Results 201 to 210 of about 4,662,895 (269)
Exploring the Patient Engagement in the Healthcare Decision-Making Process and Its Association With Patients' Satisfaction. [PDF]
Alharbi K, Almutairi HA, Albagami NS.
europepmc +1 more source
Objective The diagnosis of fibromyalgia (FM) is challenging due to the absence of definitive biomarkers, numerous overlapping comorbidities, and its reliance on patient‐reported symptoms. Discrepancies between diagnostic criteria and clinical practice imply the possibility of diagnostic biases, complicating timely and accurate identification.
Sung‐A Kim +2 more
wiley +1 more source
Patient Engagement With Open Notes Following the 21st Century Cures Act.
Sandhu S +5 more
europepmc +1 more source
Exploring unmet needs in patient engagement among cardiovascular disease patients: qualitative research in Italy. [PDF]
Bosio C +5 more
europepmc +1 more source
Objective Ambulatory care–sensitive conditions (ACSCs) serve as indicators of access, quality, and performance of the health system. This study aimed to determine rheumatoid arthritis (RA)‐specific ACSCs for use in the evaluation of care system access and quality.
Kara Irwin +7 more
wiley +1 more source
Patient Engagement Strategies for Women with Gestational Diabetes Mellitus in Low-Resource Community Health Settings: A Narrative Review and Clinical Principles. [PDF]
Martin MP, Russin N, Pangasa M.
europepmc +1 more source
Objective The aim of this study was to test the hypothesis that multijoint osteoarthritis would modify the relation between time and frailty progression, in which more affected joints would lead to larger declines over six years compared to those without osteoarthritis using data from the Canadian Longitudinal Study on Aging.
Carson Halliwell +2 more
wiley +1 more source
Enhancing patient engagement through an online educational module for gender-affirming mastectomy: A pilot study. [PDF]
Mehta NR +5 more
europepmc +1 more source
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source

