Health technology assessments (HTAs) are meant to inform health policy by taking account of all the potential impacts of using a health technology. In the 1990s, HTAs included rigorous research to produce patient-based evidence, and some supported participation of patient representatives to help focus HTA research and determine value. In the 2000s, HTAs became more closely linked to reimbursement decisions, focusing on clinical and cost effectiveness. Patient involvement should be tailored to the specific needs of each HTA. As the timeframe for HTAs has reduced, research to produce patient-based evidence has been replaced by input from patient groups. This places a burden on individuals and organizations that needs to be critically reviewed. Therefore, it is imperative that we clarify when patient involvement is likely to add value and support patients to provide their unique knowledge in the most optimal way to influence HTA decision making. To reduce the burden on patient groups, more must be done to encourage research to produce patient-based evidence early in technology development. Like clinical research, a programme of research should be carefully planned, with appropriate methodological rigor for each study, and all research should be published. For this, the development of quality standards for research to produce patient-based evidence may be needed. Patient involvement has inherent value. It should be focused, systematic and transparent, and evolve according to the experiences of all stakeholders. All countries or collaboratives that undertake HTA should consider how they can elicit the needs, preferences and experiences of patients to support creation of patient-centered healthcare policy.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s40271-018-0325-5 | DOI Listing |
Cancer Treat Rev
December 2024
Warwick Medical School, The University of Warwick, Coventry CV4 7AL, United Kingdom; Department of Plastic Surgery, University Hospitals of Coventry and Warwickshire NHS Trust, Clifford Bridge Road, Coventry CV2 2DX, United Kingdom.
Sci Rep
July 2024
Department of Psychology, University of Washington, Seattle, 98195, USA.
The field of cortical sight restoration prostheses is making rapid progress with three clinical trials of visual cortical prostheses underway. However, as yet, we have only limited insight into the perceptual experiences produced by these implants. Here we describe a computational model or 'virtual patient', based on the neurophysiological architecture of V1, which successfully predicts the perceptual experience of participants across a wide range of previously published human cortical stimulation studies describing the location, size, brightness and spatiotemporal shape of electrically induced percepts in humans.
View Article and Find Full Text PDFIn clinical settings with no commonly accepted standard-of-care, multiple treatment regimens are potentially useful, but some treatments may not be appropriate for some patients. A personalized randomized controlled trial (PRACTical) design has been proposed for this setting. For a network of treatments, each patient is randomized only among treatments which are appropriate for them.
View Article and Find Full Text PDFIEEE Trans Ultrason Ferroelectr Freq Control
July 2024
Color Doppler echocardiography enables visualization of blood flow within the heart. However, the limited frame rate impedes the quantitative assessment of blood velocity throughout the cardiac cycle, thereby compromising a comprehensive analysis of ventricular filling. Concurrently, deep learning is demonstrating promising outcomes in post-processing of echocardiographic data for various applications.
View Article and Find Full Text PDFClin Chim Acta
May 2024
Jefferson University Hospital, Philadelphia, PA, USA. Electronic address:
Background And Objectives: We assessed properties of running averages for our hospital's most common chemistry analytes, for use in real-time patient-based quality control (PBQC). We determined whether there was dependence of any running averages on 24-h clock time (time-of-day, TOD).
Materials And Methods: We analyzed 3-months' data for measurements of 13 metabolic panel components.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!