Introduction: Patient-reported outcome and experience measures (PROM and PREM) are used to guide individual care and quality improvement (QI). QI with patient-reported data is preferably organized around patients, which is challenging across organisations. We aimed to investigate network-broad learning for QI with outcome data.
Methods: In three obstetric care networks using individual-level PROM/PREM, a learning strategy for cyclic QI based on aggregated outcome data was developed, implemented and evaluated. The strategy included clinical, patient-reported, and professional-reported data; together translated into cases for interprofessional discussion. This study's data generation (including focus groups, surveys, observations) and analysis were guided by a theoretical model for network collaboration.
Results: The learning sessions identified opportunities and actions to improve quality and continuity of perinatal care. Professionals valued the data (especially patient-reported) combined with in-dept interprofessional discussion. Main challenges were professionals' time constraints, data infrastructure, and embedding improvement actions. Network-readiness for QI depended on trustful collaboration through connectivity and consensual leadership. Joint QI required information exchange and support including time and resources.
Conclusions: Current fragmented healthcare organization poses barriers for network-broad QI with outcome data, but also offers opportunities for learning strategies. Furthermore, joint learning could improve collaboration to catalyse the journey towards integrated, value-based care.
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http://dx.doi.org/10.5334/ijic.7035 | DOI Listing |
Clin Trials
January 2025
Rare Diseases Team, Office of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Background/aims: Rare disease drug development faces unique challenges, such as genotypic and phenotypic heterogeneity within small patient populations and a lack of established outcome measures for conditions without previously successful drug development programs. These challenges complicate the process of selecting the appropriate trial endpoints and conducting clinical trials in rare diseases. In this descriptive study, we examined novel drug approvals for non-oncologic rare diseases by the U.
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
January 2025
Department of Pathology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41500 Larissa, Greece.
Background: Hypoxia-inducible factor 1 alpha (HIF-1α) and its related vascular endothelial growth factor (VEGF) may play a significant role in atherosclerosis and their targeting is a strategic approach that may affect multiple pathways influencing disease progression. This study aimed to perform a systematic review to reveal current evidence on the role of HIF-1α and VEGF immunophenotypes with other prognostic markers as potential biomarkers of atherosclerosis prognosis and treatment efficacy.
Methods: We performed a systematic review of the current literature to explore the role of HIF-1α and VEGF protein expression along with the relation to the prognosis and therapeutic strategies of atherosclerosis.
Aesthet Surg J
January 2025
Department of Plastic, Reconstructive and Aesthetic Surgery, Faculty of Medicine, Altınbas University, Istanbul, Turkey.
Background: Artificial intelligence (AI)-driven technologies offer transformative potential in plastic surgery, spanning pre-operative planning, surgical procedures, and post-operative care, with the promise of improved patient outcomes.
Objectives: To compare the web-based ChatGPT-4o (omni; OpenAI, San Francisco, CA) and Gemini Advanced (Alphabet Inc., Mountain View, CA), focusing on their data upload feature and examining outcomes before and after exposure to CME articles, particularly regarding their efficacy relative to human participants.
Br J Hosp Med (Lond)
January 2025
Department of Obstetrics and Gynecology, The First Clinical Medical College of Three Gorges University, Yichang Central People's Hospital, Yichang, Hubei, China.
Gestational diabetes mellitus (GDM) is a common complication during pregnancy. This retrospective study investigates the correlation between umbilical blood flow index and maternal-fetal outcomes in pregnant women with GDM, aiming to contribute to evidence-based risk assessment and management strategy in this high-risk obstetric population. This retrospective study recruited 119 pregnant women with GDM who were admitted to the Yichang Central People's Hospital, between January 2022 and January 2024.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Nursing Department, Zhang Ye People's Hospital Affiliated to Hexi University, Zhangye, Gansu, China.
Diabetes is a chronic lifelong condition that requires consistent self-care and daily lifestyle adjustments. Effective disease management involves regular blood glucose monitoring and ongoing nursing support. Inadequate education and poor self-management are key factors contributing to increased mortality among diabetic individuals.
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