Initiation And Continuation Of Guideline Directed Medical Therapy In Patients With Incident Heart Failure In A Large Integrated Health System
HFSA ePoster Library. Reza N. 09/10/21; 343385; 16
Nosheen Reza
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Abstract
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Introduction: Pragmatic clinical trials (PCTs) employ innovative approaches to improve clinical trial efficiency and reduce trial-related costs. Leveraging electronic medical records (EMR) has the potential to lower trial burden and cost related to patient follow-up and data acquisition.
Hypothesis: Centralized (EMR-based) and traditional (trial-based) methods of heart failure (HF) hospitalization endpoint capture are comparable.
Methods: In the Veteran Affairs (VA) national integrated EMR, we used four distinct algorithms: 1) any (primary or secondary) discharge diagnosis code of HF; 2) any discharge diagnosis code of HF and IV diuretic use during associated hospitalization; 3) principal discharge diagnosis code of HF; 4) principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization, to identify HF hospitalizations for 405 Veteran participants of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated heart failure (INVESTED) PCT. HF hospitalizations identified by EMR were compared to INVESTED study events adjudicated according to FDA definitions by a blinded clinical events committee. Sensitivity and specificity of the EMR algorithms were estimated with the adjudication by the clinical events committee as the gold standard.
Results: Sensitivity and specificity for each algorithm are shown in Table 1. The algorithm comprising any discharge diagnosis code of HF had the highest sensitivity, while the principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization algorithm had the highest specificity. The algorithm containing any discharge diagnosis code for HF with IV diuretic use during associated hospitalization had the optimal balance between correctly capturing and classifying HF hospitalizations and distinguishing non-HF hospitalizations.
Conclusions: Centralized endpoint capture of HF hospitalizations is sensitive and highly specific when compared to traditional methods for all algorithms examined. Any discharge diagnosis code of HF combined with IV diuretic use during associated hospitalization had the best combination of sensitivity and specificity.
Hypothesis: Centralized (EMR-based) and traditional (trial-based) methods of heart failure (HF) hospitalization endpoint capture are comparable.
Methods: In the Veteran Affairs (VA) national integrated EMR, we used four distinct algorithms: 1) any (primary or secondary) discharge diagnosis code of HF; 2) any discharge diagnosis code of HF and IV diuretic use during associated hospitalization; 3) principal discharge diagnosis code of HF; 4) principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization, to identify HF hospitalizations for 405 Veteran participants of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated heart failure (INVESTED) PCT. HF hospitalizations identified by EMR were compared to INVESTED study events adjudicated according to FDA definitions by a blinded clinical events committee. Sensitivity and specificity of the EMR algorithms were estimated with the adjudication by the clinical events committee as the gold standard.
Results: Sensitivity and specificity for each algorithm are shown in Table 1. The algorithm comprising any discharge diagnosis code of HF had the highest sensitivity, while the principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization algorithm had the highest specificity. The algorithm containing any discharge diagnosis code for HF with IV diuretic use during associated hospitalization had the optimal balance between correctly capturing and classifying HF hospitalizations and distinguishing non-HF hospitalizations.
Conclusions: Centralized endpoint capture of HF hospitalizations is sensitive and highly specific when compared to traditional methods for all algorithms examined. Any discharge diagnosis code of HF combined with IV diuretic use during associated hospitalization had the best combination of sensitivity and specificity.
| INVESTED 2016-2018 sample*; 73 adjudicated events | ||
| Sensitivity (95% CI) | Specificity (95% CI) | |
| Any discharge HF code, n=67 | 91.8 (85.5, 98.1) | 77.6 (74.0, 81.2) |
| Any discharge HF code and IV diuretic, n=64 | 87.7 (80.1, 95.2) | 91.1 (88.7, 93.6) |
| Principal discharge HF code, n=61 | 83.6 (75.1, 92.1) | 96.3 (94.7, 98.0) |
| Principal discharge HF code and IV diuretic, n=60 | 82.2 (73.4, 91.0) | 97.7 (96.4, 99.0) |
| *Patients enrolled in multiple trial years | ||
Introduction: Pragmatic clinical trials (PCTs) employ innovative approaches to improve clinical trial efficiency and reduce trial-related costs. Leveraging electronic medical records (EMR) has the potential to lower trial burden and cost related to patient follow-up and data acquisition.
