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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.

The ICD-10-CM classification system contains more specificity than its predecessor ICD-9-CM. A stated reason for transitioning to ICD-10-CM was to increase the availability of detailed data. This study aims to determine whether the increased specificity contained in ICD-10-CM is utilized in the ambulatory care setting and inform an evidence-based approach to evaluate ICD-11 content for implementation planning in the United States.

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.