Health care provider social network analysis: A systematic review

Describing nurses' communication about evidence-based practice change: A social network analysis of hospital nurses

BACKGROUND

Nurses play a critical role in providing evidence-based, high-quality care to optimize patient outcomes. Models from implementation science suggest social networks may influence the adoption of evidence-based practices (EBPs). However, few studies have examined this relationship among hospital nurses. Social network analysis (SNA) mathematically evaluates patterns of communication, a critical step in implementation. Exploring hospital nurses' communication networks may provide insight into influences on the adoption of EBPs.

AIMS

This study aimed to describe complete communication networks of hospital nurses for practice changes on inpatient units, including upper level nursing administrators.

METHODS

This descriptive, exploratory, cross-sectional study used SNA on two inpatient units from one hospital. A sociometric survey was completed by nurses (unit to executive level) regarding communication frequency about practice changes. Network-level density, diameter, average path length, centralization, and arc reciprocity were measured. Attribute data were used to explore subnetworks.

RESULTS

Surveys from 148 nurses on two inpatient adult intensive care units (response rates 90% and 98%) revealed high communication frequency. Network measures were similar across the two units and among subnetworks. Analysis identified central (charge nurses and nurse leaders) and peripheral members of the network (new-to-practice nurses). Subnetworks aligned with the weekend and shift worked.

LINKING EVIDENCE TO ACTION

Established communication channels, including subnetworks and opinion leaders, should be used to maximize and optimize implementation strategies and facilitate the uptake of EBPs. Future work should employ SNA to measure the impact of communication networks on promoting the uptake of EBP and to improve patient outcomes.

Recommendations to Improve the Nature and Extent of Relationships Among Organizations Within a Network to Enhance Supports for Transgender Survivors of Sexual Assault

CONTEXT

To enhance the provision of comprehensive supports to transgender (trans) survivors of sexual assault, a structurally marginalized group with complex care needs, we developed an intersectoral network of trans-positive health care and community organizations in Ontario, Canada.

OBJECTIVE

As a baseline evaluation of the network, we conducted a social network analysis to determine the extent and nature of collaboration, communication, and connection among members.

DESIGN

Relational data (eg, activities of collaboration) were collected from June to July 2021, and analyzed using a validated survey tool, Program to Analyze, Record, and Track Networks to Enhance Relationships (PARTNER). We shared findings in a virtual consultation session with key stakeholders and facilitated discussion to generate action items. Consultation data were synthesized into 12 themes through conventional content analysis.

SETTING

An intersectoral network in Ontario, Canada.

PARTICIPANTS

Of the 119 representatives of trans-positive health care and community organizations invited to participate in this study, 78 (65.5%) completed the survey.

MAIN OUTCOME MEASURES

Proportion/count of organizations collaborating with other organizations. Network scores for value and trust.

RESULTS

Almost all (97.5%) invited organizations were listed as collaborators, representing 378 unique relationships. The network achieved a value score of 70.4% and trust score of 83.4%. The most prominent themes were "Communication and knowledge exchange channels," "Clearer roles and contributions," "Indicators of success," and "Client voices at the centre."

CONCLUSION

As key antecedents of network success, high value and trust indicate that network member organizations are well positioned to further foster knowledge sharing, define their roles and contributions, prioritize the integration of trans voices in all activities, and, ultimately, achieve common goals with clearly defined outcomes. There is great potential to optimize network functioning and advance the network's mission to improve services for trans survivors by mobilizing these findings into recommendations.

Greater patient sharing between hospitals is associated with better outcomes for transferred emergency general surgery patients

BACKGROUND

Access to emergency surgical care has declined as the rural workforce has decreased. Interhospital transfers of patients are increasingly necessary, and care coordination across settings is critical to quality care. We characterize the role of repeated hospital patient sharing in outcomes of transfers for emergency general surgery (EGS) patients.

METHODS

A multicenter study of Wisconsin inpatient acute care hospital stays that involved transfer of EGS patients using data from the Wisconsin Hospital Association, a statewide hospital discharge census for 2016 to 2018. We hypothesized that higher proportion of patients transferred between hospitals would result in better outcomes. We examined the association between the proportion of EGS patients transferred between hospitals and patient outcomes, including in-hospital morbidity, mortality, and length of stay. Additional variables included hospital organizational characteristics and patient sociodemographic and clinical characteristics.

RESULTS

One hundred eighteen hospitals transferred 3,197 emergency general surgery patients over the 2-year study period; 1,131 experienced in-hospital morbidity, mortality, or extended length of stay (>75th percentile). Patients were 62 years old on average, 50% were female, and 5% were non-White. In the mixed-effects model, hospitals' proportion of patients shared was associated with lower odds of an in-hospital complication; specifically, when the proportion of patients shared between two hospitals doubled, the relative odds of any outcome changed by 0.85.

CONCLUSION

Our results suggest the importance of emergent relationships between hospital dyads that share patients in quality outcomes. Transfer protocols should account for established efficiencies, familiarity, and coordination between hospitals.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.

Network approaches and interventions in healthcare settings: A systematic scoping review

INTRODUCTION

The growing interest in networks of interactions is sustained by the conviction that they can be leveraged to improve the quality and efficiency of healthcare delivery systems. Evidence in support of this conviction, however, is mostly based on descriptive studies. Systematic evaluation of the outcomes of network interventions in healthcare settings is still wanting. Despite the proliferation of studies based on Social Network Analysis (SNA) tools and techniques, we still know little about how intervention programs aimed at altering existing patterns of social interaction among healthcare providers affect the quality of service delivery. We update and extend prior reviews by providing a comprehensive assessment of available evidence.

METHODS AND FINDINGS

We searched eight databases to identify papers using SNA in healthcare settings published between 1st January 2010 and 1st May 2022. We followed Chambers et al.'s (2012) approach, using a Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. We distinguished between studies relying on SNA as part of an intervention program, and studies using SNA for descriptive purposes only. We further distinguished studies recommending a possible SNA-based intervention. We restricted our focus on SNA performed on networks among healthcare professionals (e.g., doctors, nurses, etc.) in any healthcare setting (e.g., hospitals, primary care, etc.). Our final review included 102 papers. The majority of the papers used SNA for descriptive purposes only. Only four studies adopted SNA as an intervention tool, and measured outcome variables.

CONCLUSIONS

We found little evidence for SNA-based intervention programs in healthcare settings. We discuss the reasons and challenges, and identify the main component elements of a network intervention plan. Future research should seek to evaluate the long-term role of SNA in changing practices, policies and behaviors, and provide evidence of how these changes affect patients and the quality of service delivery.

