Physician social networks and variation in outcomes for traditionally fatal cancers Open Access

Nguyen, Hannah (2017)

Permanent URL: https://etd.library.emory.edu/concern/etds/rb68xc65x?locale=en
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Abstract

This study aims to explore the relationship between physician social networks and the odds of survival from liver, stomach and pancreatic cancer. Little information is known about why some patients diagnosed with these deadliest cancers survive longer than expected, especially with respect to provider-specific factors. In this study, we constructed physician social networks based on their shared cancer patients using SEER-Medicare data from 2004 to 2010. Network clusters, comprised of providers who are more densely connected with one another, were identified from the network. We then examined whether the network clusters' structure and characteristics were associated with variation in survival outcome and the odds of long-term survival using linear mixed effects and generalized linear mixed effects models, controlling for patients' age, sex, race, comorbidity, tumor stage, geographic region and median household income. Only the network for pancreatic cancer exhibited significant network cluster structure, hence further analyses on the relationship with survival were limited to pancreatic cancer. There were 3133 physicians (medical oncologists, radiation oncologists and surgeons) and 25 large network clusters (with 20 or more patients per cluster) in this network. Significant variation in survival outcome across the network clusters was identified (Mixture test, test statistic = 11.10, p = 0.002). Patients whose providers belonged to the large clusters (with 20 or more patients per cluster) had significantly higher odds of 1-year survival compared to the small clusters (OR = 1.34, 95% CI 1.15-1.56, p <0.001). Among the 25 large network clusters, there was no significant difference in survival outcome of the patients. This study, although largely exploratory in nature, showed that survival outcomes were superior for patients involved in the large compared to small network clusters.

Table of Contents

Table of Contents Page number

I. Background 1

II. Manuscript 8

A. Title, Authors, Abstract 8

B. Introduction 8

C. Methods 12

D. Results 17

E. Discussion 20

F. References 24

G. Tables 28

H. Figures/Figure Legends 31

III. Summary, Public Health Implication, Possible Future Directions ¦ 33

IV. Appendices 34

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