Social networks in health care teams: evidence from the United States

The effect of family physician team processes on chronic disease management performance from a structural network perspective

OBJECTIVE

The family physician team has become the core carrier for delivery primary health care in China. This study aimed to measure the effect of the network structural characteristics of family physician team processes on health performance. Strategic recommendations for optimizing the family physician team processes with a view to improving performance were presented.

METHODS

A cross-sectional survey was conducted from October to December 2021 in Qianjiang in Hubei Province and Changsha in Hunan Province. Task performance, contextual performance, social networks, and sociodemographic characteristics were collected. Social network analysis was conducted to calculate density and centralization, then hierarchical linear regression analysis was employed to explore the relationship between the network structural characteristics of family physician team processes and performance.

RESULTS

In total, 88 family physician teams attended in this investigation. The transition processes of family physician team showed a distinctive low density (0.272 ± 0.112), high centralization (0.866 ± 0.197) network structure. For family physician team, the density of action processes significantly and positively affected task performance (B = 0.600, P < 0.05); the centralization of action processes positively affected task performance (B = 0.604, P < 0.01); the density of action processes positively affected contextual performance (B = 0.545, P < 0.01); the density of interpersonal processes significantly and positively affected contextual performance (B = 0.326, P < 0.05).

CONCLUSION

The network density and centralization of family physician team processes have positive effects on chronic disease management performance. The results from this study help to enhance our conceptual understanding of social network and its implications for team-dynamics. Optimizing family physician team processes is an effective way to strengthen the construction of family physician team and promote the quality and efficiency of family physician-contracted service. It is recommended to strengthen the management of team processes, enhance the internal collaboration mechanism, and optimize the centralized network structure of family physician team.

Smoking and alcohol habits in head and neck cancers: How many patients stop after diagnosis?

BACKGROUND

Smoking and alcohol are the main risk factors for head and neck cancer. Despite the significant psychological impact, many patients continue to smoke and drink alcohol after diagnosis of cancer. This study aims to analyze the patients' behavior post diagnosis and treatment of head and neck cancer.

METHODS

An observational retrospective study was conducted on patients suffering from head and neck cancer. Their smoking and alcohol habits before and after diagnosis of cancer were studied.

RESULTS

A total of 85 patients were recruited: 80 % males, mean age 61.77±9.30 years. Among smokers, 35.80 % continued smoking post-diagnosis. A statistically significant correlation was found between smoking habit after diagnosis of cancer and type of treatment and tracheostomy. Among drinkers, 65.52 % continued to consume alcohol after diagnosis of cancer. A statistically significant correlation was found between alcohol consumption post-diagnosis and sex.

CONCLUSIONS

Patients undergoing more invasive treatments are more likely to quit smoking and/or drinking alcohol, suggesting the strong psychological impact of cancer and its therapy. Many patients continue smoking and consuming alcohol due to unawareness, depression, or addiction. However, most patients reduced cigarette smoking and alcohol consumption. Comprehensive care, including psychological support, is essential for these patients.

Analyzing mechanisms of interdisciplinary cooperation in promoting students' health at university

BACKGROUND

Interdisciplinary cooperation among university actors and resulting intersectoral synergies are considered cornerstones in the process of incorporating health promotion practices in everyday university life in order to break down barriers and provide better access to health promotion services. To date, no network of a health-promoting university has been examined regarding the processes underlying tie formation, network emergence, and maintenance.

OBJECTIVES AND METHODS

The goals of this study are to obtain insight into the mechanisms of cooperation between university actors in a health-promoting network and to identify the structural and attributive factors associated with establishing cooperation between actors in the observed network in order to better understand how to build and develop successful networks in the future. For this purpose, a social network analysis was carried out and exponential random graph models were estimated to test corresponding hypotheses.

RESULTS

The network at hand consists of 33 actors (e.g. University Sports Center, General Student Committee) and shows a flat, non-hierarchical structure. Data reveal that attributed competence predicts cooperation (0.32; p < 0.05). Significant homophily effects among student actors (1.31; p < 0.05) and among university actors (0.59; p < 0.05) were found. All structural predictors examined were significant (0.22-5.40; p < 0.05) and are therefore essential in determining the likelihood of cooperation between actors involved in the network.

CONCLUSION

The results of this study provide for a better understanding of the mechanisms of cooperation and can be used to further develop the network at hand (e.g. selection of key actors for information dissemination or integration of peripheral actors). In addition, the findings offer starting points for sustained network development at other universities (e.g. significance of network governance form or goal consensus). Knowing the factors that influence the network structure, here the conditions of cooperation, results in opportunities to encourage empowerment among actors. However, the analysis of the network undertaken does not directly bear on the success of the network.

