Assessing trends in breast care surveillance metrics after implementing surgeon-specific tracking and performance reporting in a large, integrated cancer network.

BACKGROUND: There are few quality metrics and benchmarks specific to surgical oncology. Development of a surgeon-level performance metrics system based on peer comparisons is hypothesized to positively influence surgical decision-making. This study established a tracking and reporting system comprised of evidence and consensus-based metrics to assess breast care delivered by individual surgeons. METHODS: Surgeons' performance is assessed by a surveillance tracking system of metrics pertaining to referrals and surgical elements. This retrospective analysis of prospectively collected breast care data reports on recurring 6-month and cumulative data from nine care locations from 2015 to 2021. RESULTS: Breast care was provided to 6659 patients by 41 surgeons. A total of 27 breast care metrics were evaluated over 7 years. Metrics with consistent, proficient results were retired after 18 months, including the rate of core biopsy, specimen orientation, and referrals to medical oncology, genetics, and fertility, among others. In clinically node-negative, hormone receptor-positive patients 70 years of age or older, the cumulative rate of sentinel lymph node (SLN) biopsy significantly decreased by 40% over 5.5 years (p < .001). The overall breast conservation rate for T0-T2 cancer increased 10% over 7 years. At the surgeon level, improvements were made in the median number of SLNs removed and in operative note documentation. CONCLUSIONS: Implementation of a surgeon-specific, peer comparison-based metric and tracking system has yielded substantive changes in breast care management. This process and governance structure can serve as a model for quantification of breast care at other institutions and for other disease sites.

Modeling COVID-19 Latent Prevalence to Assess a Public Health Intervention at a State and Regional Scale: Retrospective Cohort Study.

BACKGROUND: Emergence of the coronavirus disease (COVID-19) caught the world off guard and unprepared, initiating a global pandemic. In the absence of evidence, individual communities had to take timely action to reduce the rate of disease spread and avoid overburdening their health care systems. Although a few predictive models have been published to guide these decisions, most have not taken into account spatial differences and have included assumptions that do not match the local realities. Access to reliable information that is adapted to local context is critical for policy makers to make informed decisions during a rapidly evolving pandemic. OBJECTIVE: The goal of this study was to develop an adapted susceptible-infected-removed (SIR) model to predict the trajectory of the COVID-19 pandemic in North Carolina and the Charlotte Metropolitan Region, and to incorporate the effect of a public health intervention to reduce disease spread while accounting for unique regional features and imperfect detection. METHODS: Three SIR models were fit to infection prevalence data from North Carolina and the greater Charlotte Region and then rigorously compared. One of these models (SIR-int) accounted for a stay-at-home intervention and imperfect detection of COVID-19 cases. We computed longitudinal total estimates of the susceptible, infected, and removed compartments of both populations, along with other pandemic characteristics such as the basic reproduction number. RESULTS: Prior to March 26, disease spread was rapid at the pandemic onset with the Charlotte Region doubling time of 2.56 days (95% CI 2.11-3.25) and in North Carolina 2.94 days (95% CI 2.33-4.00). Subsequently, disease spread significantly slowed with doubling times increased in the Charlotte Region to 4.70 days (95% CI 3.77-6.22) and in North Carolina to 4.01 days (95% CI 3.43-4.83). Reflecting spatial differences, this deceleration favored the greater Charlotte Region compared to North Carolina as a whole. A comparison of the efficacy of intervention, defined as 1 - the hazard ratio of infection, gave 0.25 for North Carolina and 0.43 for the Charlotte Region. In addition, early in the pandemic, the initial basic SIR model had good fit to the data; however, as the pandemic and local conditions evolved, the SIR-int model emerged as the model with better fit. CONCLUSIONS: Using local data and continuous attention to model adaptation, our findings have enabled policy makers, public health officials, and health systems to proactively plan capacity and evaluate the impact of a public health intervention. Our SIR-int model for estimated latent prevalence was reasonably flexible, highly accurate, and demonstrated efficacy of a stay-at-home order at both the state and regional level. Our results highlight the importance of incorporating local context into pandemic forecast modeling, as well as the need to remain vigilant and informed by the data as we enter into a critical period of the outbreak.

Does Neoadjuvant Chemotherapy for Breast Cancer Affect Lymph Node Harvest Rates?

Some authors report that patients receiving neoadjuvant chemotherapy have fewer lymph nodes harvested during axillary dissection and more dissections with < 10 nodes compared with patients who undergo surgery initially. We sought to determine whether there was a difference between these patient groups in terms of number of nodes harvested and number of dissections with < 10 nodes. Retrospective review of 258 patients diagnosed with breast cancer who underwent an axillary lymph node dissection between July 1, 2015, and December 31, 2017 was performed. Chi-squared test was used to assess differences between patient groups. Of 258 patients undergoing dissection, 48 per cent received neoadjuvant chemotherapy; 52 per cent underwent surgery as first therapeutic intervention. Mean number of nodes resected; 14.3 + 6.3 for patients with no prior chemotherapy versus 14.9 + 6.6 for patients with neoadjuvant chemotherapy (P = 0.48). For patients undergoing surgery as first intervention, 21 per cent had < 10 nodes harvested. For patients receiving neoadjuvant chemotherapy, 20 per cent had < 10 nodes harvested. Patients who received neoadjuvant chemotherapy showed no statistically significant difference in the number of lymph nodes harvested during axillary dissection compared with patients undergoing surgery as first intervention. Neoadjuvant chemotherapy does not reduce the node harvest at the time of axillary dissection.