Organizational Engineering for Health

The Organizational Engineering for Health axis proposes more robust, cooperative and efficient ways of organizing the health system.

For the health system, one of the major challenges of the next few years is to propose organizational modes adapted to the expectations of users with the imperatives of agility and personalization, while guaranteeing medical and economic efficiency. The Ma Santé 2022 law (bill adopted on 26 March 2019) aims to meet this societal need. It encourages health structures to make profound organizational and technological changes. From this perspective, one of the levers envisaged is the control of patient trajectories, whether in or outside the hospital, characterized by the uncertainty linked to the human factor and the great variety and variability of the activities that make up these trajectories.

The work of the Organizational Engineering for Health (IOS) axis is positioned in this context, with a view to providing answers to this challenge.


The objective is to propose tool-based organizational engineering and management methods that will enable healthcare organizations to customize, diagnose, improve, and pilot patient trajectories in space and time, in an agile and predictive manner.

This involves modelling patient journeys as well as processes, yet with a level of granularity that takes into account the progress, coordination and interactions of the various activities, whether they concern medical care (diagnoses, examinations, treatments), expectations, trips or transportations and administrative or support services. In this way, the performance of trajectories can be analyzed from a perspective centered on the patient experience as a whole and not only on the treatment process.

Scientific obstacles

Current knowledge makes it possible to use multiple organizational engineering tools, however, these are usually compartmentalized and above all unsuited to the specificities of patient trajectories.

To achieve the objective of the Organizational Engineering for Health axis, several scientific obstacles must be overcome in order to upgrade these tools and integrate them into different engineering methods:

  1. How to identify and represent the pieces of knowledge that make it possible to discover and model patient trajectories by comparing several sources of data? This question is crucial since patient trajectories are rarely formalized even though they are preliminary to any engineering approach.
  2. How to enrich process discovery and compliance algorithms so that they can provide diagnosis support? This question aims to go beyond the limits of current algorithms which most often restrict themselves to the objectification of symptoms using statistical reports and the identification of reference processes.
  3. How to assess the organizational impact of unexpected events in order to enable agile and predictive management of patient trajectories? This question aims to analyze and minimize the impact of sources of uncertainty that disrupt the smooth running of healthcare organizations.

Research in organizational engineering, unlike clinical research, is relatively poorly represented in the field of health, both in France and internationally.

This may be because it finds its inspiration largely in the industrial field, which can constitute barriers or barriers.

The originality of the axis is based on translational research in organizational engineering. It aims to produce concrete applications based on fundamental knowledge. It is based on the development of new methodological frameworks based on models to support the digital transformation of health systems.