Information exchange networks for chronic diseases in primary care practices in Germany: a cross-sectional study

Background

Coordination of care requires information exchange between health workers. The structure of their information exchange networks may influence the quality and efficiency of healthcare delivery. The aim of this study was to explore and classify information exchange networks in primary care for patients with chronic diseases in Germany.

Methods

A cross-sectional study was carried out between 2019 and 2021. As part of a larger project on coordination of care, this study focused on information exchange in practice teams regarding patients with type 2 diabetes (DM), coronary heart disease (CHD) and chronic heart failure (CHF). Social network analysis was applied to determine the number of connections, density and centralization for each of the health conditions for each of the practices. On the basis of the descriptive findings, we developed typologies of information exchange networks in primary care practices.

Results

We included 153 health workers from 40 practices, of which 25 practices were included in the social network analysis. Four types of information exchange structures were identified for the three chronic diseases: highly connected networks with low hierarchy, medium connected networks with medium hierarchy, medium connected networks with low hierarchy and lowly connected networks. Highly connected networks with low hierarchy were identified most frequently (18 networks for DM, 17 for CHD and 14 for CHF). Of the three chronic conditions, information sharing about patients with DM involved the most team members. Information exchange outside the family practice took place mainly with nurses and pharmacists.

Conclusions

This study identified four types of information exchange structures, which provides a practical tool for management and improvement in primary care. Some practices had few information transfer connections and could hardly be considered a network.

Trial registration

We registered the study prospectively on 7 November 2019 at the German Clinical Trials Register (DRKS, www.drks.de) under ID no. DRKS00019219.

An observational study of health care provider collaboration networks and heterogenous hospital cost efficiency and quality outcomes

Provider network structure has been linked to hospital cost, utilization, and to a lesser degree quality, outcomes; however, it remains unknown whether these relationships are heterogeneous across different acute care hospital characteristics and US states. The objective of this study is to evaluate whether there are heterogeneous relationships between hospital provider network structure and hospital outcomes (cost efficiency and quality); and to assess the sources of measured heterogeneous effects. We use recent causal random forest techniques to estimate (hospital specific) heterogeneous treatment effects between hospitals' provider network structures and their performance (across cost efficiency and quality). Using Medicare cost report, hospital quality and provider patient sharing data, we study a population of 3061 acute care hospitals in 2016. Our results show that provider networks are significantly associated with costs efficiency (P < .001 for 7/8 network measures), patient rating of their care (P < .1 in 5/8 network measures), heart failure readmissions (P < .01 for 3/8 network measures), and mortality rates (P < .02 in 5/8 cases). We find that fragmented provider structures are associated with higher costs efficiency and patient satisfaction, but also with higher heart failure readmission and mortality rates. These effects are further found to vary systematically with hospital characteristics such as capacity, case mix, ownership, and teaching status. This study used an observational design. In summary, we find that hospital treatment responses to different network structures vary systematically with hospital characteristics..

Rethinking Healthcare Teams’ Practices Using Network Science: Implications, Challenges, and Benefits

Healthcare teams act in a very complex environment and present extremely peculiar features since they are multidisciplinary, work under quickly changing conditions, and often stay together for a short period with a dynamically fluctuating team membership. Thus, in the broad discussions about the future of healthcare, the strategy for improving providers’ collaboration and team dynamics is becoming a central topic. Within this context, this paper aims to discuss different viewpoints about the application of network science to teamworking. Our results highlight the potential benefits deriving from network science-enabled analysis, and also show some preliminary empirical evidence through a real case study. In so doing, we intend to stimulate discussions regarding the implications of network science in the investigation and improvement of healthcare teams. The intention is to pave the way for future research in this context by suggesting the potential advantages of healthcare teamwork analysis, as well as recognising its challenges and threats.

The use of social network analysis in social support and care: a systematic scoping review protocol

BACKGROUND

In recent decades, the literature on Social Network Analysis and health has experienced a significant increase. Disease transmission, health behavior, organizational networks, social capital, and social support are among the different health areas where Social Network Analysis has been applied. The current epidemiological trend is characterized by a progressive increase in the population's ageing and the incidence of long-term conditions. Thus, it seems relevant to highlight the importance of social support and care systems to guarantee the coverage of health and social needs within the context of acute illness, chronic disease, and disability for patients and their carers. Thus, the main aim is to identify, categorize, summarize, synthesize, and map existing knowledge, literature, and evidence about the use of Social Network Analysis to study social support and care in the context of illness and disability.

METHODS

This scoping review will be conducted following Arksey and O'Malley's framework with adaptations from Levac et al. and Joanna Briggs Institute's methodological guidance for conducting scoping reviews. We will search the following databases (from January 2000 onwards): PubMed, MEDLINE, Web of Science Core Collection, SCOPUS, CINAHL, PsycINFO, Cochrane Database of Systematic Reviews, PROSPERO, and DARE. Complementary searches will be conducted in selected relevant journals. Only articles related to social support or care in patients or caregivers in the context of acute illnesses, disabilities or long-term conditions will be considered eligible for inclusion. Two reviewers will screen all the citations, full-text articles, and abstract the data independently. A narrative synthesis will be provided with information presented in the main text and tables.

DISCUSSION

The knowledge about the scientific evidence available in the literature, the methodological characteristics of the studies identified based on Social Network Analysis, and its main contributions will highlight the importance of health-related research's social and relational dimensions. These results will shed light on the importance of the structure and composition of social networks to provide social support and care and their impact on other health outcomes. It is anticipated that results may guide future research on network-based interventions that might be considered drivers to provide further knowledge in social support and care from a relational approach at the individual and community levels.

TRIAL REGISTRATION

Open Science Framework https://osf.io/dqkb5 .

Review of social networks of professionals in healthcare settings-where are we and what else is needed?

Background

Social Network Analysis (SNA) demonstrates great potential in exploring health professional relationships and improving care delivery, but there is no comprehensive overview of its utilization in healthcare settings. This review aims to provide an overview of the current state of knowledge regarding the use of SNA in understanding health professional relationships in different countries.

Methods

We conducted an umbrella review by searching eight academic databases and grey literature up to April 30, 2021, enhanced by citation searches. We completed study selection, data extraction and quality assessment using predetermined criteria. The information abstracted from the reviews was synthesized quantitatively, qualitatively and narratively.

Results

Thirteen reviews were included in this review, yielding 330 empirical studies. The degree of overlaps of empirical studies across included reviews was low (4.3 %), indicating a high diversity of included reviews and the necessity of this umbrella review. Evidence from low- and middle-income countries (LMIC), particularly Asian countries, was limited. The earliest review was published in 2010 and the latest in 2019. Six reviews focused on the construction or description of professional networks and seven reviews reported factors or influences of professional networks. We synthesized existing literature on social networks of health care professionals in the light of (i) theoretical frameworks, (ii) study design and data collection, (iii) network nodes, measures and analysis, and (iv) factors of professional networks and related outcomes. From the perspective of methodology, evidence lies mainly in cross-sectional study design and electronic data, especially administrative data showing “patient-sharing” relationships, which has become the dominant data collection method. The results about the impact of health professional networks on health-related consequences were often contradicting and not truly comparable.

