Clinical handover as an interactive event: Informational and interactional communication strategies in effective shift-change handovers

2013 ◽  
Vol 9 (3) ◽  
pp. 215-227 ◽  
Author(s):  
Suzanne Eggins ◽  
Diana Slade
Keyword(s):  
High Risk ◽  
Mortality Risk ◽  
Communication Strategies ◽  
Quality And Safety ◽  
Health Departments ◽  
Patient Harm ◽  
Interactive Communication ◽  
Clinical Handover ◽  
Communicative Performance ◽  
Shift Change

Clinical handover – the transfer between clinicians of responsibility and accountability for patients and their care (AMA 2006) – is a pivotal and high-risk communicative event in hospital practice. Studies focusing on critical incidents, mortality, risk and patient harm in hospitals have highlighted ineffective communication – including incomplete and unstructured clinical handovers – as a major contributing factor (NSW Health 2005; ACSQHC 2010). In Australia, as internationally, Health Departments and hospital management have responded by introducing standardised handover communication protocols. This paper problematises one such protocol – the ISBAR tool – and argues that the narrow understanding of communication on which such protocols are based may seriously constrain their ability to shape effective handovers. Based on analysis of audio-recorded shift-change clinical handovers between medical staff, we argue that handover communication must be conceptualised as inherently interactive and that attempts to describe, model and teach handover practice must recognise both informational and interactive communication strategies. By comparing the communicative performance of participants in authentic handover events we identify communication strategies that are more and less likely to lead to an effective handover and demonstrate the importance of focusing close up on communication to improve the quality and safety of healthcare interactions.

scholarly journals Identifying and characterizing high-risk clusters in a heterogeneous ICU population with deep embedded clustering

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Castela Forte ◽  
Galiya Yeshmagambetova ◽  
Maureen L. van der Grinten ◽  
Bart Hiemstra ◽  
Thomas Kaufmann ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Mortality Risk ◽  
Clustering Algorithms ◽  
Kidney Injury ◽  
Risk Groups ◽  
Admission Diagnosis ◽  
Dutch Hospital ◽  
Cluster Membership

AbstractCritically ill patients constitute a highly heterogeneous population, with seemingly distinct patients having similar outcomes, and patients with the same admission diagnosis having opposite clinical trajectories. We aimed to develop a machine learning methodology that identifies and provides better characterization of patient clusters at high risk of mortality and kidney injury. We analysed prospectively collected data including co-morbidities, clinical examination, and laboratory parameters from a minimally-selected population of 743 patients admitted to the ICU of a Dutch hospital between 2015 and 2017. We compared four clustering methodologies and trained a classifier to predict and validate cluster membership. The contribution of different variables to the predicted cluster membership was assessed using SHapley Additive exPlanations values. We found that deep embedded clustering yielded better results compared to the traditional clustering algorithms. The best cluster configuration was achieved for 6 clusters. All clusters were clinically recognizable, and differed in in-ICU, 30-day, and 90-day mortality, as well as incidence of acute kidney injury. We identified two high mortality risk clusters with at least 60%, 40%, and 30% increased. ICU, 30-day and 90-day mortality, and a low risk cluster with 25–56% lower mortality risk. This machine learning methodology combining deep embedded clustering and variable importance analysis, which we made publicly available, is a possible solution to challenges previously encountered by clustering analyses in heterogeneous patient populations and may help improve the characterization of risk groups in critical care.

scholarly journals Risk assessment in precapillary pulmonary hypertension: a comparative analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Thomas Sonnweber ◽  
Eva-Maria Schneider ◽  
Manfred Nairz ◽  
Igor Theurl ◽  
Günter Weiss ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Pulmonary Hypertension ◽  
High Risk ◽  
Risk Stratification ◽  
Risk Prediction ◽  
Mortality Risk ◽  
Assessment Tool ◽  
Risk Models ◽  
Non Invasive

