Volume 25, Issue 5 pp. 764-773
Original Article

Surveillance of waiting times for access to treatment: a registry-based computed approach in breast cancer care

A. Quillet MD

A. Quillet MD

Researcher

Registre général des cancers de Poitou-Charentes, Centre Hospitalier Universitaire de Poitiers, Université de Poitiers, Poitiers, France

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G. Defossez MD

Corresponding Author

G. Defossez MD

Researcher

Registre général des cancers de Poitou-Charentes, Centre Hospitalier Universitaire de Poitiers, Université de Poitiers, Poitiers, France

Correspondence address: Defossez Gautier, Unité d'épidémiologie, biostatistique et registre des cancers de Poitou-Charentes, Centre Hospitalier Universitaire de Poitiers, Faculté de médecine, Université de Poitiers, 6, rue de la milétrie, TSA 51115 – 86073 POITIERS Cedex 9, France (e-mail: [email protected]).Search for more papers by this author
P. Ingrand MD, PhD

P. Ingrand MD, PhD

Researcher

Registre général des cancers de Poitou-Charentes, Centre Hospitalier Universitaire de Poitiers, Université de Poitiers, Poitiers, France

INSERM, CIC 1402, Poitiers, France

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First published: 30 July 2015
Citations: 4

Abstract

The current study set out to automatically generate waiting times for access to surgery, chemotherapy and radiotherapy, and to analyse their determinants for non-metastatic breast cancer patients. We used data from the Poitou-Charentes regional cancer registry of women diagnosed with stages I–III breast carcinoma between 2008 and 2010. Waiting times were automatically computed from a previously validated algorithm modelling the care trajectory and then compared with national guidelines. The population of this study included 1082 patients. The compliance with guidelines ranged from 52.4% (access to adjuvant chemotherapy) to 89.2% (access to adjuvant radiotherapy). Younger age, a higher TNM stage, a lower grade, having a triple negative tumour, being the subject of multidisciplinary meetings and being a patient at a public hospital were associated with longer waiting times. The main result was the significant heterogeneity between geographical areas of treatment for all waiting times studied. The original, reproducible use of a registry-based automated algorithm to generate waiting times will help to follow these indicators routinely and efficiently.

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