Over the last few years, increasing attention has been directed toward the problems inherent to measuring the quality of healthcare and implementing benchmarking strategies. Besides offering accreditation and certification processes, recent approaches measure the performance of healthcare institutions in order to evaluate their effectiveness, defined as the capacity to provide treatment that modifies and improves the patient's state of health. This paper, dealing with hospital effectiveness, focuses on research methods for effectiveness analyses within a strategy comparing different healthcare institutions. The paper, after having introduced readers to the principle debates on benchmarking strategies, which depend on the perspective and type of indicators used, focuses on the methodological problems related to performing consistent benchmarking analyses. Particularly, statistical methods suitable for controlling case-mix, analyzing aggregate data, rare events, and continuous outcomes measured with error are examined. Specific challenges of benchmarking strategies, such as the risk of risk adjustment (case-mix fallacy, underreporting, risk of comparing noncomparable hospitals), selection bias, and possible strategies for the development of consistent benchmarking analyses, are discussed. Finally, to demonstrate the feasibility of the illustrated benchmarking strategies, an application focused on determining regional benchmarks for patient satisfaction (using 2009 Lombardy Region Patient Satisfaction Questionnaire) is proposed.
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http://dx.doi.org/10.1100/2012/606154 | DOI Listing |
Sci Rep
January 2025
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China.
Multi-objective and multi-stage decision-making problems require balancing multiple objectives at each stage and making optimal decision in multi-dimensional control variables, where the commonly used intelligent optimization algorithms suffer from low solving efficiency. To this end, this paper proposes an efficient algorithm named non-dominated sorting dynamic programming (NSDP), which incorporates non-dominated sorting into the traditional dynamic programming method. To improve the solving efficiency and solution diversity, two fast non-dominated sorting methods and a dynamic-crowding-distance based elitism strategy are integrated into the NSDP algorithm.
View Article and Find Full Text PDFJ Am Soc Cytopathol
November 2024
Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio. Electronic address:
Introduction: The United States Preventive Services Task Force (USPSTF) recommendation for cervical cancer screening includes the option to screen with high-risk human papilloma virus (hrHPV) alone, but some studies have reported that hrHPV testing alone missed precancerous and cancerous lesions. In this study, we evaluated the test performance characteristics of hrHPV in detecting cervical dysplasia with cervical cytology and biopsy as comparators.
Materials And Methods: We conducted a retrospective analysis of Papanicolaou smears between January and December 2019 performed at our institution with concurrent hrHPV and cytology testing.
Neural Netw
January 2025
State Key Laboratory of Public Big Data, Guizhou University, 550025, China; Engineering Research Center of Text Computing & Cognitive Intelligence, Ministry of Education, Guizhou University, 550025, China; College of Computer Science and Technology, Guizhou University, 550025, China. Electronic address:
Relation extraction independently verifies all entity pairs in a sentence to identify predefined relationships between named entities. Because these entity pairs share the same contextual features of a sentence, they lead to a complicated semantic structure. To distinguish semantic expressions between relation instances, manually designed rules or elaborate deep architectures are usually applied to learn task-relevant representations.
View Article and Find Full Text PDFACS Nano
January 2025
Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore.
Transition-metal dichalcogenides (TMDs), such as molybdenum disulfide (MoS), have emerged as a generation of nonprecious catalysts for the hydrogen evolution reaction (HER), largely due to their theoretical hydrogen adsorption energy close to that of platinum. However, efforts to activate the basal planes of TMDs have primarily centered around strategies such as introducing numerous atomic vacancies, creating vacancy-heteroatom complexes, or applying significant strain, especially for acidic media. These approaches, while potentially effective, present substantial challenges in practical large-scale deployment.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR 999078, China.
Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality retrieval task to match a person across different spectral camera views. Most existing works focus on learning shared feature representations from the final embedding space of advanced networks to alleviate modality differences between visible and infrared images. However, exclusively relying on high-level semantic information from the network's final layers can restrict shared feature representations and overlook the benefits of low-level details.
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