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Wrong drug product errors occurring in community pharmacies often originate at the transcription stage. Electronic prescribing and automated product selection are strategies to reduce product selection errors. However, it is unclear how often automated product selection succeeds in outpatient pharmacy platforms.

Determination of appropriate endoscopy sedation strategy is an important preprocedural consideration. To address manual workflow gaps that lead to sedation-type order errors at our institution, we designed and implemented a clinical decision support system (CDSS) to review orders for patients undergoing outpatient endoscopy.

Drug combination screening has advantages in identifying cancer treatment options with higher efficacy without degradation in terms of safety. A key challenge is that the accumulated number of observations in in-vitro drug responses varies greatly among different cancer types, where some tissues are more understudied than the others. Thus, we aim to develop a drug synergy prediction model for understudied tissues as a way of overcoming data scarcity problems.

Widespread technological changes, like the rapid uptake of telehealth in the US during the COVID-19 pandemic, risk creating or widening racial/ethnic disparities. We conducted a secondary analysis of a cross-sectional, nationally representative survey of internet users to evaluate whether there were racial/ethnic disparities in self-reported telehealth use early in the pandemic.

Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage, and treatment. Racial and ethnic disparities in healthcare have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess disparities in those who access healthcare via telemedicine for COVID-19.

The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe artificial intelligence (AI) is a solution to guide clinical decision-making for this novel disease, resulting in the rapid dissemination of underdeveloped and potentially biased models, which may exacerbate the disparities gap. We believe there is an urgent need to enforce the systematic use of reporting standards and develop regulatory frameworks [...]

The COVID-19 pandemic response in the United States has exposed significant gaps in information systems and processes that prevent timely clinical and public health decision-making. Specifically, the use of informatics to mitigate the spread of SARS-CoV-2, support COVID-19 care delivery, and accelerate knowledge discovery bring to the forefront issues of privacy, surveillance, limits of state powers, and interoperability between public health and clinical information systems. Using a consensus-building process, we [...]

Recently, there have been many efforts to use mobile apps as an aid in contact tracing to control the spread of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) (COVID-19 [coronavirus disease 2019]) pandemic. However, although many apps aim to protect individual privacy, the very nature of contact tracing must reveal some otherwise protected personal information. Digital contact tracing has endemic privacy risks that cannot be removed by technological means [...]

Clinical research informatics tools are necessary to support comprehensive studies of infectious diseases. The National Institute of Allergy and Infectious Diseases (NIAID) developed the publicly accessible Tuberculosis Data Exploration Portal (TB DEPOT) to address the complex etiology of tuberculosis (TB).

To develop a process for translating semi-structured clinical decision support (CDS) into shareable, computer-readable CDS.