Correlates of Between-Surgeon Variation in Breast Cancer Treatments

Bibliographic Data

ID9100657
AuthorsSarah T Hawley (0000-0001-5756-645X, Michigan Medicine, corresponding author), Timothy P Hofer (0000-0003-0434-8787, VA Ann Arbor Healthcare System, corresponding author), Tim P Hofer, Nancy K Janz, Angela Fagerlin (0000-0002-9192-2777, VA Ann Arbor Healthcare System, corresponding author), Karen Schwartz (0000-0003-0219-9036, The Barbara Ann Karmanos Cancer Institute), Kendra Schwartz, Lihua Liu (0000-0003-2252-8407, University of Southern California), Dennis Deapen (0000-0002-0037-0277, University of Southern California), Monica Morrow (0000-0003-4636-8313, University of Michigan, corresponding author), Steven J Katz (0000-0002-1151-861X, VA Ann Arbor Healthcare System, corresponding author)
Year2006
Volume44
Issue7
Pages609-616
Publication date2006-07-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/01.mlr.0000215893.01968.f1
PMID16799355
OpenAlexW2162752535
LanguageEN
Citations received5
References cited36

BACKGROUND: Determinants of between-surgeon variation in breast cancer treatment utilization are not well understood. OBJECTIVES: The objectives of this study were to evaluate variation in receipt of surgical treatment (ie, mastectomy or breast-conserving surgery with or without radiation) for women with stage I, II, or III breast cancer and receipt of breast reconstruction attributable to surgeons, and to assess factors associated with this between-surgeon variation. METHODS: We surveyed all attending surgeons (n = 456) of a population-based sample of patients with breast cancer diagnosed in Detroit and Los Angeles during 2002 (n = 1844). Our analytic dataset linked data from 1477 patients with that of 311 surgeons. We used random-effects modeling to account for the multilevel dataset and evaluated 2 outcomes: 1) primary surgical treatment (mastectomy vs. BCS); and 2) receipt of reconstruction before being surveyed (yes vs. no). Independent variables included patient-related factors (clinical and demographic), surgeon-related factors (breast procedure volume, practice setting, and demographics), surgeon treatment recommendation, and referral propensity. RESULTS: Surgeons explain some variation in use of both mastectomy and reconstruction (9.9% and 26%, respectively). Patient clinical factors and surgeon volume together explain approximately one-third of the between-surgeon variation in mastectomy. Patient factors and surgeon demographics explain approximately 60% of between-surgeon variation in reconstruction, and surgeon referral propensity explains an additional 15%. CONCLUSION: Our findings suggest that similar patients may get different treatment depending on their surgeon. Broader dissemination of guidelines coupled with increasing patient access to consultations before definitive surgery may reduce between-surgeon variation. Contributing factors such as patient-physician communication should be explored

Breast cancer · Breast reconstruction · Breast-conserving surgery · Cancer · Demographics · Family medicine · General surgery · Mastectomy · Population · Receipt · Referral · Breast Cancer Treatment Studies · Breast Implant and Reconstruction · Demography · Global Cancer Incidence and Screening · Internal Medicine · Medicine · Surgery

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