Objectives
We aimed to design and test a method to extract information on antithrombotic therapy from anonymised free-text notes in the Clinical Practice Research Datalink (CPRD).
SettingGeneral practice database representative of the UK.
ParticipantsAll patients undergoing total hip replacement (THR, n=25 898) or total knee replacement (TKR, n=22 231) between January 2008 and October 2012 were included. Antithrombotic drug use related to THR or TKR was identified using anonymised free text and prescription data.
Primary and secondary outcome measuresInternal validity of our newly designed method was determined by calculating positive predictive values (PPVs) of hits for predefined keywords in a random sample of anonymised free-text notes. In order to determine potential detection bias, total joint replacement (TJR) patient characteristics were compared as per their status of exposure to antithrombotics.
ResultsPPVs ranging between 97% and 99% for new oral anticoagulants (NOAC) or low-molecular weight heparins (LMWH) exposure related to TJR were obtained with our method. Our search strategy increased detection rates by 57%, yielding a total proportion of 18.5% of all THR and 18.6% of all TKR surgeries. Identified users of NOACs and LMWHs were largely similar with regards to age, sex, lifestyle, disease and drug history compared to patients without identified drug use.
ConclusionsWe have developed a useful method to identify additional exposure to NOACs or LMWHs with TJR surgery.
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