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Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
Building a coronavirus disease 2019 healthcare registry in an evolving pandemic
Indumathi Venkatachalam1,2, Edwin Philip Conceicao3, Jean Xiang Ying Sim4
1Department of Infection Prevention and Epidemiology, Singapore General Hospital, Singapore, Singapore. indumathi.venkatachalam@singhealth.com.sg.
Insights
Singapore Health Services developed a COVID-19 registry to track patient data for clinical and research needs. This automated database efficiently managed information, supporting pandemic response and healthcare management.
Area of Science:
- Public Health
- Health Informatics
- Epidemiology
Background:
- The COVID-19 pandemic necessitated rapid data collection to understand disease characteristics and epidemiology.
- Effective healthcare resource management required high-quality data early in the pandemic.
Purpose of the Study:
- To describe the development process of the Singapore Health Services (SingHealth) COVID-19 registry.
- To outline how the registry supports clinical, operational, and research needs during the pandemic.
Main Methods:
- A COVID-19 registry was established within SingHealth's Electronic Health Intelligence System (eHIntS).
- Patient identification used laboratory results and electronic disease tags.
- A minimum data set (MDS) with over 100 variables across 15 domains was created, including raw and derived data on comorbidities and complications.
Main Results:
- The registry includes data from 156,262 unique patients as of December 31, 2023.
- 27,630 patients were admitted to SingHealth hospitals for COVID-19.
- The registry has provided valuable data for operational, clinical, and research purposes.
Conclusions:
- The SingHealth COVID-19 registry serves as a model for developing low-cost, automated databases during evolving pandemics.
- Leveraging standardized clinical workflows facilitated efficient pandemic operations, clinical management, and research.
- The registry effectively supports data-driven decision-making in public health crises.
Abstract:
COVID-19 emerged in Wuhan, China in December 2019 and was declared a pandemic on March 11, 2020. As there were many unknowns about COVID-19, an immediate priority early in the pandemic was to collect high-quality data to understand disease characteristics and epidemiology to inform healthcare resource management. A COVID-19 registry was developed by Singapore Health Services (SingHealth) to support clinical, operational, and research needs. We describe the development process of the SingHealth COVID-19 registry. Patients diagnosed with COVID-19 and managed by the Singapore Health Services (SingHealth), the largest of three public healthcare clusters in Singapore that includes acute hospitals, national specialty centres, subacute hospitals, and primary health centres, were included in the registry. A combination of laboratory test results and nationally administered electronic disease tags were used to identify COVID-19 patients. A dashboard was built in the Electronic Health Intelligence System (eHIntS), the data repository within SingHealth, linking variables in a minimum data set (MDS) using patient identifiers. Healthcare utilization in different ward types was computed, and 19 comorbidities and 14 complications were derived and coded from raw data sources within eHints for hospitalized patients. The COVID-19 registry contains more than 100 variables across 15 data domains, including raw data in long format (e.g. problem list, movement within hospital) and derived variables (e.g. comorbidities, complications, outcomes). As of December 31, 2023, the COVID-19 registry comprises of 156,262 unique patients of whom, 27,630 were admitted for COVID-19 at least once at one of the SingHealth hospitals. It has provided data for operational, clinical, and research purposes. The SingHealth COVID-19 registry is a model of how a low-cost, automated database can be developed amidst an evolving pandemic, leveraging on pandemic-necessitated standardized clinical workflows for pandemic operations, clinical management and research.
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