Identifying patients with chronic kidney disease from general practice computer records

Fam Pract. 2005 Jun;22(3):234-41. doi: 10.1093/fampra/cmi026. Epub 2005 Apr 6.

Abstract

Background: Chronic kidney disease (CKD) is an important predictor of end-stage renal disease, as well as a marker of increased mortality. The New Opportunities for Early Renal Intervention by Computerised Assessment (NEOERICA) project aimed to assess whether people with undiagnosed CKD who might benefit from early intervention could be identified from GP computer records.

Methods: The simplified Modification of Diet in Renal Disease (MDRD) equation was used to estimate glomerular filtration rate (GFR) and determine stage of CKD in patients from 12 practices in Surrey, Kent and Greater Manchester with SCr recorded in their notes. Further data were extracted on associated co-morbidities and potentially modifiable risk factors.

Results: One quarter (25.7%; 28,862/112,215) had an SCr recorded and one in five (18.9%) of them had a GFR <60 ml/min/1.73 m2 (equivalent to Stage 3-5 CKD), representing 4.9% of the population. Only 3.6% of these were recorded as having renal disease. Three-quarters (74.6%; 4075/5449) of those with Stage 3-5 CKD had one or more circulatory diseases; 346 were prescribed potentially nephrotoxic drugs and over 4000 prescriptions were issued for drugs recommended to be used with caution in renal impairment.

Conclusions: Patients with CKD can be identified by searching GP computer databases; along with associated co-morbidities and treatment. Results revealed a similar rate of Stage 3-5 CKD to that found previously in the USA. The very low rate of recording of renal disease in patients found to have CKD indicates scope for improving detection and early intervention.

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • England / epidemiology
  • Family Practice / organization & administration*
  • Family Practice / statistics & numerical data
  • Feasibility Studies
  • Female
  • Glomerular Filtration Rate
  • Humans
  • Kidney Failure, Chronic / diagnosis
  • Kidney Failure, Chronic / epidemiology*
  • Kidney Failure, Chronic / physiopathology
  • Male
  • Medical Records Systems, Computerized / statistics & numerical data*
  • Middle Aged
  • Prevalence
  • Risk Factors
  • Sex Distribution