e.g. mhealth
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Recent studies have also used machine learning models specifically trained to automate the capture and characterization of clinician documentation of tumor response. These specialized models have shown varying accuracies [9,10].
JMIR Cancer 2025;11:e64697
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The increased sophistication of EHR systems has introduced documentation requirements and clinician decision support tools, potentially increasing clinicians’ documentation burden [4]. The American Medical Informatics Association (AMIA) describes documentation burden as the stress resulting from excessive work that is required to document in the EHR [5].
Nurses are one of the largest user groups of the EHR system and are primary users of flowsheet tools for documentation [6].
JMIR Nursing 2025;8:e69651
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Guideline-Incorporated Large Language Model-Driven Evaluation of Medical Records Using MedCheckLLM
documentation
JMIR Form Res 2025;9:e53335
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Documentation in the electronic health record (EHR) can provide this opportunity. Furthermore, poor documentation can reflect lack of refined CR and has been hypothesized to be linked to diagnostic errors [2-4].
J Med Internet Res 2025;27:e67967
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Furthermore, Levy et al [23] emphasized that health professionals encounter an excessive documentation burden when the usability of the documentation systems fails to adequately support patient care delivery. This highlights the crucial role of systems’ usability and the need to assess their impact on documentation practices.
JMIR Form Res 2025;9:e63902
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documentation scientific response documentation
JMIR AI 2025;4:e55277
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Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study
In total, 21 medical students with experience in clinical practice and clinical documentation from Leiden University Medical Center consented to participate in our study. All students had a bachelor’s degree in medicine and completed a course in clinical documentation. The students received a compensation of €100 (US $111) for their participation.
Autoscriber is a web-based software application that transcribes and summarizes medical conversations (currently with support for Dutch, English, and German).
JMIR AI 2024;3:e60020
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Other barriers to escalation include delays in documentation, lack of familiarity with the escalation protocol, failure to follow the protocol, and poor communication [10,11].
Digital EWS systems have been proposed as a solution. These systems automatically calculate the EWS based on data input by staff and display relevant information from the escalation protocol.
J Med Internet Res 2024;26:e46691
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Mobile devices may also reduce duplicate documentation [13] and potential documentation errors [17,20] because client data can be documented at the time of its occurrence. In addition, improved decision-making is one of the main advantages [9,20]. Mobile devices continuously provide the latest information on the situation of the clients, which can improve safety and the quality of care [14,18].
J Med Internet Res 2024;26:e46954
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