Care delivery team composition effect on hospitalization risk in African Americans with congestive heart failure

The care delivery team (CDT) is critical to providing care access and equity to patients who are disproportionately impacted by congestive heart failure (CHF). However, the specific clinical roles that are associated with care outcomes are unknown. The objective of this study was to examine the extent to which specific clinical roles within CDTs were associated with care outcomes in African Americans (AA) with CHF. Deidentified electronic medical record data were collected on 5,962 patients, representing 80,921 care encounters with 3,284 clinicians between January 1, 2014 and December 31, 2021. Binomial logistic regression assessed associations of specific clinical roles and the Mann Whitney-U assessed racial differences in outcomes. AAs accounted for only 26% of the study population but generated 48% of total care encounters, the same percentage of care encounters generated by the largest racial group (i.e., Caucasian Americans; 69% of the study population). AAs had a significantly higher number of hospitalizations and readmissions than Caucasian Americans. However, AAs had a significantly higher number of days at home and significantly lower care charges than Caucasian Americans. Among all CHF patients, patients with a Registered Nurse on their CDT were less likely to have a hospitalization (i.e. 30%) and a high number of readmissions (i.e., 31%) during the 7-year study period. When stratified by heart failure phenotype, the most severe patients who had a Registered Nurse on their CDT were 88% less likely to have a hospitalization and 50% less likely to have a high number of readmissions. Similar decreases in the likelihood of hospitalization and readmission were also found in less severe cases of heart failure. Specific clinical roles are associated with CHF care outcomes. Consideration must be given to developing and testing the efficacy of more specialized, empirical models of CDT composition to reduce the disproportionate impact of CHF.

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.

The Ties That Bind: Camaraderie in Military Interprofessional Healthcare Teams

INTRODUCTION

Multiple aspects of interpersonal dynamics can help or hinder the success of teams, particularly those in a Military Interprofessional Healthcare Team (MIHT). One specific mechanism for MIHTs' success is camaraderie and how these military teams are able to achieve, maintain, and enable the development of this important characteristic. Despite our understanding of military service members as being bonded like a family, we have a limited understanding of how this bond is translated into their MIHT experiences.

MATERIALS AND METHODS

This study conducted interviews among 30 individuals who had participated in, led individual, and/or led many MIHTs, using a grounded theory methodology. Participants represented 11 different health professions, including officers and enlisted military members, and three branches of the U.S. military (e.g., army, navy, and air force). Data were collected and analyzed in iterative cycles until saturation was achieved.

RESULTS

We identified six themes that shaped the overarching concept of camaraderie in MIHTs. These themes were (1) confidence in competent peers, (2) shared goals, (3) mutual respect, (4) desire to help one another improve, (5) personal is professional, and (6) bonds of military service. This paper describes each of these themes, provides illustrative examples from the data, and describes how these components contribute to MIHTs' team dynamics. We present a model for how to understand these themes.

CONCLUSIONS

Through the identification and exploration of these aspects of camaraderie, we are able to better understand how MIHTs are able to be successful. MIHTs that demonstrated confidence in their brother/sister in arms possessed shared goals and missions, while maintaining mutual respect, a desire to help one another do better, and creating a personal and professional overlap tended to form stronger bonds of military service. Critically, these six aspects support a more nuanced understanding of the spirit of camaraderie and how it underpins MIHT success.

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.

An introduction to network analysis for studies of medication use

BACKGROUND

Network Analysis (NA) is a method that has been used in various disciplines such as Social sciences and Ecology for decades. So far, NA has not been used extensively in studies of medication use. Only a handful of papers have used NA in Drug Prescription Networks (DPN). We provide an introduction to NA terminology alongside a guide to creating and extracting results from the medication networks.

OBJECTIVE

To introduce the readers to NA as a tool to study medication use by demonstrating how to apply different NA measures on 3 generated medication networks.

METHODS

We used the Norwegian Prescription Database (NorPD) to create a network that describes the co-medication in elderly persons in Norway on January 1, 2013. We used the Norwegian Electronic Prescription Support System (FEST) to create another network of severe drug-drug interactions (DDIs). Lastly, we created a network combining the two networks to show the actual use of drugs with severe DDIs. We used these networks to elucidate how to apply and interpret different network measures in medication networks.

RESULTS

Interactive network graphs are made available online, Stata and R syntaxes are provided. Various useful network measures for medication networks were applied such as network topological features, modularity analysis and centrality measures. Edge lists data used to generate the networks are openly available for readers in an open data repository to explore and use.

CONCLUSION

We believe that NA can be a useful tool in medication use studies. We have provided information and hopefully inspiration for other researchers to use NA in their own projects. While network analyses are useful for exploring and discovering structures in medication use studies, it also has limitations. It can be challenging to interpret and it is not suitable for hypothesis testing.

