NDT Advance Access originally published online on July 19, 2005
Nephrology Dialysis Transplantation 2005 20(10):2089-2096; doi:10.1093/ndt/gfi006
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The validity of searching routinely collected general practice computer data to identify patients with chronic kidney disease (CKD): a manual review of 500 medical records
1 St George's and 2 Primary Care Informatics, Division of Community Health Sciences, St George's, University of London, London SW17 0RE, UK, 3 Department of Renal Medicine, Kent and Canterbury Hospital, Ethelbert Road, Canterbury, Kent CT1 3NG, UK, 4 Department of Renal Medicine, Salford Royal Hospitals NHS Trust, Hope Hospital, Salford M6 8HD, UK and 5 Roche Products Ltd, Welwyn Garden City, Hertfordshire, AL7 3AY, UK
Correspondence and offprint requests to: Simon de Lusignan, St George's, University of London, London SW17 0RE, UK. Email: slusigna{at}sgul.ac.uk
Background. We conducted a search of 12 practices’ routinely collected computer data in three localities across the UK and found that 4.9% of the registered population had an estimated glomerular filtration rate (GFR) of <60 ml/min/1.73 m2 (equivalent to stages 3–5 CKD). Only 3.6% of these were known to have renal disease. Although UK general practice is computerized, important clinical data might be recorded in letters or free-text computer entries and might therefore be invisible to the standard computer search tools. We therefore manually searched through all the records of patients with stages 3–5 CKD in one practice, to test the validity of the computer generated diagnosis and to see if other relevant information was missed by the computer search.
Methods. We identified 492 people with stages 3–5 CKD using computer searching and then manually searched their computer records and written notes for any missed data. The dataset included cardiovascular morbidities and risk factors including diabetes; drugs which may impair renal function; known renal disease; and terminal diagnoses and dementia.
Results. The manual searches only added four renal diagnoses to the 36 already identified. Although heart failure and stroke appear to be over-estimated by computer searches, other cardiovascular diagnoses were reliably recorded. Cardiovascular risk factors and drug recording is a strength of general practice computer data. It is complete and contemporary, though most patients had scope to have their cardiovascular risk reduced further. Eighty-four percent had a haemoglobin estimation, and a higher proportion with reduced renal function were anaemic (P<0.001). Testing for proteinuria was less well recorded; negative stick tests were not recorded. Clinical diagnoses of prostatism and bladder outflow problems made these data hard to interpret.
Conclusions. Automated searching of general practice computer records could provide a reliable and valid way of identifying people with stages 3–5 CKD who could benefit from interventions readily available in primary care.
Keywords: chronic kidney disease; computerized medical records system; computers; family practice; glomerular filtration rate; mass screening
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