Applying social network analysis to the examination of interruptions in healthcare

Bridging and Bonding Social Capital by Analyzing the Demographics, User Activities, and Social Network Dynamics of Sexual Assault Centers on Twitter: Mixed Methods Study

BACKGROUND

Social media platforms have gained popularity as communication tools for organizations to engage with clients and the public, disseminate information, and raise awareness about social issues. From a social capital perspective, relationship building is seen as an investment, involving a complex interplay of tangible and intangible resources. Social media-based social capital signifies the diverse social networks that organizations can foster through their engagement on social media platforms. Literature underscores the great significance of further investigation into the scope and nature of social media use, particularly within sectors dedicated to service delivery, such as sexual assault organizations.

OBJECTIVE

This study aims to fill a research gap by investigating the use of Twitter by sexual assault support agencies in Canada. It seeks to understand the demographics, user activities, and social network structure within these organizations on Twitter, focusing on building social capital. The research questions explore the demographic profile, geographic distribution, and Twitter activity of these organizations as well as the social network dynamics of bridging and bonding social capital.

METHODS

This study used purposive sampling to investigate sexual assault centers in Canada with active Twitter accounts, resulting in the identification of 124 centers. The Twitter handles were collected, yielding 113 unique handles, and their corresponding Twitter IDs were obtained and validated. A total of 294,350 tweets were collected from these centers, covering >93.54% of their Twitter activity. Preprocessing was conducted to prepare the data, and descriptive analysis was used to determine the center demographics and age. Furthermore, geolocation mapping was performed to visualize the center locations. Social network analysis was used to explore the intricate relationships within the network of sexual assault center Twitter accounts, using various metrics to assess the network structure and connectivity dynamics.

RESULTS

The results highlight the substantial presence of sexual assault organizations on Twitter, particularly in provinces such as Ontario, British Columbia, and Quebec, underscoring the importance of tailored engagement strategies considering regional disparities. The analysis of Twitter account creation years shows a peak in 2012, followed by a decline in new account creations in subsequent years. The monthly tweet activity shows November as the most active month, whereas July had the lowest activity. The study also reveals variations in Twitter activity, account creation patterns, and social network dynamics, identifying influential social queens and marginalized entities within the network.

CONCLUSIONS

This study presents a comprehensive landscape of the demographics and activities of sexual assault centers in Canada on Twitter. This study suggests that future research should explore the long-term consequences of social media use and examine stakeholder perceptions, providing valuable insights to improve communication practices within the nonprofit human services sector and further the missions of these organizations.

Biomarker detection using corrected degree of domesticity in hybrid social network feature selection for improving classifier performance

BACKGROUND

Dimension reduction, especially feature selection, is an important step in improving classification performance for high-dimensional data. Particularly in cancer research, when reducing the number of features, i.e., genes, it is important to select the most informative features/potential biomarkers that could affect the diagnostic accuracy. Therefore, researchers continuously try to explore more efficient ways to reduce the large number of features/genes to a small but informative subset before the classification task. Hybrid methods have been extensively investigated for this purpose, and research to find the optimal approach is ongoing. Social network analysis is used as a part of a hybrid method, although there are several issues that have arisen when using social network tools, such as using a single environment for computing, constructing an adjacency matrix or computing network measures. Therefore, in our study, we apply a hybrid feature selection method consisting of several machine learning algorithms in addition to social network analysis with our proposed network metric, called the corrected degree of domesticity, in a single environment, R, to improve the support vector machine classifier's performance. In addition, we evaluate and compare the performances of several combinations used in the different steps of the method with a simulation experiment.

RESULTS

The proposed method improves the classifier's performance compared to using the whole feature set in all the cases we investigate. Additionally, in terms of the area under the receiver operating characteristic (ROC) curve, our approach improves classification performance compared to several approaches in the literature.

CONCLUSION

When using the corrected degree of domesticity as a network degree centrality measure, it is important to use our correction to compare nodes/features with no connection outside of their community since it provides a more accurate ranking among the features. Due to the nature of the hybrid method, which includes social network analysis, it is necessary to investigate possible combinations to provide an optimal solution for the microarray data used in the research.