Abstract Background Risk stratification is essential to assess mortality risk and guide treatment in patients with precapillary pulmonary hypertension (PH). We herein compared the accuracy of different currently used PH risk stratification tools and evaluated the significance of particular risk parameters. Methods We conducted a retrospective longitudinal observational cohort study evaluating seven different risk assessment approaches according to the current PH guidelines. A comprehensive assessment including multi-parametric risk stratification was performed at baseline and 4 yearly follow-up time-points. Multi-step Cox hazard analysis was used to analyse and refine risk prediction. Results Various available risk models effectively predicted mortality in patients with precapillary pulmonary hypertension. Right-heart catheter parameters were not essential for risk prediction. Contrary, non-invasive follow-up re-evaluations significantly improved the accuracy of risk estimations. A lack of accuracy of various risk models was found in the intermediate- and high-risk classes. For these patients, an additional evaluation step including assessment of age and right atrium area improved risk prediction significantly. Discussion Currently used abbreviated versions of the ESC/ERS risk assessment tool, as well as the REVEAL 2.0 and REVEAL Lite 2 based risk stratification, lack accuracy to predict mortality in intermediate- and high-risk precapillary pulmonary hypertension patients. An expanded non-invasive evaluation improves mortality risk prediction in these individuals.

scholarly journals Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue-Mendoza ◽  
Juan C. Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Greater Mexico ◽  
Spatio Temporal ◽  
Child Mortality Rate

Abstract Background Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

scholarly journals Establishment of a novel scoring model for mortality risk prediction in HIV-infected patients with cryptococcal meningitis

2021 ◽  
Author(s):  
Ting Zhao ◽  
Xiao-Lei Xu ◽  
Jing-Min Nie ◽  
Xiao-Hong Chen ◽  
Zhong-Sheng Jiang ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Prediction ◽  
Mortality Risk ◽  
Cryptococcal Meningitis ◽  
Area Under Curve ◽  
The Novel ◽  
Multicenter Cohort Study ◽  
Scoring Model ◽  
Risk Of Death ◽  
Prediction Probability

Abstract Purpose: Cryptococcal meningitis (CM) remains a leading cause of death in HIV-infected patients, despite advances in CM diagnostic and therapeutic strategies. This study was performed with the aim to develop and validate a novel scoring model to predict mortality risk in HIV-infected patients with CM (HIV/CM).Methods: Data on HIV/CM inpatients were obtained from a Multicenter Cohort study in China. Independent risk factors associated with mortality were identified based on data from 2013 to 2017, and a novel scoring model for mortality risk prediction was established. The prediction probability of the novel model was evaluated and verified using data from 2018 to 2020.Results: We found that six predictors, including age, stiff neck, impaired consciousness, intracranial pressure, CD4+ T-cell count, and urea levels, were associated with poor prognosis in HIV/CM patients. The novel scoring model could effectively identify HIV/CM patients at high risk of death on admission (area under curve 0.876; p＜0.001). When the cut-off value of 5.5 points or more was applied, the sensitivity and specificity was 74.1% and 83.8%, respectively. Additionally, our scoring model showed a good discriminatory ability in the validation cohort (area under curve 0·886; p＜0.001).Conclusions: Our developed scoring model of six variables is simple, convenient, and accurate for screening high-risk patients with HIV/CM, which may be a useful tool for physicians to assess prognosis in HIV/CM inpatients.

scholarly journals Temporal Trend in Young-Onset Type 2 Diabetes - the Macrovascular and Mortality Risk: Study of UK Primary Care Electronic Medical Records

2020 ◽  
Author(s):  
Digsu N. Koye ◽  
Joanna Ling ◽  
John Dibato ◽  
Kamlesh Khunti ◽  
Olga Montvida ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Risk Factor ◽  
High Risk ◽  
Mortality Risk ◽  
Cardiometabolic Risk ◽  
Low Risk ◽  
Young Onset ◽  
Onset Type

