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To synthesize data quality (DQ) dimensions and assessment methods of real-world data, especially electronic health records, through a systematic scoping review and to assess the practice of DQ assessment in the national Patient-centered Clinical Research Network (PCORnet).

We describe our approach in using health information technology to provide a continuum of services during the coronavirus disease 2019 (COVID-19) pandemic. COVID-19 challenges and needs required health systems to rapidly redesign the delivery of care.

The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present [...]

Accumulating evidence demonstrates the impact of bias that reflects social inequality on the performance of machine learning (ML) models in health care. Given their intended placement within healthcare decision making more broadly, ML tools require attention to adequately quantify the impact of bias and reduce its potential to exacerbate inequalities. We suggest that taking a patient safety and quality improvement approach to bias can support the quantification of bias-related effects [...]

Increasing recognition of biases in artificial intelligence (AI) algorithms has motivated the quest to build fair models, free of biases. However, building fair models may be only half the challenge. A seemingly fair model could involve, directly or indirectly, what we call "latent biases." Just as latent errors are generally described as errors "waiting to happen" in complex systems, latent biases are biases waiting to happen. Here we describe 3 [...]

Systematic reviews are important in health care but are expensive to produce and maintain. The authors explore the use of automated transformations of Boolean queries to improve the identification of relevant studies for updates to systematic reviews.

Reducing risk of coronavirus disease 2019 (COVID-19) infection among healthcare personnel requires a robust occupational health response involving multiple disciplines. We describe a flexible informatics solution to enable such coordination, and we make it available as open-source software.

Biomedical informatics attracts few underrepresented racial minorities (URMs) into PhD programs. We examine graduation trends from 2002 to 2017 to determine how URM representation has changed over time. We also examine academic job placements by race and identify individual and institutional characteristics associated with URM graduates being successfully placed in academic jobs.