1. Impact of Setting and Clinical Information on ECG Interpretation R. Roberts, M. Everett,R. McNutt,, T. Kirages, A. Papadapolos, R. Rydman, R. Doug Scott

2. Introduction Accurate ECG assessment is paramount Accurate ECG assessment is paramount ECGs provide key information important in: ECGs provide key information important in: Thrombolytics Thrombolytics Risk Adjustment for Chest Pain Risk Adjustment for Chest Pain Diagnosis Diagnosis Changes in clinical status Changes in clinical status

3. Objective Our aim was to explore the effect of: Our aim was to explore the effect of: 1) Intra-rater reliability: inter-settings (same MD, different setting) (same MD, different setting) 2) Intra-rater reliability: intra-settings (same MD, same setting) (same MD, same setting)

4. Methods Intra-rater: inter-setting Setting: 21 ED Physicians (MD) who documented the ECG interpretation for 1600 patients with chest pain admitted to the hospital. Setting: 21 ED Physicians (MD) who documented the ECG interpretation for 1600 patients with chest pain admitted to the hospital. We randomly selected 10 ECGs per MD originally interpreted as “abnormal” We randomly selected 10 ECGs per MD originally interpreted as “abnormal” Abnormal ECG: Abnormal ECG: Pathologic q waves Pathologic q waves ST elevation or depression ST elevation or depression T wave inversion (TWI) T wave inversion (TWI) Left Bundle Branch Block (LBBB) Left Bundle Branch Block (LBBB)

5. Methods Intra-rater: intra-setting Intra-rater reliability Re-interpretation of the ECGs by the same MD in a different setting Re-interpretation of the ECGs by the same MD in a different setting Inter-rater reliability 10 ECGs (never seen before) were interpreted by 20 MDs on 2 separate occasions in the same setting (conference room) 10 ECGs (never seen before) were interpreted by 20 MDs on 2 separate occasions in the same setting (conference room)

6. Methods (1) ECG reading (real time) Randomly selected 10/ MD (2) MD rereads 2 nd ECG (conference room) (3) 10 new ECGs MD reads (conference room) (4) Same 10 ECGs MD reads (conference room) Hypothesis: Difference between #1 & #2 > difference between #3 & #4 Difference is due to setting and clinical concerns

7. Finding ED-Con Kappa Overall Agreement Con-ComKappa ST elev 86%89% Q waves 83%89% ST dep 83%82% TWI67%91% LBBB94%96% Total.5383%.6289% Results: Overall Agreement p<.05

8. Results - Summary Intra-rater reliability / Inter-setting: Intra-rater reliability / Inter-setting: 204 ECGs Perfect Agreement 83% 12% of “Abnormal” ECGs re-read as normal 12% of “Abnormal” ECGs re-read as normal Intra-rater reliability / Intra-setting: Intra-rater reliability / Intra-setting: 110 ECG Perfect Agreement 89%

9. Results Same Setting n= 209 (418 readings) ECGs p=<0.8 NS (T-test & Rank Sum) 71% 24 % 4% 0% Perfect Agreement

10. Results Different Setting ECGs Perfect Agreement n= 239 (478 readings) 48% 42% 7% 1% p=<.001 (T-test & Rank Sum)

11. Conclusions Agreement between 2 readings by the same MD is significantly greater when both readings occur in a non-clinical setting when compared to the readings between two different settings Agreement between 2 readings by the same MD is significantly greater when both readings occur in a non-clinical setting when compared to the readings between two different settings Rates of reversal from abnormal to normal interpretations are similar to rates of reversal seen in thrombolytic trials when ECGs are re- interpreted by a central authority Rates of reversal from abnormal to normal interpretations are similar to rates of reversal seen in thrombolytic trials when ECGs are re- interpreted by a central authority

12. Conclusions The difference in setting and the availability of clinical information may explain some of the variability in ECG interpretation The difference in setting and the availability of clinical information may explain some of the variability in ECG interpretation Previous studies showing the value of ECGs in predicting patient outcome often rely upon the clinical physician’s interpretation which may be influenced by clinical information Previous studies showing the value of ECGs in predicting patient outcome often rely upon the clinical physician’s interpretation which may be influenced by clinical information Our findings are similar to that of others

13. Final Thoughts Clinical information for ECG interpretation may influence patient outcomes Clinical information for ECG interpretation may influence patient outcomes Quality assurance is tied to clinical factors and settings Quality assurance is tied to clinical factors and settings

14. Limitations We used abnormal ECGs: “stacked the deck” We used abnormal ECGs: “stacked the deck” All patients were admitted All patients were admitted Future studies: Future studies: Larger sample Larger sample Include patients sent home Include patients sent home Study impact on patient outcomes and resource utilization Study impact on patient outcomes and resource utilization