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http://dx.doi.org/10.1016/j.ejim.2022.03.018 | DOI Listing |
BMC Med Inform Decis Mak
July 2025
Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
Background: Sub-optimal healthcare quality in low-resource settings is attributed in part to poor adherence to clinical guidelines. Clinical decision support systems (CDSS) help to integrate guideline-based algorithms into logical workflows and improve adherence to evidence-based recommendations, and hence quality of care. However, the process of translating paper-based guidelines into electronic algorithmic formats is often complex, inefficient, expensive, and error-prone due to reliance on advanced software development skills and clinical knowledge.
View Article and Find Full Text PDFRes Nurs Health
August 2025
Department of Clinical Nursing Research and Quality Management, Nursing Department, Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany.
Artificial Intelligence (AI)-based applications have significant potential to differentiate between pressure injuries (PI) and incontinence-associated dermatitis (IAD), common challenges in nursing practice. Within the KIADEKU overall project, we are developing an AI-based application to aid in the nursing care of PI and IAD and to facilitate personalized, evidence-based nursing interventions. The KIADEKU clinical sub-study described in this study protocol is a controlled, non-randomized clinical pilot intervention study investigating the effects of the AI-based application, fully developed in the KIADEKU overall project, on the duration of wound assessment, dressing change and documentation, guideline adherence, and nurse task load.
View Article and Find Full Text PDFPflege
September 2022
Fakultät Wirtschafts- und Sozialwissenschaften, Hochschule Osnabrück, Deutschland.
Staffing situation in home-care services: A qualitative study on current and future challenges There are increasing signs of staff shortages in home-care nursing in Germany. Home care providers have an increasing number of vacancies and the provision of care for people in need of care is a challenge. There are only a few approaches to planning personnel requirements in home care and the existing ones are rather complex.
View Article and Find Full Text PDFEur J Intern Med
July 2022
on behalf of the Italian Society of Geriatric Cardiology, (Società Italiana di Cardiologia Geriatrica - SICGe), via Matteotti 7, 50121 Florence, Italy; University of Florence, Head, Division of General Cardiology, Cardiothoracovascular Department, A.O.U. Careggi, Largo Brambilla 3, 50134 Florence,
Artif Intell Med
September 2019
VU Amsterdam, Amsterdam, the Netherlands.
Background: In the last ten years, the international workshop on knowledge representation for health care (KR4HC) has hosted outstanding contributions of the artificial intelligence in medicine community pertaining to the formalization and representation of medical knowledge for supporting clinical care. Contributions regarding modeling languages, technologies and methodologies to produce these models, their incorporation into medical decision support systems, and practical applications in concrete medical settings have been the main contributions and the basis to define the evolution of this field across Europe and worldwide.
Objectives: Carry out a review of the papers accepted in KR4HC in the 2009-2018 decade, analyze and characterize the topics and trends within this field, and identify challenges for the evolution of the area in the near future.