This review examines how the adoption of the electronic health record (EHR) has changed the most fundamental unit of medicine: the clinical examination. The impact of the EHR on the clinical history, physical examination, documentation, and the doctor-patient relationship is described. The EHR now has a dominant role in clinical care and will be a central factor in clinical work of the future. Conversation needs to be shifted toward defining best practices with current EHRs inside and outside of the examination room.
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http://dx.doi.org/10.1016/j.mcna.2017.12.009 | DOI Listing |
JMIR Ment Health
December 2024
Otsuka Pharmaceutical Development & Commercialization, Inc, 508 Carnegie Center Drive, Princeton, NJ, 08540, United States, 1 609 535 9035.
Background: Sleep-wake patterns are important behavioral biomarkers for patients with serious mental illness (SMI), providing insight into their well-being. The gold standard for monitoring sleep is polysomnography (PSG), which requires a sleep lab facility; however, advances in wearable sensor technology allow for real-world sleep-wake monitoring.
Objective: The goal of this study was to develop a PSG-validated sleep algorithm using accelerometer (ACC) and electrocardiogram (ECG) data from a wearable patch to accurately quantify sleep in a real-world setting.
Proc (IEEE Int Conf Healthc Inform)
June 2024
College of Medicine, University of Florida, Gainesville, FL, USA.
Multivariate clinical time series data, such as those contained in Electronic Health Records (EHR), often exhibit high levels of irregularity, notably, many missing values and varying time intervals. Existing methods usually construct deep neural network architectures that combine recurrent neural networks and time decay mechanisms to model variable correlations, impute missing values, and capture the impact of varying time intervals. The complete data matrices thus obtained from the imputation task are used for downstream risk prediction tasks.
View Article and Find Full Text PDFProc (IEEE Int Conf Healthc Inform)
June 2024
Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA.
Delirium is an acute decline or fluctuation in attention, awareness, or other cognitive function that can lead to serious adverse outcomes. Despite the severe outcomes, delirium is frequently unrecognized and uncoded in patients' electronic health records (EHRs) due to its transient and diverse nature. Natural language processing (NLP), a key technology that extracts medical concepts from clinical narratives, has shown great potential in studies of delirium outcomes and symptoms.
View Article and Find Full Text PDFFront Nutr
December 2024
School of Nursing, Fujian Medical University, Fuzhou, China.
Background: Cholesterol is essential for pregnant women to maintain maternal health and fetal support development. This study aimed to assess the cholesterol intake of women with gestational diabetes mellitus (GDM) during the second and third trimesters of pregnancy and to explore its effects on blood glucose and pregnancy outcomes.
Methods: This prospective cohort study collected dietary data using a food frequency questionnaire (FFQ) administered during the 24-30 gestational weeks (first survey) and the 34-42 gestational weeks (second survey).
Cureus
December 2024
Trauma and Orthopaedics, Wrightington Hospital, Wigan, GBR.
Introduction Increasing demand and financial burdens are placing significant strain on current health resources. To help ease pressures, there has been increased emphasis on improving patient flow and saving costs within the health service. Routine postoperative blood tests in otherwise healthy patients may add to delays and healthcare costs without influencing subsequent management.
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