Development and Validation of Algorithms to Identify COVID-19 Patients Using a US Electronic Health Records Database: A Retrospective Cohort Study

Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview

Electronic Health Records (EHR) are increasingly being perceived as a unique source of data for clinical research as they provide unprecedentedly large volumes of real-time data from real-world settings. In this review of the secondary uses of EHR, we identify the anticipated breadth of opportunities, pointing out the data deficiencies and potential biases that are likely to limit the search for true causal relationships. This paper provides a comprehensive overview of the types of biases that arise along the pathways that generate real-world evidence and the sources of these biases. We distinguish between two levels in the production of EHR data where biases are likely to arise: (i) at the healthcare system level, where the principal source of bias resides in access to, and provision of, medical care, and in the acquisition and documentation of medical and administrative data; and (ii) at the research level, where biases arise from the processes of extracting, analyzing, and interpreting these data. Due to the plethora of biases, mainly in the form of selection and information bias, we conclude with advising extreme caution about making causal inferences based on secondary uses of EHRs.

Burden of disease in patients hospitalised with COVID-19 during the first and second pandemic wave in Switzerland: a nationwide cohort study

AIM OF THE STUDY

The first and second waves of the COVID-19 pandemic led to a tremendous burden of disease and influenced several policy directives, prevention and treatment strategies as well as lifestyle and social behaviours. We aimed to describe trends of hospitalisations with COVID-19 and hospital-associated outcomes in these patients during the first two pandemic waves in Switzerland.

METHODS

In this nationwide retrospective cohort study, we used in-hospital claims data of patients hospitalised with COVID-19 in Switzerland between January 1st and December 31st, 2020. First, stratified by wave (first wave: January to May, second wave: June to December), we estimated incidence rates (IR) and rate differences (RD) per 10,000 person-years of COVID-19-related hospitalisations across different age groups (0-9, 10-19, 20-49, 50-69, and ≥70 years). IR was calculated by counting the number of COVID-19 hospitalisations for each patient age stratum paired with the number of persons living in Switzerland during the specific wave period. Second, adjusted odds ratios (aOR) of outcomes among COVID-19 hospitalisations were calculated to assess the association between COVID-19 wave and outcomes, adjusted for potential confounders.

RESULTS

Of 36,517 hospitalisations with COVID-19, 8,862 (24.3%) were identified during the first and 27,655 (75.7%) during the second wave. IR for hospitalisations with COVID-19 was highest during the second wave and among patients above 50 years (50-69 years: first wave: 31.49 per 10,000 person-years; second wave: 62.81 per 10,000 person-years; RD 31.32 [95% confidence interval [CI]: 29.56 to 33.08] per 10,000 person-years; IRR 1.99 [95% CI: 1.91 to 2.08]; ≥70 years: first wave: 88.59 per 10,000 person-years; second wave: 228.41 per 10,000 person-years; RD 139.83 [95% CI: 135.42 to 144.23] per 10,000 person-years; IRR 2.58 [95% CI: 2.49 to 2.67]). While there was no difference in hospital readmission, when compared with the first wave, patients hospitalised during the second wave had a lower probability of death (aOR 0.88 [95% CI: 0.81 to 0.95], ARDS (aOR 0.56 [95% CI: 0.51 to 0.61]), ICU admission (aOR 0.66 [95% CI: 0.61 to 0.70]), and need for ECMO (aOR 0.60 [95% CI: 0.38 to 0.92]). LOS was -16.1 % (95% CI: -17.8 to -14.2) shorter during the second wave.

CONCLUSION

In this nationwide cohort study, rates of hospitalisations with COVID-19 were highest among adults older than 50 years and during the second wave. Except for hospital readmission, the likelihood of adverse outcomes was lower during the second pandemic wave, which may be explained by advances in the understanding of the disease and improved treatment options.