Quality criteria for Real-World Data in pharmaceutical research and healthcare decision making. An Austrian Expert Consensus (Preprint)

UNSTRUCTURED Real-world data (RWD) collected in routine healthcare processes and transformed to real-world evidence (RWE) has become increasingly interesting within research and medical communities to enhance medical research and support regulatory decision making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which quality RWD must meet in order to be acceptable for decision making within regulatory or routine clinical decision support. An Austrian expert group led by GPMed (Gesellschaft für Pharmazeutische Medizin, Austrian Society for Pharmaceutical Medicine) reviewed drafted guidelines, published recommendations or viewpoints to derive a consensus statement on quality criteria for RWD to be used more effectively for medical research purposes beyond registry-based studies discussed in the European Medicines Agency (EMA) guideline for registry-based studies

[1]  O. López.  MHRA Guidance – Revisited , 2020, Ensuring the Integrity of Electronic Health Records.

[2]  N. Sharma,et al.  Correlation between tissue PD-L1, TMB, and blood PD-L1, MSI biomarkers in patients with advanced-stage non-small cell lung cancer (NSCLC). , 2020 .

[3]  Rosa Gini,et al.  Different Strategies to Execute Multi‐Database Studies for Medicines Surveillance in Real‐World Setting: A Reflection on the European Model , 2020, Clinical pharmacology and therapeutics.

[4]  Michael Strassnig,et al.  Zugang zu Register- und Individualdaten für die wissenschaftliche Forschung in Österreich , 2020 .

[5]  Alison Cave,et al.  Big Data – How to Realize the Promise , 2019, Clinical pharmacology and therapeutics.

[6]  David Bourque,et al.  Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non–Small Cell Lung Cancer Using a Clinicogenomic Database , 2019, JAMA.

[7]  Health Data Science: Using Real World Evidence in Medical Research , 2019 .

[8]  Jacqueline Corrigan-Curay,et al.  Real-World Evidence and Real-World Data for Evaluating Drug Safety and Effectiveness. , 2018, JAMA.

[9]  F. Arnaud,et al.  From core referencing to data re-use: two French national initiatives to reinforce paleodata stewardship (National Cyber Core Repository and LTER France Retro-Observatory) , 2017 .

[10]  Stephanie Kohl.  Joint HMA/EMA task force on big data established , 2017, European Journal of Hospital Pharmacy: Science and Practice.

[11]  Olaf Klungel,et al.  What Is Real-World Data? A Review of Definitions Based on Literature and Stakeholder Interviews. , 2016, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[12]  Sigrun Alba Johannesdottir Schmidt,et al.  The Danish National Patient Registry: a review of content, data quality, and research potential , 2015, Clinical epidemiology.

[13]  R. Sund.  Quality of the Finnish Hospital Discharge Register: A systematic review , 2012, Scandinavian journal of public health.

[14]  Elsebeth Lynge,et al.  The Danish National Patient Register , 2011, Scandinavian journal of public health.

[15]  J. Ludvigsson,et al.  External review and validation of the Swedish national inpatient register , 2011, BMC public health.

[16]  G. Thorgeirsson,et al.  Rofecoxib, but not celecoxib, increases the risk of thromboembolic cardiovascular events in young adults—a nationwide registry-based study , 2010, European Journal of Clinical Pharmacology.

[17]  R. Guarino.  Adverse Experiences, Adverse Reactions, and Interactions of Drugs , 2004 .

[18]  Peter Davey,et al.  A checklist for retrospective database studies--report of the ISPOR Task Force on Retrospective Databases. , 2003, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[19]  Nicolette de Keizer,et al.  Model Formulation: Defining and Improving Data Quality in Medical Registries: A Literature Review, Case Study, and Generic Framework , 2002, J. Am. Medical Informatics Assoc..

[20]  H. Sørensen,et al.  Regional administrative health registries as a resource in clinical epidemiologyA study of options, strengths, limitations and data quality provided with examples of use. , 1997, The International journal of risk & safety in medicine.

[21]  H T Sorensen,et al.  A framework for evaluation of secondary data sources for epidemiological research. , 1996, International journal of epidemiology.