Objectives: To identify and describe studies using the RAND/UCLA method to evaluate the appropriateness of health procedures. This method is a consensus technique that involves several phases to develop appropriateness criteria.
Methods: We performed a literature search in 2005. OVIDMedline, ISI Web of Knowledge, IME and Highwire were consulted. Articles published between 1999 and 2004 and using the key words "appropriateness", "utilization review" and "physician practice patterns" were selected. Studies using the RAND method were included and those that did not explain the methodology in sufficient detail were excluded. Information on the procedure studied, the place and year of publication, and the characteristics of the journal were extracted from each article.
Results And Discussion: A total of 5092 articles were identified and 205 were selected. Slightly more than half analyzed surgical or medical procedures, while 16.5% evaluated healthcare quality. More than 50% were published in journals of public health, general medicine, and gastroenterology and hepatology. The mean impact factor was 4.07. A quarter (25.4%) of the articles was published in 1999. CONCLUSIONS AND PERSPECTIVE: The RAND method is still widely used. Appropriateness criteria can be used to review utilization of procedures, to design guidelines, or to support for decision making. These tools should be reviewed to obtain evermore valid and reliable results.
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http://dx.doi.org/10.1016/j.gaceta.2007.06.001 | DOI Listing |
Sci Rep
December 2024
Pharmacy Department, Hospices Civils de Lyon, Hôpital E. Herriot, Plateforme FRIPHARM, 69437, Lyon, France.
Phage therapy uses viruses (phages) against antibiotic resistance. Tailoring treatments to specific patient strains requires stocks of various highly concentrated purified phages. It, therefore, faces challenges: titration duration and specificity to a phage/bacteria couple; purification affecting stability; and highly concentrated suspensions tending to aggregate.
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December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
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December 2024
Department of Dermatology, Niazi Hospital, Lahore, Pakistan.
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information.
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December 2024
Department of Computer Science and Digital Technologies, University of East London, London, UK.
Nursing activity recognition has immense importance in the development of smart healthcare management and is an extremely challenging area of research in human activity recognition. The main reasons are an extreme class-imbalance problem and intra-class variability depending on both the subject and the recipient. In this paper, we apply a unique two-step feature extraction, coupled with an intermediate feature 'Angle' and a new feature called mean min max sum to render the features robust against intra-class variation.
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December 2024
Department of Clinical Pharmacy, Baoshan Hospital Affiliated to, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.
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