Improving care safety by characterizing task interruptions during interactions between healthcare professionals: an observational study

Few studies have investigated interruptions to the work of professionals practicing in inpatient hospitals, and even fewer take account of the functions that make up the system. Safety of care can be improved by considering avoidable interruptions during interactions between managerial and care delivery functions. The present study describes the characteristics of interruptions to the work of professionals working in the inpatient hospital sector, with respect to their typology, frequency, duration, and avoidability in the context of interactions between functions. This direct observational study of interruptions in hospital care was performed in the Pays de la Loire (west coast) area of France. A total of 23 teams (17 institutions) working in medical or surgical specialties (excluding intensive care) were included. Observations were performed between May and September 2019, and lasted seven consecutive hours per team. A pair of observers simultaneously observed the same professional for ∼30 min. Each occupational category was examined. Reported characteristics were: (i) the method and duration of the request, (ii) the location of interrupted and interrupting persons, (iii) the reaction of the interrupted person, (iv) the characteristics of the interrupting person, and (v) the classification of interrupted and interrupting tasks according to their function. An avoidable interruption was defined. Interruptions during interactions between professionals were categorised in terms of their function and avoidability. Descriptive statistical analyses (mean, standard deviation, and distribution) were run. In particular, cross-comparisons were run to highlight avoidability interruptions and interactions between managerial and care delivery functions during the working day, for different professional categories, and for the location of the request. Overall, 286 interrupted professionals were observed and 1929 interruptions were characterised. The majority of interruptions were due to a face-to-face request (58.7%), lasting ≤30 s (72.5%). Professionals engaged in the response in 49.3% of cases. A total of 57.4% of interruptions were avoidable. The average number of interruptions was 10.5 (SD = 3.2) per hour per professional. An analysis of avoidability and interactions between managerial and care delivery functions found that the period between 12:00 and 13:00 was the riskiest in terms of care safety. This study highlighted the characteristics of interruptions to the activity of professionals working in inpatient hospitals. Care teams could focus on making medical and nursing professionals much more aware of the importance of interruptions, and each team could decide how to best-manage interruptions, in the context of their specific working environment.

Task interruptions from the perspective of work functions: The development of an observational tool applied to inpatient hospital care in France The Team'IT tool

BACKGROUND

In France, hospital units responsible for providing inpatient care have few opportunities to address the issue of task interruptions. In Australia, the Dual Perspectives Method (DMP) has been developed to assess interruptions. The method makes it possible to link teamwork and interruptions, by considering the work functions that constitute the system.

OBJECTIVE

To develop a tool that can characterize interruptions from the point of view of work functions that is tailored to French hospital units providing inpatient care. The aim was to adapt the items recorded using the DPM and their response categories, and to study the acceptability of observing interruptions for participating teams.

METHOD

The items recorded in the DPM were translated and adapted taking into account the French definition of interruptions. This step identified 19 items that targeted the interrupted professional, and 16 that targeted the interrupting professional. The characteristics of interruptions were recorded in September 2019 among 23 volunteer teams in a region in western France. Two observers simultaneously observed the same professional. Observations lasted seven consecutive hours, and targeted all professional categories within the same team.

RESULTS

The characteristics of 1,929 interruptions were noted. The observation period was well-received by teams. The following terminology regarding the work functions of the interrupting professional was clarified: "coordination of institutional resources", in relation to "the establishment's support processes", "patient services", and "the patient's social life". We believe that our categorization of response modes is exhaustive.

CONCLUSIONS

We have developed an observational tool, Team'IT, which is tailored to inpatient hospital care in France. Its implementation is the first step in a system to support teams in managing interruptions, and will enable them to reflect on their working methods, and whether interruptions can be avoided. Our work is part of an approach that seeks to improve and enhance the safety of professional practices, by contributing to the longstanding, complex debate about the flow and effectiveness of patient care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03786874 (December 26, 2018).

Explaining emergency physicians' capacity to recover from interruptions

OBJECTIVE

To assess whether the capacity to utilize cues amongst emergency physicians is associated with differences in the capacity to recover performance following an interruption.

BACKGROUND

Interruptions are implicated in errors in emergency medicine due to the cognitive load that they impose on working memory, resulting in a loss of performance on the primary task. The utilization of cues is associated with a reduction in cognitive load during the performance of a task, thereby enabling the allocation of residual resources that mitigates the loss of performance following interruptions.

METHOD

Thirty-nine emergency physicians, recruited at a medical conference, completed an assessment of cue utilization (EXPERTise 2.0) and an online simulation (Septris) that involved the management of patients presenting with sepsis. During the simulation, physicians were interrupted and asked to check a medication order. Task performance was assessed using scores on Septris, with points awarded for the accurate management of patients.

RESULTS

Emergency physicians with higher cue utilization recorded significantly higher scores on the simulation task following the interruption, compared to physicians with lower cue utilization (p = .028).

