Cohort profile: the British Columbia COVID-19 Cohort (BCC19C)-a dynamic, linked population-based cohort.

Purpose: The British Columbia COVID-19 Cohort (BCC19C) was developed from an innovative, dynamic surveillance platform and is accessed/analyzed through a cloud-based environment. The platform integrates recently developed provincial COVID-19 datasets (refreshed daily) with existing administrative holdings and provincial registries (refreshed weekly/monthly). The platform/cohort were established to inform the COVID-19 response in near "real-time" and to answer more in-depth epidemiologic questions. Participants: The surveillance platform facilitates the creation of large, up-to-date analytic cohorts of people accessing COVID-19 related services and their linked medical histories. The program of work focused on creating/analyzing these cohorts is referred to as the BCC19C. The administrative/registry datasets integrated within the platform are not specific to COVID-19 and allow for selection of "control" individuals who have not accessed COVID-19 services. Findings to date: The platform has vastly broadened the range of COVID-19 analyses possible, and outputs from BCC19C analyses have been used to create dashboards, support routine reporting and contribute to the peer-reviewed literature. Published manuscripts (total of 15 as of July, 2023) have appeared in high-profile publications, generated significant media attention and informed policy and programming. In this paper, we conducted an analysis to identify sociodemographic and health characteristics associated with receiving SARS-CoV-2 laboratory testing, testing positive, and being fully vaccinated. Other published analyses have compared the relative clinical severity of different variants of concern; quantified the high "real-world" effectiveness of vaccines in addition to the higher risk of myocarditis among younger males following a 2nd dose of an mRNA vaccine; developed and validated an algorithm for identifying long-COVID patients in administrative data; identified a higher rate of diabetes and healthcare utilization among people with long-COVID; and measured the impact of the pandemic on mental health, among other analyses. Future plans: While the global COVID-19 health emergency has ended, our program of work remains robust. We plan to integrate additional datasets into the surveillance platform to further improve and expand covariate measurement and scope of analyses. Our analyses continue to focus on retrospective studies of various aspects of the COVID-19 pandemic, as well as prospective assessment of post-acute COVID-19 conditions and other impacts of the pandemic.

A Survey of Standard Information Models for Clinical Decision Support Systems.

HL7 CDA, vMR, and openEHR archetypes have been utilized as standard information models for clinical decision support systems. Compared to openEHR archetypes, vMR typically requires less time to develop and extend which makes it a good fit for rapid prototyping and pilot projects, while openEHR archetypes handle the data and semantic specification better. Using CDA for clinical decision support systems is discouraged due to its complexity, steep learning curve, and potential safety issues.

Assessing Hepatitis C Burden and Treatment Effectiveness through the British Columbia Hepatitis Testers Cohort (BC-HTC): Design and Characteristics of Linked and Unlinked Participants.

BACKGROUND: The British Columbia (BC) Hepatitis Testers Cohort (BC-HTC) was established to assess and monitor hepatitis C (HCV) epidemiology, cost of illness and treatment effectiveness in BC, Canada. In this paper, we describe the cohort construction, data linkage process, linkage yields, and comparison of the characteristics of linked and unlinked individuals. METHODS: The BC-HTC includes all individuals tested for HCV and/or HIV or reported as a case of HCV, hepatitis B (HBV), HIV or active tuberculosis (TB) in BC linked with the provincial health insurance client roster, medical visits, hospitalizations, drug prescriptions, the cancer registry and mortality data using unique personal health numbers. The cohort includes data since inception (1990/1992) of each database until 2012/2013 with plans for annual updates. We computed linkage rates by year and compared the characteristics of linked and unlinked individuals. RESULTS: Of 2,656,323 unique individuals available in the laboratory and surveillance data, 1,427,917(54%) were included in the final linked cohort, including about 1.15 million tested for HCV and about 1.02 million tested for HIV. The linkage rate was 86% for HCV tests, 89% for HCV cases, 95% for active TB cases, 48% for HIV tests and 36% for HIV cases. Linkage rates increased from 40% for HCV negatives and 70% for HCV positives in 1992 to ~90% after 2005. Linkage rates were lower for males, younger age at testing, and those with unknown residence location. Linkage rates for HCV testers co-infected with HIV, HBV or TB were very high (90-100%). CONCLUSION: Linkage rates increased over time related to improvements in completeness of identifiers in laboratory, surveillance, and registry databases. Linkage rates were higher for HCV than HIV testers, those testing positive, older individuals, and females. Data from the cohort provide essential information to support the development of prevention, care and treatment initiatives for those infected with HCV.