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ObjectiveOur study of informal networks aimed to explore information-sharing environments for the management of disaster medicine and public health preparedness. Understanding interagency coordination in preparing for and responding to extreme events such as disease outbreaks is central to reducing risks and coordination costs.MethodsWe evaluated the pattern of information flow for actors involved in disaster medicine through social network analysis. Social network analysis of agencies can serve as a basis for the effective design and reconstruction of disaster medicine response coordination structures. This research used new theoretical approaches in suggesting a framework and a method to study the outcome of complex inter-organizational networks in coordinating disease outbreak response. We present research surveys of 70 health professionals from different skill sets and organizational positions during the swine influenza A (H1N1) PDM09 2009 pandemic. The survey and interviews were designed to collect both qualitative and quantitative data in order to build a comprehensive and in-depth understanding of the dynamics of the inter-organizational networks that evolved during the pandemic.ResultsThe degree centrality of the informal network showed a positive correlation with performance, in which the ego’s performance is related to the number of links he or she establishes informally—outside the standard operating structure during the pandemic. Informal networks facilitate the transmission of both strong (ie, infections, confirmed cases, deaths in hospital or clinic settings) and weak (ie, casual acquaintances) ties.ConclusionsThe results showed that informal networks promoted community-based ad hoc and formal networks, thus making overall disaster medicine and public health preparedness more effective. (Disaster Med Public Health Preparedness. 2017;11:343–354)

We suggest that effective management of Ebola disaster and public health preparedness needs to focus on connecting the dots among different originating points of the spread using locally situated knowledge through community partnership networks so that the wider transmission to other geographic locations can be managed effectively and in a timely manner. Effective management of outbreaks, like the current West African 2014 Ebola epidemic, is dependent on public health preparedness. In this study, a systematic analysis of the spread during the months of March to October 2014 was performed using data from the Programme for Monitoring Emerging Diseases (ProMED) and the Factiva database. This study aims to draw network connections of individuals/groups from a localised to a globalised transmission of Ebola using reported suspected/probable/confirmed cases at different locations around the world. Public health preparedness can be strengthened by understanding the social network connections between resp...

The goal of this study was to understand research trends and collaboration patterns together with scholarly impact within the domain of global obesity research. We developed and analysed bibliographic affiliation data collected from 117,340 research articles indexed in Scopus database on the topic of obesity and published from 1993-2012. We found steady growth and an exponential increase of publication numbers. Research output in global obesity research roughly doubled each 5 years, with almost 80% of the publications and authors from the second decade (2003-2012). The highest publication output was from the USA - 42% of publications had at least one author from the USA. Many US institutions also ranked highly in terms of research output and collaboration. Fifteen of the top-20 institutions in terms of publication output were from the USA; however, several European and Japanese research institutions ranked more highly in terms of average citations per paper. The majority of obesity research and collaboration has been confined to developed countries although developing countries have showed higher growth in recent times, e.g. the publication ratio between 2003-2012 and 1993-2002 for developing regions was much higher than that of developed regions (9:1 vs. 4:1). We also identified around 42 broad disciplines from authors' affiliation data, and these showed strong collaboration between them. Overall, this study provides one of the most comprehensive longitudinal bibliometric analyses of obesity research. This should help in understanding research trends, spatial density, collaboration patterns and the complex multi-disciplinary nature of research in the obesity domain.

Foodborne disease outbreaks are increasingly being seen as a greater concern by public health authorities. It has also become a global research agenda to identify improved pathways to coordinating outbreak detection. Furthermore, a significant need exists for timely coordination of the detection of potential foodborne disease outbreaks to reduce the number of infected individuals and the overall impact on public health security. This study aimed to offer an effective approach for coordinating foodborne disease outbreaks. First, we identify current coordination processes, complexities, and challenges. We then explore social media surveillance strategies, usage, and the power of these strategies to influence decision-making. Finally, based on informal (social media) and formal (organizational) surveillance approaches, we propose a hybrid information network model for improving the coordination of outbreak detection. (Disaster Med Public Health Preparedness. 2015;9:186-198)

We argue that social media provides a new platform to explore how public responds to disasters and, in particular, disasters related to emerging infectious diseases such as Ebola. A critical aspect to early detection and effective containment of communicable diseases lies at the heart of how we leverage different types of social media to promote public awareness and safety protocol for the general population as well as the health workforce for dealing with emerging communicable diseases in a timely manner. China consists of more than 100 cities with a population of over one million people each. Effective monitoring and public awareness of global epidemics and early detection to its possible transmission to local population is critical for China for monitoring the spread of communicable disease, which can potentially have deadly effect for the Chinese population and the world. The recent West African Ebola disaster deserves attention due to the number of annual arrivals from Africa and also significantly large Chinese employees engaged in African cooperative projects. Weibo, the most popular social media in China with more than 2 billion users and over 300 million daily posts can essentially serve as a platform monitoring, promoting of public health awareness as well as early detection of possible cases of Ebola. This, in turn, can provide an effective and timely alternative to improve the overall preparedness for and response to disaster medicine. This study presents a timely and important investigation of Chinese public reaction to the Ebola disaster by analyzing related data from Weibo.

Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system’s output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks’ influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.

Background In this study, we explore the nexus between social networks and expertise development of Australian breast radiologists. Background literature has shown that a lack of appropriate social networks and interaction among certain professional group(s) may be an obstacle for knowledge acquisition, information flow and expertise sharing. To date there have not been any systematic studies investigating how social networks and expertise development are interconnected and whether this leads to improved performance for breast radiologists. Methods This study explores the value of social networks in building expertise alongside with other constructs of performance for the Australian radiology workforce using semi-structured in-depth interviews with 17 breast radiologists. Results The findings from this study emphasise the influences of knowledge transfer and learning through social networks and interactions as well as knowledge acquisition and development through experience and feedback. The results also show that accessibility to learning resources and a variety of timely feedback on performance through the information and communication technologies (ICT) is likely to facilitate improved performance and build social support. Conclusions We argue that radiologists’ and, in particular, breast radiologists’ work performance, needs to be explored not only through individual numerical characteristics but also by analysing the social context and peer support networks in which they operate and we identify multidisciplinary care as a core entity of social learning. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1938-9) contains supplementary material, which is available to authorized users.

Materials and Methods In this paper, we propose a theoretical model based upon previous studies about personal and social network dynamics of job performance. We provide empirical support for this model using real-world data within the context of the Australian radiology profession. An examination of radiologists’ professional network topology through structural-positional and relational dimensions and radiologists’ personal characteristics in terms of knowledge, experience and self-esteem is provided. Thirty one breast imaging radiologists completed a purpose designed questionnaire regarding their network characteristics and personal attributes. These radiologists also independently read a test set of 60 mammographic cases: 20 cases with cancer and 40 normal cases. A Jackknife free response operating characteristic (JAFROC) method was used to measure the performance of the radiologists’ in detecting breast cancers. Results Correlational analyses showed that reader performance was positively correlated with the social network variables of degree centrality and effective size, but negatively correlated with constraint and hierarchy. For personal characteristics, the number of mammograms read per year and self-esteem (self-evaluation) positively correlated with reader performance. Hierarchical multiple regression analysis indicated that the combination of number of mammograms read per year and network’s effective size, hierarchy and tie strength was the best fitting model, explaining 63.4% of the variance in reader performance. The results from this study indicate the positive relationship between reading high volumes of cases by radiologists and expertise development, but also strongly emphasise the association between effective social/professional interactions and informal knowledge sharing with high performance.

Background: Previous studies have documented the effect of collaboration among physicians on the effectiveness in delivering health services and in producing better patient outcomes. However, there is no systematic empirical study suggesting the underlying relationship between the collaboration network of physicians and its effect on hospitalization cost and readmission rate. In this study, we explore the effect of different attributes (i.e. degree centrality, betweenness centrality, network density and network distance) of physician collaboration network (PCN) on hospitalization cost and readmission rate. Method: We analyse health insurance claim data set of total hip replacement (THR) patients to construct PCN and to test the effect of its network attributes on hospitalization cost and readmission rate. We consider patient age as moderating factor, which could affect the relation of the PCN attributes with hospitalization cost and readmission rate. Results: We find that degree centrality (i.e. level of involvement) and network density (i.e. level of connectedness) of PCN are negatively correlated with hospitalization cost and readmission rate. In contrast, betweenness centrality (i.e. capacity to control the flow of information) is found positively correlated with hospitalization cost and readmission rate. Distance (i.e. embeddedness of actors in a network) is found positively correlated with hospitalization cost but negatively correlated with readmission rate. We do not notice any significant impact of patient age on the relation of PCN attributes with hospitalization cost and readmission rate. Conclusion: The results show that the structure of PCNs is related to indicators of hospital costs and quality (readmission). In their respective hospitals, health-care managers or administrators may follow our research findings to reduce cost and improve quality.

