ESI XXXI: OR applied to health in a modern world
- 598 Downloads
At the early stages of a research career, it is vital to have a forum to discuss and learn from peers and experts. The Association of European Operational Research Societies (EURO) provides one such form through the EURO Summer and Winter Institutes.
From the 11th to the 20th of June 2014, the Italian and United Kingdom OR societies organised a EURO Summer Institute (ESI) particular focused to healthcare research. The theme of this ESI was “Operational Research applied to Health in a Modern World” and it took place in the stunning setting of Bard, Italy.
This special issue is the second special issue resulting from the ESI. The first (Aringhieri et al, 2016), published in Operations Research for Healthcare, consisted of contributions regarding a single aspect of a healthcare system exploiting innovative OR modelling and solution approaches. This special issue considers work that spans across the healthcare system and/or comparisons of methodological approaches.
As we stated in Aringhieri et al (2016) OR modelling for health care has developed with the complexities of the modern world and data is now an abundant resource which underpinned the theming of the ESI. To ensure the efficient and precise use of these resources in a patient-centred manner, it is vital to consider the health system as a whole which is the subject of the articles in this special issue.
One of the main challenges in health systems analysis is therefore the use of big data to support public health policies. The healthcare sector is characterised by the collection, storage and processing of immense amounts of data, which are generated by an increasing plurality of healthcare providers. Furthermore, they can be integrated using data coming from different sources, such as social networks, environment surveillance systems, real-time traffic systems, and so on. Big data in healthcare can enable the development of more detailed health system models since they can replicate, step by step, the flow of each single patient entering in the NHS. This opens the possibility for the development of new integrated modelling approaches.
Papiya Bhattacharjee, IIT Kharagpur, India
Nardo Borgman, University of Twente, the Netherlands
Aleida Braaksma, Academic Medical Center, University of Twente, the Netherlands
Omar El-Rifai, École Nationale Supérieure des Mines de Saint-Étienne, France
Anna Graber-Naidich, University of Toronto, Canada
Paolo Landa, Università degli Studi di Genova, Italy
Mário Amorim Lopes, Universidade do Porto, Portugal
Manolitzas Panagiotis, Technical University of Crete, Greece
Melanie Reuter, Karlsruhe Institute of Technology, Germany
Ines Raschendorfer, University of Kaiserslautern, Germany
Paolo Tubertini, Università degli Studi di Bologna, Italy
Pieter van den Berg, Delft University of Technology, the Netherlands
Maartje van de Vrugt, University of Twente, the Netherlands
Houra Mahmoudzadeh, University of Toronto, Canada
Jennifer Morgan, Cardiff University, United Kingdom
Sheetal Prakash Silal, University of Cape Town, South Africa
Julie Vile, Cardiff University, United Kingdom
Jacqueline Wirnitzer, Karlsruhe Institute of Technology, Germany
Roberto Aringhieri, Università degli Studi di Torino, Italy
Sally Brailsford, University of Southampton, UK
Vito Fragnelli, Università degli Studi del Piemonte Orientale, Italy
Paul Harper, Cardiff University, UK
Vincent Knight, Cardiff University, UK
Stefan Nickel, Karlsruhe Institute of Technology, Germany
Marion Rauner, University of Vienna, Austria
Giovanni Righini, Università degli Studi di Milano, Italy
Honora Smith, University of Southampton, UK
For more details about the ESI, please refer to the official report published on the EURO website: https://www.euro-online.org/web/pages/309/last-activity-reports.
As stated previously in this special issue, we have collected all the contributions that cover more than one aspect of the healthcare system and/or comparisons of methodological approaches. This special issue is composed of four papers which we are excited to describe here.
Two stalwarts of the OR simulation toolbox include Discrete Event Simulation and System Dynamics which is considered by Morgan et al (2016). In particular, this paper offers a reflection on the methodological implications of mixing both of these approaches. The paper uses a radiotherapy treatment centre as the background which is particularly suited due to the multi-stage process. The reflections and discussions will be of interest to all modellers aiming to combine approaches.
The next paper in this special issue by Silal et al (2015) will also be of interest from a methodological point of view. In this paper, disease transmission dynamics using compartmental models of varying levels of complexity are considered and compared to data. Some initial conclusions seem to indicate that simpler models are more appropriate, however, the main take-home message is to be sure to use the appropriate model for the problem considered. The mathematical models and their comparisons should be of interest to not only epidemiologists but all OR researchers.
Lopes et al (2016) move to not compare methodologies but international health care systems. This comparison is technically challenging due to the differences between countries. This paper discusses a novel approach of clustering countries which makes for the grouping of similar countries (across a variety of dimensions) possible. Using this approach, data from the World Health Organisation are investigated to illustrate how the proposed methodology can be used to best inform policy. This paper should be of interest to data miners and policy researchers alike.
The final paper of the special issue is by Lodi et al (2015). This paper considers funding of medical research, and in some sense we return to the first paper of the issue (Morgan et al 2016) as a System Dynamics model is considered. This model is used to obtain parameters based on the need for medical specialisation. These are in turn used to define an integer program optimisation model that returns an optimal allocation of grants. The paper considers various scenarios that should be of interest across the methodological and applied point of views.
To summarise this editorial, we feel that the ESI was a great success and would like to thank all participants for making it so. The papers in this special issue and by Aringhieri et al (2016) prove that the healthcare modelling landscape has a very bright future. Furthermore, our thanks go to the editors of Health Systems for their support in putting this special issue together.