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This study aimed to evaluate and compare the diagnostic responses generated by two artificial intelligence (AI) models developed 54 years apart, and encourage physicians to explore the use of large language models (LLMs) like GPT-4o in clinical practice.A clinical case of metabolic acidosis was presented to GPT-4o, and the model's diagnostic reasoning, data interpretation, and management recommendations were recorded. These outputs were then compared with the responses from Schwartz's 1970 [...]

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.The concept of a lens of equity was adopted to disaggregate common measures such as breast cancer screening rates to expose inequities across neighborhoods and races in populations served [...]

Quantify the effect of ambient artificial intelligence (AI) scribe technology on work experience, clinical operations, and patient experience in pediatric primary care.We conducted a 12-week study of 39 clinicians within a large pediatric primary care network. Clinician experience was measured using a custom survey instrument which included a combination of discrete and free-text responses. Qualitative analysis of free-text responses provided additional context and identified key facilitators and barriers to optimal [...]

Health professionals (HPs) trainee burnout is hard to capture. A lack of rigorous review and systematic methodological consideration hinders the development of qualitative methodological tools that can elicit rich and trustworthy qualitative data on HPs trainee burnout.This study aimed to report the process, results, and lessons learned while developing and pilot testing a qualitative tool to assess HPs' trainee experiences of burnout to complement quantitative tools.We developed a set of [...]

In recent years, there has been an expansion in the literature on the effects of computerized alerts on prescribing and patient outcomes. The aim of our study was to examine the impact of these systems on clinician prescribing and patient outcomes.We searched three databases (Medline, Embase, and PsychINFO) for studies that had been conducted since 2009 and included studies that examined the effects of alerts at the point of prescribing [...]

Clinical decision support systems (CDSS) are central to modern health care, but their effectiveness is compromised during system downtimes, which affect 96% of health care organizations. During these failures, clinicians lose access to critical decision-making tools like order sets, increasing the risk of medical errors. Traditional downtime solutions, such as paper-based protocols, are often impractical and difficult to maintain.This study introduces and evaluates Offsite Repository for Clinical Assets (ORCA), a [...]

Electronic health records (EHRs) are widely implemented and consume nearly half of physicians' work time. Despite the importance of efficient data entry, physicians' typing skills-potential contributors to documentation burden-remain poorly studied.This study aims to evaluate the typing skills of physicians and their associations with demographic characteristics and professional roles.This cross-sectional pilot study included a convenience sample of physicians (residents, chief residents, and attending physicians) from the internal medicine division of [...]

Risk prediction models are used in hospitals to identify pediatric patients at risk of clinical deterioration, enabling timely interventions and rescue. The objective of this study was to develop a new explainer algorithm that uses a patient's clinical notes to generate text-based explanations for risk prediction alerts.

In real-world data (RWD), defining the observation period-the time during which a patient is considered observable-is critical for estimating incidence rates (IRs) and other outcomes. Yet, in the absence of explicit enrollment information, this period must often be inferred, introducing potential bias.