Conclusions

Methodological limitations, inconsistent findings, and lack of evidence from LMIC imply an urgent need for further investigations. The potential for broader utilization of SNA among providers remains largely untapped and the findings of this review may contain important value for building optimal healthcare delivery networks.

PROSPERO registration number

The protocol was published and registered with PROSPERO, the International Prospective Register of Systematic Reviews (CRD42020205996).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-021-00772-7.

Characteristics and Network Influence of Providers Involved in the Treatment of Patients With Chronic Back, Neck or Joint Pain in Arkansas

Increasing emphasis on guidelines and prescription drug monitoring programs highlight the role of healthcare providers in pain treatment. Objectives of this study were to identify characteristics of key players and influence of opioid prescribers through construction of a referral network of patients with chronic pain. A retrospective cohort study was performed and patients with commercial or Medicaid coverage with chronic back, neck, or joint pain were identified using the Arkansas All-Payer Claims-Database. A social network comprised of providers connected by patient referrals based on 12-months of healthcare utilization following chronic pain was constructed. Network measures evaluated were indegree and eigen (referrals obtained), betweenness (involvement), and closeness centrality (reach). Outcomes included influence of providers, opioid prescribers, and brokerage status. Exposures included provider demographics, specialties and network characteristics. There were 51,941 chronic pain patients who visited 8,110 healthcare providers. Primary care providers showed higher betweenness and closeness whereas specialists had higher indegree. Opioid providers showed higher centrality compared to non-opioid providers, which decreased with increasing volume of opioid prescribing. Non-pharmacologic providers showed significant brokerage scores. Findings from this study such as primary care providers having better reach, non-central positions of high-volume prescribers and non-pharmacologic providers having higher brokerage can aid interventional physician detailing. PERSPECTIVE: Opioid providers held central positions in the network aiding provider-directed interventions. However, high-volume opioid providers were at the borders making them difficult targets for interventions. Primary care providers had the highest reach, specialists received the most referrals and non-pharmacological providers and specialists acted as brokers between non-opioid and opioid prescribers.

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.

Promoting Students' Health at University: Key Stakeholders, Cooperation, and Network Development

Background: Cooperation among university units is considered a cornerstone for the promotion of students' health. The underlying mechanisms of health-promoting networks at universities have rarely been examined so far. Shedding light on partnerships is generally limited to the naming of allied actors in a network.

Objectives and Methods: In this study, we used network analysis intending to visualize and describe the positions and characteristics of the network actors, and examine organizational relationships to determine the characteristics of the complete network.

Results: The network analysis at hand provides in-depth insights into university structures promoting students' health comprising 33 organizational units and hundreds of ties. Both cooperation and communication network show a flat, non-hierarchical structure, which is reflected by its low centralization indices (39–43%) and short average distances (1.43–1.47) with low standard deviations (0.499–0.507), small diameter (3), and the non-existence of subgroups. Density lies between 0.53 and 0.57. According to the respondents, the University Sports Center is considered the most important actor in the context of students' health. Presidium and Institute of Sport and Sports Science play an integral role in terms of network functionality.

Conclusion: In the health-promoting network, numerous opportunities for further integration and interaction of actors exist. Indications for transferring results to other universities are discussed. Network analysis enables universities to profoundly analyze their health-promoting structures, which is the basis for sustained network governance and development.

Analyzing Medical Guideline Dissemination Behaviors Using Culturally Infused Agent Based Modeling Framework

Clinical practice guidelines are a critical medium for the standardization of practices within the overall medical community. However, several studies have shown that, in general, there is a significant delay in the adoption of recommendations in such guidelines. Surveys have identified multiple barriers, including clinical inertia, organizational culture/incentives, access to information and peer influence on guideline dissemination and adoption. Although modeling techniques, especially agent-based models, have shown promise, a rigorous computational model for guideline dissemination that incorporates the intricacies of medical decision making and interactions of healthcare workers, and can identify more effective dissemination strategies, is needed. Similar modeling and simulation issues are also prevalent in many other domains such as opinion diffusion, innovation, and technology adoption. In this paper, we introduce a novel overarching computational modeling and simulation framework called the Culturally Infused Agent Based Modeling (CI-ABM) Framework. CI-ABM is a generalizable framework that provides the capability to model a wide range of real-world complex scenarios. To validate the framework, we focus on modeling and analyzing the dissemination of a Type 2 diabetes guideline that recommends individualizing glycemic (A1C) goals. Using existing cross-sectional surveys from physicians across the US, we demonstrate how our methodology for incorporating various socio-cultural and other related factors in agent based models lead to better posterior probability-based analysis and prediction of guideline dissemination behaviors.

Information access and sharing among prosthetics and orthotics faculty in Ghana and the United States

BACKGROUND

Information access is essential for quality healthcare provision and education. Despite technological advances, access to prosthetics and orthotics information in low- and middle-income countries is not ubiquitous. The current state of information access, availability, and exchange among prosthetics and orthotics faculty is unknown.

OBJECTIVES

Describe information exchange networks and access at two prosthetics and orthotics programs in Ghana and the United States.

STUDY DESIGN

Cross-sectional survey, social network analysis.

METHODS

An online survey of faculty at two prosthetics and orthotics programs using REDCap. The survey included a social network analysis, demographics, and prosthetics and orthotics information resources and frequency of use. Descriptive statistics were calculated.

RESULTS

Twenty-one faculty members completed the survey (84% response). Ghanaian faculty were on average younger (median Ghana: 27 years, United States: 43 years), had less teaching experience, and had less education than US faculty. Textbooks were the most commonly used resource at both programs. The Ghanaian network had more internal connections with few outside sources. The US network had fewer internal connections, relied heavily upon four key players, and had numerous outside contacts.

CONCLUSION

Ghana and US faculty have two distinct information exchange networks. These networks identify key players and barriers to dissemination among faculty to promote successful knowledge translation of current scientific literature and technology development. Social network analysis may be a useful method to explore information sharing among prosthetics and orthotics faculty, and identify areas for further study.