Hypothesis: Centralized (EMR-based) and traditional (trial-based) methods of heart failure (HF) hospitalization endpoint capture are comparable.
Methods: In the Veteran Affairs (VA) national integrated EMR, we used four distinct algorithms: 1) any (primary or secondary) discharge diagnosis code of HF; 2) any discharge diagnosis code of HF and IV diuretic use during associated hospitalization; 3) principal discharge diagnosis code of HF; 4) principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization, to identify HF hospitalizations for 405 Veteran participants of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated heart failure (INVESTED) PCT. HF hospitalizations identified by EMR were compared to INVESTED study events adjudicated according to FDA definitions by a blinded clinical events committee. Sensitivity and specificity of the EMR algorithms were estimated with the adjudication by the clinical events committee as the gold standard.
Results: Sensitivity and specificity for each algorithm are shown in Table 1. The algorithm comprising any discharge diagnosis code of HF had the highest sensitivity, while the principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization algorithm had the highest specificity. The algorithm containing any discharge diagnosis code for HF with IV diuretic use during associated hospitalization had the optimal balance between correctly capturing and classifying HF hospitalizations and distinguishing non-HF hospitalizations.
Conclusions: Centralized endpoint capture of HF hospitalizations is sensitive and highly specific when compared to traditional methods for all algorithms examined. Any discharge diagnosis code of HF combined with IV diuretic use during associated hospitalization had the best combination of sensitivity and specificity.
Hypothesis: Centralized (EMR-based) and traditional (trial-based) methods of heart failure (HF) hospitalization endpoint capture are comparable.
Methods: In the Veteran Affairs (VA) national integrated EMR, we used four distinct algorithms: 1) any (primary or secondary) discharge diagnosis code of HF; 2) any discharge diagnosis code of HF and IV diuretic use during associated hospitalization; 3) principal discharge diagnosis code of HF; 4) principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization, to identify HF hospitalizations for 405 Veteran participants of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated heart failure (INVESTED) PCT. HF hospitalizations identified by EMR were compared to INVESTED study events adjudicated according to FDA definitions by a blinded clinical events committee. Sensitivity and specificity of the EMR algorithms were estimated with the adjudication by the clinical events committee as the gold standard.
Results: Sensitivity and specificity for each algorithm are shown in Table 1. The algorithm comprising any discharge diagnosis code of HF had the highest sensitivity, while the principal discharge diagnosis code of HF and IV diuretic use during associated hospitalization algorithm had the highest specificity. The algorithm containing any discharge diagnosis code for HF with IV diuretic use during associated hospitalization had the optimal balance between correctly capturing and classifying HF hospitalizations and distinguishing non-HF hospitalizations.
Conclusions: Centralized endpoint capture of HF hospitalizations is sensitive and highly specific when compared to traditional methods for all algorithms examined. Any discharge diagnosis code of HF combined with IV diuretic use during associated hospitalization had the best combination of sensitivity and specificity.
| INVESTED 2016-2018 sample*; 73 adjudicated events | ||
| Sensitivity (95% CI) | Specificity (95% CI) | |
| Any discharge HF code, n=67 | 91.8 (85.5, 98.1) | 77.6 (74.0, 81.2) |
| Any discharge HF code and IV diuretic, n=64 | 87.7 (80.1, 95.2) | 91.1 (88.7, 93.6) |
| Principal discharge HF code, n=61 | 83.6 (75.1, 92.1) | 96.3 (94.7, 98.0) |
| Principal discharge HF code and IV diuretic, n=60 | 82.2 (73.4, 91.0) | 97.7 (96.4, 99.0) |
| *Patients enrolled in multiple trial years | ||
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