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 To understand the status quo and related influencing factors of machine alarm fatigue of hemodialysis nurses in tertiary hospitals in Liaoning Province.

 Patient data are fragmented across multiple repositories, yielding suboptimal and costly care. Record linkage algorithms are widely accepted solutions for improving completeness of patient records. However, studies often fail to fully describe their linkage techniques. Further, while many frameworks evaluate record linkage methods, few focus on producing gold standard datasets. This highlights a need to assess these frameworks and their real-world performance. We use real-world datasets and expand upon previous [...]

 Managing acute postoperative pain and minimizing chronic opioid use are crucial for patient recovery and long-term well-being.

 Intensive care unit (ICU) clinicians encounter frequent challenges with managing vast amounts of fragmented data while caring for multiple critically ill patients simultaneously. This may lead to increased provider cognitive load that may jeopardize patient safety.

 Falls in older adults are a serious public health problem that can lead to reduced quality of life or death. Patients often do not receive fall prevention guidance from primary care providers (PCPs), despite evidence that falls can be prevented. Mobile health technologies may help to address this disparity and promote evidence-based fall prevention.

The goal of this study is to propose and test a scalable framework for machine learning (ML) algorithms to predict near-term severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases by incorporating and evaluating the impact of real-time dynamic public health data.

The Observational Health Data Sciences and Informatics (OHDSI) community has emerged as a leader in observational research on real-world clinical data for promoting evidence for healthcare and decision-making. The community has seen rapid growth in publications, citations, and the number of authors. Components of its successful uptake have been attributed to an open science and collaborative culture for research and development. Investigating the adoption of OHDSI as a field of [...]

To use natural language processing (NLP) of clinical notes to augment existing structured electronic health record (EHR) data for classification of a patient's menopausal status.

Despite the importance of using information for ovarian cancer (OvCa) disease management and decision-making, some women with OvCa do not actively seek out information. The purpose of this study is to investigate factors that influence information seeking behaviors and information avoidance behaviors and information resources among women with OvCa and their caregivers.

We sought to determine whether average cumulated time to chart closure (CTCC), a novel construct to measure clinician workload burden, and electronic health record (EHR) measures were associated with a validated measure of burnout.