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This work evaluated algorithmic bias in biomarkers classification using electronic pathology reports from female breast cancer cases. Bias was assessed across 5 subgroups: cancer registry, race, Hispanic ethnicity, age at diagnosis, and socioeconomic status.

The objective of the study was to determine, after medication review, the patient risk score threshold that would distinguish between stays with prescriptions triggering pharmacist intervention (PI) and stays with prescriptions not triggering PI.

Data-sharing policies are rapidly evolving toward increased data sharing. However, participants' perspectives are not well understood and could have an adverse impact on participation in research. We evaluated participants' preferences for sharing specific types of data with specific groups, and strategies to enhance trust in data-sharing practices.

Electronic patient portals (PP) allow for targeted and efficient research recruitment. We assessed pre- and postnatal women's recruitment methods preferences, focusing on PP.

To semantically enrich the laboratory data dictionary of the Study of Health in Pomerania (SHIP), a population-based cohort study, with LOINC to achieve better compliance with the FAIR principles for data stewardship.

To develop and disseminate a technical framework for administering the Research Participant Perception Survey (RPPS) and aggregating data across institutions using REDCap.

We conducted a scoping review to identify barriers to telehealth use and uptake from the perspective of patient, provider, and system that were documented in the literature. In addition to identifying and categorizing the barriers, we aimed to assess how barriers differed for studies conducted during the COVID-19 pandemic, as well as how barriers differed between the United States vs internationally based studies.

Observational data have been actively used to estimate treatment effect, driven by the growing availability of electronic health records (EHRs). However, EHRs typically consist of longitudinal records, often introducing time-dependent confounding that hinder the unbiased estimation of treatment effect. Inverse probability of treatment weighting (IPTW) is a widely used propensity score method since it provides unbiased treatment effect estimation and its derivation is straightforward. In this study, we aim to [...]

There is limited knowledge on how providers and patients in the emergency department (ED) use electronic health records (EHRs) to facilitate the diagnostic process. While EHRs can support diagnostic decision-making, EHR features that are not user-centered may increase the likelihood of diagnostic error. We aimed to identify how EHRs facilitate or impede the diagnostic process in the ED and to identify opportunities to reduce diagnostic errors and improve care quality.

To assess the capacity of a bespoke artificial intelligence (AI) process to help medical writers efficiently generate quality plain language summary abstracts (PLSAs).