Validation of acute myocardial infarction (AMI) in electronic medical records: the SPEED-EXTRACT Study

Abstract

ObjectivesTo determine whether data captured in electronic medical records (eMR) is sufficient to serve as a clinical data source to make a reliable determination of ST elevation myocardial infarction (STEMI) and non-ST elevation myocardial infarction (NSTEMI) and to use these eMR derived diagnoses to validate ICD-10 codes for STEMI and NSTEMI.DesignRetrospective validation by blind chart review of a purposive sample of patients with a troponin test result, ECG record, and medical note available in the eMR.SettingTwo local health districts containing two tertiary hospitals and six referral hospitals in New South Wales, Australia.ParticipantsN = 897 adult patients who had a hs-troponin test result indicating suspected AMI.Primary outcome measuresInter-rater reliability of clinical diagnosis (κ) for ST-elevated myocardial infarction (STEMI) and Non-ST elevated myocardial infarction (NSTEMI); and sensitivity, specificity, and positive predictive value (PPV) of ICD-10 codes for STEMI and NSTEMI.ResultsThe diagnostic agreement between clinical experts was high for STEMI (κ = 0.786) but lower for NSTEMI (κ = 0.548). ICD-10 STEMI codes had moderate sensitivity (Se = 88±6.7), very high specificity (Sp = 99±0.7) and high positive predictive value (PPV = 91±6). NSTEMI ICD-10 codes were lower in each case (Se = 69±6.4, Sp = 96.0±1.5, PPV = 84±6).ConclusionsThe eMR held sufficient clinical data to reliably diagnose STEMI, producing high inter-rater agreement among our expert reviewers as well as allowing reasonably precise estimates of the accuracy of administrative ICD-10 codes. However the clinical detail held in the eMR was less sufficient to diagnose NSTEMI, indicated by a lower inter-rater agreement. Efforts should be directed towards operationalising the clinical definition of NSTEMI and improving clinical record keeping to enable an accurate description of the clinical phenotype in the eMR, and thus improve reliability of the diagnosis of NSTEMI using these data sources.Article SummaryStrengths and limitations of this studyExpert chart review provided a robust evaluation of the reliability and sufficiency of data directly extracted from the EMR for the diagnosis of AMIComputational interrogation and extraction of the eMR (via SPEED-EXTRACT) allowed us to use a wide selection for inclusion in the sample on the basis of clinical data independent of ICD-10 code, enabling the capture of missed cases (i.e., uncoded AMI) and so determine estimates for the false negative rate and sensitivityResults were necessarily based on the subset of patients with sufficient clinical data in the eMR. Inferences from this subset to the wider patient pool will be biased when the availability of records varies with diagnosisAt least two sources of uncertainty in the gold reference standard we used are indistinguishable: uncertainty due to poor clinical detail in the eMR, and uncertainty due to a weak operational definition of the diagnosis (e.g., NSTEMI).

Comparison of care and outcomes for myocardial infarction by heart failure status between United Kingdom and Japan

“…Fourth, in using ICD10 codes, JROAD may have misclassified some patients with STEMI. However, a recent study showed selecting STEMI by ICD10 code had high sensitivity and specificity 33,34 . Fifth, our data do not include comparable information on emergency care prior to hospitalization.…”

“…However, a recent study showed selecting STEMI by ICD10 code had high sensitivity and specificity. 33 , 34 Fifth, our data do not include comparable information on emergency care prior to hospitalization. Though emergency medical care is provided to the entire population under the NHS system in the United Kingdom and the compulsory and universal health insurance system in Japan, there may be differences in the process of treatment pre‐hospital which could lead to differences in the distribution of disease severity between two cohorts.…”

Registry randomised trials: a methodological perspective

“… 23 It has recently been suggested that linkage of electronic medical records can be successfully used to provide near real-time clinical audit with feedback to clinicians, and provide a framework for clinical decision support. 24 …”

“…Medical records contain a tremendous accumulation of data, and it was hoped that electronic data processing systems would allow for organised, chronological records of patient information that could be used to facilitate research and hospital reporting 23. It has recently been suggested that linkage of electronic medical records can be successfully used to provide near real-time clinical audit with feedback to clinicians, and provide a framework for clinical decision support 24…”