Graphical Depiction of Longitudinal Study Designs in Health Care Databases

Abstract

Pharmacoepidemiologic and pharmacoeconomic analysis of health care databases has become a vital source of evidence to support health care decision making and efficient management of health care organizations. However, decision makers often consider studies done in nonrandomized health care databases more difficult to review than randomized trials because many design choices need to be considered. This is perceived as an important barrier to decision making about the effectiveness and safety of medical products. Design flaws in longitudinal database studies are avoidable but can be unintentionally obscured in the convoluted prose of methods sections, which often lack specificity. We propose a simple framework of graphical representation that visualizes study design implementations in a comprehensive, unambiguous, and intuitive way; contains a level of detail that enables reproduction of key study design variables; and uses standardized structure and terminology to simplify review and communication to a broad audience of decision makers. Visualization of design details will make database studies more reproducible, quicker to review, and easier to communicate to a broad audience of decision makers.

Transparency in real‐world evidence (RWE) studies to build confidence for decision‐making: Reporting RWE research in diabetes

“…It is vital to enable readers and decision‐makers to understand quickly yet comprehensively the basic temporality of the study design used to generate RWE. A group of experts and advisors from academia, regulatory, publishers, payers and industry, therefore, proposed a visualization schematic that illustrates comparative effectiveness study designs with longitudinal data . In this section, we summarize the proposed visualization framework.…”

“…This may include claims data, electronic health records, wearable devices, patient‐reported outcomes, or patient registries . These recommendations were discussed with multiple stakeholders, including, regulators, payers, academics and journal editors, and endorsed by two professional societies that focus on RWE, the International Society of Pharmacoepidemiology and the International Society for Pharmacoeconomics and Outcomes Research, and aim to provide guidance to the readership of RWE diabetes studies to understand each study more efficiently and assess a study's validity before making decisions based on its findings.…”

When Randomized Clinical Trials and Real‐World Evidence Say the Same: Tocilizumab and Its Cardiovascular Safety

“…However, it is important to note that the analysis of real‐world data requires experience with the data sources and training in pharmacoepidemiology. Steps that might improve confidence in RWE studies could include ways to improve transparency of data , preregistration of RWE studies , and systematic comparisons of RWE studies that emulate RCTs (see http://rctduplicate.org).…”

Discussion of Schuemie et al: “A plea to stop using the case‐control design in retrospective database studies”

“…Figure illustrates how a cohort study is constructed, starting with a cohort entry date, applying exclusion criteria, a covariate assessment window, exposure assessment, and follow‐up . Panels A and B illustrate the cohort and nested case‐control designs respectively, where all covariates were measured before the start of exposure, a key requirement for causal inference and avoiding adjusting for causal intermediates .…”