CONCLUSION

The results confirm a relationship between cue utilization and the recovery of performance following an interruption. This is likely due to the advantages afforded by associated reductions in cognitive load.

APPLICATION

Assessments of cue utilization may assist in the development of interventions to support clinicians in interruptive environments.

Food Bloggers on the Twitter Social Network: Yummy, Healthy, Homemade, and Vegan Food

Many people now consider social networking to be an indispensable tool. There are now over 4.6 billion social media users, who leave a digital footprint through their online interactions. These big data provide enormous research potential for identifying the social and cultural aspects of the monitored topic. Moreover, the use of social media platforms has been found to have an impact on eating habits. The analysis of these social networks is thus essential to understand the factors that influence eating habits. To this aim, we identified the main topics associated with food bloggers on Twitter using the Social Media Analysis based on the Hashtag Research Framework of 686,450 Tweets captured from 171,243 unique users from 1 January 2017 to 30 May 2022. Based on the analysis of communication on Twitter, the most communicated hashtags in the food blogger sphere were as follows: #yummy, #healthy, #homemade, and #vegan. From the point of view of communities, three major clusters were identified, including (1) healthy lifestyle, (2) home-made food, and (3) fast food, and two minor clusters were identified, namely, (4) breakfast and brunch and (5) food traveling.

Interruptions to Intensive Care Nurses and Clinical Errors and Procedural Failures: A Controlled Study of Causal Connection

OBJECTIVES

Interruptions occur frequently in the intensive care unit (ICU) and are associated with errors. To date, no causal connection has been established between interruptions and errors in healthcare. It is important to know whether interruptions directly cause errors before implementing interventions designed to reduce interruptions in ICUs. The aim of the study was to investigate whether ICU nurses who receive a higher number of workplace interruptions commit more clinical errors and procedural failures than those who receive a lower number of interruptions.

METHODS

We conducted a prospective controlled trial in a high-fidelity ICU simulator. A volunteer sample of ICU nurses from a single unit prepared and administered intravenous medications for a patient manikin. Nurses received either 3 (n = 35) or 12 (n = 35) scenario-relevant interruptions and were allocated to either condition in an alternating fashion. Primary outcomes were the number of clinical errors and procedural failures committed by each nurse.

RESULTS

The rate ratio of clinical errors committed by nurses who received 12 interruptions compared with nurses who received 3 interruptions was 2.0 (95% confidence interval = 1.41-2.83, P < 0.001). The rate ratio of procedural failures committed by nurses who received 12 interruptions compared with nurses who were interrupted 3 times was 1.2 (95% confidence interval = 1.05-1.37, P = 0.006).

CONCLUSIONS

More workplace interruptions during medication preparation and administration lead to more clinical errors and procedural failures. Reducing the frequency of interruptions may reduce the number of errors committed; however, this should be balanced against important information that interruptions communicate.

Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector

Ever-changing conditions and emerging new challenges affect the ability of the healthcare sector to survive with the current system, and to maintain its processes effectively. In the healthcare sector, the conservation of the natural resources is being obstructed by insufficient infrastructure for managing residual waste resulting from single-use medical materials, increased energy use, and its environmental burden. In this context, circularity and sustainability concepts have become essential in healthcare to meliorate the sector’s negative impacts on the environment. The main aim of this study is to identify the barriers related to circular economy (CE) in the healthcare sector, apply big data analytics in healthcare, and provide solutions to these barriers. The contribution of this research is the detailed examination of the current healthcare literature about CE adaptation, and a proposal for a big data-enabled solutions framework to barriers to circularity, using fuzzy best-worst Method (BWM) and fuzzy VIKOR. Based on the findings, managerial, policy, and theoretical implementations are recommended to support sustainable development initiatives in the healthcare sector.

Examining Social Networks in Text Messages About Nursing Home Resident Health Status

Social network analysis (SNA) uses quantitative methods to analyze relationships between people. In the current study, SNA was applied in two nursing homes (NHs) to describe how health care teams interact via text messages. Two data sources were used: (a) a Qualtrics^® survey completed by advanced practice RNs containing resident transfer data, and (b) text messages from a secure platform called Mediprocity™. SNA software was used to generate a visual representation of the social networks and calculate quantitative measures of network structure, including density, clustering coefficient, hierarchy, and centralization. Differences were found in the low and high transfer rate NHs for all SNA measures. Staff in the NH with low transfer rate had greater decision-making interactions, higher information exchange rates, and more individuals communicating with each other compared to the high transfer rate NH. SNA can be applied to examine communication patterns found in text messages occurring around the time of NH resident transfers. [Journal of Gerontological Nursing, 47(7), 16-22.].