A network analysis of patient referrals in two district health systems in Tanzania

Patient referral systems are fragile and overlooked components of the health system in Tanzania. Our study aims at exploring patient referral networks in two rural districts in Tanzania, Kilolo and Msalala. Firstly, we ask whether secondary-level facilities act as gatekeepers, mediating referrals from primary- to tertiary-level facilities. Secondly, we explore the facility and network-level determinants of patient referrals focusing on treatment of childhood illnesses and non-communicable diseases. We use data collected across all public health facilities in the districts in 2018. To study gatekeeping, we employ descriptive network analysis tools. To explore the determinants of referrals, we use exponential random graph models. In Kilolo, we find a disproportionate share of patients referred directly to the largest hospital due to geographical proximity. In Msalala, small and specialized secondary-level facilities seem to attract more patients. Overall, the results call for policies to increase referrals to secondary facilities avoiding expensive referrals to hospitals, improving timeliness of care and reducing travel-related financial burden for households.

Using an Agent-based Model to Examine Deimplementation of Breast Cancer Screening

OBJECTIVE

The objective of this study was to examine the potential impact of provider social networks and experiences with patients on deimplementation of breast cancer screening.

RESEARCH DESIGN

We constructed the Breast Cancer-Social network Agent-based Model (BC-SAM), which depicts breast cancer screening decisions, incidence, and progression among 10,000 women ages 40 and over and the screening recommendations of their providers over a 30-year period. The model has patient and provider modules that each incorporate social network influences. Patients and providers were connected in a network, which represented patient-patient peer connections, provider-provider peer connections, connections between providers and patients they treat, and friend/family relationships between patients and providers. We calibrated provider decisions in the model using data from the CanSNET national survey of primary care physicians in the United States, which we fielded in 2016.

RESULTS

First, assuming that providers' screening recommendations for women ages 50-74 remain unchanged but their recommendations for screening among younger (below 50 y old) and older (75+ y old) women decrease, we observed a decline in predicted screening rates for women ages 50-74 due to spillover effects. Second, screening rates for younger and older women were slow to respond to changes in provider recommendations; a 78% decline in provider recommendations to older women over 30 years resulted in an estimated 23% decline in patient screening in that group. Third, providers' experiences with unscreened patients, friends, and family members modestly increased screening recommendations over time (7 percentage points). Finally, we found that provider peer effects can have a substantial impact on population screening rates and can entrench existing practices.

CONCLUSION

Modeling cancer screening as a complex social system demonstrates a range of potential effects and may help target future interventions designed to reduce overscreening.

The impact of The Florence Network in advancing nursing and midwifery in Europe

Diversity of the nursing workforce and multiculturalism of European cities have mandated the need for culturally sensitive nurses and midwives able to provide effective, engaging, high quality and socially just healthcare. The Florence Network is a professional network that aims to bring together like-minded professionals and to cultivate relationships amongst nurses and midwives from different European Union (EU) countries to create synergies on matters of common interest by transcending national and cultural barriers. A qualitative study based upon a focus group interview was conducted with six former Presidents and one present President of the Florence Network, each with a tenure of two years. The study explored the impact of the Florence Network in advancing cultural awareness and promoting educational, research and professional synergies. The outcome of the study identified that from the Presidents perspectives networks create awareness of cultural diversity, enable the delivery of multicultural nursing care and develop future leaders regarding global health-related issues. Furthermore, professional networks contribute to the refining of educational curricula, in developing applicable research evidence, and in sharing formal and informal professional knowledge.

Health coalition collaboration network, perceived satisfaction and success

PURPOSE

The health equity and prosperity of communities is closely linked to the effectiveness and success of local health coalitions. Social network analysis (SNA) is one mechanism to quantify and understand the factors leading to collaboration and effectiveness within these coalitions. This study aims to investigate network characteristics associated with perceived success and satisfaction in a health coalition and determine significant factors related to organizational collaborations.

DESIGN/METHODOLOGY/APPROACH

This study examined the Olympic Peninsula Healthy Community Coalition (OPHCC) which aims to prevent chronic disease in rural Clallam County, Washington. Representatives (n = 21) from member organizations (n = 18) were asked to report on organization characteristics, perceived satisfaction in coalition activities, perceived success toward coalition's mission, and collaborations with other organizations in the coalition. Multilevel modeling used to analyze whether an organization's position within the coalition network was associated with their perceived satisfaction and perceived success. Exponential random graph modeling was used to examine what factors may impact collaboration ties between coalition members.

FINDINGS

Organization representatives reported a total of 252 collaboration ties. In multilevel models, organization characteristics and network centrality scores accounted for between 61 and 68% of variance displayed in satisfaction scores and 45-61% of variance in perceived success scores. Exponential random graph modeling revealed activity level, for-profit status, and transitivity as significant factors in collaborative tie presence.

ORIGINALITY/VALUE

Encouraging consistent active participation, a balance of organizational type, and projects which require more than two collaborators may provide an environment for collaborative ties between organizations.

Exploring the structure of social media application-based information-sharing clinical networks in a community in Japan using a social network analysis approach

OBJECTIVE

Currently, use of social networking services (SNSs) for interprofessional collaboration is increasing. However, few studies have reported on virtual interprofessional interactions in community healthcare services. Revealing such structural characteristics of the networks can provide insight into the functions of the interprofessional information-sharing network and lead to smoother collaboration. Thus, we aimed to explore the structure of SNS-based information-sharing clinical networks.

DESIGN

Social network analysis (SNA).

SETTING

We selected a community in City X in Japan.

DATA COLLECTION

We analysed SNS-based information-sharing clinical network data linked to patients receiving home medical care or care services between January and December 2018. A network was created for each patient to allow healthcare professionals to post and view messages on the web platform. In the SNA, healthcare professions registered in a patient group were represented as nodes, and message posting/viewing relationships were represented as links in the patient network. We investigated the structural characteristics of the target networks using several measures for SNA, including indegree centrality and outdegree centrality, which reflect the number of incoming and outgoing links to/from a node, respectively. Additionally, the professions forming the most central nodes were investigated based on their ranking to identify those with a central role in the networks. Finally, to compare the networks of nursing care levels 1-3 (lighter care requirement) and those with nursing care levels 4-5 (heavier care requirement), we analysed the structural differences in the networks and investigated the roles of healthcare professionals using centrality measures of nodes.

RESULTS

Among 844 groups, 247 groups with any nursing care level data were available for analysis. Increasing nursing care level showed higher density, reciprocity and lower centralisation. Healthcare professions with high indegree centrality (physicians, care workers and physical therapists) differed from those with high outdegree centrality (home care workers, physical therapists, and registered dieticians). Visiting nurses and nurses in the clinic played a central role, but visiting nurses tended to have higher indegree and outdegree centrality, while nurses in the clinic had higher closeness and betweenness centrality in networks with heavier care requirement.

CONCLUSION

The SNS-based information-sharing clinical network structure showed that different professions played some form of a central role. Associations between network structures and patient outcomes, cost effectiveness and other factors warrant further investigation.

