{"title":"Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence.","authors":"Reo Tanoshima, Naoko Inagaki, Manabu Nitta, Soichiro Sue, Sayuri Shimizu, Tatsuya Haze, Kotaro Senuki, Chihiro Sano, Hajime Takase, Makoto Kaneko, Akito Nozaki, Kozo Okada, Kohei Ohyama, Atsushi Kawaguchi, Yusuke Kobayashi, Hideki Oi, Shin Maeda, Yuichiro Yano, Yuji Kumagai, Etsuko Miyagi","doi":"10.1007/s43441-024-00695-6","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":23084,"journal":{"name":"Therapeutic innovation & regulatory science","volume":" ","pages":"1006-1013"},"PeriodicalIF":2.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic innovation & regulatory science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s43441-024-00695-6","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/3 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Therapeutic Innovation & Regulatory Science (TIRS) is the official scientific journal of DIA that strives to advance medical product discovery, development, regulation, and use through the publication of peer-reviewed original and review articles, commentaries, and letters to the editor across the spectrum of converting biomedical science into practical solutions to advance human health.
The focus areas of the journal are as follows:
Biostatistics
Clinical Trials
Product Development and Innovation
Global Perspectives
Policy
Regulatory Science
Product Safety
Special Populations