Objective: To understand how the public understand comparative quality information as presented on NHS Choices, the Department of Health website in England. We explore what quality information people value, how they understand different measures of quality, and their preferences for different types of information.
Method: Seven focus groups were conducted.
Results: Participants' preferences for types of information changed at different stages of the focus groups. Participants attempted to compare hospitals option-wise, building up an overall picture of the hospital's performance. Faced with abundance of conflicting criteria, participants attempted to make trade offs, but found it difficult. Older and less numerate participants used summative measures to overcome this difficulty. Some indicators were poorly understood and the multiplicity of formats and labels was confusing. Missing data were mistrusted.
Conclusion: The presentation of information affects what information people value, how they understand and process it. The design of scorecards is crucial in order to support use of scorecards for informed patient choice.
Practice Implications: We offer guidelines for changing presentation of comparative quality information with the aim to improve its use by patients when choosing between hospitals, especially online.
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http://dx.doi.org/10.1016/j.pec.2010.01.009 | DOI Listing |
Neuromodulation
January 2025
Department of Anesthesiology, University of Wisconsin, Madison, WI, USA.
Objectives: Past studies have shown the efficacy of spinal targeted drug delivery (TDD) in pain relief, reduction in opioid use, and cost-effectiveness in long-term management of complex chronic pain. We conducted a survey to determine treatment variables associated with patient satisfaction.
Materials And Methods: Patients in a single pain clinic who were implanted with Medtronic pain pumps to relieve intractable pain were identified from our electronic health record.
Commun Biol
January 2025
Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Single cell studies have transformed our understanding of cellular heterogeneity in disease but the need for fresh starting material can be an obstacle, especially in the context of international multicenter studies and archived tissue. We developed a protocol to obtain high-quality cells and nuclei from dissected human skeletal muscle archived in the preservative Allprotect® Tissue Reagent. After fluorescent imaging microscopy confirmed intact nuclei, we performed four protocol variations that compared sequencing metrics between cells and nuclei enriched by either filtering or flow cytometry sorting.
View Article and Find Full Text PDFSci Rep
January 2025
Foot and Ankle Research and Innovation Lab (FARIL), Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Tendon injuries present significant medical, social, and economic challenges globally. Despite advancements in tendon injury repair techniques, outcomes remain suboptimal due to inferior tissue quality and functionality. Tissue engineering offers a promising avenue for tendon regeneration, with biocompatible scaffolds playing a crucial role.
View Article and Find Full Text PDFBackground: Current guidelines recommend empiric antibiotic therapy for patients who require hospitalization for community-acquired pneumonia (CAP). We sought to determine whether clinical, imaging or laboratory features in patients hospitalized for CAP in whom PCR is positive for a respiratory virus enable exclusion of bacterial coinfection so that antibiotics can be withheld.
Methods: For this prospective study, we selected patients in whom an etiologic diagnosis was likely to be reached, namely those who provided a high-quality sputum sample at or shortly after admission, and in whom PCR was done to test for a respiratory virus.
Sci Rep
January 2025
College of Computer and Data Science, Minjiang University, Fuzhou, 350018, China.
This study presents a novel approach to identifying meters and their pointers in modern industrial scenarios using deep learning. We developed a neural network model that can detect gauges and one or more of their pointers on low-quality images. We use an encoder network, jump connections, and a modified Convolutional Block Attention Module (CBAM) to detect gauge panels and pointer keypoints in images.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!