Key performance indicators for monitoring the integrated care pathway in breast cancer: the E.Pic.A. project

Altini, Mattia; Balzi, William; Maltoni, Roberta; Falcini, Fabio; Foca, Flavia; Ioli, Giovanni Messori; Ricotti, Andrea; Bertetto, Oscar; Mistrangelo, Marinella; Amunni, Gianni; Gemmi, Fabrizio; Bachini, Letizia; Silenzi, Andrea; Pastorino, Roberta; Barbará, Andréa; Pierini, Andrea; Massa, Ilaria

doi:10.33393/abtpn.2019.291

Cited by 2 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…KPIs Bot : The goal of this PoC is to create, through data clustering, a group of Key Performance Indicators (KPIs) based on diagnostic and therapeutic performance [ 11 ]. Among other potential exploitations, this is a simplified example of how the DataMart can be used for rule-based patients’ recruitment.…”

Section: Resultsmentioning

confidence: 99%

“…Given that radiotherapy should be started as soon as reasonably possible, a monitoring system such as Waiting Time BOT could allow not only to track possible delays in pts’ pathway of care, but also to learn to predict factors that can be associated to this delay and can be prevented. On the other hand, the KPIs BOT, which allows users to track the performance of breast tumor pathway of care, is based on a system of indicators published by Altini et al [ 11 ] in 2019. In this system, multidisciplinary evaluation is fundamental, but in the hospital system, services provided by the various departments can be reported on different informatic platforms or archives.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives

Marazzi

Tagliaferri

Masiello

et al. 2021

JPM

Self Cite

View full text Add to dashboard Cite

Background: Artificial Intelligence (AI) is increasingly used for process management in daily life. In the medical field AI is becoming part of computerized systems to manage information and encourage the generation of evidence. Here we present the development of the application of AI to IT systems present in the hospital, for the creation of a DataMart for the management of clinical and research processes in the field of breast cancer. Materials and methods: A multidisciplinary team of radiation oncologists, epidemiologists, medical oncologists, breast surgeons, data scientists, and data management experts worked together to identify relevant data and sources located inside the hospital system. Combinations of open-source data science packages and industry solutions were used to design the target framework. To validate the DataMart directly on real-life cases, the working team defined tumoral pathology and clinical purposes of proof of concepts (PoCs). Results: Data were classified into “Not organized, not ‘ontologized’ data”, “Organized, not ‘ontologized’ data”, and “Organized and ‘ontologized’ data”. Archives of real-world data (RWD) identified were platform based on ontology, hospital data warehouse, PDF documents, and electronic reports. Data extraction was performed by direct connection with structured data or text-mining technology. Two PoCs were performed, by which waiting time interval for radiotherapy and performance index of breast unit were tested and resulted available. Conclusions: GENERATOR Breast DataMart was created for supporting breast cancer pathways of care. An AI-based process automatically extracts data from different sources and uses them for generating trend studies and clinical evidence. Further studies and more proof of concepts are needed to exploit all the potentials of this system.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%