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Background: Oral anticoagulants reduce stroke risk among atrial fibrillation (AF) patients, yet treatment rates remain low. A technology known as SMART on FHIR allows third party apps to integrate with electronic medical records (EMR) and provide decision support tools. University of Utah Health implemented an alpha version of an integrated MDCalc app - MDCalc on FHIR (MoF) - in the Epic EHR using a SMART on FHIR interface to enable multiple calculations, one of which was the CHA2DS2-VASc calculation. While MDCalc on FHIR is designed to automate inputs that are then reviewed by the practicing clinician with an opportunity to override with clinical judgment, we prospectively compared the automated app score - without physician oversight - with the clinician score, as an early measurement to evaluate accuracy and identify areas for improvement. Methods: We identified outpatient AF patients who were seen in the University of Utah’s cardiovascular clinics between 11/5/2018 and 12/7/2018. We used the MoF app to automatically calculate the CHA2DS2-VASc score within 24 hours of the identified clinic visit - without the MoF feature of allowing clinician interaction - and compared these values to the score documented by the clinician. We also categorized patients as either low risk of stroke or high risk of stroke and calculated the net reclassification index (NRI) using the app compared to documentation. Patients with an app score ≥2 were considered high risk, while patients with a documented score of ≥2 or were prescribed an oral anticoagulant were considered high risk. Results: We identified 200 AF patients, of whom 111 had a documented clinician score. The mean MoF app score was 3.79 (SD 1.86) compared to a mean clinician score of 3.25 (SD 1.63; p=0.02). The NRI was 13.5% (27 of 200) using the app compared to documentation. Ten percent (19 of 200) of patients were “up-classified” by the app, meaning they were high risk by app and low risk by the clinician. Four percent (8 of 200) of patients were “down-classified” by the app, meaning they were low risk by the app and high risk by the clinician. Upon review of these cases, and after accounting for patients who were or were not anticoagulated for a clinically relevant reason (history of bleeding, recent cardioversion, or patient preference), we found that three percent (5 of 200) of patients were “up-classified” by the app, and two percent (3 of 200) of patients were “down-classified” by the app, making the adjusted NRI 4% (8 of 200). Conclusion: SMART on FHIR enables third party vendors to create EMR-based apps, which could provide decision support and improve care. We found that our FHIR-app based approach tended to identify more comorbidities by using medication data to assign conditions, resulting in a higher CHA2DS2-VASc score compared to clinicians. These differences would have had a 4% effect on the actual decision to anticoagulate.

BackgroundClinical decision support tools for atrial fibrillation (AF) should include CHA2DS2- VASc scores to guide oral anticoagulant (OAC) treatment.ObjectiveWe compared automated, electronic medical record (EMR) generated CHA2DS2- VASc scores to clinician-documented scores, and report the resulting proportions of patients in the OAC treatment group.MethodsPatients were included if they had both a clinician documented and EMR-generated CHA2DS2-VASc score on the same day. EMR scores were based on billing codes, left ventricular ejection fraction from echocardiograms, and demographics; documented scores were identified using natural language processing. Patients were deemed “re-classified” if the EMR score was ≥2 but the documented score was <2, and vice versa. For the overall cohort and subgroups (sex and age group), we compared mean scores using paired t-tests and re-classification rates using chi-squared tests.ResultsAmong 5,767 patients, the mean scores were higher using EMR compared to documented scores (4.05 [SD 2.1] versus 3.13 [SD 1.8]; p<0.01) for the full cohort, and all subgroups (p<0.01 for all comparisons). If EMR scores were used to determine OAC treatment instead of documented scores, 8.3% (n=479, p<0.01) of patients would be re-classified, with 7.2% moving into and 1.1% moving out of the treatment group. Among 2,322 women, 4.7% (n=109, p<0.01) would be re-classified, with 4.1% into and 0.7% out of the treatment group. Among 3,445 men, 10.7% (n=370, p<0.01) would be re-classified, with 9.2% into and 1.5% out of the treatment group. Among 2,060 patients <65 years old, 18.1% (n=372, p<0.01) would be re-classified, with 15.8% into and 2.3% out of the treatment group. Among 1,877 patients 65-74 years old, 5.4% (n=101, p<0.01) would be re-classified, with 4.4% into and 1.0% out of the treatment group. Among 1,830 patients ≥75 years old, <1% would move into to the treatment group and none would move out of the treatment group.ConclusionsEMR-based CHA2DS2-VASc scores were, on average, almost a full point higher than the clinician-documented scores. Using EMR scores in lieu of documented scores would result in a significant proportion of patients moving into the treatment group, with the highest re-classifications rates in men and patients <65 years old.

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