Vjola Hoxhaj, Constanza L Andaur Navarro, Judit Riera-Arnau, Roel J H J Elbers, Ema Alsina, Caitlin Dodd, Miriam C J M Sturkenboom
{"title":"INSIGHT：用于医学和疫苗安全真实世界证据的标准化观测数据源的适合目的评估和质量评估的工具。","authors":"Vjola Hoxhaj, Constanza L Andaur Navarro, Judit Riera-Arnau, Roel J H J Elbers, Ema Alsina, Caitlin Dodd, Miriam C J M Sturkenboom","doi":"10.1002/pds.70089","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To describe the development of INSIGHT, a real-world data quality tool to assess completeness, consistency, and fitness-for-purpose of observational health data sources.</p><p><strong>Methods: </strong>We designed a three-level pipeline with data quality assessments (DQAs) to be performed in ConcePTION Common Data Model (CDM) instances. The pipeline has been coded using R.</p><p><strong>Results: </strong>INSIGHT is an open-source tool that identifies potential data quality issues in CDM-standardized instances through the systematic execution and summary of over 588 configurable DQAs. Level 1 focuses on conformance to the ConcePTION CDM specifications. Level 2 evaluates the temporal plausibility of events and uniqueness of records. Level 3 provides an overview of distributions, outliers, and trends over time to facilitate fit-for-purpose evaluation. Therefore, level 1 and 2 assure a proper data standardization, while level 3 provides information regarding the study population, and potential sub-populations. The DQAs are run locally and assessed centrally by a data quality revisor together with the data access provider's representatives.</p><p><strong>Discussion: </strong>Data quality is the sum of several internal and external features of the data. While DQAs can provide reassurance about fitness-for-purpose for secondary-use data sources, improvements in data collection are essential to reduce errors and enhance overall data quality for Real World Evidence.</p><p><strong>Conclusion: </strong>INSIGHT aims to support clinical and regulatory decision-making for medicines and vaccines by evaluating the quality of observational health data sources to support fit for purpose assessment. Assessing and improving data quality will enhance the reliability and quality of the generated evidence.</p><p><strong>Study registration: </strong>This research was registered in EU PAS registration with number EU50142.</p>","PeriodicalId":19782,"journal":{"name":"Pharmacoepidemiology and Drug Safety","volume":"34 1","pages":"e70089"},"PeriodicalIF":2.4000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11730612/pdf/","citationCount":"0","resultStr":"{\"title\":\"INSIGHT: A Tool for Fit-for-Purpose Evaluation and Quality Assessment of Standardized Observational Data Sources for Real World Evidence on Medicine and Vaccine Safety.\",\"authors\":\"Vjola Hoxhaj, Constanza L Andaur Navarro, Judit Riera-Arnau, Roel J H J Elbers, Ema Alsina, Caitlin Dodd, Miriam C J M Sturkenboom\",\"doi\":\"10.1002/pds.70089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>To describe the development of INSIGHT, a real-world data quality tool to assess completeness, consistency, and fitness-for-purpose of observational health data sources.</p><p><strong>Methods: </strong>We designed a three-level pipeline with data quality assessments (DQAs) to be performed in ConcePTION Common Data Model (CDM) instances. The pipeline has been coded using R.</p><p><strong>Results: </strong>INSIGHT is an open-source tool that identifies potential data quality issues in CDM-standardized instances through the systematic execution and summary of over 588 configurable DQAs. Level 1 focuses on conformance to the ConcePTION CDM specifications. Level 2 evaluates the temporal plausibility of events and uniqueness of records. Level 3 provides an overview of distributions, outliers, and trends over time to facilitate fit-for-purpose evaluation. Therefore, level 1 and 2 assure a proper data standardization, while level 3 provides information regarding the study population, and potential sub-populations. The DQAs are run locally and assessed centrally by a data quality revisor together with the data access provider's representatives.</p><p><strong>Discussion: </strong>Data quality is the sum of several internal and external features of the data. 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INSIGHT: A Tool for Fit-for-Purpose Evaluation and Quality Assessment of Standardized Observational Data Sources for Real World Evidence on Medicine and Vaccine Safety.
Purpose: To describe the development of INSIGHT, a real-world data quality tool to assess completeness, consistency, and fitness-for-purpose of observational health data sources.
Methods: We designed a three-level pipeline with data quality assessments (DQAs) to be performed in ConcePTION Common Data Model (CDM) instances. The pipeline has been coded using R.
Results: INSIGHT is an open-source tool that identifies potential data quality issues in CDM-standardized instances through the systematic execution and summary of over 588 configurable DQAs. Level 1 focuses on conformance to the ConcePTION CDM specifications. Level 2 evaluates the temporal plausibility of events and uniqueness of records. Level 3 provides an overview of distributions, outliers, and trends over time to facilitate fit-for-purpose evaluation. Therefore, level 1 and 2 assure a proper data standardization, while level 3 provides information regarding the study population, and potential sub-populations. The DQAs are run locally and assessed centrally by a data quality revisor together with the data access provider's representatives.
Discussion: Data quality is the sum of several internal and external features of the data. While DQAs can provide reassurance about fitness-for-purpose for secondary-use data sources, improvements in data collection are essential to reduce errors and enhance overall data quality for Real World Evidence.
Conclusion: INSIGHT aims to support clinical and regulatory decision-making for medicines and vaccines by evaluating the quality of observational health data sources to support fit for purpose assessment. Assessing and improving data quality will enhance the reliability and quality of the generated evidence.
Study registration: This research was registered in EU PAS registration with number EU50142.
期刊介绍：
The aim of Pharmacoepidemiology and Drug Safety is to provide an international forum for the communication and evaluation of data, methods and opinion in the discipline of pharmacoepidemiology. The Journal publishes peer-reviewed reports of original research, invited reviews and a variety of guest editorials and commentaries embracing scientific, medical, statistical, legal and economic aspects of pharmacoepidemiology and post-marketing surveillance of drug safety. Appropriate material in these categories may also be considered for publication as a Brief Report.
Particular areas of interest include:
design, analysis, results, and interpretation of studies looking at the benefit or safety of specific pharmaceuticals, biologics, or medical devices, including studies in pharmacovigilance, postmarketing surveillance, pharmacoeconomics, patient safety, molecular pharmacoepidemiology, or any other study within the broad field of pharmacoepidemiology;
comparative effectiveness research relating to pharmaceuticals, biologics, and medical devices. Comparative effectiveness research is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, as these methods are truly used in the real world;
methodologic contributions of relevance to pharmacoepidemiology, whether original contributions, reviews of existing methods, or tutorials for how to apply the methods of pharmacoepidemiology;
assessments of harm versus benefit in drug therapy;
patterns of drug utilization;
relationships between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines;
evaluations of risk management plans and programmes relating to pharmaceuticals, biologics and medical devices.
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