The implementation of an emergency nursing framework (HIRAID) reduces patient deterioration: A multi-centre quasi-experimental study

Introduction Timely recognition and treatment of acutely ill patients at appropriate levels of the health system are fundamental to the quality and safety of healthcare. This study determines if the implementation of an emergency nursing framework HIRAID (History, Identify Red flags, Assessment, Interventions, Diagnostics, communication and reassessment) improves patient safety. Methods A quasi-experimental cohort study was conducted in two emergency departments in [Anonymised], Australia. HIRAID was implemented using a multi-pronged behaviour change intervention. Data of 920 patients (374 pre and 546 post) who deteriorated within 72-hours of ED departure were collected. Statistical tests were conducted as two-sided, with a 95% confidence interval to determine pre/post cohort association. Results Patients in the post group had more comorbidities, but experienced less deterioration associated with care delivered in the ED (27% to 13%). There was a reduction in treatment delays [ 28.3% to 15.1%, p = 0.041, 95% CI (1.1%–25.3%)], and delay or failure to escalate care when abnormal vital signs were identified [20.2% to6.9%, p = 0.014, 95% CI (3.5%–23.1%)]. Isolated nursing-related causal factors decreased from 20 (21%) to 6 (8%). Conclusions Implementing a standardised emergency nursing framework is associated with a reduction in clinical deterioration related to emergency care

Opportunities and challenges for data physicalization

Physical representations of data have existed for thousands of years. Yet it is now that advances in digital fabrication, actuated tangible interfaces, and shape-changing displays are spurring an emerging area of research that we call Data Physicalization. It aims to help people explore, understand, and communicate data using computer-supported physical data representations. We call these representations physicalizations, analogously to visualizations -- their purely visual counterpart. In this article, we go beyond the focused research questions addressed so far by delineating the research area, synthesizing its open challenges and laying out a research agenda

The use of Raman spectroscopy to differentiate between different prostatic adenocarcinoma cell lines

Raman spectroscopy (RS) is an optical technique that provides an objective method of pathological diagnosis based on the molecular composition of tissue. Studies have shown that the technique can accurately identify and grade prostatic adenocarcinoma (CaP) in vitro. This study aimed to determine whether RS was able to differentiate between CaP cell lines of varying degrees of biological aggressiveness. Raman spectra were measured from two well-differentiated, androgen-sensitive cell lines (LNCaP and PCa 2b) and two poorly differentiated, androgen-insensitive cell lines (DU145 and PC 3). Principal component analysis was used to study the molecular differences that exist between cell lines and, in conjunction with linear discriminant analysis, was applied to 200 spectra to construct a diagnostic algorithm capable of differentiating between the different cell lines. The algorithm was able to identify the cell line of each individual cell with an overall sensitivity of 98% and a specificity of 99%. The results further demonstrate the ability of RS to differentiate between CaP samples of varying biological aggressiveness. RS shows promise for application in the diagnosis and grading of CaP in clinical practise as well as providing molecular information on CaP samples in a research setting