Open AccessSurgeon peer network characteristics and adoption of new imaging techniques in breast cancer: A study of perioperative MRI
Author(s) -
Tannenbaum Sara S.,
Soulos Pamela R.,
Herrin Jeph,
Pollack Craig E.,
Xu Xiao,
Christakis Nicholas A.,
Forman Howard P.,
Yu James B.,
Killelea Brigid K.,
Wang ShiYi,
Gross Cary P.
Publication year - 2018
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.1821
Subject(s) - medicine , breast cancer , breast mri , perioperative , cohort , epidemiology , magnetic resonance imaging , cancer , radiology , surgery , mammography
Background Perioperative MRI has disseminated into breast cancer practice despite equivocal evidence. We used a novel social network approach to assess the relationship between the characteristics of surgeons’ patient‐sharing networks and subsequent use of MRI. Methods We identified a cohort of female patients with stage 0‐III breast cancer from the Surveillance, Epidemiology, and End Results (SEER)‐Medicare database. We used claims data from these patients and non‐cancer patients from the 5% Medicare sample to identify peer groups of physicians who shared patients during 2004‐2006 (T1). We used a multivariable hierarchical model to identify peer group characteristics associated with uptake of MRI in T2 (2007‐2009) by surgeons who had not used MRI in T1. Results Our T1 sample included 15 149 patients with breast cancer, treated by 2439 surgeons in 390 physician groups. During T1, 9.1% of patients received an MRI; the use of MRI varied from 0% to 100% (IQR 0%, 8.5%) across peer groups. After adjusting for clinical characteristics, patients treated by surgeons in groups with a higher proportion of primary care physicians (PCPs) in T1 were less likely to receive MRI in T2 (OR = 0.81 for 10% increase in PCPs, 95% CI = 0.71, 0.93). Surgeon transitivity (ie, clustering of surgeons) was significantly associated with MRI receipt ( P = 0.013); patients whose surgeons were in groups with higher transitivity in T1 were more likely to receive MRI in T2 (OR = 1.29 for 10% increase in clustering, 95% CI = 1.06, 1.58). Conclusion The characteristics of a surgeon's peer network are associated with their patients’ subsequent receipt of perioperative MRI.