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To identify a frame of reference for resident safety management in nursing homes.
Q-methodology.
This study was conducted using Q-methodology to identify shared perspectives about resident safety management among nursing home professionals. Data were collected from 13 May 2023, through 29 August 2023. Thirty-four professionals, including nurses, care workers, social workers and physical therapists, classified Q-samples into a normal distribution grid through Q-sorting. Data analysis was performed using the PQmethod programme. Q-factors were interpreted by integrating interview transcripts, demographic data and factor arrays that organised the analysis results.
The analysis included the Q-sort of 33 professionals, with an average age of 46.03 years and 6.53 years of nursing home experience, after excluding one individual who did not fit any Q-factor. Four Q factors explaining 63% of the total variance were identified: constructing individualised possible risk trajectories, utilising ingrained safety principles, creating supportive safety environments and coordinating safety principles with individual needs.
Understanding the diverse subjectivities of professionals can help develop strategies that promote collaboration among nursing home professionals and support preventive safety management practices.
The frame of reference derived from nursing home professionals' perspectives suggests a resident-tailored framework.
This study supports the development of interprofessional education tailored to the specific needs of nursing home settings by identifying shared perspectives among nursing home professionals. The findings highlight the need for clear guidelines to help professionals balance resident autonomy with safety and assess the impact of family involvement.
Reporting involved qualitative and quantitative approaches, in compliance with the MMAT criteria for mixed-method research.
No Patient or Public Contribution.
To develop a method for computationally detecting fall events using clinical language models to complement existing self-reporting mechanisms.
Retrospective observational study.
Text data were collected from the unstructured nursing notes of three hospitals' electronic health records and the Korean national patient safety reports, totalling 34,480 records covering the period from January 2015 to December 2019. Note-level labelling was conducted by two researchers with 95% agreement. Preprocessing data anonymisation and English translation were followed by semantic validation. Five language models based on pretrained Bidirectional Encoder Representations from Transformers (BERT) and Generative Pretrained Transformer (GPT)-4 with prompt programming were explored. Model performance was assessed using F measurements. Error analysis was conducted for the GPT-4 results.
Fine-tuned BERT models with the English data set outperformed GPT-4, with Bio+Clinical BERT achieving the highest F1 score of 0.98. Fine-tuned Korean BERT with the Korean data set also reached an F1 score of 0.98, while GPT-4 achieved a competitive F1 score of 0.94. GPT-4 with prompt programming showed much higher F1 scores than GPT-4 with a standardised prompt for the English data set (0.85 vs. 0.39) and the Korean data set (0.94 vs. 0.03). The error analysis identified that the common misclassification patterns included fall history and homonyms, causing false positives and implicit expressions and missing contextual information, causing false negatives.
The clinical language model approach, if used alongside the existing self-reporting, promises to increase the chance of identifying the majority of factual falls without the need for additional chart reviews.
Inpatient falls are often underreported, with up to 91% of incidents missed in self-reports. Using language models, we identified a significant portion of these unreported falls, improving the accuracy of adverse event tracking while reducing the self-reporting burden on nurses.
Not applicable.
Standardised triage systems have been in place for decades with minor modifications, while nurses' skills and knowledge have significantly advanced.
To determine whether nurses' clinical expertise outperforms triage systems in simulated clinical cases.
A multicenter simulated observational study.
The study was conducted from January 1, 2024 to March 31, 2024, in four Italian emergency departments, enrolling triage-performing nurses. Thirty clinical cases, based on real patients representing daily emergency department influx, were reconstructed. The primary outcome was the agreement between the triage code assigned by the Manchester Triage System and the code assigned based on clinical expertise. The secondary outcome compared the predictive ability of the codes assigned by nurses regarding clinical outcomes, such as death within 72 h, the need for hospitalisation, and the need for life-saving intervention. The study was reported in accordance with the STROBE statement.
Seventy-seven triage nurses completed the 30 vignettes. The agreement between the MTS-assigned code and the clinical expertise triage reported a Cohen's kappa of 0.576 (95% CI: 0.564–0.598). For death within 72 h, the clinical expertise code reported better results than the Manchester Triage System. For life-saving interventions, the Manchester Triage System reported a lower performance than clinical expertise. The variability in triage code assignment was higher for clinical expertise compared to the Manchester Triage System.
Triage codes assigned by nurses based on clinical expertise perform better in terms of clinical outcomes, suggesting a need to update triage systems to incorporate nurses' knowledge and skills. However, standardised triage systems should be maintained to reduce variability and ensure consistent patient classification.
The study was conducted and reported according to the STROBE statement.
No patient or public contribution.
To explore clinicians' and patients' perceptions of implementing evidence-based practice to improve clinical practice for preventing and managing surgical site infections within hospital acute care settings.
A convergent integrated mixed-methods systematic review using the Joanna Briggs Institute approach.
Included studies reported (i) acute care hospital clinicians' and patients' experiences and preferences for preventing and managing surgical site infections and (ii) barriers and facilitators to implementing surgical site infection prevention and management guidelines. The Mixed Methods Appraisal Tool and the Quality Improvement Minimum Quality Criteria Set were used for critical appraisal. Quantitative data was transformed into qualitised data, then thematically synthesised with qualitative data and coded all findings into themes. Clinicians' and patients' views were also compared.
