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

Abstract

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.

Routinely collected general practice data: goldmines for research? A report of the European Federation for Medical Informatics Primary Care Informatics Working Group (EFMI PCIWG) from MIE2006, Maastricht, The Netherlands

“…Programmes of research should include either direct or simulated methods for validating routinely collected data. The former might include painstaking hand searches through records (for instance, a hand search of 500 records of people with chronic kidney disease to validate a larger study 21 ), comparison with other studies and simulation of a clinical case to explore how it might be represented in the clinical record (see Box 1).…”

Routinely-collected general practice data are complex, but with systematic processing can be used for quality improvement and research

“…Only a manual search of 500 paper records confirmed that the computer data were reliable. 21 Data quality is also variable between different clinical areas. The input problems associated with the diagnosis of bronchitis make it hard to extract meaningful data about COPD from general practice computer records.…”

Online resources for chronic kidney disease (CKD) for primary care

“…A subsequent hand-search of 500 records in one practice suggested the computer results were reliable, with only four more cases having an indication that they had CKD only in their written records but not in the computer record. 21 The challenge of improving the management of CKD Primary care professionals involved in the CKD improvement programme had four challenges: GP colleagues were often unaware that the prevalence of CKD was so high (5%); they were not familiar with the evidence base; the stratification of risk took place outside the computerised medical record using a method with which they were unfamiliar (i.e. the estimation of GFR); and they were found lacking in implementing best practice.…”