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Measurement-based care (MBC) improves clinical decision-making but remains underutilized in the Veterans Health Administration due to barriers such as provider awareness, time constraints, and user-experience limitations. This study describes the development of the War Related Illness and Injury Study Center Veteran Dashboard (VetDash), a patient-level clinical dashboard designed to integrate the VA's Collect, Share, Act model into the provider workflow.

Venous thromboembolism (VTE) prophylaxis in hospitalized patients must balance risks of bleeding and thrombosis. Clinical changes such as bleeding or renal injury can also trigger changes or delays in thromboprophylaxis. Electronic health record alerts (EHRAs) can allow for targeted notification to providers to improve venous thromboembolism prophylaxis and improve patient outcomes at the risk of alert fatigue if not carefully designed and implemented.

Artificial intelligence (AI) scribes may reduce documentation burden and improve clinician experience through generative AI automatically producing provider note sections from recordings of patient-provider encounters.

Background Health consumers can use generative artificial intelligence (GenAI) chatbots to seek health information. As GenAI chatbots continue to improve and be adopted, it is crucial to examine how health information generated by such tools is used and perceived by health consumers. Objective To conduct a scoping review of health consumers' use and perceptions of health information from GenAI chatbots. Methods Arksey and O'Malley's five-step protocol was used to guide [...]

Despite the benefits of Clinical Decision Support (CDS), concerns of potential risks arise amidst increasing reports of CDS malfunctions. Without objective and standard methods to evaluate CDS in post-live stage, CDS performance in dynamic healthcare environment remains a black box from user perspective. In this study, we proposed a comprehensive framework to identify and evaluate post-live CDS malfunctions from the perspective of healthcare settings.

Telemedicine use has surged since the COVID-19 pandemic, offering a convenient way for patients to access healthcare. Whereas digital literacy (general comfort with and ability to use digital tools) is necessary to utilize telemedicine, digital health literacy is a subset of this, focusing on the ability to use digital tools to seek out, understand, and utilize health information. As such, barriers such as the lack of high-speed internet and limited [...]

Despite its morbidity, mortality, and financial burden, in-hospital malnutrition remains underdiagnosed and undertreated. Artificial intelligence offers a promising clinical informatics solution for identifying malnutrition risk and one that can be coupled with clinician-delivered patient care.

Appropriate Use Criteria Clinical Decision Support (AUC CDS) was legislatively mandated in the United States in 2014, and multiple CDS vendors were designated as qualified Clinical Decision Support Mechanisms by the Centers for Medicare and Medicaid Services. Little is known about the costs and benefits of these systems in real-world settings.

To evaluate and compare the diagnostic responses generated by two artificial intelligence models developed 54 years apart and to encourage physicians to explore the use of large language models (LLMs) like GPT-4o in clinical practice.

Health equity is greatly impacted by the systems and processes with which health systems deliver care. Given the minimal guidance on measurement and reporting of health inequities specific to key population health outcomes, a solution for measurement of health equity is proposed.