The association between patient sharing network structure and healthcare costs

STUDY QUESTION

While physician relationships (measured through shared patients) are associated with clinical and utilization outcomes, the extent to which this is driven by local or global network characteristics is not well established. The objective of this research is to examine the association between local and global network statistics with total medical spending and utilization.

DATA SOURCE

Data used are the 2011 Massachusetts All Payer Claims Database.

STUDY DESIGN

The association between network statistics and total medical spending and utilization (using standardized prices) is estimated using multivariate regression analysis controlling for patient demographics and health status.

DATA COLLECTION

We limit the sample to continuously enrolled commercially insured patients in Massachusetts in 2011.

PRINCIPAL FINDINGS

Mean patient age was 45 years, and 56.3% of patients were female. 73.4% were covered by a health maintenance organization. Average number of visits was 5.43, with average total medical spending of $4,911 and total medical utilization of $4,252. Spending was lower for patients treated by physicians with higher degree (p<0.001), eigenvector centrality (p<0.001), clustering coefficient (p<0.001), and measures reflecting the normalized degree (p<0.001) and eigenvector centrality (p<0.001) of specialists connected to a patient's PCP. Spending was higher for patients treated by physicians with higher normalized degree, which accounts for physician specialty and patient panel size (p<0.001). Results were similar for utilization outcomes, although magnitudes differed indicating patients may see different priced physicians.

CONCLUSIONS

Generally, higher values of network statistics reflecting local connectivity adjusted for physician characteristics are associated with increased costs and utilization, while higher values of network statistics reflecting global connectivity are associated with decreased costs and utilization. As changes in the financing and delivery system advance through policy changes and healthcare consolidation, future research should examine mechanisms through which this structure impacts outcomes and potential policy responses to determine ways to reduce costs while maintaining quality and coordination of care.

WHAT THIS STUDY ADDS

It is unknown whether local and global measures of physician network connectivity associated with spending and utilization for commercially insured patients?In this social network analysis, we found generally higher values of network statistics reflecting local connectivity are associated with increased costs and utilization, while higher values of network statistics reflecting global connectivity are associated with decreased costs and utilization.Understanding how to influence local and global physician network characteristics may be important for reducing costs while maintaining quality.

Professional advice for primary healthcare workers in Ethiopia: a social network analysis

BACKGROUND

In an era of increasingly competitive funding, governments and donors will be looking for creative ways to extend and maximise resources. One such means can include building upon professional advice networks to more efficiently introduce, scale up, or change programmes and healthcare provider practices. This cross-sectional, mixed-methods, observational study compared professional advice networks of healthcare workers in eight primary healthcare units across four regions of Ethiopia. Primary healthcare units include a health centre and typically five satellite health posts.

METHODS

One hundred sixty staff at eight primary healthcare units were interviewed using a structured tool. Quantitative data captured the frequency of healthcare worker advice seeking and giving on providing antenatal, childbirth, postnatal and newborn care. Network and actor-level metrics were calculated including density (ratio of ties between actors to all possible ties), centrality (number of ties incident to an actor), distance (average number of steps between actors) and size (number of actors within the network). Following quantitative network analyses, 20 qualitative interviews were conducted with network study participants from four primary healthcare units. Qualitative interviews aimed to interpret and explain network properties observed. Data were entered, analysed or visualised using Excel 6.0, UCINET 6.0, Netdraw, Adobe InDesign and MaxQDA10 software packages.

RESULTS

The following average network level metrics were observed: density .26 (SD.11), degree centrality .45 (SD.08), distance 1.94 (SD.26), number of ties 95.63 (SD 35.46), size of network 20.25 (SD 3.65). Advice networks for antenatal or maternity care were more utilised than advice networks for post-natal or newborn care. Advice networks were typically limited to primary healthcare unit staff, but not necessarily to supervisors. In seeking advice, a colleague's level of training and knowledge were valued over experience. Advice exchange primarily took place in person or over the phone rather than over email or online fora. There were few barriers to seeking advice.

CONCLUSION

Informal, inter-and intra-cadre advice networks existed. Fellow primary healthcare unit staff were preferred, particularly midwives, but networks were not limited to the primary healthcare unit. Additional research is needed to associate network properties with outcomes and pilot network interventions with central actors.

Exploring the Stability of Communication Network Metrics in a Dynamic Nursing Context

Network stability is of increasing interest to researchers as they try to understand the dynamic processes by which social networks form and evolve. Because hospital patient care units (PCUs) need flexibility to adapt to environmental changes (Vardaman, Cornell, & Clancy, 2012), their networks are unlikely to be uniformly stable and will evolve over time. This study aimed to identify a metric (or set of metrics) sufficiently stable to apply to PCU staff information sharing and advice seeking communication networks over time. Using Coefficient of Variation, we assessed both Across Time Stability (ATS) and Global Stability over four data collection times (Baseline and 1, 4, and 7 months later). When metrics were stable using both methods, we considered them "super stable." Nine metrics met that criterion (Node Set Size, Average Distance, Clustering Coefficient, Density, Weighted Density, Diffusion, Total Degree Centrality, Betweenness Centrality, and Eigenvector Centrality). Unstable metrics included Hierarchy, Fragmentation, Isolate Count, and Clique Count. We also examined the effect of staff members' confidence in the information obtained from other staff members. When confidence was high, the "super stable" metrics remained "super stable," but when low, none of the "super stable" metrics persisted as "super stable." Our results suggest that nursing units represent what Barker (1968) termed dynamic behavior settings in which, as is typical, multiple nursing staff must constantly adjust to various circumstances, primarily through communication (e.g., discussing patient care or requesting advice on providing patient care), to preserve the functional integrity (i.e., ability to meet patient care goals) of the units, thus producing the observed stability over time of nine network metrics. The observed metric stability provides support for using network analysis to study communication patterns in dynamic behavior settings such as PCUs.

Satisfaction with Social Support Received from Social Relationships in Cases of Chronic Pain: The Influence of Personal Network Characteristics in Terms of Structure, Composition and Functional Content

The worldwide burden of chronic illnesses, constitutes a major public health concern and a serious challenge for health systems. In addition to the strategies of self-management support developed by nursing and health organizations, an individual’s personal network represents a major resource of social support in the long-term. Adopting a cross-sectional design based on personal network analysis methods, the main aim of this study is to explore the relationship between satisfaction with the social support received by individuals suffering chronic pain and the structure, composition, and functional content in social support of their personal networks. We collected personal and support network data from 30 people with chronic pain (20 person’s contacts (alters) for each individual (ego), 600 relationships in total). Additionally, we examined the level of satisfaction with social support in each of the 600 relationships. Bivariate and multivariate tests were performed to analyze the satisfaction with the social support received. Using cluster analysis, we established a typology of the 600 relationships under study. Results showed that higher satisfaction was associated with a balance between degree centrality and betweenness (i.e., measures of network cohesion and network modularity, respectively). Finally, new lines of research are proposed in order to broaden our understanding of this subject.

