Temporal representation of care trajectories of cancer patients using data from a regional information system: an application in breast cancer

BMC Medical Informatics and Decision Making

Research Article

Alexandre Rollet¹  Gautier Defossez¹  Pierre Ingrand²  Olivier Dameron³ 

[1] Unité d’épidémiologie, biostatistique et registre général des cancers de Poitou-Charentes, Faculté de médecine, Centre Hospitalier Universitaire de Poitiers, Université de Poitiers, 6, rue de la milétrie, 199 86034, Poitiers, Cedex BP, France;Unité d’épidémiologie, biostatistique et registre général des cancers de Poitou-Charentes, Faculté de médecine, Centre Hospitalier Universitaire de Poitiers, Université de Poitiers, 6, rue de la milétrie, 199 86034, Poitiers, Cedex BP, France;INSERM, CIC 802, Poitiers, France;Université de Rennes 1, IRISA UMR6074, Rennes, France;

关键词: Epidemiology;    Evaluation;    Care trajectory;    Temporal reasoning;    Data integration;    Cancer;   

DOI  :  10.1186/1472-6947-14-24

 received in 2013-05-22, accepted in 2014-03-27,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundEnsuring that all cancer patients have access to the appropriate treatment within an appropriate time is a strategic priority in many countries. There is in particular a need to describe and analyse cancer care trajectories and to produce waiting time indicators. We developed an algorithm for extracting temporally represented care trajectories from coded information collected routinely by the general cancer Registry in Poitou-Charentes region, France. The present work aimed to assess the performance of this algorithm on real-life patient data in the setting of non-metastatic breast cancer, using measures of similarity.MethodsCare trajectories were modeled as ordered dated events aggregated into states, the granularity of which was defined from standard care guidelines. The algorithm generates each state from the aggregation over a period of tracer events characterised on the basis of diagnoses and medical procedures. The sequences are presented in simple form showing presence and order of the states, and in an extended form that integrates the duration of the states. The similarity of the sequences, which are represented in the form of chains of characters, was calculated using a generalised Levenshtein distance.ResultsThe evaluation was performed on a sample of 159 female patients whose itineraries were also calculated manually from medical records using the same aggregation rules and dating system as the algorithm. Ninety-eight per cent of the trajectories were correctly reconstructed with respect to the ordering of states. When the duration of states was taken into account, 94% of the trajectories matched reality within three days. Dissimilarities between sequences were mainly due to the absence of certain pathology reports and to coding anomalies in hospitalisation data.ConclusionsThese results show the ability of an integrated regional information system to formalise care trajectories and automatically produce indicators for time-lapse to care instatement, of interest in the planning of care in cancer. The next step will consist in evaluating this approach and extending it to more complex trajectories (metastasis, relapse) and to other cancer localisations.

【 授权许可】

CC BY   
© Defossez et al.; licensee BioMed Central Ltd. 2014