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Identification and Mapping Real-World Data Sources for Heart Failure, Acute Coronary Syndrome, and Atrial
Rachel Studer1, Claudio Sartini2, Kiliana Suzart-Woischnik2
1Novartis Pharma AG, Novartis Campus, Basel, Switzerland.
Insights
This review identified global real-world data sources for heart failure, acute coronary syndrome, and atrial fibrillation. The comprehensive resource aids future cardiovascular research and patient outcomes.
Area of Science:
- Cardiovascular medicine
- Health informatics
- Epidemiology
Background:
- Real-world data (RWD) is crucial for global health, particularly for cardiovascular diseases.
- This study aimed to identify global RWD sources for heart failure (HF), acute coronary syndrome (ACS), and atrial fibrillation (AF).
Approach:
- A systematic review of publications (2010-2018) related to HF, ACS, and AF was conducted.
- Metadata on data source type, study design, population, clinical characteristics, follow-up, outcomes, and data availability were extracted.
Key Points:
- Over 322 (HF), 287 (ACS), and 220 (AF) unique RWD sources were identified from thousands of publications.
- Demographic and comorbidity data were widely available, but drug codes and caregiver involvement were sparsely reported.
- Limited information was available on data accessibility for researchers (11%) and data linkage potential (20%).
Conclusions:
- A comprehensive resource of cardiovascular RWD sources was created.
- This resource offers new opportunities to enhance real-world research in cardiovascular diseases.
- The findings aim to contribute to achieving better patient outcomes through improved research.
Background:
Transparent and robust real-world evidence sources are increasingly important for global health, including cardiovascular (CV) diseases. We aimed to identify global real-world data (RWD) sources for heart failure (HF), acute coronary syndrome (ACS), and atrial fibrillation (AF).
Methods:
We conducted a systematic review of publications with RWD pertaining to HF, ACS, and AF (2010-2018), generating a list of unique data sources. Metadata were extracted based on the source type (e.g., electronic health records, genomics, and clinical data), study design, population size, clinical characteristics, follow-up duration, outcomes, and assessment of data availability for future studies and linkage.
Results:
Overall, 11,889 publications were retrieved for HF, 10,729 for ACS, and 6,262 for AF. From these, 322 (HF), 287 (ACS), and 220 (AF) data sources were selected for detailed review. The majority of data sources had near complete data on demographic variables (HF: 94%, ACS: 99%, and AF: 100%) and considerable data on comorbidities (HF: 77%, ACS: 93%, and AF: 97%). The least reported data categories were drug codes (HF, ACS, and AF: 10%) and caregiver involvement (HF: 6%, ACS: 1%, and AF: 1%). Only a minority of data sources provided information on access to data for other researchers (11%) or whether data could be linked to other data sources to maximize clinical impact (20%). The list and metadata for the RWD sources are publicly available at www.escardio.org/bigdata.
Conclusions:
This review has created a comprehensive resource of CV data sources, providing new avenues to improve future real-world research and to achieve better patient outcomes.
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