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American Journal of Kidney Diseases

Burden and Cost of Caring for US Veterans With CKD: Initial Findings From the VA Renal Information System (VA-REINS)

Published:September 02, 2020DOI:https://doi.org/10.1053/j.ajkd.2020.07.013
      Kidney disease is a common, complex, costly, and life-limiting condition. Most kidney disease registries or information systems have been limited to single institutions or regions. A national US Department of Veterans Affairs (VA) Renal Information System (VA-REINS) was recently developed. We describe its creation and present key initial findings related to chronic kidney disease (CKD) without kidney replacement therapy (KRT). Data from the VA’s Corporate Data Warehouse were processed and linked with national Medicare data for patients with CKD receiving KRT. Operational definitions for VA user, CKD, acute kidney injury, and kidney failure were developed. Among 7 million VA users in fiscal year 2014, CKD was identified using either a strict or liberal operational definition in 1.1 million (16.4%) and 2.5 million (36.3%) veterans, respectively. Most were identified using an estimated glomerular filtration rate laboratory phenotype, some through proteinuria assessment, and very few through International Classification of Diseases, Ninth Revision coding. The VA spent ∼$18 billion for the care of patients with CKD without KRT, most of which was for CKD stage 3, with higher per-patient costs by CKD stage. VA-REINS can be leveraged for disease surveillance, population health management, and improving the quality and value of care, thereby enhancing VA’s capacity as a patient-centered learning health system for US veterans.

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      References

        • Saran R.
        • Robinson B.
        • Abbott K.C.
        • et al.
        US Renal Data System 2018 Annual Data Report: epidemiology of kidney disease in the United States.
        Am J Kidney Dis. 2019; 73: A7-A8
        • Jha V.
        • Garcia-Garcia G.
        • Iseki K.
        • et al.
        Chronic kidney disease: global dimension and perspectives [erratum in: Lancet. 2013;382(9888):208].
        Lancet. 2013; 382: 260-272
        • Romagnani P.
        • Remuzzi G.
        • Glassock R.
        • et al.
        Chronic kidney disease.
        Nat Rev Dis Primers. 2017; 3: 17088
        • Levin A.
        • Tonelli M.
        • Bonventre J.
        • et al.
        ISN Global Kidney Health Summit participants. Global kidney health 2017 and beyond: a roadmap for closing gaps in care, research, and policy.
        Lancet. 2017; 390: 1888-1917
        • Saran R.
        • Hedgeman E.
        • Plantinga L.
        • et al.
        • CKD Surveillance Team
        Establishing a national chronic kidney disease surveillance system for the United States.
        Clin J Am Soc Nephrol. 2010; 5: 152-161
        • Atkins D.
        • Kilbourne A.M.
        • Shulkin D.
        Moving from discovery to system-wide change: the role of research in a learning health care system: experience from three decades of health systems research in the Veterans Health Administration.
        Annu Rev Public Health. 2017; 38: 467-487
      1. Department of Veterans Affairs FY 2018-2024 Strategic Plan.
        (Accessed May 11, 2019)
        • Arnold N.
        • Sohn M.
        • Maynard C.
        • Hynes D.M.
        VIReC Technical Report 2: VANDI Mortality Data Merge Project.
        Edward Hines, Jr VA Hospital, VA Information Resource Center, Hines, ILApril 9, 2006
        • Levey A.S.
        • Stevens L.A.
        • Schmid C.H.
        • et al.
        CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate [erratum in: Ann Intern Med. 2011;155(6):408].
        Ann Intern Med. 2009; 150: 604-612
        • Regenstrief Institute
        Logical observation identifiers names and codes.
        (Accessed March 21, 2020)
        • Centers for Medicare & Medicaid Services
        Dialysis Facility Reports.
        (Accessed March 21, 2020)
        • Charlson M.E.
        • Pompei P.
        • Ales K.L.
        • MacKenzie C.R.
        A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
        J Chronic Dis. 1987; 40: 373-383
        • Groll D.L.
        • To T.
        • Bombardier C.
        • Wright J.G.
        The development of a comorbidity index with physical function as the outcome.
        J Clin Epidemiol. 2005; 58: 595-602
        • Blow F.C.
        • McCarthy J.F.
        • Valenstein M.
        • Zeber J.
        • Gillon L.
        Care for veterans with psychosis in the VHA, FY02: 4th Annual National Psychosis Registry Report. 2003. VA National Serious Mental Illness Treatment Research and Evaluation Center.
        (Accessed March 15, 2020)
      2. Chronic Conditions Data Warehouse.
        (Accessed March 21, 2020)
        • KDIGO: Kidney Disease: Improving Global Outcomes CKD Work Group
        KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease.
        Kidney Int Suppl. 2013; 3: 1-150
        • Carroll M.F.
        • Temte J.L.
        Proteinuria in adults: a diagnostic approach.
        Am Fam Physician. 2000; 62: 1333-1340
        • Dunn A.
        • Grosse S.D.
        • Zuvekas S.H.
        Adjusting health expenditures for inflation: a review of measures for health services research in the United States.
        Health Serv Res. 2018; 53: 175-196
        • Navaneethan S.D.
        • Jolly S.E.
        • Schold J.D.
        • et al.
        Development and validation of an electronic health record-based chronic kidney disease registry.
        Clin J Am Soc Nephrol. 2011; 6: 40-49
        • Rutkowski M.
        • Mann W.
        • Derose S.
        • et al.
        Implementing KDOQI CKD definition and staging guidelines in Southern California Kaiser Permanente.
        Am J Kidney Dis. 2009; 53: S86-S99
        • Mendu M.L.
        • Ahmed S.
        • Maron J.K.
        • et al.
        Development of an electronic health record-based chronic kidney disease registry to promote population health management.
        BMC Nephrol. 2019; 20: 72
        • Shahinian V.B.
        • Hedgeman E.
        • Gillespie B.W.
        • et al.
        Estimating prevalence of CKD stages 3-5 using health system data.
        Am J Kidney Dis. 2013; 61: 930-938
        • Saran R.
        • Li Y.
        • Robinson B.
        • et al.
        US Renal Data System 2015 Annual Data Report: epidemiology of kidney disease in the United States.
        Am J Kidney Dis. 2016; 67 (S1-S305): Svii