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Identification and Mapping Real-World Data Sources for Heart Failure, Acute Coronary Syndrome, and Atrial Fibrillation.
Studer, Rachel; Sartini, Claudio; Suzart-Woischnik, Kiliana; Agrawal, Rumjhum; Natani, Harshul; Gill, Simrat K; Wirta, Sara Bruce; Asselbergs, Folkert W; Dobson, Richard; Denaxas, Spiros; Kotecha, Dipak.
Afiliación
  • Studer R; Novartis Pharma AG, Novartis Campus, Basel, Switzerland.
  • Sartini C; Bayer AG, Global Epidemiology, Berlin, Germany.
  • Suzart-Woischnik K; Bayer AG, Global Epidemiology, Berlin, Germany.
  • Agrawal R; Novartis Healthcare Pvt. Ltd., Hyderabad, India.
  • Natani H; Novartis Healthcare Pvt. Ltd., Hyderabad, India, harshul.natani@novartis.com.
  • Gill SK; Institute of Cardiovascular Sciences, University of Birmingham, Medical School, Vincent Drive, Birmingham, United Kingdom.
  • Wirta SB; Novartis Pharma AG, Novartis Campus, Basel, Switzerland.
  • Asselbergs FW; Institute of Health Informatics, Institute of Cardiovascular Science & Health Data Research UK, University College London, London, United Kingdom.
  • Dobson R; Department of Cardiology, University Medical Centre Utrecht, Utrecht, The Netherlands.
  • Denaxas S; Institute of Health Informatics, Institute of Cardiovascular Science & Health Data Research UK, University College London, London, United Kingdom.
  • Kotecha D; Institute of Health Informatics, Institute of Cardiovascular Science & Health Data Research UK, University College London, London, United Kingdom.
Cardiology ; 147(1): 98-106, 2022.
Article en En | MEDLINE | ID: mdl-34781301
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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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Fibrilación Atrial / Síndrome Coronario Agudo / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Cardiology Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Fibrilación Atrial / Síndrome Coronario Agudo / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Cardiology Año: 2022 Tipo del documento: Article País de afiliación: Suiza