Analyzing Nursing Leadership at an Academic Historical Event: A Descriptive Study Based on Social Networks

PURPOSE

To analyze the leadership network structure among nursing leaders in Spain identified through the Grupo40Enfermeras y Universidad event.

METHODS

A descriptive cross-sectional study using social network analysis was used. Study sample consisted of 210 individuals, of whom 119 received nominations as referents. Structural analysis of the network was conducted using centrality and cohesion.

RESULTS

A network structure was generated in which different leadership strategies were identified through InDegree, Eigenvector, and Betweenness Centrality. Five leaders were identified as bridges to other individuals using Betweenness. The whole network presented little cohesion although two highly cohesive cores were detected by K-core measurements.

CONCLUSION

A strategy is needed to support nursing leaders with high degree of Betweenness to serve as bridges to connect other nursing leaders.

Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary Syndrome Patients Using Data-Driven Network Analysis

Healthcare systems are challenged to deliver high-quality and efficient care. Studying patient flow in a hospital is particularly fundamental as it demonstrates effectiveness and efficiency of a hospital. Since hospital is a collection of physically nearby services under one administration, its performance and outcome are shaped by the interaction of its discrete components. Coordination of processes at different levels of organizational structure of a hospital can be studied using network analysis. Hence, this article presents a data-driven static and temporal network of departments. Both networks are directed and weighted and constructed using seven years’ (2010–2016) empirical data of 24902 Acute Coronary Syndrome (ACS) patients. The ties reflect an episode-based transfer of ACS patients from department to department in a hospital. The weight represents the number of patients transferred among departments. As a result, the underlying structure of network of departments that deliver healthcare for ACS patients is described, the main departments and their role in the diagnosis and treatment process of ACS patients are identified, the role of departments over seven years is analyzed and communities of departments are discovered. The results of this study may help hospital administration to effectively organize and manage the coordination of departments based on their significance, strategic positioning and role in the diagnosis and treatment process which, in-turn, nurtures value-based and precision healthcare.

Receipt of Promotional Payments at the Individual and Physician Network Level Associated with Higher Branded Antipsychotic Prescribing Rates

Pharmaceutical promotion can lead to market size expansion, which is beneficial if previously untreated patients access treatment but deleterious if it leads to overuse, an area of concern for second generation antipsychotics (SGA). We contribute to a growing body of work suggesting that networks of social and professional relationships shape prescribing behavior. We examined 88,439 Medicare Part D prescribing physicians, finding that promotion is associated with SGA market size expansion (elasticity: 0.062) and that network-level promotional activity is associated with network members' branded product prescribing. Research on the effects of promotion should account for its effects in prescribers' networks.

Data-driven modeling of diabetes care teams using social network analysis

OBJECTIVE

We assess working relationships and collaborations within and between diabetes health care provider teams using social network analysis and a multi-scale community detection.

MATERIALS AND METHODS

Retrospective analysis of claims data from a large employer over 2 years was performed. The study cohort contained 827 patients diagnosed with diabetes. The cohort received care from 2567 and 2541 health care providers in the first and second year, respectively. Social network analysis was used to identify networks of health care providers involved in the care of patients with diabetes. A multi-scale community detection was applied to the network to identify groups of health care providers more densely connected. Social network analysis metrics identified influential providers for the overall network and for each community of providers.

RESULTS

Centrality measures identified medical laboratories and mail-order pharmacies as the central providers for the 2 years. Seventy-six percent of the detected communities included primary care physicians, and 97% of the communities included specialists. Pharmacists were detected as central providers in 24% of the communities.

DISCUSSION

Social network analysis measures identified the central providers in the network of diabetes health care providers. These providers could be considered as influencers in the network that could enhance the implication of promotion programs through their access to a large number of patients and providers.

CONCLUSION

The proposed framework provides multi-scale metrics for assessing care team relationships. These metrics can be used by implementation experts to identify influential providers for care interventions and by health service researchers to determine impact of team relationships on patient outcomes.

Social Network Analysis of Dementia Wards in Psychiatric Hospitals to Explore the Advancement of Personhood in Patients with Alzheimer's Disease

Background:

Little is known on investigating how healthcare teams in dementia wards act for promoting personhood in persons with Alzheimer’s disease (PWA).

Objective:

The current research aimed to identify the social networks of dementia health carers promoting the personhood of PWA in acute or long-term dementia wards in public and private psychiatric hospitals.

Methods:

We used a mixed-method research approach. Ethnographic observations and two-mode Social Network Analysis (SNA) captured the role and social networks of healthcare professionals promoting PWA personhood, using SocNetv version 2.4. The social network graphs illustrated how professionals participated in PWA care by computing the degree of centrality (%DC) for each professional; higher values indicated more statistical significance of a professional role compared to others in the provision of personhood care. The categories of personhood were biological, individual, and sociologic. Nurses, doctors, ward managers, hospital managers, clinical psychologists, occupational therapists, care coordinators, physiotherapists, healthcare assistants, and family members were observed if they were promoting PWA personhood.

Results:

The highest %DC in SNA in biological personhood was held by the ward nurses (36%), followed by the ward doctors (20%) and ward managers (20%). All professional roles were involved in 16% of cases in the promotion of individual personhood, while the hospital managers had the highest %DC (33%) followed by the ward managers and nurses (27%) in the sociologic personhood.

Conclusion:

All professional roles were deemed to promote PWA personhood in dementia wards, although some limitation exists according to the context of the assessment.

Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data

OBJECTIVES

The study sought to identify collaborative electronic health record (EHR) usage patterns for pediatric trauma patients and determine how the usage patterns are related to patient outcomes.

MATERIALS AND METHODS

A process mining-based network analysis was applied to EHR metadata and trauma registry data for a cohort of pediatric trauma patients with minor injuries at a Level I pediatric trauma center. The EHR metadata were processed into an event log that was segmented based on gaps in the temporal continuity of events. A usage pattern was constructed for each encounter by creating edges among functional roles that were captured within the same event log segment. These patterns were classified into groups using graph kernel and unsupervised spectral clustering methods. Demographics, clinical and network characteristics, and emergency department (ED) length of stay (LOS) of the groups were compared.