Objective Although the medical system has expanded considerably over the past two decades in almost all countries, so too has the demand for health care. The radiology specialisation may be an early system indicator, being especially sensitive to changes in supply and demand in both rural and urban environments. The question is whether the new policies of increasing the number of radiologists can be a proper long-term solution for the imbalance of workforce supply and demand or not. Methods Using system dynamics modelling, we present our integrated descriptive models for the supply and demand of Australian radiologists to find the actual gap. Followed by this, we pose a prescriptive model for the supply in order to lessen the identified imbalance between supply and demand. Our system dynamics models compare the demand and supply of Australian radiologists over 40 years between 2010 and 2050. Results The descriptive model shows that even if the radiology training program grows at a higher rate than the medical training growth rate and its own historical growth, the system will never be able to meet demand. The prescriptive model also indicates that although changing some influential factors (e.g the intake rate) reduces the level of imbalance, the system will still stay unstable during the study period. Conclusion We posit that Australia may need to design a new system of radiology provision to meet future demands for high-quality medical radiation services. We also suggest some strategies, such as greater development of radiographers’ role, are critical for enabling sustainable change over time. What is known about the topic? Long-term workforce planning for medical services at the national level has been very challenging for policy makers of the 21st century. The current demographic imbalance in the supply and demand of the Australian radiologist workforce makes it difficult to plan the effects of extra inflow of radiology students over time. What does this paper add? This paper discovers the current situation facing the Australian Radiology profession and identifies all the factors that influence the long-term matching of radiologist workforce supply and demand. This Australian case study adds to the current literature of medical workforce planning and its challenges. Moreover, this paper answers how the problem of workforce imbalance can be solved through a sustainable change over time. What are the implications for practitioners? Conventional responses in Australia and many developed countries in response to radiological services demand have been to increase the number of radiologists. However, our models and analyses show that this is not an all-inclusive long-term solution: merely increasing the number of radiologists will not result in a balance between supply and demand.

At global and local levels, we are observing an increasing range and rate of disease outbreaks that show evidence of jumping from animals to humans, and from food to humans. Zoonotic infections (i.e. Hendra, swine flu, anthrax) affect animal health and can be deadly to humans. The increasing rate of outbreaks of infectious diseases transferring from animals to humans (i.e. zoonotic diseases) necessitates detailed understanding of the education, research and practice of animal health and its connection to human health. These emerging microbial threats underline the need to exploring the evolutionary dynamics of zoonotic research across public health and animal health. This study investigates the collaboration network of different countries engaged in conducting zoonotic research. We explore the dynamics of this network from 1980 to 2012 based on large scientific data developed from Scopus. In our analyses, we compare several properties of the network including density, clustering coefficient, giant component and centrality measures over time. We also map the network over different time intervals using VOSviewer. We analyzed 5182 publication records. We found United States and United Kingdom as the most collaborative countries working with 110 and 74 other countries in 1048 and 599 cases, respectively. Our results show increasing close collaboration among scientists from the United States, several European countries including United Kingdom, Italy, France, Netherland, Switzerland, China and Australia with scientists from other parts of the world.

In this study, we introduce a social networks enabled coordination model for exploring the effect of network position of ''patient,'' ''physician,'' and ''hospital'' actors in a patient-centered care network that evolves during patient hospitalization period on the total cost of coordination. An actor is a node, which represents an entity such as individual and organization in a social network. In our analysis of actor networks and coordination in the healthcare literature, we identified that there is significant gap where a number of promising hospital coordination model have been developed (e.g., Guided Care Model, Chronic Care Model) for the current healthcare system focusing on quality of service and patient satisfaction. The health insurance dataset for total hip replacement (THR) from hospital contribution fund, a prominent Australian Health Insurance Company, are analyzed to examine our proposed coordination model. We consider network attributes of degree, connectedness, in-degree, out-degree, and tie strength to measure network position of actors. To measure the cost of coordination for a particular hospital, average of total hospitalization expenses for all THR hospital admissions is used. Results show that network positions of ''patient,'' ''physician,'' and ''hospital'' actors considering all hospital admissions that a particular hospital has have effect on the average of total hospitalization expenses of that hospital. These results can be used as guidelines to set up a cost-effective healthcare practice structure for patient hospitalization expenses.

Effective provisioning of healthcare services during patient hospitalization requires collaboration involving a set of interdependent complex tasks, which needs to be carried out in a synergistic manner. Improved patients' outcome during and after hospitalization has been attributed to how effective different health services provisioning groups carry out their tasks in a coordinated manner. Previous studies have documented the underlying relationships between collaboration among physicians on the effective outcome in delivering health services for improved patient outcomes. However, there are very few systematic empirical studies with a focus on the effect of collaboration networks among healthcare professionals and patients' medical condition. On the basis of the fact that collaboration evolves among physicians when they visit a common hospitalized patient, in this study, we first propose an approach to map collaboration network among physicians from their visiting information to patients. We termed this network as physician collaboration network (PCN). Then, we use exponential random graph (ERG) models to explore the microlevel network structures of PCNs and their impact on hospitalization cost and hospital readmission rate. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks such as PCN. It simplifies a complex structure down to a combination of basic parameters such as 2-star, 3-star, and triangle. By applying our proposed mapping approach and ERG modeling technique to the electronic health insurance claims dataset of a very large Australian health insurance organization, we construct and model PCNs. We notice that the 2-star (subset of 3 nodes in which 1 node is connected to each of the other 2 nodes) parameter of ERG has significant impact on hospitalization cost. Further, we identify that triangle (subset of 3 nodes in which each node is connected to the rest 2 nodes), alternative k-star (subset of k nodes in which 1 node is connected to each of other k - 1 nodes), and alternative k - 2 path (subset of k nodes in which, between a specific pair of nodes, there exists k - 2 paths of length 2) parameters of ERG have impact on the hospital readmission rate. Our findings can have implications for healthcare administrators or managers who could potentially improve the practice cultures in their organizations by following these outcomes.

