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The Safety Assurance Factors for Electronic Health Record (EHR) Resilience (SAFER) Guides provide recommendations to healthcare organizations for conducting proactive self-assessments of the safety and effectiveness of their EHR implementation and use. Originally released in 2014, they were last updated in 2016. In 2022, the Centers for Medicare and Medicaid Services required their annual attestation by US hospitals.

Large language models (LLMs) are increasingly utilized in healthcare, transforming medical practice through advanced language processing capabilities. However, the evaluation of LLMs predominantly relies on human qualitative assessment, which is time-consuming, resource-intensive, and may be subject to variability and bias. There is a pressing need for quantitative metrics to enable scalable, objective, and efficient evaluation.

We developed and validated a large language model (LLM)-assisted system for conducting systematic literature reviews in health technology assessment (HTA) submissions.

The vast and complex nature of human genomic sequencing data presents challenges for effective analysis. This review aims to investigate the application of natural language processing (NLP) techniques, particularly large language models (LLMs) and transformer architectures, in deciphering genomic codes, focusing on tokenization, transformer models, and regulatory annotation prediction. The goal of this review is to assess data and model accessibility in the most recent literature, gaining a better understanding [...]

Accurate, complete allergy histories are critical for decision-making and medication prescription. However, allergy information is often spread across the electronic health record (EHR); thus, allergy lists are often inaccurate or incomplete. Discrepant allergy information can lead to suboptimal or unsafe clinical care and contribute to alert fatigue. We developed an allergy reconciliation module within Mass General Brigham (MGB)'s EHR to support accurate and intuitive reconciliation of discrepancies in the allergy [...]

Modernizing and strengthening the US public health data and information infrastructure requires a strong public health informatics (PHI) workforce. The study objectives were to characterize existing PHI specialists and assess informatics-related training needs.

Digital health research involves collecting vast amounts of personal health data, making data management practices complex and challenging to convey during informed consent.

To assess the prevalence of recommended design elements in implemented electronic health record (EHR) interruptive alerts across pediatric care settings.

With the global population aging and advancements in the medical system, long-term care in healthcare institutions and home settings has become essential for older adults with disabilities. However, the diverse and scattered care requirements of these individuals make developing effective long-term care plans heavily reliant on professional nursing staff, and even experienced caregivers may make mistakes or face confusion during the care plan development process. Consequently, there is a rigid [...]