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This study evaluates the effect of speech recognition software Dragon Medical One (DMO) on physician documentation burden and EHR workflows using Epic Signal usage metrics.

This study evaluated the usability of EzList, a Brazilian digital platform developed to optimize elective surgical waitlist management.

Many institutions have reported poor mapping of laboratory results to Logical Observation Identifiers Names and Codes (LOINC). A human in the loop machine learning approach for clinical terminology management may help.

Hospital supply rooms are dense, vertically complex environments where clinicians may lose time locating items. Existing text-based inventory logs require mental translation from alphanumeric codes to physical space, adding cognitive load during time-sensitive tasks. Despite growing use of digital twins in health care, this technology has been underreported in supply room navigation.

To support the artificial intelligence (AI) lifecycle in an integrated academic health system, we implemented a modular monitoring system to oversee electronic health record (EHR) vendor-provided clinical predictive models. This case study describes the lessons learned using this modular system to support sustainable oversight of the deployed predictive models across their lifecycle.

Admission history and physical (H&P) notes influence inpatient documentation, risk adjustment, and reimbursement. In high-acuity settings, time constraints and fragmented chart data contribute to under-documentation of comorbidities. Generative AI systems that draft admission notes from existing electronic health record data may improve documentation completeness, but real-world inpatient performance remains insufficiently characterized.

Central line-associated bloodstream infections (CLABSIs) are a significant concern in pediatric intensive care units (PICUs), leading to increased morbidity and limited treatment options. Electronic health record (EHR)-based documentation for monitoring CLABSIs may enhance bundle compliance and reduce infection rates. However, data in pediatric settings are limited.This study evaluated the impact of transitioning from paper-based to EHR-based documentation for central line maintenance on CLABSI rates in intensive care units (ICUs).A retrospective [...]

Electronic patient-centered clinical decision support enhances chronic disease self-management, yet few studies describe how qualitative user feedback is systematically translated into programming improvements. The Collaboration-Oriented Approach to Controlling High Blood Pressure (COACH) is a patient-facing decision support tool for hypertension management, designed for primary care and integration with electronic health records (EHRs) and patient portals.This study aimed to describe how end-user feedback informed COACH programming decisions and the MoSCoW (Must [...]

The objective of this study is to determine whether primary care electronic health record (EHR) data are sufficiently complete and plausible to support automated audits of antimicrobial prescribing quality.Cross-sectional descriptive assessment of antimicrobial auditing-related fields in Patron, a large Australian primary care EHR dataset with 3.5 million patients from 129 consenting general practices. Data from 2018 to 2022 were evaluated using the Harmonized Data Quality Assessment Terminology and Framework, covering [...]

Guidelines recommend measuring glycated hemoglobin (HgbA1c) levels on all inpatients with diabetes mellitus, if untested in the prior 3 months. In response, our health system applies default HgbA1c orders in the electronic insulin orders for qualifying patients. However, recent red blood cell transfusions may cause falsely low HgbA1c values, leading to inappropriate management. Clinicians often forget to deselect default HgbA1c orders after transfusion, leading to erroneous results. We evaluated a [...]