Objectives: To describe practice innovations that can lead to measurable advances in the safety and effectiveness of medication use and to recommend a course of action that is likely to lead to practicable improvements in the medication use system.
Data Sources: Proceedings of a national conference; review of the medical literature.
Data Synthesis: Only those interventions that can be reliably implemented by typical practitioners in a wide range of practice settings can produce lasting benefits for considerable numbers of patients. Teamwork between and among disciplines is needed for new insights and novel approaches to delivering pharmaceutical products and services. Building on the experience of other health disciplines, a cross section of pharmacy practitioners, researchers, educators, and leaders were able to identify the key questions, strategies, and actions needed to form collaborations for devising and testing new ideas and transferring the findings into everyday practice.
Conclusion: Pharmacy practice research that leads to improvements in the medication use process is needed. Practice-based research networks provide a model for building a synergy among pharmacists and other stakeholders to devise improvements that provide sustainable and systemwide improvements in medication use.
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http://dx.doi.org/10.1331/JAPhA.2008.08018 | DOI Listing |
Biomed Phys Eng Express
January 2025
National School of Electronics and Telecommunication of Sfax, Sfax rte mahdia, sfax, sfax, 3012, TUNISIA.
Deep learning has emerged as a powerful tool in medical imaging, particularly for corneal topographic map classification. However, the scarcity of labeled data poses a significant challenge to achieving robust performance. This study investigates the impact of various data augmentation strategies on enhancing the performance of a customized convolutional neural network model for corneal topographic map classification.
View Article and Find Full Text PDFAnn Intern Med
January 2025
Durham VA Health Care System, Durham; and Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina (K.M.G.).
Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.
Purpose: To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.
Data Sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.
J Med Internet Res
January 2025
Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Background: Delayed cerebral ischemia (DCI) is a primary contributor to death after subarachnoid hemorrhage (SAH), with significant incidence. Therefore, early determination of the risk of DCI is an urgent need. Machine learning (ML) has received much attention in clinical practice.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Basic and Community Nursing, School of Nursing, Nanjing Medical University, NanJing, China.
Background: Telehealth interventions can effectively support caregivers of people with dementia by providing care and improving their health outcomes. However, to successfully translate research into clinical practice, the content and details of the interventions must be sufficiently reported in published papers.
Objective: This study aims to evaluate the completeness of a telehealth intervention reporting in randomized controlled trials (RCTs) conducted for caregivers of people with dementia.
J Med Internet Res
January 2025
Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Shenzhen, China.
Background: With the rapid expansion of social media platforms, the demand for health information has increased substantially, leading to innovative approaches and new opportunities in health education.
Objective: This study aims to analyze the characteristics of articles published on the "Dr Ding Xiang" WeChat official account (WOA), one of the most popular institutional accounts on the WeChat platform, to identify factors influencing readership engagement and to propose strategies for enhancing the effectiveness of health information dissemination.
Methods: A total of 5286 articles published on the "Dr Ding Xiang" WOA from January 2021 to December 2021 were collected and analyzed.
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