tetano
Editor, Senior Moderator
Sci Rep
. 2025 Oct 6;15(1):34669.
doi: 10.1038/s41598-025-98723-4. Building a coronavirus disease 2019 healthcare registry in an evolving pandemic
Indumathi Venkatachalam[SUP] 1 2 [/SUP], Edwin Philip Conceicao[SUP] 3 [/SUP], Jean Xiang Ying Sim[SUP] 4 [/SUP], Shalvi Arora[SUP] 4 [/SUP], Yue Yang[SUP] 4 [/SUP], Jin Yee Shoon[SUP] 4 [/SUP], Yingqi Xu[SUP] 5 6 [/SUP], Marcus Eng Hock Ong[SUP] 5 6 7 [/SUP], Sze Ling Chan[SUP] 5 6 [/SUP]
Affiliations
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.
Keywords: Automated surveillance; COVID-19; Disease registry.
. 2025 Oct 6;15(1):34669.
doi: 10.1038/s41598-025-98723-4. Building a coronavirus disease 2019 healthcare registry in an evolving pandemic
Indumathi Venkatachalam[SUP] 1 2 [/SUP], Edwin Philip Conceicao[SUP] 3 [/SUP], Jean Xiang Ying Sim[SUP] 4 [/SUP], Shalvi Arora[SUP] 4 [/SUP], Yue Yang[SUP] 4 [/SUP], Jin Yee Shoon[SUP] 4 [/SUP], Yingqi Xu[SUP] 5 6 [/SUP], Marcus Eng Hock Ong[SUP] 5 6 7 [/SUP], Sze Ling Chan[SUP] 5 6 [/SUP]
Affiliations
- PMID: 41053419
- DOI: 10.1038/s41598-025-98723-4
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.
Keywords: Automated surveillance; COVID-19; Disease registry.