RESULTS

Three distinct usage patterns that differed by network density were discovered: fully connected (clique), partially connected, and disconnected (isolated). Compared with the fully connected pattern, encounters with the partially connected pattern had an adjusted median ED LOS that was significantly longer (242.6 [95% confidence interval, 236.9-246.0] minutes vs 295.2 [95% confidence, 289.2-297.8] minutes), more frequently seen among day shift and weekday arrivals, and involved otolaryngology, ophthalmology services, and child life specialists.

DISCUSSION

The clique-like usage pattern was associated with decreased ED LOS for the study cohort, suggesting greater degree of collaboration resulted in shorter stay.

CONCLUSIONS

Further investigation to understand and address causal factors can lead to improvement in multidisciplinary collaboration.

How the study of networks informs knowledge translation and implementation: a scoping review

Background

To date, implementation science has focused largely on identifying the individual and organizational barriers, processes, and outcomes of knowledge translation (KT) (including implementation efforts). Social network analysis (SNA) has the potential to augment our understanding of KT success by applying a network lens that examines the influence of relationships and social structures on research use and intervention acceptability by health professionals. The purpose of this review was to comprehensively map the ways in which SNA methodologies have been applied to the study of KT with respect to health professional networks.

Methods

Systematic scoping review methodology involved searching five academic databases for primary research on KT that employed quantitative SNA methods, and inclusion screening using predetermined criteria. Data extraction included information on study aim, population, variables, network properties, theory use, and data collection methods. Descriptive statistics and chronology charting preceded theoretical analysis of findings.

Results

Twenty-seven retained articles describing 19 cross-sectional and 2 longitudinal studies reported on 28 structural properties, with degree centrality, tie characteristics (e.g., homophily, reciprocity), and whole network density being most frequent. Eleven studies examined physician-only networks, 9 focused on interprofessional networks, and 1 reported on a nurse practitioner network. Diffusion of innovation, social contagion, and social influence theories were most commonly applied.

Conclusions

Emerging interest in SNA for KT- and implementation-related research is evident. The included articles focused on individual level evidence-based decision-making: we recommend also applying SNA to meso- or macro-level KT activities. SNA research that expands the range of professions under study, examines network dynamics over time, extends the depth of analysis of the role of network structure on KT processes and outcomes, and employs mixed methods to triangulate findings, is needed to advance the field. SNA is a valuable approach for evaluating key network characteristics, structures and positions of relevance to KT, implementation, and evidence informed practice. Examining how network structure influences connections and the implications of those holding prominent network positions can provide insights to improve network-based KT processes.

Team Collaboration Networks and Multidisciplinarity in Diabetes Care: Implications for Patient Outcomes

Prevalence of type 2 diabetes mellitus (T2DM) has almost doubled in recent decades and commonly presents comorbidities and complications. T2DM is a multisystemic disease, requiring multidisciplinary treatment provided by teams working in a coordinated and collaborative manner. The application of social network analysis techniques in the healthcare domain has allowed researchers to analyze interaction between professionals and their roles inside care teams. We studied whether the structure of care teams, modeled as complex social networks, is associated with patient progression. For this, we illustrate a data-driven methodology and use existing social network analysis metrics and metrics proposed for this research. We analyzed appointment and HbA1c blood test result data from patients treated at three primary health care centers, representing six different practices. Patients with good metabolic control during the analyzed period were treated by teams that were more interactive, collaborative and multidisciplinary, whereas patients with worsening or unstable metabolic control were treated by teams with less collaboration and more continuity breakdowns. Results from the proposed metrics were consistent with the previous literature and reveal relevant aspects of collaboration and multidisciplinarity.

A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies

Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships. This is usually done by completing a questionnaire containing different types of questions that will be later used to obtain the SNA measures needed to perform the study. There are, then, a great number of different possible network-generating questions and also many possibilities for mapping the responses to the corresponding characteristics and relationships. Many variations may be introduced into these questions (the way they are posed, the weights given to each of the responses, etc.) that may have an effect on the resulting networks. All these different variations are difficult to achieve manually, because the process is time-consuming and error-prone. The tool described in this paper uses semantic knowledge representation techniques in order to facilitate this kind of sensitivity studies. The base of the tool is a conceptual structure, called “ontology” that is able to represent the different concepts and their definitions. The tool is compared to other similar ones, and the advantages of the approach are highlighted, giving some particular examples from an ongoing SNA study about alcohol consumption habits in adolescents.

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.

Do learning collaboratives strengthen communication? A comparison of organizational team communication networks over time

BACKGROUND

Collaborative learning models were designed to support quality improvements, such as innovation implementation by promoting communication within organizational teams. Yet the effect of collaborative learning approaches on organizational team communication during implementation is untested.

PURPOSE

The aim of this study was to explore change in communication patterns within teams from children's mental health organizations during a year-long learning collaborative focused on implementing a new treatment. We adopt a social network perspective to examine intraorganizational communication within each team and assess change in (a) the frequency of communication among team members, (b) communication across organizational hierarchies, and (c) the overall structure of team communication networks.

METHODOLOGY/APPROACH

A pretest-posttest design compared communication among 135 participants from 21 organizational teams at the start and end of a learning collaborative. At both time points, participants were asked to list the members of their team and rate the frequency of communication with each along a 7-point Likert scale. Several individual, pair-wise, and team level communication network metrics were calculated and compared over time.

FINDINGS

At the individual level, participants reported communicating with more team members by the end of the learning collaborative. Cross-hierarchical communication did not change. At the team level, these changes manifested differently depending on team size. In large teams, communication frequency increased, and networks grew denser and slightly less centralized. In small teams, communication frequency declined, growing more sparse and centralized.

PRACTICE IMPLICATIONS

Results suggest that team communication patterns change minimally but evolve differently depending on size. Learning collaboratives may be more helpful for enhancing communication among larger teams; thus, managers might consider selecting and sending larger staff teams to learning collaboratives. This study highlights key future research directions that can disentangle the relationship between learning collaboratives and team networks.

A scoping review of patient-sharing network studies using administrative data

There is a robust literature examining social networks and health, which draws on the network traditions in sociology and statistics. However, the application of social network approaches to understand the organization of health care is less well understood. The objective of this work was to examine approaches to conceptualizing, measuring, and analyzing provider patient-sharing networks. These networks are constructed using administrative data in which pairs of physicians are considered connected if they both deliver care to the same patient. A scoping review of English language peer-reviewed articles in PubMed and Embase was conducted from inception to June 2017. Two reviewers evaluated article eligibility based upon inclusion criteria and abstracted relevant data into a database. The literature search identified 10,855 titles, of which 63 full-text articles were examined. Nine additional papers identified by reviewing article references and authors were examined. Of the 49 papers that met criteria for study inclusion, 39 used a cross-sectional study design, 6 used a cohort design, and 4 were longitudinal. We found that studies most commonly theorized that networks reflected aspects of collaboration or coordination. Less commonly, studies drew on the strength of weak ties or diffusion of innovation frameworks. A total of 180 social network measures were used to describe the networks of individual providers, provider pairs and triads, the network as a whole, and patients. The literature on patient-sharing relationships between providers is marked by a diversity of measures and approaches. We highlight key considerations in network identification including the definition of network ties, setting geographic boundaries, and identifying clusters of providers, and discuss gaps for future study.

