ProDeM: A Process-Oriented Delphi Method for systematic asynchronous and consensual surgical process modelling

Gonzalez-Lopez, Fernanda; Martin, Niels; de la Fuente, Rene; Galvez-Yanjari, Victor; Guzman, Javiera; Kattan, Eduardo; Sepulveda, Marcos; Munoz-Gama, Jorge

Abstract

Surgical process models support improving healthcare provision by facilitating communication and reasoning about processes in the medical domain. Modelling surgical processes is challenging as it requires integrating information that might be fragmented, scattered, and not process-oriented. These challenges can be faced by involving healthcare domain experts during process modelling. This paper presents ProDeM: a novel ProcessOriented Delphi Method for the systematic, asynchronous, and consensual modelling of surgical processes. ProDeM is an adaptable and flexible method that acknowledges that: (i) domain experts have busy calendars and might be geographically dispersed, and (ii) various elements of the process model need to be assessed to ensure model quality. The contribution of the paper is twofold as it outlines ProDeM, but also demonstrates its operationalisation in the context of a well-known surgical process. Besides showing the method's feasibility in practice, we also present an evaluation of the method by the experts involved in the demonstration.

Más información

Título según WOS: ID WOS:000892449400002 Not found in local WOS DB
Título de la Revista: ARTIFICIAL INTELLIGENCE IN MEDICINE
Volumen: 135
Editorial: Elsevier
Fecha de publicación: 2023
DOI:

10.1016/j.artmed.2022.102426

Notas: ISI