Background And Objectives: A summary indicator for evaluating the breast cancer network has never been measured at the regional level. The aim is to design treemaps providing a summary description of hospitals (including breast units) and Local Health Units (LHUs) in terms of their levels of performance within the breast cancer network of the Lazio region (central Italy). The treemap structure has an intuitive design and displays information from both general and specific analyses.

Methods: Patients admitted to the regional hospitals for malignant breast cancer (MBC) surgery in 2010-2017 were selected in a population-based cohort study. These quality indicators were calculated based on the international guidelines (EUSOMA, ESMO) to assess the performance in terms of volume of activity, surgery procedure, post-surgery assistance and timeliness of medical therapy or radiotherapy beginning. The quality indicators were calculated using administrative health data systematically collected at the regional level and were included in the treemap to represent the surgery or the post-surgery areas of the breast cancer clinical pathway. In order to allow aggregation of scores for different indicators belonging to the same clinical area, up to five evaluation classes were defined using the "Jenks Natural Breaks" algorithm. A score and a colour were assigned to each clinical area based on the ranking of the indicators involved. The analyses were performed on an annual basis, by the LHU of residence and by the hospital which performed the surgical intervention.

Results: In 2017, 6218 surgical interventions for MBC were performed in the hospitals of Lazio. The results showed a continuous increase of the level of performance over the years. Hospitals showed higher variability in the levels of performance than the LHUs. 36% of the evaluated hospitals reached a high level of performance. An audit of the S. Filippo Neri breast unit revealed incorrect coding of the input data. For this reason, the score for the indicator for the volume of wards was re-calculated and re-evaluated, with a subsequent improvement of the level of performance. Most LHUs achieved at least an average overall level of performance, with 20% of the LHUs reaching a high level of performance.

Conclusions: This is the first attempt to apply the treemap logic to a single clinical network, in order to obtain a summary indicator for the evaluation of the breast cancer care network. Our results supply decision makers with a transparent instrument of governance for heterogeneous users, directing efforts improving and promoting equity of care. The treemaps could be reproduced and adapted for other local contexts, in order to limit inappropriateness and ensure uniform levels of breast cancer care within local areas. The next step is the evaluation of audit and feedback interventions to improve the quality of care and to guarantee homogeneous levels of care throughout the region.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7470269PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238562PLOS

Publication Analysis

Top Keywords

breast cancer
28
level performance
16
cancer care
12
evaluation breast
8
care network
8
network lazio
8
lazio region
8
region central
8
central italy
8
summary indicator
8

Similar Publications

Galectin-3 secreted by triple-negative breast cancer cells regulates T cell function.

Neoplasia

December 2024

Felsenstein Medical Research Center, Beilinson Campus, Petah Tikva, Israel; Tel Aviv University, Faculty of Medicine and Health Sciences, Tel Aviv, Israel; Rabin Medical Center, Beilinson Campus, Petah Tikva, Israel; Davidoff Cancer Center, Beilinson Campus, Petah Tikva, Israel. Electronic address:

Triple-negative breast cancer (TNBC) is an aggressive subtype that accounts for 10-15 % of breast cancer. Current treatment of high-risk early-stage TNBC includes neoadjuvant chemo-immune therapy. However, the substantial variation in immune response prompts an urgent need for new immune-targeting agents.

View Article and Find Full Text PDF

Background: This study investigates a multi-angle acquisition method aimed at improving image quality in organ-targeted PET detectors with planar detector heads. Organ-targeted PET technologies have emerged to address limitations of conventional whole-body PET/CT systems, such as restricted axial field-of-view (AFOV), limited spatial resolution, and high radiation exposure associated with PET procedures. The AFOV in organ-targeted PET can be adjusted to the organ of interest, minimizing unwanted signals from other parts of the body, thus improving signal collection efficiency and reducing the dose of administered radiotracer.

View Article and Find Full Text PDF

Purpose: Approximately 20% of all breast cancer cases are classified as triple-negative breast cancer (TNBC), which represents the most challenging subtype due to its poor prognosis and high metastatic rate. Caffeic acid phenethyl ester (CAPE), the main component extracted from propolis, has been reported to exhibit anticancer activity across various tumor cell types. This study aimed to investigate the effects and mechanisms of CAPE on TNBC.

View Article and Find Full Text PDF

Background: Breast cancer is a significant global health issue, responsible for a large number of female cancer deaths. Early detection through breast cancer screening is crucial in reducing mortality rates. However, regions such as Sub-Saharan Africa (SSA) face challenges in identifying breast cancer early, resulting in higher mortality rates and a lower quality of life.

View Article and Find Full Text PDF

Metastasis in patients with oral squamous cell carcinoma has been associated with a poor prognosis. However, sensitive and reliable tests for monitoring their occurrence are unavailable, with the exception of PET-CT. Circulating tumor cells and cell-free DNA have emerged as promising biomarkers for determining treatment efficacy and as prognostic predictors in solid tumors such as breast cancer and colorectal cancer.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!