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One key aspect of a learning health system (LHS) is utilizing data generated during care delivery to inform clinical care. However, institutional guidelines that utilize observational data are rare and require months to create, making current processes impractical for more urgent scenarios such as those posed by the COVID-19 pandemic. There exists a need to rapidly analyze institutional data to drive guideline creation where evidence from randomized control trials are [...]

The purpose of this study was to explore the effect of telehealth education and care guidance via WeChat (Tencent Ltd., Shenzhen, China; a popular smartphone-based social media application) on improving the quality of life of parents of children with type-1 diabetes mellitus.

Food practice plays an important role in health. Food practice data collected in daily living settings can inform clinical decisions. However, integrating such data into clinical decision-making is burdensome for both clinicians and patients, resulting in poor adherence and limited utilization. Automation offers benefits in this regard, minimizing this burden resulting in a better fit with a patient's daily living routines, and creating opportunities for better integration into clinical workflow [...]

Providing patients with medical records access is one strategy that health systems can utilize to reduce medical errors. However, how often patients request corrections to their records on a national scale is unknown.

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic threatened to oversaturate hospitals worldwide, necessitating rapid patient discharge to preserve capacity for the most severe cases. This need, as well as the high risk of SARS-CoV-2 transmission, led many hospitals to implement remote patient monitoring (RPM) programs for SARS-CoV-2 positive patients in an effort to provide care that was safe and preserve scarce resources.

The rapid, large-scale deployment of new health technologies can introduce challenges to clinicians who are already under stress. The novel coronavirus disease 19 (COVID-19) pandemic transformed health care in the United States to include a telehealth model of care delivery. Clarifying paths through which telehealth technology use is associated with change in provider well-being and interest in sustaining virtual care delivery can inform planning and optimization efforts.

Predictive analytic models, including machine learning (ML) models, are increasingly integrated into electronic health record (EHR)-based decision support tools for clinicians. These models have the potential to improve care, but are challenging to internally validate, implement, and maintain over the long term. Principles of ML operations (MLOps) may inform development of infrastructure to support the entire ML lifecycle, from feature selection to long-term model deployment and retraining.

The term "data science" encompasses several methods, many of which are considered cutting edge and are being used to influence care processes across the world. Nursing is an applied science and a key discipline in health care systems in both clinical and administrative areas, making the profession increasingly influenced by the latest advances in data science. The greater informatics community should be aware of current trends regarding the intersection of [...]