Internal medicine journal
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Internal medicine journal · Sep 2021
Safety and efficacy of telephone clinics during the COVID-19 pandemic in the provision of care for patients with cancer.
Due to the COVID-19 pandemic, telephone clinics have been utilised to reduce the risk of transmission. Evidence supporting its quality and safety is required. ⋯ Generally, patients and clinicians viewed telephone clinics favourably. Nevertheless, a large portion of patients still prefer face-to-face clinics. Services should be tailored to individual preferences. Although there were no 'red flags' in terms of mortality or admission rates, further longitudinal research is required.
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Internal medicine journal · Sep 2021
How is mobile health technology transforming physician-nurse collaboration?
The integration of mobile health technologies in medical practice has the potential to promote in-person, high-quality care. We examine the impact of Voalte, a healthcare-specific mobile application, on bedside rounding and care coordination. ⋯ The frequency of physician-nurse overlap at the bedside was 50.3%, representing a >20% increase when compared with the 2018 baseline before Voalte's introduction. Our results show that mobile health technologies can strengthen inpatient medicine workflows and interdisciplinary collaboration when implemented successfully.
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Internal medicine journal · Sep 2021
Practical ethical challenges and moral distress among staff in a hospital COVID-19 screening service.
The COVID-19 pandemic has led to unprecedented disruptions to established models of healthcare and healthcare delivery, creating a host of new ethical challenges for healthcare institutions, their leadership and their staff. Hospitals and other large organisations have an obligation to understand and recognise the downstream effects that highly unusual situations and professionally demanding policy may have on workers tasked with its implementation, in order to institute risk-mitigation strategies and provide additional support where required. In our experience, targeted ethics-based forums that provide a non-confrontational platform to discuss and explore the ethical dilemmas that may have arisen have been well received, and can also serve as useful and immediate feedback mechanisms to managers and leadership. Using two case illustrations, this article examines some of the ethical challenges and dilemmas faced by these staff, based on discussions of shared experience during a clinical ethics forum for the Screening Clinic staff at Austin Health, Melbourne, Victoria.
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Internal medicine journal · Sep 2021
"Concerns and Psychological Wellbeing of Health Care Workers During the COVID-19 Pandemic in a Tertiary Care Hospital in NSW".
In early 2020, the impending COVID-19 pandemic placed a once-in-a-generation professional and personal challenge on healthcare workers. Publications on direct physical disease abound. The authors wanted to focus on doctors' psychological well-being. ⋯ Both COVID-19 specific concerns and psychological well-being improved greatly in the second survey. Possible explanations are the fall in COVID-19 cases in the district, improvements in PPE supply and supportive measures communicated to doctors during this period.
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Internal medicine journal · Sep 2021
ReviewDemystifying machine learning - a primer for physicians.
Machine learning is a tool for analysing digitised data sets and formulating predictions that can optimise clinical decision-making. It aims to identify complex patterns in large data sets and encode them into models that can then classify new unseen cases or make predictions on new data. Machine learning methods take several forms and individual models can be of many different types. ⋯ The reliability and robustness of any model depends on multiple factors, including the quality and quantity of the data used to develop the models, and the selection of features in the data considered most important to maximising accuracy. In ensuring models are safe, effective and reproducible in routine care, physicians need to have some understanding of how these models are developed and evaluated, and to collaborate with data and computer scientists in their design and validation. This narrative review introduces principles, methods and examples of machine learning in a way that does not require mastery of highly complex statistical and computational concepts.