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Maternal harm, especially for Black women, is a significant health care issue. Unstructured clinical notes in electronic health records (EHRs) may reveal unsafe maternal care. Prior studies using natural language processing (NLP) have shown that tone and sentiment in notes contribute to preventable safety events.This study aimed to examine whether negative patient descriptors in EHR clinical notes are associated with adverse maternal outcomes and how their use varies by patient [...]

Direct Secure Messaging (DSM) is a communication standard for exchanging information between health care entities and practitioners. It relies on access to an address directory. When directory entry is incomplete, health information exchange breaks down. There is an urgent need for standardized DSM address directory management and synchronization workflows that support universal access in a timely manner.Our objective was to develop best practices for maintenance of DSM address directories and [...]

Our objective was to identify barriers to implementing a custom clinical decision support (CDS) alert to randomize individuals in a pragmatic study, specifically those with a positive antinuclear antibody (ANA) test.We integrated a validated logistic regression model into the electronic health record to predict the risk of developing autoimmune disease for individuals with a positive ANA (titer ≥ 1:80). A custom CDS alert was created to randomize eligible individuals into [...]

Long COVID, characterized by persistent or recurring symptoms post-COVID-19 infection, poses challenges for pediatric care and research due to the lack of a standardized clinical definition. Adult-focused phenotypes do not translate well to children, given developmental and physiological differences, and pediatric-specific phenotypes have not been compared with chart review.This study introduces and evaluates a pediatric-specific rule-based computable phenotype (CP) to identify long COVID using electronic health record data. We compare [...]

The widespread adoption of health information technology (HIT) has deepened hospitals' reliance on electronic health records (EHR). However, EHR downtime events, which refer to partial or complete system failures, can disrupt hospital operations and threaten patient safety. Systematic research on HIT downtime events in China remains limited.This study aims to identify and classify reported EHR downtime events in a Chinese hospital, assess their frequency and severity, and propose improvement recommendations [...]

The digital availability of health data not only improves processes in primary care, but it also facilitates the evaluation of healthcare delivery. Nevertheless, the preprocessing of data for secondary use is still time-consuming and expensive, particularly in head and neck cancer (HNC), where patients undergo complex multidisciplinary treatment trajectories. Therefore, we have looked further into the effects on data quantity and quality following the implementation of structured care pathways. Leveraging [...]

The adoption of electronic health records (EHRs) into clinical practice has changed clinical workflows and, in some cases, increased documentation burden and clinician burnout. Identifying factors associated with perceived EHR usability after the implementation of a new EHR may guide efforts to reduce burden and burnout.This study measured: (1) group-level perceptions of EHR usability pre- and postimplementation of a new EHR; (2) adaptation to the new EHR; and (3) the [...]

Clinical decision support (CDS) tools are critical for improving care delivery and guideline adherence but are associated with clinician burnout when inadequately designed and implemented. User-centered design (UCD) and implementation science (IS) methods are evidence-based approaches to optimizing CDS tools, but are infrequently used in part due to limited guidance on how to apply them within resource-constrained health systems.This paper focuses on pragmatic application of an integrated UCD-IS approach, demonstrating [...]

Federated network studies allow data to remain locally while the research is conducted through the sharing of analytical code and aggregated results across different health care settings and countries. A large number of databases have been mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), boosting the use of analytical pipelines for standardized observational research within this open science framework. Transparency, reproducibility, and robustness of results have [...]

This study aimed to leverage a large language model (LLM) to improve the efficiency and thoroughness of medical record documentation. This study focused on aiding clinical staff in creating structured summaries with the help of an LLM and assessing the quality of these artificial intelligence (AI)-proposed records in comparison to those produced by doctors.This strategy involved assembling a team of specialists, including data engineers, physicians, and medical information experts, to [...]