Development of a real-world database for asthma and COPD: The SingHealth-Duke-NUS-GSK COPD and Asthma Real-World Evidence (SDG-CARE) collaboration.

PURPOSE: The SingHealth-Duke-GlaxoSmithKline COPD and Asthma Real-world Evidence (SDG-CARE) collaboration was formed to accelerate the use of Singaporean real-world evidence in research and clinical care. A centerpiece of the collaboration was to develop a near real-time database from clinical and operational data sources to inform healthcare decision making and research studies on asthma and chronic obstructive pulmonary disease (COPD). METHODS: Our multidisciplinary team, including clinicians, epidemiologists, data scientists, medical informaticians and IT engineers, adopted the hybrid waterfall-agile project management methodology to develop the SingHealth COPD and Asthma Data Mart (SCDM). The SCDM was developed within the organizational data warehouse. It pulls and maps data from various information systems using extract, transform and load (ETL) pipelines. Robust user testing and data verification was also performed to ensure that the business requirements were met and that the ETL pipelines were valid. RESULTS: The SCDM includes 199 data elements relevant to asthma and COPD. Data verification was performed and found the SCDM to be reliable. As of December 31, 2019, the SCDM contained 36,407 unique patients with asthma and COPD across the spectrum from primary to tertiary care in our healthcare system. The database updates weekly to add new data of existing patients and to include new patients who fulfil the inclusion criteria. CONCLUSIONS: The SCDM was systematically developed and tested to support the use RWD for clinical and health services research in asthma and COPD. This can serve as a platform to provide research and operational insights to improve the care delivered to our patients.

Series: Pragmatic trials and real world evidence: Paper 8. Data collection and management.

Pragmatic trials can improve our understanding of how treatments will perform in routine practice. In a series of eight papers, the GetReal Consortium has evaluated the challenges in designing and conducting pragmatic trials and their specific methodological, operational, regulatory, and ethical implications. The present final paper of the series discusses the operational and methodological challenges of data collection in pragmatic trials. A more pragmatic data collection needs to balance the delivery of highly accurate and complete data with minimizing the level of interference that data entry and verification induce with clinical practice. Furthermore, it should allow for the involvement of a representative sample of practices, physicians, and patients who prescribe/receive treatment in routine care. This paper discusses challenges that are related to the different methods of data collection and presents potential solutions where possible. No one-size-fits-all recommendation can be given for the collection of data in pragmatic trials, although in general the application of existing routinely used data-collection systems and processes seems to best suit the pragmatic approach. However, data access and privacy, the time points of data collection, the level of detail in the data, and the lack of a clear understanding of the data-collection process were identified as main challenges for the usage of routinely collected data in pragmatic trials. A first step should be to determine to what extent existing health care databases provide the necessary study data and can accommodate data collection and management. When more elaborate or detailed data collection or more structured follow-up is required, data collection in a pragmatic trial will have to be tailor-made, often using a hybrid approach using a dedicated electronic case report form (eCRF). In this case, the eCRF should be kept as simple as possible to reduce the burden for practitioners and minimize influence on routine clinical practice.