Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink
Hammad, T. A., Margulis, A., Ding, Y., Strazzeri, M. M., & Epperly, H. (2013). Determining the predictive value of Read codes to identify congenital cardiac malformations in the UK Clinical Practice Research Datalink. Pharmacoepidemiology and Drug Safety, 22(11), 1233-1238. DOI: 10.1002/pds.3511
The purposes of this study were to determine (i) the positive predictive value (PPV) of multiple Read codes used to identify congenital cardiac malformation (CCM) cases in the UK Clinical Practice Research Datalink (CPRD); (ii) the accuracy of the diagnosis date; and (iii) the source of information that the general practitioners (GPs) use for validating the diagnosis suggested by the code.
Eight hundred eighty-eight records with Read diagnostic and procedures codes for CCM, between January 1996 and November 2010, were identified from CPRD. Questionnaires were sent to GPs to verify the diagnoses and date of the code-identified events.
A total of 719 questionnaires were returned (81% response rate). The PPV of the CCM codes was 93% (670/719). Thirty-one percent of cases had a different event date than the one recorded in the electronic medical record (EMR); 10% of these differing dates were within 30?days of the code-identified CCM date. GPs used a variety of data sources to confirm CCM diagnoses. Although the EMR was the most frequently used data source (70%), 66% reported using consultation letters, 9% reported using clinical notes or paper charts, and 35% of GPs reported using the hospital record to confirm the CCM diagnosis.
Clinical Practice Research Datalink Read codes for CCMs have 93% PPV and most likely point to true cases. However, the accuracy of diagnosis dates and the age at diagnosis may not be as reliable. The findings of this study indicate that GPs use information beyond what is available for researchers in the EMR to confirm clinical diagnoses when responding to validation questionnaires. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.