English language peer-reviewed studies published from 2009 to March 2023 were identified from Medline, EMBASE, CINAHL, PsycINFO and Cochrane Central Library.
Thirty-seven studies (16 quantitative, 17 qualitative, 3 mixed-methods and 1 quality improvement) met the inclusion criteria. Five main themes represent key factors believed to influence the implementation of evidence-based surgical site infection prevention and management guidelines: (1) Intentional non-adherence to insufficiently detailed and outdated guidelines, (2) Knowledge deficits on evidence-based SSI care bring about inconsistent clinical practice, (3) Collaborative interdisciplinary and patient-provider relationship to enhance guideline uptake, (4) Infection surveillance to improve patient safety and quality of life and (5) Negative physical and psychological impacts on patients.
The five themes reflect a need for updated hospital guidelines as a medium to improve surgical site infection knowledge and ensure consistent and evidence-based clinical practice. This review also highlights the significance of interdisciplinary and patient-provider collaboration and infection surveillance to facilitate guideline uptake. The effectiveness of intervention bundles designed to improve these aspects of care will need to be evaluated in future research.
A future intervention bundle that includes (1) ensuring up-to-date hospital guidelines/policies; (2) fostering collaborative interdisciplinary teamwork culture between physicians, nurses, podiatrists, pharmacists and allied health professionals; (3) encouraging patient or carer involvement in shared decision-making and (4) implementing audit and feedback mechanism on infection surveillance is proposed to improve SSI prevention and management in acute care settings.
This paper followed the PRISMA 2020 checklist guideline for reporting systematic reviews.
This mixed-methods systematic review collates evidence of clinicians' and patients' experiences and preferences for preventing and managing surgical site infections. The inclusion of hospital patients' perspectives supports the development of patient-centred interventions.
Trial Registration: The review protocol is registered on the International Prospective Register of Systematic Reviews (PROSPERO 2021 CRD42021250885). Available at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021250885
To present the pooled estimated prevalence of adverse events in pronated intubated adult COVID-19 patients.
A systematic review and meta-analysis.
This study used the Cochrane Library, CINAHL, Embase, LILACS, Livivo, PubMed, Scopus, and Web of Science databases as data sources.
The studies were meta-analysed using JAMOVI 1.6.15 software. A random-effects model was used to identify the global prevalence of adverse events, confidence intervals and the heterogeneity data. Risk of bias was assessed using the Joanna Briggs Institute tool, and the certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach.
Of the 7904 studies identified, 169 were included for full reading, and 10 were included in the review. The most prevalent adverse events were pressure injuries (59%), haemodynamic instability (23%), death (17%) and device loss or traction (9%).
The most prevalent adverse events in mechanically ventilated pronated patients with COVID-19 are pressure injuries, presence of haemodynamic instability, death and device loss or traction.
The evidence identified in this review can help improve the quality and safety of patient care by helping to design care protocols to avoid the development of adverse events that can cause permanent sequelae in these patients.
This systematic review addressed the adverse events related to prone position in intubated adult COVID-19 patients. We identified that the most prevalent adverse events in these patients were pressure injuries, haemodynamic instability, device loss or traction and death. The results of this review may influence the clinical practice of nurses who work in intensive care units and, consequently, the nursing care provided not only to COVID-19 patients but for all intubated patients due to other reasons in intensive care units.
This systematic review adhered to the PRISMA reporting guideline.
As this is a systematic review, we analysed data from primary studies conducted by many researchers. Thus, there was no patient or public contribution in this review.
Single studies support the presence of several post-COVID-19 symptoms; however, there is no evidence for the synthesis of symptoms.
We attempt to provide an overview of the persistent symptoms that post-COVID-19 patients encounter, as well as the duration of these symptoms to help them plan their rehabilitation.
Systematic review and meta-analysis.
A total of 16 studies involving 8756 patients post-COVID-19 were included.
The CINAHL, PubMed, EMBASE, Scopus, and Web of Science databases were searched from 2019 to August 2021. Observational studies that reported data on post-COVID-19 symptoms were included. The methodological quality of the studies was assessed using the Joanna Briggs Institute Critical Appraisal for Observational Studies. We included medium- to high-quality studies. We used a random-effects model for the meta-analytical pooled prevalence of each post-COVID-19 symptom, and I 2 statistics for heterogeneity.
From the 2481 studies identified, 16 met the inclusion criteria. The sample included 7623 hospitalised and 1133 non-hospitalised patients. We found the most prevalent symptoms were fatigue and dyspnea with a pooled prevalence ranging from 42% (27%–58%). Other post-COVID-19 symptoms included sleep disturbance 28% (14%–45%), cough 25% (10%–44%), anosmia/ageusia 24% (7%–47%), fever 21% (4%–47%), myalgia 17% (2%–41%), chest pain 11% (5%–20%), and headache 9% (2%–20%). In addition to physical symptoms, anxiety/depression was also prevalent 27% (8%–53%).
Fatigue and dyspnea were the most prevalent post-COVID-19 symptoms and experienced up to 12 months.
Multiple persistent symptoms are still experienced until 12 months of post-Covid 19. This meta-analysis should provide some awareness to nurses to highlights the unmet healthcare needs of post-COVID-19 patients. Long-term monitoring for the evaluation and treatment of symptoms and conditions and rehabilitation programs should be conducted.
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