Chronic kidney disease in an electronic health record problem list: quality of care, ESRD, and mortality

Am J Nephrol. 2014;39(4):288-96. doi: 10.1159/000360306. Epub 2014 Apr 1.


Background: Whether chronic kidney disease (CKD) recognition in an electronic health record (EHR) problem list improves processes of care or clinical outcomes of end-stage renal disease (ESRD) and death is unclear.

Methods: We identified patients who had at least 1 year of follow-up (2005-2009) in our EHR-based CKD registry (n = 25,742). CKD recognition was defined by having ICD-9 codes for CKD, diabetic kidney disease, or hypertensive kidney disease in the problem list. We calculated proportions of patients with and without CKD recognition and examined differences by demographics, clinical factors, and development of ESRD or mortality. We evaluated differences in the proportion of patients with CKD-specific laboratory results checked before and after recognition among cases and propensity-matched controls.

Results: Only 11% (n = 2,735) had CKD recognition in the problem list and they were younger (68 vs. 71 years), a higher proportion were male (61 vs. 37%) and African-American (21 vs. 10%) compared to those unrecognized. CKD-specific laboratory results for patients with estimated glomerular filtration rate (eGFR) 30-59 including intact parathyroid hormone (23 vs. 6%), vitamin D (22 vs. 18%), phosphorus (29 vs. 7%), and a urine check for proteinuria (55 vs. 36%) were significantly more likely to be done among those with CKD recognition (all p < 0.05). Similar results were found for eGFR <30 except for proteinuria and in our propensity score-matched control analysis. There was no independent association of CKD recognition with ESRD or mortality.

Conclusions: CKD recognition in the EHR problem list was low, but translated into more CKD-specific processes of care; however ESRD or mortality were not affected.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Electronic Health Records / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Ohio / epidemiology
  • Propensity Score
  • Quality of Health Care / statistics & numerical data*
  • Renal Insufficiency, Chronic / epidemiology*
  • Renal Insufficiency, Chronic / therapy