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. 2023 Jan 9;23(1):4.
doi: 10.1186/s12911-022-02071-6.

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

Sean Shao Wei Lam  1   2   3   4 , Andrew Hao Sen Fang  5 , Mariko Siyue Koh  6   7 , Sumitra Shantakumar  7   8 , See-Hwee Yeo  8 , David Bruce Matchar  7   9   10 , Marcus Eng Hock Ong  11   12   13   14 , Ken Mei Ting Poon  15 , Liming Huang  15 , Sudha Harikrishan  12 , Dominique Milea  8 , Des Burke  8 , Dave Webb  8 , Narayanan Ragavendran  12   7 , Ngiap Chuan Tan  5   7 , Chian Min Loo  6   7
Affiliations

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

Sean Shao Wei Lam et al. BMC Med Inform Decis Mak. .

Abstract

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.

Keywords: Asthma; COPD; Chronic obstructive pulmonary disease; Database; Real world data; Real world evidence.

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Conflict of interest statement

This study was funded by GlaxoSmithKline plc (study number PRJ3057). SS, SHY, DM, DB and DW are full-time employees of GSK. SS, DM, DB and DW also own stocks in GlaxoSmithKline plc. SWSL, HSAF, MSK, DBM, EHMO, MTKP, HL, SH, NR, NCT and CML are full-time employees of SingHealth Duke NUS Academic Medical Centre (including SingHealth Polyclinics, Singapore General Hospital, Singapore Health Services Research Centre and Integrated Health Information Systems) and Duke-NUS Medical School. They report no conflicts of interest.

Figures

Fig. 1
Fig. 1
Overview of analytics support infrastructure in SingHealth. Note Electronic Health Intelligence System (eHints) [19] is the enterprise data warehouse for SingHealth. It integrates data from various IT systems and feeds them into analytics tools for research and clinical care
Fig. 2
Fig. 2
Screen capture of SingHealth COPD and Asthma Data Mart (SCDM) user interface in eHints. Note The Oracle Business Intelligence Enterprise Edition (OBIEE) analytics platform is the front-end of Electronic Health Intelligence System (eHints), allows users to drag-and-drop columns for data extraction, instead of having to write SQL codes. It is meant to support self-service data extraction
Fig. 3
Fig. 3
ETL Process for data sources from both SGH and SHP (target data tables are listed in the intermediate ETL steps)
Fig. 4
Fig. 4
Cohorts used in the preliminary analysis—Combined, SGH and SHP. Note There are some patients who would fall under both circles when the cohorts are combined, hence the lower number in the combined cohort than compared to adding the individual SGH and SHP cohorts
See this image and copyright information in PMC

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