Abstract
BackgroundThe capacity of electronic health record (EHR) data to guide targeted surveillance in chronic kidney disease (CKD) is unclear. We sought to leverage EHR data for predicting risk of progressing from CKD to end-stage renal disease (ESRD) to help inform surveillance of CKD among vulnerable patients from the healthcare safety-net.MethodsWe conducted a retrospective cohort study of adults (n = 28,779) with CKD who received care within 2 regional safety-net health systems during 1996–2009 in the Western United States. The primary outcomes were progression to ESRD and death as ascertained by linkage with United States Renal Data System and Social Security Administration Death Master files, respectively, through September 29, 2011. We evaluated the performance of 3 models which included demographic, comorbidity and laboratory data to predict progression of CKD to ESRD in conditions commonly targeted for disease management (hypertension, diabetes, chronic viral diseases and severe CKD) using traditional discriminatory criteria (AUC) and recent criteria intended to guide population health management strategies.ResultsOverall, 1730 persons progressed to end-stage renal disease and 7628 died during median follow-up of 6.6 years. Performance of risk models incorporating common EHR variables was highest in hypertension, intermediate in diabetes and chronic viral diseases, and lowest in severe CKD. Surveillance of persons who were in the highest quintile of ESRD risk yielded 83–94 %, 74–95 %, and 75–82 % of cases who progressed to ESRD among patients with hypertension, diabetes and chronic viral diseases, respectively. Similar surveillance yielded 42–71 % of ESRD cases among those with severe CKD. Discrimination in all conditions was universally high (AUC ≥0.80) when evaluated using traditional criteria.ConclusionsRecently proposed discriminatory criteria account for varying risk distribution and when applied to common clinical conditions may help to inform surveillance of CKD in diverse populations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12882-016-0272-0) contains supplementary material, which is available to authorized users.
Highlights
The capacity of electronic health record (EHR) data to guide targeted surveillance in chronic kidney disease (CKD) is unclear
We defined CKD stage 3–5 based on the presence of 2 or more serum creatinine measurements yielding an estimated glomerular filtration rate
Men comprised a majority of patients with chronic viral disease and severe CKD, and women comprised over half of patients in the hypertension and diabetes mellitus subgroups
Summary
The capacity of electronic health record (EHR) data to guide targeted surveillance in chronic kidney disease (CKD) is unclear. Xie et al BMC Nephrology (2016) 17:57 increasingly receive their care from Chronic Disease Management teams [12, 13] These clinic-based teams typically target patients with specific conditions (e.g., diabetes mellitus, hypertension, chronic viral diseases, congestive heart failure, severe CKD, etc.) and seek to optimize important risk factors for progressive disease, disability and mortality [13, 14]. Even within these clinic- or disease-based practices most individuals with CKD will not progress to ESRD. Whether data from the EHR can be “meaningfully” used to identify persons at high risk for progressive CKD within this practice-based construct is unclear
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