A declarative approach for interactive process discovery in the clinical domain

Abstract

Objective:

Process Mining (PM) is an established discipline with increasing adoption in the clinical domain. In this context, PM seeks to infer clinical processes from healthcare data collected in the Electronic Health Record. However, the particularities of clinical practice cause that, in most cases, the processes obtained result in an intricate network that hardly corresponds to clinical algorithms and, thus, are difficult to understand for clinical and IT personnel. To address these problems, our aim is to incorporate specialized clinical knowledge into the PM discovery algorithm.

Methods:

We propose a declarative approach to interactive process discovery in the clinical domain. Concretely, we present a set of declarative techniques that allows clinicians to incorporate their knowledge in the process, based on the Declare formalism.

Results:

The results of this work encompass both the declarative interactive approach and its implementation in the I-PALIA PM discovery algorithm, as well as an application to a use case for the treatment of prostate cancer. This application demonstrates that the implemented techniques are useful in managing typical problems that arise when applying PM methods to the clinical domain.

Conclusion:

This work proposes a novel approach with techniques for interactive process discovery in the clinical domain. This approach not only allows the clinical expert to interactively incorporate specialized knowledge into the PM algorithm, but also serves to obtain process models that are more comprehensible and better resemble treatment procedures.