Coordination theory provides a theoretical framework for analysing complex processes of project groups working towards a common goal. In this study, we explore the relationship between coordination and social networks for the development of a network-based coordination model. This model is applied to measure the performance and quality of complex and dynamic project coordination such as in hospital emergency departments. The dataset used for the study was collected by the 2004 National Hospital Ambulatory Medical Care Survey-a national probability sample survey of visits to emergency and outpatient departments of non-Federal, short-stay and general hospitals in the United States. Using social network analysis, this study allows us to understand the possible causes of inefficient coordination performance and coordination quality resulting in access blocks. Language: en

Improving operations and delivery of cost-effective healthcare services is considered to be an important area of investigation due to the challenges in allocation of resources in meeting the increasing cost of health care for the twenty-first century. To date, appropriate mechanisms for systematic evaluation of hospital operations and its impact of the delivery of cost-effective healthcare services are lacking. This is, perhaps, the first study, which focuses on using large insurance claims data to develop a social network-based model for exploring the effect of patient-doctor tie strength and patient socio-demographic factors for exploring the social structure of operations and delivery of cost-effective healthcare services. We suggest that delivery of cost-effective healthcare services and operation is embedded within the social structure of hospitals. By exploring the mode of hospital operations in terms of their patient-centric care network, we are able to develop a better understanding of the operation and delivery of cost-effective healthcare services.

In this study, we explore whether there is correlation between the personal network and its impact on physical, mental and psychological health of aging population. Previous research on aging and health suggest the importance of individual family network and social network on different aspects of health assessments and outcomes. We examine the impact of family network and social network on physical, mental and psychological health of elderly men and women by using a cross-national sample (N = 4412) from four Eastern Mediterranean countries of Bahrain, Egypt, Jordan, and Tunisia. We analyse the dataset entitled World Health Organisation Collaborative Study on Social and Health Aspects of Aging in Bahrain, Egypt, Jordan, and Tunisia both at a macro and a micro level. Results show that there is a strong impact of family network and social network on individual physical, mental, and psychological health both at a macro and a micro level.

Background: Physician collaboration, which evolves among physicians during the course of providing healthcare services to hospitalised patients, has been seen crucial to effective patient outcomes in healthcare organisations and hospitals. This study aims to explore physician collaborations using measures of social network analysis (SNA) and exponential random graph (ERG) model. Methods. Based on the underlying assumption that collaborations evolve among physicians when they visit a common hospitalised patient, this study first proposes an approach to map collaboration network among physicians from the details of their visits to patients. This paper terms this network as physician collaboration network (PCN). Second, SNA measures of degree centralisation, betweenness centralisation and density are used to examine the impact of SNA measures on hospitalisation cost and readmission rate. As a control variable, the impact of patient age on the relation between network measures (i.e. degree centralisation, betweenness centralisation and density) and hospital outcome variables (i.e. hospitalisation cost and readmission rate) are also explored. Finally, ERG models are developed to identify micro-level structural properties of (i) high-cost versus low-cost PCN; and (ii) high-readmission rate versus low-readmission rate PCN. An electronic health insurance claim dataset of a very large Australian health insurance organisation is utilised to construct and explore PCN in this study. Results: It is revealed that the density of PCN is positively correlated with hospitalisation cost and readmission rate. In contrast, betweenness centralisation is found negatively correlated with hospitalisation cost and readmission rate. Degree centralisation shows a negative correlation with readmission rate, but does not show any correlation with hospitalisation cost. Patient age does not have any impact for the relation of SNA measures with hospitalisation cost and hospital readmission rate. The 2-star parameter of ERG model has significant impact on hospitalisation cost. Furthermore, it is found that alternative-k-star and alternative-k-two-path parameters of ERG model have impact on readmission rate. Conclusions: Collaboration structures among physicians affect hospitalisation cost and hospital readmission rate. The implications of the findings of this study in terms of their potentiality in developing guidelines to improve the performance of collaborative environments among healthcare professionals within healthcare organisations are discussed in this paper. © 2013 Uddin et al.; licensee BioMed Central Ltd., published_or_final_version