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Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence.

Publication ,  Journal Article
Tanoshima, R; Inagaki, N; Nitta, M; Sue, S; Shimizu, S; Haze, T; Senuki, K; Sano, C; Takase, H; Kaneko, M; Nozaki, A; Okada, K; Ohyama, K ...
Published in: Ther Innov Regul Sci
November 2024

The results of observational studies using real-world data, known as real-world evidence, have gradually started to be used in drug development and decision-making by policymakers. A good quality management system-a comprehensive system of process, data, and documentation to ensure quality-is important in obtaining real-world evidence. A risk-based approach is a common quality management system used in interventional studies. We used a quality management system and risk-based approach in an observational study on a designated intractable disease. Our multidisciplinary team assessed the risks of the real-world data study comprehensively and systematically. When using real-world data and evidence to support regulatory decisions, both the quality of the database and the validity of the outcome are important. We followed the seven steps of the risk-based approach for both database selection and research planning. We scored the risk of two candidate databases and chose the Japanese National Database of designated intractable diseases for this study. We also conducted a quantitative assessment of risks associated with research planning. After prioritizing the risks, we revised the research plan and outcomes to reflect the risk-based approach. We concluded that implementing a risk-based approach is feasible for an observational study using real-world data. Evaluating both database selection and research planning is important. A risk-based approach can be essential to obtain robust real-world evidence.

Duke Scholars

Published In

Ther Innov Regul Sci

DOI

EISSN

2168-4804

Publication Date

November 2024

Volume

58

Issue

6

Start / End Page

1006 / 1013

Location

Switzerland

Related Subject Headings

  • Statistics & Probability
  • Risk Assessment
  • Research Design
  • Observational Studies as Topic
  • Humans
  • Evidence-Based Medicine
  • Databases, Factual
  • 4905 Statistics
  • 3214 Pharmacology and pharmaceutical sciences
  • 1117 Public Health and Health Services
 

Citation

APA
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MLA
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Tanoshima, R., Inagaki, N., Nitta, M., Sue, S., Shimizu, S., Haze, T., … Miyagi, E. (2024). Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence. Ther Innov Regul Sci, 58(6), 1006–1013. https://doi.org/10.1007/s43441-024-00695-6
Tanoshima, Reo, Naoko Inagaki, Manabu Nitta, Soichiro Sue, Sayuri Shimizu, Tatsuya Haze, Kotaro Senuki, et al. “Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence.Ther Innov Regul Sci 58, no. 6 (November 2024): 1006–13. https://doi.org/10.1007/s43441-024-00695-6.
Tanoshima R, Inagaki N, Nitta M, Sue S, Shimizu S, Haze T, et al. Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence. Ther Innov Regul Sci. 2024 Nov;58(6):1006–13.
Tanoshima, Reo, et al. “Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence.Ther Innov Regul Sci, vol. 58, no. 6, Nov. 2024, pp. 1006–13. Pubmed, doi:10.1007/s43441-024-00695-6.
Tanoshima R, Inagaki N, Nitta M, Sue S, Shimizu S, Haze T, Senuki K, Sano C, Takase H, Kaneko M, Nozaki A, Okada K, Ohyama K, Kawaguchi A, Kobayashi Y, Oi H, Maeda S, Yano Y, Kumagai Y, Miyagi E. Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence. Ther Innov Regul Sci. 2024 Nov;58(6):1006–1013.
Journal cover image

Published In

Ther Innov Regul Sci

DOI

EISSN

2168-4804

Publication Date

November 2024

Volume

58

Issue

6

Start / End Page

1006 / 1013

Location

Switzerland

Related Subject Headings

  • Statistics & Probability
  • Risk Assessment
  • Research Design
  • Observational Studies as Topic
  • Humans
  • Evidence-Based Medicine
  • Databases, Factual
  • 4905 Statistics
  • 3214 Pharmacology and pharmaceutical sciences
  • 1117 Public Health and Health Services