The Importance of External Contacts in Job Performance: A Study in Healthcare Organizations Using Social Network Analysis

There is evidence that relations between physicians and nurses within healthcare institutions might be shaped by informal aspects of such relations and by links to people external to the organization, with an impact on work performance. Social network analysis is underutilized in exploring such associations. The paper aims to describe physicians’ and nurses’ relationships outside their clinical units and to explore what kind of ties are related to job performance. A network analysis was performed on cross-sectional data. The study population consisted of 196 healthcare employees working in a public hospital and a primary healthcare centre in Spain. Relational data were analysed using the UCINET software package. Measures included: (i) sample characteristics; (ii) social network variables; and (iii) team performance ratings. Descriptive statistics (means, medians, percentages) were used to characterize staff and performance ratings. A correlational analysis was conducted to examine the strength of relationships between four different types of ties. Our findings suggest that external ties only contribute to improving the performance of physicians at both the individual and team level. They are focused on the decision-making process about the therapeutic plan and, therefore, might need to seek advice outside the workplace. In contrast, external ties are not relevant for the work performance of nurses, as they need to find solutions to immediate problems in a short period of time, having strong ties in the workplace. Social network analysis can illuminate relations within healthcare organizations and inform the development of innovative interventions.

Applications of network analysis to routinely collected health care data: a systematic review

Objective

To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research.

Materials and Methods

A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis.

Results

The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities.

Discussion

We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.

Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review

BACKGROUND

Social network analysis quantifies and visualizes relationships between and among individuals or organizations. Applications in the health sector remain underutilized. This systematic review seeks to analyze what social network methods have been used to study professional communication and performance among healthcare providers.

METHODS

Ten databases were searched from 1990 through April 2016, yielding 5970 articles screened for inclusion by two independent reviewers who extracted data and critically appraised each study. Inclusion criteria were study of health care worker professional communication, network methods used, and patient outcomes measured. The search identified 10 systematic reviews. The final set of articles had their citations prospectively and retrospectively screened. We used narrative synthesis to summarize the findings.

RESULTS

The six articles meeting our inclusion criteria described unique health sectors: one at primary healthcare level and five at tertiary level; five conducted in the USA, one in Australia. Four studies looked at multidisciplinary healthcare workers, while two focused on nurses. Two studies used mixed methods, four quantitative methods only, and one involved an experimental design. Four administered network surveys, one coded observations, and one used an existing survey to extract network data. Density and centrality were the most common network metrics although one study did not calculate any network properties and only visualized the network. Four studies involved tests of significance, and two used modeling methods. Social network analysis software preferences were evenly split between ORA and UCINET. All articles meeting our criteria were published in the past 5 years, suggesting that this remains in clinical care a nascent but emergent research area. There was marked diversity across all six studies in terms of research questions, health sector area, patient outcomes, and network analysis methods.

CONCLUSION

Network methods are underutilized for the purposes of understanding professional communication and performance among healthcare providers. The paucity of articles meeting our search criteria, lack of studies in middle- and low-income contexts, limited number in non-tertiary settings, and few longitudinal, experimental designs, or network interventions present clear research gaps.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42015019328.

Medicine information exchange networks among healthcare professionals and prescribing in geriatric medicine wards

AIMS

Effective transfer of information is vital for rational drug therapy. This is particularly important for older patients, who have a high prevalence of polypharmacy and are managed by multidisciplinary teams. We aimed to assess medicine information exchange (MIE) networks in geriatric medicine wards and whether they are associated with prescribing patterns.

METHODS

We conducted network analysis in acute geriatric medicine wards from four hospitals to characterize MIE networks among multidisciplinary team members. Corresponding patient data were collected to analyze high-risk prescribing in conjunction with network characteristics.

RESULTS

We found that junior doctors, senior nurses and pharmacists were central to MIE across all four hospitals. Doctors were more likely than other professions to receive medicines information in three hospitals. Reciprocity and the tendency to communicate within one's own profession also influenced network formation. No difference was observed in prescribing practice between hospitals.

CONCLUSIONS

Understanding MIE networks can identify gaps in multidisciplinary communication that can be addressed. Networks may identify targets for dissemination of interventions to improve prescribing.

Information exchange networks of health care providers and evidence-based cardiovascular risk management: an observational study

BACKGROUND

Although a wide range of preventive and clinical interventions has targeted cardiovascular risk management (CVRM), outcomes remain suboptimal. Therefore, the question is what additional determinants of CVRM and outcomes can be identified and addressed to optimize CVRM. In this study, we aimed to identify new perspectives for improving healthcare delivery and explored associations between information exchange networks of health care providers and evidence-based CVRM.

METHODS

This observational study was performed parallel to a randomized clinical trial which aimed to improve professional performance of practice nurses in the Netherlands. Information exchange on medical policy for CVRM ("general information networks") and CVRM for individual patients ("specific information networks") of 180 health professionals in 31 general practices was measured with personalized questionnaires. Medical record audit was performed concerning 1620 patients in these practices to document quality of care delivery and two risk factors (systolic blood pressure (SBP) and LDL cholesterol level). Hypothesized effects of five network characteristics (density, frequency of contact, centrality of CVRM-coordinators, homophily on positive attitudes for treatment target achievement, and presence of an opinion leader for CVRM) constructed on both general and specific information exchange networks were tested and controlled for practice and patient factors using logistic multilevel analyses.

RESULTS

Odds for adequate performance were enhanced in practices with an opinion leader for CVRM (OR 2.75, p < .05). Odds for achievement of SBP targets were reduced in practices who had networks with low homophily on positive attitudes for SBP and LDL targets (homophily for SBP targets OR 0.57, p < .05 and OR 0.60, p < .05, homophily for LDL targets OR 0.59, p < .05 and OR 0.61, p < .05 in general and specific information networks, respectively). No effects of network characteristics on cholesterol were found.

CONCLUSIONS

Delivery of evidence-based CVRM is associated with homophily of clinical attitudes and presence of opinion leaders in primary care teams. These results signal the potential of social networks to be taken into account in further attempts to improve the implementation of evidence-based care for CVRM. Future research is needed to identify and formulate optimal strategies for using opinion leaders to improve CVRM. Future interventions may be more effective if they target a common vision on CVRM within practices.