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 Clinical decision support systems (CDSSs) are computer applications, which can be applied to give guidance to practitioners in antimicrobial stewardship (AS) activities; however, further information is needed for their optimal use.

The integration of these preventive guidelines with Electronic Health Records (EHRs) systems, coupled with the generation of personalized preventive care recommendations, holds significant potential for improving healthcare outcomes. Our study investigates the feasibility of using Large Language Models (LLMs) to automate the assessment criteria and risk factors from the guidelines for future analysis against medical records in EHR.

Author name incompleteness, referring to only first initial available instead of full first name, is a long-standing problem in MEDLINE and has a negative impact on biomedical literature systems. The purpose of this study is to create an Enhanced Author Names (EAN) dataset for MEDLINE that maximizes the number of complete author names.

The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the [...]

 The coronavirus disease 2019 pandemic accelerated the use of telehealth. However, this also exacerbated health care disparities for vulnerable populations.

 Though public health is an information-intense profession, there is a paucity of workforce with Public Health Informatics and Technology (PHIT) skills, which was evident during the coronavirus disease 2019 (COVID-19) pandemic. This need is addressed through the PHIT workforce program (2021-2025) by the Office of the National Coordinator for training and to increase racial and ethnic diversity in the PHIT workforce. The objective is to share details on the Training [...]

 The lack of feasible and meaningful measures of clinicians' behavior hinders efforts to assess and improve obesity management in pediatric primary care. In this study, we examined the external validity of a novel algorithm, previously validated in a single geographic region, using structured electronic health record (EHR) data to identify phenotypes of clinicians' attention to elevated body mass index (BMI) and weight-related comorbidities.

The current medical paradigm of evidence-based medicine relies on clinical guidelines derived from randomized clinical trials (RCTs), but these guidelines often overlook individual variations in treatment effects. Approaches have been proposed to develop models predicting the effects of individualized management, such as predictive allocation, individualizing treatment allocation. It is currently unknown whether widespread implementation of predictive allocation could result in better population-level outcomes over guideline-based therapy. We sought to simulate [...]