Social Network Analysis of Alzheimer's Teams: A Clinical Review and Applications in Psychiatry to Explore Interprofessional Care

INTRODUCTION

Understanding the social networks of professionals in psychiatric hospitals and communities working with persons with Alzheimer's (PWA) disease helps tackle the flow of knowledge in patient care and the centrality of team members in providing information and advice to colleagues.

OBJECTIVES

To use Social Network Analysis (SNA) to confirm or reject the hypothesis that psychiatric professionals have equal status in sharing information and advice on the care of PWA and have reciprocal ties in a social network.

METHODS

The sample consisting of 50 psychiatric professionals working in geriatric psychiatry in the UK completed an anonymous online survey asking them to select the professional categories of the colleagues in the interprofessional team who are most frequently approached when providing or receiving advice about patient care and gathering patient information. SNA is both a descriptive qualitative analysis and a quantitative method that investigates the degree of the prestige of professionals in their working network and the reciprocity of their ties with other team members.

FINDINGS

The social network graphs and numerical outcomes showed that interprofessional teams in geriatric psychiatry have health carers who play central roles in providing the whole team with the knowledge necessary for patient care; these are primarily senior professionals in nursing and medical roles. However, the study reported that only 13% of professionals had reciprocal ties within teams.

CONCLUSION

The current research findings show that the impact of psychiatric health carers in interprofessional teams caring for PWA is not evenly distributed. Those with apparently higher seniority and experience are more frequently consulted; however, other more peripheral figures can be equally valuable in integrated care.

Healthy Food on Instagram Social Network: Vegan, Homemade and Clean Eating

Social media platforms have become part of many people's lives. Users are spending more and more time on these platforms, creating an active and passive digital footprint through their interaction. This footprint has high research potential in many research areas because understanding people's communication on social media is essential in understanding their values, attitudes, experiences and behaviors. Researchers found that the use of social networking sites impacts adolescents' eating behavior. If we define adolescents as individuals between ages 10 and 24 (WHO's definition), 76% of USA young people at age 18-⁠24 use Instagram, so the Instagram social network analysis is important for understanding young people's expressions in the context of healthy food. This study aims to identify the main topic associated with healthy food on the Instagram social network via hashtag and community analysis based on 2,045,653 messages created by 427,936 individual users. The results show that users most associate Healthy food with healthy lifestyle, fitness, weight loss and diet. In terms of food, these are foods that are Vegan, Homemade, Clean and Plant-based. Given that young people change their behavior in relation to people's behavior on social networks, it is possible to use this data to predict their future association with healthy food characteristics.

Framework for Social Media Analysis Based on Hashtag Research

Social networks have become a common part of many people’s daily lives. Users spend more and more time on these platforms and create an active and passive digital footprint through their interaction with other subjects. These data have high research potential in many fields, because understanding people’s communication on social media is essential to understanding their attitudes, experiences and behaviours. Social media analysis is a relatively new subject. There is still a need to develop methods and tools for researchers to help solve typical problems associated with this area. A researcher will be able to focus on the subject of research entirely. This article describes the Social Media Analysis based on Hashtag Research (SMAHR) framework, which uses social network analysis methods to explore social media communication through a network of hashtags. The results show that social media analysis based on hashtags provides information applicable to theoretical research and practical strategic marketing and management applications.

Healthy Food on the Twitter Social Network: Vegan, Homemade, and Organic Food

Online social networks have become an everyday aspect of many people’s lives. Users spend more and more time on these platforms and, through their interactions on social media platforms, they create active and passive digital footprints. These data have a strong potential in many research areas; indeed, understanding people’s communication on social media is essential for understanding their attitudes, experiences, behaviors and values. Researchers have found that the use of social networking sites impacts eating behavior; thus, analyzing social network data is important for understanding the meaning behind expressions used in the context of healthy food. This study performed a communication analysis of data from the social network Twitter, which included 666,178 messages posted by 168,134 individual users. These data comprised all tweets that used the #healthyfood hashtag between 2019 and 2020 on Twitter. The results revealed that users most commonly associate healthy food with a healthy lifestyle, diet, and fitness. Foods associated with this hashtag were vegan, homemade, and organic. Given that people change their behavior according to other people’s behavior on social networks, these data could be used to identify current and future associations with current and future perceptions of healthy food characteristics.

