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Our study aims to assess the time-cost burden reduction of transitioning from manual case reporting to electronic case reporting (eCR) for COVID-19 among healthcare organizations (HCOs) over a 1-year period.

Efficient exchange of health information requires consistent representation of clinical concepts across laboratories, hospitals, and public health systems. LOINC supports this interoperability by standardizing laboratory test codes, but mapping remains difficult when datasets are incomplete, inconsistently formatted, or structurally diverse. These challenges often create a mismatch between algorithmic performance in controlled settings and real-world deployment. This study aimed to develop a biomedical natural language processing (NLP) approach for mapping heterogeneous [...]

To comprehensively evaluate the validity of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes for both prevalent diagnoses and less common diseases, and to assess the performance of a large language model (LLM)-based system in validating these codes.

Implementing biomedical informatics (BMI) tools and applications into clinical and other settings remains a significant challenge. Unintended consequences remain common post-implementation. This paper addresses the above issue by integrating systems thinking and implementation science approaches to support health information technology (HIT) implementation.

Ohio has been severely impacted by the opioid crisis, with opioid overdose (OD) death rates exceeding national averages. Accurate OD death prediction supports proactive prevention and treatment allocation. Existing methods often focus on ZIP Code Tabulation Area (ZCTA)-level prediction for small-area resource allocation; however, performance at this resolution is poor due to substantial fluctuations in OD death counts, which introduce noise. This raises a critical methodological question: what is the [...]

This study compares multiple LLMs, including ChatGPT, DeepSeek, and Llama, to generate meaningful, audience-adapted labels for the existing latent classes among patients with chronic low back pain (cLBP).

The pandemic dramatically increased in the frequency of audiovisual medical visits and the rate of audiovisual visits remains higher than before the pandemic. These visits have the potential to be an important clinical modality. Researchers have assessed several aspects of audiovisual visits but they have not investigated their clinical note quality. The goal of this study is to determine the quality of audiovisual and in-person clinical notes and to compare [...]

This study aims to understand how inpatient nurses determine and prioritize necessary documentation within the context of the Excessive Documentation Burden (ExDocBurden) in Electronic Health Records (EHRs).

This proof of concept for utilizing automatic data extraction methods to extract health technology assessment (HTA) attributes from HTA reports of medicines aimed to explore which attributes could be extracted and how accurately, using different data extraction methods. This enables easy access to insights into HTA recommendations for policymaking and policy-related research.

This study aimed to provide a comprehensive understanding of factors associated with Alzheimer's disease (AD) and AD-related dementias (AD/ADRD), which could aid in studies to develop new treatments for AD/ADRD patients and identify high-risk populations for prevention.