and albuminuria—to identify patients at greatest risk and therefore who can benefit most.
Disclosures
D.E. Weiner is the Medical Director of Clinical Research for Dialysis Clinic, Inc. (DCI), with salary support paid to his institution for this role; participated in medical advisory boards for Akebia (2020, 2021), Cara Therapeutics (2020), Janssen Biopharmaceuticals (2019), and Tricida (2019), with honoraria for Akebia paid to DCI; reports receiving research funding from AstraZeneca (site PI, completed 2020), CSL Behring (site PI, ongoing), DCI (site PI for trials contracted with DCI including Ardelyx [completed] and Cara Therapeutics [completed]), Goldfinch Bio (site PI, ongoing), and Janssen Biopharmaceuticals (site PI, completed 2019), with all compensation paid to Tufts Medical Center; receiving honoraria from National Kidney Foundation for editorial positions at Kidney Medicine and the American Journal of Kidney Diseases and from Elsevier for royalties from the National Kidney Foundation’s Primer on Kidney Diseases; serving as a member of American Society of Nephrology (ASN) Quality and Policy Committees and ASN representative to KCP, chair of adjudications committee of VALOR Trial (George Institute, CRO), and member of the Data Monitoring Committee for “Feasibility of Hemodialysis with GARNET? in Chronic Hemodialysis Patients with a Bloodstream Infection” Trial (Avania CRO); and serving on the Scientific Advisory Board of National Kidney Foundation. The remaining author has nothing to disclose.
Funding
A.C. Reaves is funded by National Center for Advancing Translational Sciences grant TL1TR002546.
Acknowledgments
The content of this article reflects the personal experience and views of the author(s) and should not be considered medical advice or recommendation. The content does not reflect the views or opinions of the American Society of Nephrology (ASN) or CJASN. Responsibility for the information and views expressed herein lies entirely with the author(s).
References
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