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Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+
Linden Head1, Carolyn Nessim1, Kirsty Usher Boyd1
1From the Faculty of Medicine, University of Ottawa, Ottawa, Ont. (Head); the Division of General Surgery, Department of Surgery, University of Ottawa, Ottawa, Ont. (Nessim); and the Division of Plastic Surgery, Department of Surgery, University of Ottawa, Ottawa, Ont. (Usher Boyd).
Background:
Bilateral prophylactic mastectomy (BPM) has demonstrated breast cancer risk reduction in high-risk/BRCA+ patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency.
Methods:
We retrospectively reviewed the cases of all high-risk/BRCA+ patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1-2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/BRCA+ status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared.
Results:
There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model (p = 0.003, p < 0.001 and p = 0.015, respectively).
Conclusion:
A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization.
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