Full agonist opioid prescribing by primary care clinicians after buprenorphine training

Background: While primary care clinicians are being trained to use buprenorphine for the treatment of Opioid Use Disorder (OUD) in order to increase access to addiction treatment, it is not known what impact such training and subsequent experience treating patients with OUD has on full agonist opioid prescribing. Methods: This retrospective cohort study compares the full agonist opioid prescribing patterns of Drug Addiction Treatment Act (DATA)-waivered ("X-waivered") primary care clinicians to non-trained, non-waivered clinicians in a rural health network. X-waivered clinicians also received Project ECHO training and telementoring support for one year. Using prescriber data generated by an electronic medical record system, opioid prescribing and morphine milligram equivalents (MME) per day per patient were calculated. A between-group analysis was used to compare the study groups six months pre-versus post-training. Results: Although the mean number of full agonist opioid prescriptions per clinician and per 100 patient encounters decreased among all clinicians, there was no change in full agonist opioid prescribing MME. As expected, buprenorphine prescribing by X-waivered, trained clinicians increased significantly post-training. Conclusions: X-waivers plus Project ECHO support for the treatment of OUD using buprenorphine had no effect on full agonist opioid prescribing by primary care clinicians.

Network analysis of medical care services

Medical care services can be organized into a network. Understanding the structure of this network cannot only help analyze common clinical protocols but can also help reveal previously unknown patterns of care. The objective of this research is to introduce the concept and methods for constructing and analyzing the network of medical care services. We start by demonstrating how to build the network itself and then develop algorithms, based on principal component analysis and social network analysis, to detect communities of services. Finally, we propose novel graphical techniques for representing and assessing patterns of care. We demonstrate the application of our algorithms using data from an Emergency Department in New York State. One of the implications of our research is that clinical experts could use our algorithms to detect deviations from either existing protocols of care or administrative norms.

Using Social Network Analysis to Investigate Positive EOL Communication

CONTEXT

End-of-life (EOL) communication is a complex process involving the whole family and multiple care providers. Applications of analysis techniques that account for communication beyond the patient and patient/provider will improve clinical understanding of EOL communication.

OBJECTIVES

The objectives of the study were to introduce the use of social network analysis to EOL communication data and to provide an example of applying social network analysis to home hospice interactions.

METHODS

We provide a description of social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e., magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver across gender and time were also examined.

RESULTS

Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or between nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined toward day of death but increased on day of actual patient death. There was a variation in reciprocity by the type of positive emotion expressed.

CONCLUSION

Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision making and health care teamwork.

How to improve healthcare? Identify, nurture and embed individuals and teams with "deep smarts"

Purpose Unlocking and transferring skills and capabilities in individuals to the teams they work within, and across, is the key to positive organisational development and improved patient care. Using the "deep smarts" model, the purpose of this paper is to examine these issues. Design/methodology/approach The "deep smarts" model is described, reviewed and proposed as a way of transferring knowledge and capabilities within healthcare organisations. Findings Effective healthcare delivery is achieved through, and continues to require, integrative care involving numerous, dispersed service providers. In the space of overlapping organisational boundaries, there is a need for "deep smarts" people who act as "boundary spanners". These are critical integrative, networking roles employing clinical, organisational and people skills across multiple settings. Research limitations/implications Studies evaluating the barriers and enablers to the application of the deep smarts model and 13 knowledge development strategies proposed are required. Such future research will empirically and contemporary ground our understanding of organisational development in modern complex healthcare settings. Practical implications An organisation with "deep smarts" people - in managerial, auxiliary and clinical positions - has a greater capacity for integration and achieving improved patient-centred care. Originality/value In total, 13 developmental strategies, to transfer individual capabilities into organisational capability, are proposed. These strategies are applicable to different contexts and challenges faced by individuals and teams in complex healthcare organisations.

Mapping a Careflow Network to assess the connectedness of Connected Health

Connected Health is an emerging and rapidly developing field which has the potential to transform healthcare service systems by increasing its safety, quality and overall efficiency. From a healthcare perspective, process improvement models have mainly focused on the static workflow viewpoint. The objective of this article is to study and model the dynamic nature of healthcare delivery, allowing us to identify where potential issues exist within the service system and to examine how Connected Health technological solutions may support service efficiencies. We explore the application of social network analysis (SNA) as a modelling technique which captures the dynamic nature of a healthcare service. We demonstrate how it can be used to map the 'Careflow Network' and guide Connected Health innovators to examine specific opportunities within the healthcare service. Our results indicate that healthcare technology must be correctly identified and implemented within the Careflow Network to enjoy improvements in service delivery. Oftentimes, prior to making the transformation to Connected Health, researchers use various modelling techniques that fail to identify where Connected Health innovation is best placed in a healthcare service network. Using SNA allows us to develop an understanding of the current operation of healthcare system within which they can effect change. It is important to identify and model the resource exchanges to ensure that the quality and safety of care are enhanced, efficiencies are increased and the overall healthcare service system is improved. We have shown that dynamic models allow us to study the exchange of resources. These are often intertwined within a socio-technical context in an informal manner and not accounted for in static models, yet capture a truer insight on the operations of a Careflow Network.