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Advancing the development of real-world data for healthcare research in China: challenges and opportunities.
Zhong, Jia; Zhang, Jun; Fang, Honghao; Liu, Larry; Xie, Jipan; Wu, Eric.
Afiliação
  • Zhong J; Analysis Group, Inc, Beijing, China Jia.Zhong@analysisgroup.com.
  • Zhang J; MSD R&D (China) Co., Ltd, Beijing, China.
  • Fang H; Analysis Group, Inc, Beijing, China.
  • Liu L; Merck & Co., Inc, Rahway, New Jersey, USA.
  • Xie J; Weill Cornell Medical College, New York, New York, USA.
  • Wu E; Analysis Group, Inc, Los Angeles, California, USA.
BMJ Open ; 12(7): e063139, 2022 07 29.
Article em En | MEDLINE | ID: mdl-35906059
ABSTRACT
Various real-world data (RWD) sources have emerged in China with the intention of generating real-world evidence (RWE) that can be used in clinical and regulatory decision-making. Despite these efforts, significant barriers remain that hinder high-quality healthcare research. A workshop with 30 representatives from healthcare research agencies, technology companies focused on healthcare big data and pharmaceutical companies was held in December 2020 to identify strategies to overcome the barriers associated with the usability and quality of RWD in China. Across all sectors, examples of barriers identified included inconsistencies in terminology and non-standardised coding practices; the absence of longitudinal data; the absence of transparent data processing and validation practices; and the inability to access and share RWD. While cutting-edge technological innovations and data solutions provided powerful tools, the development of collaborative and synergistic research networks across multiple stakeholders is key to generate accessible, high-quality RWD in China. RWD has the potential to provide clinical, regulatory and reimbursement decision-makers with critical insights that can improve healthcare delivery in China. However, barriers to its access, collection and use must be addressed to generate RWE to guide healthcare stakeholders.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal / 2_ODS3 Base de dados: MEDLINE Assunto principal: Atenção à Saúde / Pesquisa sobre Serviços de Saúde Tipo de estudo: Prognostic_studies Aspecto: Determinantes_sociais_saude Limite: Humans País/Região como assunto: Asia Idioma: En Revista: BMJ Open Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal / 2_ODS3 Base de dados: MEDLINE Assunto principal: Atenção à Saúde / Pesquisa sobre Serviços de Saúde Tipo de estudo: Prognostic_studies Aspecto: Determinantes_sociais_saude Limite: Humans País/Região como assunto: Asia Idioma: En Revista: BMJ Open Ano de publicação: 2022 Tipo de documento: Article