<b>Objectives: </b>To evaluate temporal prevalence trend, cardiometabolic risk factors, and the risk of atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality (ACM) in incident young- and usual-onset type 2 diabetes. <p><b>Research Design and Methods: </b>From the UK primary care database, 370,854 people with new diagnosis of type 2 diabetes from 2000 to 2017 were identified. Analyses were conducted by age groups (18-39, 40-49, 50-59, 60-69, 70-79 years) and high/low risk status without history of ASCVD at diagnosis - ≥ two of current smoking, high SBP, high LDL-C or chronic kidney disease were classified as high-risk. </p> <p><b>Results:</b> Proportion of people aged <50 years at diagnosis increased during 2000-2010 and then stabilised. The incidence rates of ASCVD and ACM declined in people aged ≥50 years, but did not decrease in people <50 years. Compared to people aged ≥50 years, those aged 18-39 years at diagnosis had higher obesity (71% obese), higher HbA1c (8.6%), 71% had high LDL-C, while only 18% were on cardio-protective therapy. Although 2% in this age group had ASCVD at diagnosis, 23% were identified as high-risk. In the 18-39 years group, the adjusted average years to ASCVD /ACM in high-risk individuals (years (95% CI): 9.1 (8.2–10.0) /9.3 (8.1–10.4)) were similar to those with low-risk (years (95% CI): 10.0 (9.5 – 10.5) /10.5 (9.7–11.2)). However, individuals ≥50 years with high-risk were likely to experience an ASCVD event 1.5 - 2 years earlier and death 1.1 – 1.5 years earlier compared to low-risk groups (p<0.01). </p> <p><b>Conclusions: </b>Unlike usual-onset,<b> </b>young-onset type 2 diabetes have similar cardiovascular and mortality risk irrespective of their cardiometabolic risk factor status at diagnosis. The guidelines on the management of young-onset type 2 diabetes for intensive risk-factor management and cardioprotective therapies need to be urgently re-evaluated through prospective studies.<b> </b></p>

The Role of Social Media in Creating and Maintaining Social Networks Including its Impact on Enhancing Competitive Positioning within the Education Sector

2015 ◽  
pp. 212-230
Author(s):  
Adam Raman
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Social Media ◽  
Higher Education Institutions ◽  
Communication Strategies ◽  
Strategy Development ◽  
Interactive Communication ◽  
Strategic Goals ◽  
Future Strategy

Social media is being increasingly utilised within society as an interactive communication platform. It has revolutionised the manner in which organisations communicate with their stakeholders, from the old way of simply designing messages and transmitting them across a desired medium, described as a static, one-way communication channel. Communications are the means by which organisations achieve their strategic goals through influencing their stakeholders. Social media allows stakeholders to connect to one another in relational, interactional networks. This means that stakeholders can now interact with organisations and each other and have a greater influence on the outcomes of communication strategies, which was impossible with traditional media. Organisations have less power dictating communications to stakeholders who in turn have more power in co-creating communication with each other. Social media is likely to have a major competitive impact on higher education institutions and these institutions should be accounting for these changes in their future strategy development. This chapter explores how social media is being utilized in organisations.

scholarly journals Gene Expression Patterns Distinguish Mortality Risk in Patients with Postsurgical Shock

2020 ◽  
Vol 9 (5) ◽  
pp. 1276
Author(s):  
Pedro Martínez-Paz ◽  
Marta Aragón-Camino ◽  
Esther Gómez-Sánchez ◽  
Mario Lorenzo-López ◽  
Estefanía Gómez-Pesquera ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Mortality Risk ◽  
Validation Cohort ◽  
Expression Patterns ◽  
Gene Expression Signature ◽  
Mrna Levels ◽  
Characteristic Analysis ◽  
Discovery Cohort ◽  
Risk Of Death

