Myocardial infarction and the validation of physician billing and hospitalization data using electronic medical records.
OBJECTIVE
Population-based identification of patients with a myocardial infarction is limited to patients presenting to hospital with an acute event. We set out to determine if adding physician billing data to hospital discharge data would result in an accurate capture of patients who have had a myocardial infarction.


METHODS
We performed a retrospective chart abstraction of 969 randomly selected adult patients using data abstracted from primary care physicians on an electronic medical record in Ontario, Canada, as the reference standard.


RESULTS
An algorithm of 3 physician billings in a one-year period with at least one being by a specialist or within a hospital or emergency room plus one hospital discharge abstract performed with a sensitivity of 80.4% (95% CI: 69.5-91.3), specificity of 98.0% (95% CI: 97.1-98.9), positive predictive value of 69.5% (95% CI: 57.7-81.2), negative predictive value of 98.9% (95% CI: 98.2% to 99.6%) and kappa statistic of 0.73 (95% CI: 0.63-0.83).


CONCLUSIONS
Using a combination of hospital discharge abstracts and physician billing data may be the best way of assessing trends of MI occurrence over time since it increases the capture of MI beyond those patients who have been hospitalized.
Tu
K
K
Institute for Clinical Evaluative Sciences (ICES), Toronto, Canada. karen.tu@ices.on.ca
Mitiku
T
T
Guo
H
H
Lee
D S
DS
Tu
J V
JV
D057286:Electronic Health Records; D005251:Fees, Medical / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D009203:Myocardial Infarction / Q000453:epidemiology*; D009864:Ontario / Q000453:epidemiology; D011320:Primary Health Care / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity