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A Nurse-Initiated Protocol for Interprofessional Management of Changed Behaviours in Hospital Patients With Dementia and/or Delirium: A Modified e-Delphi Study.
J Adv Nurs
January 2025
Nursing Practice Development Unit, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia.
Aim: To develop a nurse-initiated protocol for early ward-based interprofessional coordination and formulation of person-centred care plans to assist in point-of-care management of behaviour in older patients on general hospital wards.
Design: A modified e-Delphi method was employed to establish expert consensus.
Method: Multidisciplinary acute-care experts experienced in hospital care of patients with dementia and/or delirium in Australia were recruited by email from 35 professional networks.
Diagnoses of postpartum urinary retention using next-generation non-piezo ultrasound technology: assessing the accuracy and benefits.
Sci Rep
December 2024
Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Venusberg Campus 1, 53127, Bonn, Germany.
Postpartum urinary retention has a wide range of publicized incidences, likely caused by frequent misdiagnosis of this puerperal complication. Especially covert postpartum urinary retention has a high number of missed diagnoses due to the lack of symptoms and the time-extensive diagnostics via ultrasound, leading to no treatment and no appropriate follow-up. To simplify the diagnosis and establish a screening tool we analyzed the application of portable handheld-ultrasound devices (PUD) as used in Point-of-care diagnostics in comparison to established standard ultrasound devices (SUD).
View Article and Find Full Text PDFPathways for Identifying Problems in Nursing Quality on-Site Supervision: A Descriptive Qualitative Study.
J Multidiscip Healthc
December 2024
Department of Digestive Oncology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, People's Republic of China.
Background: When the nursing department of our hospital checked the ward round records of the head nurse, it was found that some problems could not be found during rounds, and most of the problems found were superficial; Some studies have also found that most nursing managers are only going through the motions during rounds or are unable to identify problems due to a mismatch between their professional competence and the supervised department, or fail to identify superficial or deep-seated problems, making the quality of nursing supervision unsatisfactory.
Purpose: To sort out the ideas and ways for nursing managers to identify problems in on-site supervision of nursing quality and to provide ideas and directions for being able to identify problems, identifying problems quickly, and identifying high-quality problems in the supervision.
Methods: A descriptive qualitative study was used to conduct face-to-face semi-structured interviews with 14 nursing managers from Bethune Hospital in Shanxi, China.
Finite Element Analysis of the Stress Changes Associated With the Growth of Acne Keloids.
Plast Reconstr Surg Glob Open
December 2024
Department of Plastic, Reconstructive and Regenerative Surgery, Graduate School of Medicine, Nippon Medical School, Bunkyo Ward, Tokyo, Japan.
Background: Almost half of all spontaneously occurring keloids are acne keloids on the anterior chest. These keloids often grow in a crab-claw shape due to predominant tractional stresses on the scar; such stresses are risk factors for keloid growth/progression. To understand the relationship between acne keloid growth and mechanical stress, we conducted finite element analysis (FEA), measured the long/short dimensions of photographed acne keloids, and subjected acne keloids to microscopy.
View Article and Find Full Text PDFEvaluating the Impact of Artificial Intelligence (AI) on Clinical Documentation Efficiency and Accuracy Across Clinical Settings: A Scoping Review.
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.
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