Neighborhood Socioeconomic Status and Identification of Patients With CKD Using Electronic Health Records

Rationale & objective: Screening for chronic kidney disease (CKD) is recommended for patients with diabetes and hypertension as stated by the respective professional societies. However, CKD, a silent disease usually detected at later stages, is associated with low socioeconomic status (SES). We assessed whether adding census tract SES status to the standard screening approach improves our ability to identify patients with CKD.

Study design: Screening test analysis.

Settings & participants: Electronic health records (EHR) of 256,162 patients seen at a health care system in the 7-county Minneapolis/St. Paul area and linked census tract data.

Exposure: The first quartile of census tract SES (median value of owner-occupied housing units <$165,200; average household income <$35,935; percentage of residents >25 years of age with a bachelor's degree or higher <20.4%), hypertension, and diabetes.

Outcomes: CKD (eGFR <60 mL/min/1.73 m², or urinary albumin-creatinine ratio >30mg/g, or urinary protein-creatinine ratio >150mg/g, or urinary analysis [albuminuria] >30 mg/d).

Analytical approach: Sensitivity, specificity, and number needed to screen (NNS) to detect CKD if we screened patients who had hypertension and/or diabetes and/or who lived in low-SES tracts (belonging to the first quartile of any of the 3 measures of tract SES) versus the standard approach.

Results: CKD was prevalent in 13% of our cohort. Sensitivity, specificity, and NNS of detecting CKD after adding tract SES to the screening approach were 67% (95% CI, 66.2%-67.2%), 61% (95% CI, 61.1%-61.5%), and 5, respectively. With the standard approach, sensitivity of detecting CKD was 60% (95% CI, 59.4%-60.4%), specificity was 73% (95% CI, 72.4%-72.7%), and NNS was 4.

Limitations: One health care system and selection bias.

Conclusions: Leveraging patients' addresses from the EHR and adding tract-level SES to the standard screening approach modestly increases the sensitivity of detecting patients with CKD at a cost of decreased specificity. Identifying further factors that improve CKD detection at an early stage are needed to slow the progression of CKD and prevent cardiovascular complications.