Corporate Social Responsibility and Social Media: Comparison between Developing and Developed Countries

Social media allow companies to engage with their interest groups, thus enabling them to solidify corporate social responsibility (CSR) policies. The concept of CSR is now well-established for companies in Western countries, and CSR is becoming an increasingly popular topic in developing countries. This study investigated differences in the perception of the term ‘CSR’ on Instagram between developing and developed countries. We analysed 113,628 Instagram messages from 38,590 unique users worldwide. The data were recorded between 19 November 2017 and 11 December 2018. In both developed and developing countries, charity and social good were common features. On the contrary, a difference was identified in the area of sustainability, which is an important part of communication in developed countries, and the area of education, which is an important part of communication in developing countries. Community analysis revealed four dominant communities in developed countries: (1) philanthropic responsibility, (2) environmental sustainability, (3) pleasure from working and (4) start-ups with CSR; and three in developing countries: (1) social and environmental responsibility, (2) philanthropic responsibility and (3) reputation management. These results could facilitate the strategic management of CSR to adapt communication to local environments and company contexts. Our findings could allow managers to focus CSR activities on relevant issues in developing countries and thus differentiate their CSR communication from competing organizations.

Distributed situation awareness: a health-system approach to assessing and designing patient flow management

Patient flow management is a system-wide process but many healthcare providers do not integrate multiple departments into the process to minimise the time between treatments or medical services for maximum patient throughput. This paper presents a case study of applying Distributed Situation Awareness (DSA) to characterise system-wide patient flow management and identify opportunities for improvements in a healthcare system. This case study employed a three-part method of data elicitation, extraction, and representation to investigate DSA. Social, task, and knowledge networks were developed and then combined to characterise patient flow management and identify deficiencies of the command and control centre of a healthcare facility. Social network analysis provided centrality metrics to further characterise patient flow management. The DSA model helped identify design principles and deficiencies in managing patient flow. These findings indicate that DSA is promising for analysing patient flow management from a system-wide perspective. Practitioner summary: This article examines Distribution Situation Awareness (DSA) as an analysis framework to study system-wide patient flow management. The DSA yields social, task, and knowledge networks that can be combined to characterise patient flow and identify deficiencies in the system. DSA appears promising for analysing communication and coordination of complex systems. Abbreviations: CDM: critical decision method; CTaC: carilion transfer and communications center; EAST: event analysis systematic teamwork; ED: emergency department; DES: discrete event simulation; DSA: distributed situation awareness; SA: situation awareness; SNA: social network analysis.

Twitter Analysis of Global Communication in the Field of Sustainability

The increasing popularity of social media worldwide provides us with an opportunity to understand social, cultural, and environmental issues about people’s perception of sustainability. The article aims at identifying the main topics of communication related to hashtag # sustainability based on a communication analysis on the Twitter network. We investigated the perception of sustainability using data from 414,926 Twitter interactions by 223,476 users worldwide. The data were recorded between April 17, 2018 and July 12, 2019. We identified Innovation, Environment, Climate Change, Corporate Social Responsibility, Technology, and Energy as key hashtags in the field of sustainability. In conjunction with this, we identified the six following communities: (1) Environmental Sustainability, (2) Sustainability Awareness, (3) Renewable Energy and Climate Change, (4) Innovative Technology, (5) Green Architecture, and (6) Food Sustainability. The usage of these communities is applicable in marketing communication as well as in the Corporate Social Responsibility activities of the given companies. The results of the analysis give the organizations a possible direction for their sustainable business model improvement via the contribution of society´s voice.

Interruptions in Health Care: Assessing Their Connection With Error and Patient Harm

OBJECTIVE

We address the problem of how researchers investigate the actual or potential causal connection between interruptions and medical errors, and whether interventions might reduce the potential for harm.

BACKGROUND

It is widely assumed that interruptions lead to errors and patient harm. However, many reviewers and authors have commented that there is not strong evidence for a causal connection.

METHOD

We introduce a framework of criteria for assessing how strongly evidence implies causality: the so-called Bradford Hill criteria. We then examine four key "metanarratives" of research into interruptions in health care-applied cognitive psychology, epidemiology, quality improvement, and cognitive systems engineering-and assess how each tradition has addressed the causal connection between interruptions and error.

RESULTS

Outcomes of applying the Bradford Hill criteria are that the applied cognitive psychology and epidemiology metanarratives address the causal connection relatively directly, whereas the quality improvement metanarrative merely assumes causality, and the cognitive systems engineering metanarrative either implicitly or explicitly questions the feasibility of finding a direct causal connection with harm.

