ISPE‐Endorsed Guidance in Using Electronic Health Records for Comparative Effectiveness Research in COVID‐19: Opportunities and Trade‐Offs

Abstract

As the scientific research community along with healthcare professionals and decision makers around the world fight tirelessly against the coronavirus disease 2019 (COVID‐19) pandemic, the need for comparative effectiveness research (CER) on preventive and therapeutic interventions for COVID‐19 is immense. Randomized controlled trials markedly under‐represent the frail and complex patients seen in routine care, and they do not typically have data on long‐term treatment effects. The increasing availability of electronic health records (EHRs) for clinical research offers the opportunity to generate timely real‐world evidence reflective of routine care for optimal management of COVID‐19. However, there are many potential threats to the validity of CER based on EHR data that are not originally generated for research purposes. To ensure unbiased and robust results, we need high‐quality healthcare databases, rigorous study designs, and proper implementation of appropriate statistical methods. We aimed to describe opportunities and challenges in EHR‐based CER for COVID‐19‐related questions and to introduce best practices in pharmacoepidemiology to minimize potential biases. We structured our discussion into the following topics: (1) study population identification based on exposure status; (2) ascertainment of outcomes; (3) common biases and potential solutions; and (iv) data operational challenges specific to COVID‐19 CER using EHRs. We provide structured guidance for the proper conduct and appraisal of drug and vaccine effectiveness and safety research using EHR data for the pandemic. This paper is endorsed by the International Society for Pharmacoepidemiology (ISPE).

Prognostic Factors of COVID‐19: An Umbrella Review Endorsed by the International Society for Pharmacoepidemiology

“…to COVID-19, as recommended by a recent ISPE-endorsed publication. 8 We found more consistent evidence for some predictors/risk factors compared with others, and this was noted in the findings when possible. There may have been differences in the robustness of results across SLRs (for example, some of them only included observational studies with adjusted results for key confounders or population-based studies 40 ), which is reflected in both the quality assessments and through their interpretation such as supplementary sensitivity analyses.…”

Advancing evidence-based treatment of infectious diseases in children with real-world data: Opportunities and challenges

“…Such evidence can be useful in informing treatment selection to optimize effectiveness and safety or identify patient subgroups that may benefit from one pharmaceutical intervention over another ( Arterburn et al, 2018 ; Suchard et al, 2019 ). The study population, design, and statistical methodologies must be well-defined and rigorously developed to ensure findings are valid and unbiased ( Sarri et al, 2022 ). Safety analysis will be limited to known adverse events where data (e.g., laboratory measurements) is routinely collected as part of therapeutic management and monitoring.…”

Methods for comparative effectiveness based on time to confirmed disability progression with irregular observations in multiple sclerosis

“…Although these databases with real-world data (RWD) offer new opportunities to study the effectiveness of medical interventions, exposure and outcome variables are often unavailable for key study dates. [1][2][3][4] Missing outcome data is particularly common in registries, where the measurement interval of outcome variables is irregular and tends to vary across individuals due to a lack of formalized data recording processes. The analysis of RWD therefore often requires censoring individuals with incomplete outcome data, which is problematic when outcome variables are incomplete for most individuals and may lead to bias when the censoring mechanism is informative.…”