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null Validating hospital data for research and surveillance

Statistical analysis by an RI-MUHC team confirms the validity of hospital diagnostic codes in identifying SARS-CoV-2 infection

SOURCE: RI-MUHC

November 30, 2023

In new work published in the Canadian Medical Journal (CMAJ), researchers from the Research Institute of the McGill University Health Centre (RI-MUHC) have produced one of the first Canadian studies to show that the hospital diagnostic codes used to identify SARS-CoV-2 infections in patient data are valid.

When COVID-19 emerged, the global healthcare community faced unprecedented challenges. One such challenge was identifying and tracking patients infected with the novel coronavirus, SARS-CoV-2.

In April 2020, the World Health Organization (WHO) released a new International Classification of Disease (ICD) code, U07.1, to help hospitals identify lab-confirmed cases of SARS-CoV-2 infection. If a patient was confirmed to have COVID-19, the required procedure was to enter the code U07.1 in their hospital file at the time of discharge. Potentially a valuable tool for identifying SARS-CoV-2 within health data, the code would need to have been applied accurately and similarly across different hospitals and regions to yield reliable information for studies. But has that been the case?

Sasha Bernatsky, MD, PhD, and her team addressed this pressing question. A senior scientist in the Infectious Diseases and Immunity in Global Health Program and Centre for Outcomes Research and Evaluation (CORE) at the RI-MUHC, Dr. Bernatsky uses large volumes of patient data to study health outcomes across populations. Like other researchers focusing on epidemiology and population health, she and her team depend on high-quality data to expedite important research and surveillance activities.

Sasha Bernatsky, MD, PhD, senior scientist in the Infectious Diseases and Immunity in Global Health Program and Centre for Outcomes Research and Evaluation (CORE) at the RI-MUHC
Sasha Bernatsky, MD, PhD, senior scientist in the Infectious Diseases and Immunity in Global Health Program and Centre for Outcomes Research and Evaluation (CORE) at the RI-MUHC

“We wanted to find out if the U07.1 code has been applied correctly in healthcare settings,” says Dr. Bernatsky. “Would researchers who study large volumes of data be able to count on this code to accurately identify patients with confirmed cases of COVID-19?”

The research team reviewed more than 50,000 hospital admissions that occurred during 2020. They assessed demographic data, admission and discharge information, as well as test results. They found that 11,852 of these admissions were associated with a positive or negative PCR test. Of those admissions, 3.7% were confirmed to have SARS-CoV-2 infection.

The team then used advanced statistical techniques to look at the data across sex, age groups and calendar periods. The results confirmed the validity of the SARS-CoV-2 infection code U07.1 in the data used for this study.

“Our results help contribute to a better understanding of COVID-19 case definitions and their use in Canada,” says Dr. Bernatsky. “This is reassuring for research and surveillance activities relying on administrative hospitalization data to identify SARS-CoV-2 infections.”

About the study

Read the publication, “Validity of hospital diagnostic codes to identify SARS-CoV-2 infections in reference to polymerase chain reaction results: a descriptive study,” in the Canadian Medical Association Journal (CMAJ). Published October 24, 2023 by Cristiano S. Moura, Autumn Neville, Fangming Liao, Bijun Wen, Fahad Razak, Surain Roberts, Amol A. Verma and Sasha Bernatsky. DOI: https://doi.org/10.9778/cmajo.20230033

The authors gratefully acknowledge support from the CAnadian Network for Advanced Interdisciplinary Methods for Comparative Effectiveness Research (CAN-AIM), a team grant from the Canadian Institutes of Health Research.

The GEMINI data platform used in this work is supported with funding from the Canadian Cancer Society, the Canadian Frailty Network, the Canadian Institutes of Health Research, the Canadian Medical Protective Association, Green Shield Canada Foundation, the Natural Sciences and Engineering Research Council of Canada, Ontario Health, the St. Michael’s Hospital Association Innovation Fund, the University of Toronto Department of Medicine, and in-kind support from partner hospitals and Vector Institute.


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