Background: Working in unhealthy environments is associated with negative nurse and patient outcomes. Previous body of evidence in this area is limited as it investigated only a few factors within nurses' workplaces.
Purpose: The purpose of this study was to identify the most important workplace factors predicting nurses' provision of quality and safe patient care using a 13-factor measure of workplace conditions.
Methods: A cross-sectional correlational survey study involving 4029 direct care nurses in British Columbia was conducted using random forest data analytics methods.
Results: Nurses' reports of healthier workplaces, particularly workload management, psychological protection, physical safety and engagement, were associated with higher ratings of quality and safe patient care.
Conclusion: These workplace conditions are perceived to impact patient care through influencing nurses' mental health. To ensure a high standard of patient care, data-driven policies and interventions promoting overall nurse mental health and well-being are urgently required.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860211 | PMC |
http://dx.doi.org/10.1097/NCQ.0000000000000600 | DOI Listing |
Cancer Genet
January 2025
Department of Pathology and Laboratory Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA; Rutgers Cancer Institute, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.
Collision tumors, characterized by the coexistence of two unique neoplasms in close approximation, are rare and pose diagnostic challenges. This is particularly true when the unique neoplasms are of the same histologic type. Here we report such a case where comprehensive tumor profiling by next generation sequencing (NGS) as well as immunohistochemistry revealed two independent adenocarcinomas comprising what was initially diagnosed as a single adenocarcinoma of the gastroesophageal (GEJ) junction.
View Article and Find Full Text PDFAnn Intern Med
January 2025
Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System; Department of Population Health Sciences, Duke University School of Medicine; and Durham Evidence Synthesis Program, Durham Veterans Affairs Health Care System, Durham, North Carolina (J.M.G.).
Background: Postdischarge contacts (PDCs) after hospitalization are common practice, but their effectiveness in reducing use of acute care after discharge remains unclear.
Purpose: To assess the effects of PDC on 30-day emergency department (ED) visits, 30-day hospital readmissions, and patient satisfaction.
Data Sources: MEDLINE, Embase, and CINAHL searched from 2012 to 25 May 2023.
J Med Internet Res
January 2025
ETH Zurich, Zurich, Switzerland.
Background: The escalating global scarcity of skilled health care professionals is a critical concern, further exacerbated by rising stress levels and clinician burnout rates. Artificial intelligence (AI) has surfaced as a potential resource to alleviate these challenges. Nevertheless, it is not taken for granted that AI will inevitably augment human performance, as ill-designed systems may inadvertently impose new burdens on health care workers, and implementation may be challenging.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Department of Public Health and Primary Care, KU Leuven-University of Leuven, Leuven, Belgium.
Background: Young patients aged 16 to 25 years with type 1 diabetes (T1D) often encounter challenges related to deteriorating disease control and accelerated complications. Mobile apps have shown promise in enhancing self-care among youth with diabetes. However, inconsistent findings suggest that further evidence is necessary to confirm the effectiveness of app-based interventions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!