CONCLUSION

The Bradford Hill criteria are useful for evaluating the existing literature on the relationship between interruptions in health care, clinical errors, and the potential for patient harm. In the future, more attention is needed to the issue of why interruptions usually do not lead to harm, and the implications for how we approach patient safety.

Role network measures to assess healthcare team adaptation to complex situations: the case of venous thromboembolism prophylaxis

Hospitals are complex environments that rely on clinicians working together to provide appropriate care to patients. These clinical teams adapt their interactions to meet changing situational needs. Venous thromboembolism (VTE) prophylaxis is a complex process that occurs throughout a patient's hospitalisation, presenting five stages with different levels of complexity: admission, interruption, re-initiation, initiation, and transfer. The objective of our study is to understand how the VTE prophylaxis team adapts as the complexity in the process changes; we do this by using social network analysis (SNA) measures. We interviewed 45 clinicians representing 9 different cases, creating 43 role networks. The role networks were analysed using SNA measures to understand team changes between low and high complexity stages. When comparing low and high complexity stages, we found two team adaptation mechanisms: (1) relative increase in the number of people, team activities, and interactions within the team, or (2) relative increase in discussion among the team, reflected by an increase in reciprocity.   Practitioner Summary: The reason for this study was to quantify team adaptation to complexity in a process using social network analysis (SNA). The VTE prophylaxis team adapted to complexity by two different mechanisms, by increasing the roles, activities, and interactions among the team or by increasing the two-way communication and discussion throughout the team. We demonstrated the ability for SNA to identify adaptation within a team.

Relationship of Staff Information Sharing and Advice Networks to Patient Safety Outcomes

OBJECTIVE

The aim of this study was to compare information sharing and advice networks' relationships with patient safety outcomes.

BACKGROUND

Communication contributes to medical errors, but rarely is it clear what elements of communication are key.

METHODS

We investigated relationships of information-sharing and advice networks to patient safety outcomes in 24 patient care units from 3 hospitals over 7 months. Web-based questionnaires completed via Android tablets provided data to create 2 networks using ORA, a social network analysis application. Each hospital provided nurse-sensitive patient safety outcomes.

RESULTS

In both networks, medication errors correlated positively with node count and average distance and negatively with clustering coefficient. Density and weighted density negatively correlated with medication errors and falls in both networks. Eigenvector and total degree centrality correlated negatively with both safety outcomes, whereas betweenness centrality positively related to falls in the information-sharing network.

CONCLUSION

Technology-enabled social network analysis data collection is feasible and can provide managers actionable system-level information.

Workflow interruptions and stress atwork: a mixed-methods study among physicians and nurses of a multidisciplinary emergency department

OBJECTIVES

Dealing with multiple workflow interruptions is a major challenge in emergency department (ED) work. This study aimed to establish a taxonomy of workflow interruptions that takes into account the content and purpose of interruptive communication. It further aimed to identify associations of workflow interruptions with ED professionals' work stress.

DESIGN

Combined data from expert observation sessions and concomitant self-evaluations of ED providers.

SETTING

ED of an academic community hospital in Germany.

PARTICIPANTS

Multidisciplinary sample of ED physicians and nurses. 77 matched observation sessions of interruptions and self-evaluations of work stress were obtained on 20 randomly selected days.

OUTCOME MEASURES

ED professionals' stress evaluations were based on standardised measures. ED workload data on patient load, patient acuity and staffing were included as control variables in regression analyses.

RESULTS

Overall mean rate was 7.51 interruptions/hour. Interruptions were most frequently caused by ED colleagues of another profession (27.1%; mean interruptions/hour rate: 2.04), by ED colleagues of the same profession (24.1%; 1.81) and by telephone/beeper (21%; 1.57). Concerning the contents of interruption events, interruptions most frequently occurred referring to a parallel case under care (30.3%, 2.07), concerning the current case (19.1%; 1.28), or related to coordination activities (18.2%, 1.24). Regression analyses revealed that interruptive communication related to parallel cases significantly increased ED providers' stress levels (β=0.24, P=0.03). This association remained significant after controlling for ED workload.

DISCUSSION

Interruptions that refer to parallel cases under care were associated with increased stress among ED physicians and nurses. Our approach to distinguish between sources and contents of interruptions contributes to an improved understanding of potential benefits and risks of workflow interruptions in ED work environments. Despite some limitations, our findings add to future research on the implications of interruptions for effective and safe patient care and work in complex and dynamic care environments.