Process mining for the evaluation of fast track diagnostic pathways
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Identificadores
URI: http://hdl.handle.net/20.500.11940/13865
ISBN: 978-90-829673-4-0
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Fecha de publicación
2019-10Tipo de contenido
Publicación de congreso
DeCS
minería de datosMeSH
Data MiningResumen
Background:
Within the national cancer care strategies, colorectal neoplasm (CRC) is a priority. In a prior experience in
Madrid, only 27 out of 112 (24.1%) patients in a fast trak diagnosis (FTD) pathway were diagnosed of CRC.
Reasons why patients with CRC do not use FTD are still unknown. We hypothesize that new process
analytics techniques, such as process mining, are ideal tools to identify more efficient circuits or clinical
pathways in any pathology. We seek to redesign our FTD based on the results of process mining
Research questions:
Is it feasible to use process mining for the evaluation of the efficiency of a Diagnostic Fast Track (DFT) of
suspected colorectal cancer?
Method:
Through the process mining technique, a review of the existing DFT in the National Health System will be
performed for the diagnosis of CRC suspicion in order to establish all the events that may be related to these
processes. The DFT of our environment (Pontevedra-North Sanitary Area) will be analyzed, while new events
that may be of interest for its incorporation into this DFT will be proposed. This new DFT will be incorporated
in our center into the practice of care for a period of 18 months, after which the diagnostic process of CRC will
be re-evaluated through a new process mining.
Results:
The process will be considered efficient if no new avenues of assistance have been generated outside the
proposed DFT.
Conclusions:
The systematic proposal will constitute a new paradigm in the continuous evaluation of programs of early
diagnosis and dynamics of collaboration between primary care and hospital care.
Points for discussion:
Process mining may be useful for the follow-up and redesign of clinical pathways
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