Assessing the conformity to clinical guidelines in oncology: An example for the multidisciplinary management of locally advanced colorectal cancer treatment

Jacopo Lenkowicz, Roberto Gatta, Carlotta Masciocchi, Calogero Casà, Francesco Cellini, Andrea Damiani, Nicola Dinapoli, Vincenzo Valentini

Research output: Contribution to journalArticle

Abstract

Purpose: The purpose of this paper is to describe a methodology to deal with conformance checking through the implementation of computer-interpretable-clinical guidelines (CIGs), and present an application of the methodology to real-world data and a clinical pathway for radiotherapy-related oncological treatment. Design/methodology/approach: This methodology is implemented by a software able to use the hospital electronic health record data to assess the adherence of the actual executed clinical processes to a clinical pathway, monitoring at the same time management-related efficiency and performance parameters, and ideally, suggesting ways to improve them. Findings: Three use cases are presented, in which the results of conformance checking are used to compare different branches of the executed guidelines with respect to the adherence to ideal process, temporal distribution of state-to-state transitions, and overall treatment efficacy, in order to extract data-driven evidence that could be of interest for the hospital management. Originality/value: This approach has the result of applying management-oriented data mining technique on sequential data, typical of process mining, to the result of a conformity check between the preliminary knowledge defined by clinicians and the real-world data, typical of CIGs.

Original languageEnglish
Pages (from-to)2172-2186
Number of pages15
JournalManagement Decision
Volume56
Issue number10
DOIs
Publication statusPublished - Oct 8 2018

Keywords

  • Clinical guidelines
  • Clinical pathway
  • Conformance checking
  • Evidence-based practice
  • Process mining

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Management Science and Operations Research

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