Use of electronic health records to ascertain, validate and phenotype acute myocardial infarction: A systematic review and recommendations

•1/33 studies used EHR-derived markers of myocardial necrosis.•0/33 used electrocardiogram findings from EHR.•31/33 had PPV ≥ 70% between EHR diagnosis and reference.•There is no definition of “gold standard” for cross-referencing AMI diagnosis.•Clear need to enhance EHR data for use in clinical care and research.

Electronic health records (EHRs) offer the opportunity to ascertain clinical outcomes at large scale and low cost, thus facilitating cohort studies, quality of care research and clinical trials. For acute myocardial infarction (AMI) the extent to which different EHR sources are accessible and accurate remains uncertain.Using MEDLINE and EMBASE we identified thirty three studies, reporting a total of 128 658 patients, published between January 2000 and July 2014 that permitted assessment of the validity of AMI diagnosis drawn from EHR sources against a reference such as manual chart review. In contrast to clinical practice, only one study used EHR-derived markers of myocardial necrosis to identify possible AMI cases, none used electrocardiogram findings and one used symptoms in the form of free text combined with coded diagnosis. The remaining studies relied mostly on coded diagnosis. Thirty one studies reported positive predictive value (PPV) ≥ 70% between AMI diagnosis from both secondary care and primary care EHRs and the reference. Among fifteen studies reporting EHR-derived AMI phenotypes, three cross-referenced ST-segment elevation AMI diagnosis (PPV range 71-100%), two non-ST-segment elevation AMI (PPV 91.0, 92.1%), three non-fatal AMI (PPV range 82-92.2%) and six fatal AMI (PPV range 64-91.7%).Clinical coding of EHR-derived AMI diagnosis in primary care and secondary care was found to be accurate in different clinical settings and for different phenotypes. However, markers of myocardial necrosis, ECG and symptoms, the cornerstones of a clinical diagnosis, are underutilised and remain a challenge to retrieve from EHRs.