Nowadays, mortality rates in intensive care units are the highest of all hospital units. However, there is not a reliable prognostic system to predict the likelihood of death in patients with postsurgical shock. Thus, the aim of the present work is to obtain a gene expression signature to distinguish the low and high risk of death in postsurgical shock patients. In this sense, mRNA levels were evaluated by microarray on a discovery cohort to select the most differentially expressed genes between surviving and non-surviving groups 30 days after the operation. Selected genes were evaluated by quantitative real-time polymerase chain reaction (qPCR) in a validation cohort to validate the reliability of data. A receiver-operating characteristic analysis with the area under the curve was performed to quantify the sensitivity and specificity for gene expression levels, which were compared with predictions by established risk scales, such as acute physiology and chronic health evaluation (APACHE) and sequential organ failure assessment (SOFA). IL1R2, CD177, RETN, and OLFM4 genes were upregulated in the non-surviving group of the discovery cohort, and their predictive power was confirmed in the validation cohort. This work offers new biomarkers based on transcriptional patterns to classify the postsurgical shock patients according to low and high risk of death. The results present more accuracy than other mortality risk scores.

scholarly journals Enhanced Mortality Risk Prediction With a Focus on High-Risk Percutaneous Coronary Intervention

2013 ◽  
Vol 6 (8) ◽  
pp. 790-799 ◽  
Author(s):  
J. Matthew Brennan ◽  
Jeptha P. Curtis ◽  
David Dai ◽  
Susan Fitzgerald ◽  
Akshay K. Khandelwal ◽  
...  
Keyword(s):  
Percutaneous Coronary Intervention ◽  
High Risk ◽  
Risk Prediction ◽  
Mortality Risk ◽  
Coronary Intervention ◽  
Percutaneous Coronary

scholarly journals Is safety of childhood growth hormone therapy related to dose? Data from a large observational study

2016 ◽  
Vol 174 (5) ◽  
pp. 681-691 ◽  
Author(s):  
Lars Sävendahl ◽  
Effie Pournara ◽  
Birgitte Tønnes Pedersen ◽  
Oliver Blankenstein
Keyword(s):  
Growth Hormone ◽  
High Risk ◽  
Observational Study ◽  
Mortality Risk ◽  
Growth Hormone Treatment ◽  
Risk Group ◽  
Safety Data ◽  
Hormone Treatment ◽  
Low Risk ◽  
Intermediate Risk

AbstractObjectiveConcerns have been raised of increased mortality risk in adulthood in certain patients who received growth hormone treatment during childhood. This study evaluated the safety of growth hormone treatment in childhood in everyday practice.DesignNordiNet®International Outcome Study (IOS) is a noninterventional, observational study evaluating safety and effectiveness of Norditropin®(somatropin; Novo Nordisk A/S, Bagsvaerd, Denmark).MethodsLong-term safety data (1998–2013) were collected on 13 834 growth hormone treated pediatric patients with short stature. Incidence rates (IRs) of adverse events (AEs) defined as adverse drug reactions (ADRs), serious ADRs (SADRs), and serious AEs (SAEs) were calculated by mortality risk group (low/intermediate/high). The effect of growth hormone dose on IRs and the occurrence of cerebrovascular AEs were investigated by the risk group.ResultsWe found that 61.0% of patients were classified as low-risk, 33.9% intermediate-risk, and 5.1% high-risk. Three hundred and two AEs were reported in 261 (1.9%) patients during a mean (s.d.) treatment duration of 3.9 (2.8) years. IRs were significantly higher in the high- vs the low-risk group (high risk vs low risk—ADR: 9.11 vs 3.14; SAE: 13.66 vs 1.85; SADR: 4.97 vs 0.73 events/1000 patient-years of exposure;P< 0.0001 for all). Except for SAEs in the intermediate-risk group (P= 0.0486) in which an inverse relationship was observed, no association between IRs and growth hormone dose was found. No cerebrovascular events were reported.ConclusionsWe conclude that safety data from NordiNet®IOS do not reveal any new safety signals and confirm a favorable overall safety profile in accordance with other pediatric observational studies. No association between growth hormone dose and the incidence of AEs during growth hormone treatment in childhood was found.

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