Critical evaluation of factors contributing to time to mastectomy within a single health care system

Jenna C Bekeny1, Kyle Luvisa1, Peter Wirth1

  • 1Department of Plastic and Reconstructive Surgery, MedStar Georgetown University Hospital, Washington, District of Columbia.

The Breast Journal
|July 14, 2020
PubMed

Increased time to mastectomy (TTM) has significant implications for mortality, well-being, and satisfaction. However, certain populations are subject to disparities that increase TTM. This study examines vulnerable populations and the patient-, disease-, provider-, and system-level factors related to treatment delays. Patients undergoing mastectomy for breast cancer from 2014 to 2018 across 8 hospitals in a single health care system were retrospectively reviewed. Demographics, disease characteristics, and provider- and system-level information were collected. Time from biopsy-proven diagnosis to mastectomy was calculated. Univariate analysis identified variables for inclusion in the multivariable model. One thousand, three hundred thirty patients met inclusion. Median TTM was 55.0 days. Factors from all levels-patient, disease, provider, and systemic-were significantly related to disparities. African-American patients had 11.6% longer TTM compared to white patients (69.0 vs 56.0 days, P < .0001). TTM was 15.5% longer for low-income patients when compared to high-income patients (65.0 vs 49.0 days, P = .0014). Preoperative plastic surgery visits led to 19.3% longer TTM (P = .0012); oncologic appointments for neo-adjuvant chemotherapy led to a 231.0% increase (P < .0001). Average time from last neo-adjuvant treatment to mastectomy was 44.4 days (SD 26.5); average TTM from diagnosis for patients not receiving neo-adjuvant chemotherapy was 58.5 days (SD 13.3). Patients with Medicaid waited 14.5% longer compared to patients with commercial insurance (94.0 vs 62.0 days, P = .0005). In our review of care across a large health care system, we identified multiple levels contributing to disparities in TTM. Identification of these disparities offers valuable insight into process improvement and intervention.

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