Social Network Analysis as a Method of Assessing Institutional Culture: Three Case Studies

Lurie, Stephen J.; Fogg, Thomas T.; Dozier, Ann

doi:10.1097/acm.0b013e3181ad16d3

Cited by 41 publications

(30 citation statements)

References 12 publications

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“…In conclusion, this novel compendium of methods for network construction and applications of network methodology has the potential to yield insights about latent phenomena, such as organizational traits of hospitals and structural importance of physicians, for which we do not have direct observations (Lurie et al 2009). This approach holds promise in identifying new aspects of regional differences in health care delivery and diffusion of appropriate (or inappropriate) application of new technologies and health care practices.…”

Section: Discussionmentioning

confidence: 99%

An analysis of patient-sharing physician networks and implantable cardioverter defibrillator therapy

Moen

Austin

Bynum

et al. 2016

Health Serv Outcomes Res Method

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The application of social network analysis to the organization of healthcare delivery is a relatively new area of research that may not be familiar to health services statisticians and other methodologists. We present a methodological introduction to social network analysis with a case study of physicians’ adherence to clinical guidelines regarding use of implantable cardioverter defibrillators (ICDs) for the prevention of sudden cardiac death. We focus on two hospital referral regions (HRRs) in Indiana, Gary and South Bend, characterized by different rates of evidence-based ICD use (86% and 66%, respectively). Using Medicare Part B claims, we construct a network of physicians who care for cardiovascular disease patients based on patient-sharing relationships. Approaches for weighting physician dyads and aggregating physician dyads by hospital are discussed. Then, we obtain a set of weighted network statistics for the positions of hospitals in their referral region, global statistics for the physician network within each hospital, and of the network positions of individual physicians within hospitals, providing the mathematical specification and sociological intuition underlying each measure. We find that adjusting for network measures can reduce the observed differences between referral regions for evidence-based ICD therapy. This study supports previous reports on how variation in physician network structure relates to utilization of care, and motivates future work using physician network measures to examine variation in evidence-based medicine.

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Section: Discussionmentioning

confidence: 99%

An analysis of patient-sharing physician networks and implantable cardioverter defibrillator therapy

Moen

Austin

Bynum

et al. 2016

Health Serv Outcomes Res Method

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“…A few of the stakeholders include physicians, nurses, laboratory technicians, physician's office staff, hospital admitting, and researchers [45]. It was found that physicians carry the deciding vote on utilizing EMR systems, due to their dominance in health care and status within the medical community [34,49]. Therefore, this paper focuses on physicians as the key stakeholders due to their power to influence the utilization of EMR systems within the health care system.…”

Section: Introductionmentioning

confidence: 98%

Understanding continuance intentions of physicians with electronic medical records (EMR): An expectancy-confirmation perspective

Ayanso

Herath

O'Brien

2015

Decision Support Systems

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“…Social network constructs have been applied to individuals in populations to better understand the spread of behaviors, ideas, 4–10 and diseases4,11–13 and their control measures 4,12,7. However, to our knowledge our study is the first to apply social network frameworks and measures to hospitals to understand how hospitals within a county are interconnected by patient sharing.…”

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confidence: 99%

Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California

et al. 2011

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Objectives. We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. Methods. Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with intervening nonhospital stays). We considered these networks at 3 thresholds of patient sharing: at least 1, at least 10, and at least 100 patients shared. Results. Geographically proximate hospitals were somewhat more likely to share patients, but many hospitals shared patients with distant hospitals. Number of patient admissions and percentage of cancer patients were associated with greater connectivity across the system. The TPS network revealed numerous connections not seen in the UPS network, meaning that direct transfers only accounted for a fraction of total patient sharing. Conclusions. Our analysis demonstrated that Orange County's 32 hospitals were highly and heterogeneously interconnected by patient sharing. Different hospital populations had different levels of influence over the patient-sharing network.

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Social Network Analysis as a Method of Assessing Institutional Culture: Three Case Studies

Cited by 41 publications

References 12 publications

An analysis of patient-sharing physician networks and implantable cardioverter defibrillator therapy

An analysis of patient-sharing physician networks and implantable cardioverter defibrillator therapy

Understanding continuance intentions of physicians with electronic medical records (EMR): An expectancy-confirmation perspective

Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California

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