The problem of clinical documentation burden is ever-growing. Electronic documentation tools such as "dotphrases" were invented to help with the documentation burden. Despite the ubiquity of these tools, they are understudied. We present work on the usage of dotphrases within the emergency department. We find that dotphrases are most often used by medical scribes, they significantly increase note length, and are completely unstandardized as to their naming conventions, content, and usage. We find that there is inconsistent usage across and within providers and that there is much duplication in the dotphrase content. We also show that dotphrases have no effect on the time to complete and cosign a note. Finally, we demonstrate that even when accounting for patient complexity upon presentation, note authorship, and note length - notes with higher dotphrase usage are billed at higher billing levels.
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Europace
December 2024
Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
In 1924, the Dutch physiologist Willem Einthoven received the Nobel Prize in Physiology or Medicine for his discovery of the mechanism of the electrocardiogram (ECG). Anno 2024, the ECG is commonly used as a diagnostic tool in cardiology. In the paper 'Le Télécardiogramme', Einthoven described the first recording of the now most common cardiac arrhythmia: atrial fibrillation (AF).
View Article and Find Full Text PDFJ Psychosom Res
December 2024
Department of Psychosomatic Medicine and Psychotherapy, General Hospital Nuremberg, Paracelsus Medical University, Prof.-Ernst-Nathan-Str. 1, 90419 Nuremberg, Germany. Electronic address:
Background: Clinical experiences using a psychosomatic-oriented multimodal treatment approach in patients with post-COVID are promising. We established a half-day multimodal treatment program for post-COVID patients at the Department of Psychosomatic Medicine at General Hospital Nuremberg, Paracelsus Medical University, Germany.
Methods: This observational study between January 2022 and March 2023 comprised baseline documentation of Patient Health Questionnaire (PHQD), ICD-10 Symptom Rating (ISR), Fatigue Scale (FS) and Health Status Questionnaire (SF-12) at admission and discharge of 65 patients suffering from post-COVID.
J Gen Intern Med
December 2024
Division of General Internal Medicine and Geriatrics, Indiana University School of Medicine, Indianapolis, IN, USA.
Background: Patients who have been discharged "against medical advice" (AMA) are at increased risk of morbidity and mortality, but there is little research about patients who have had more than one AMA discharge.
Objective: We aimed to describe the socio-demographic and clinical characteristics of patients with more than one AMA discharge.
Design: We conducted a cross-sectional, retrospective chart review of a sample of adult patients who were discharged AMA more than once between 2016 and 2021 and abstracted detailed characteristics of this sample.
Cureus
November 2024
General Internal Medicine, University Hospitals Plymouth NHS Trust, Plymouth, GBR.
Artificial intelligence (AI) technologies (natural language processing (NLP), speech recognition (SR), and machine learning (ML)) can transform clinical documentation in healthcare. This scoping review evaluates the impact of AI on the accuracy and efficiency of clinical documentation across various clinical settings (hospital wards, emergency departments, and outpatient clinics). We found 176 articles by applying a specific search string on Ovid.
View Article and Find Full Text PDFLancet Digit Health
January 2025
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK; Centre for Patient Reported Outcomes Research, School of Health Sciences, College of Medical and Dental Sciences, Birmingham, UK; University of Birmingham, Birmingham, UK. Electronic address:
Without careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups.
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