Assessing the Socio-Economic Impact of High-Level Health Care Decisions

Guest post by Peter Ylén, Principal Scientist, VTT

Are Politicians stupid?

No, they are not stupid on the whole, although, the jury is still out on some cases. They are quite intelligent individuals facing the difficult task of making decisions in a complex, ever-changing world where every decision creates desired and undesired ripple effects on various areas of society, such as, economy, popularity, re-election, well-being, innovations, environment, employment to name but a few.

Everybody wants to make good decisions – and making good decisions can be relatively easy in simple isolated situations with short-term focus. In these cases, using decision support system creates little additional benefit. But if we think about the typical decisions that politicians has to make – one decision that might feel simple e.g. to decrease resources or money from one sector may have large multidimensional short term and long term impact that one individual, no matter how smart, cannot realize or evaluate without a tool support. However, there is not many politicians that would like to make high-level decisions e.g.  dealing with health care in isolated manner, focusing only on short-term benefits and without understanding the real long term impact of the decision.

Evaluation and Impact assessment

Systematic evaluation and outcome assessment have played a particularly important role in the context of health related research and daily practice health care decision-making, e.g., in diagnostics and deciding on treatment paths. In many cases, these are relatively focused situations with clear relationships between cause and effect.

On the other hand, let us consider the big picture consisting of health care system decisions dealing with well-being, quality of life, economics, social aspects, innovations, employment, business ecosystems, ethics, regulation, etc.  In these cases, the systemic impacts are numerous, interconnected and difficult for one person or team to evaluate. The formal impact assessment framework has been a good way to implement evaluation to provide information for performance-related steering and monitoring, i.e. accountability (Chelimsky, 1997, Hyytinen 2017).

Typically the traditional decision making approaches 1) simplify the phenomena, 2) focus only on economical aspect, 3) take into account only few impact characteristics of many, 4) focuses only on individual organizations  and 5) guide politicians to make decisions only based on the problems not in preventive manner (Hyytinen 2017).

The MIDAS Assessment Platform

The MIDAS project presents a new impact assessment platform, which overcomes many of the limitations described above. The approach integrates the data from multiple sources to the Midas platform allowing the creation of novel future-oriented data driven decision support system that helps to simulate how politicians could, in the future, make decisions knowing the decision potential multidimensional impact.

In Midas, system dynamic approach (ref needed) help us to understand the cause and impact relations and data sources that are needed for this multidimensional system development.  It creates a framework to take in account such issues as social innovation, social value, quality and reputation. It allows for

  • Participatory approaches to provide multiple voices to evaluation
  • Broader definitions of impact assessment to capture multi-faceted nature of health care impacts
  • Integration of a system perspective to make the dynamic interrelationships visible

The Midas platform and decision support system will enable what-if simulations of the impacts of various decisions based on current data and various future scenarios.  Sensitivity analysis and visualization of different options help in making informed decisions under uncertainties.

One MIDAS pilot case

The Finnish pilot case, one example in which the data driven decision support system and Midas platform is developed and tested, concentrating on how to prevent youth social exclusion and mental health problems (Iivari et al. 2017). In our case substance abuse and unemployment prevention emerged as very close concerns for decision-makers.  It was found however that the social exclusion and mental health prevention demands a multileveled decision making in which the continuously updated data is used, analysed and visualized from heterogeneous data sources such as patient records, social data bases, 3th party databases and in some cases even from individual’s tracking devices or social media applications. (Iivari et al. 2017).  The assessment dimensions, systemic causalities and potential data sources were mapped with both regional and national decision makers.  The resulting system dynamic model visualizes complex cause and effect relations and simulates impacts on a multitude of metrics.


Thus, there is a great need for  decision making support when talking about the complexity of decisions that the politicians have to make e.g. in the shaping health care sector. Decision makers are increasingly held accountable for their actions while the surrounding uncertainty and rate of change are constantly growing.  Without proper tools for future-oriented impact assessment, such as the ones developed in MIDAS project, we keep returning to the original question “Are Politicians stupid?”.


  • Chelimsky, E. (1997), The Coming Transformation in Evaluation. In Chelimsky, E. and Shadish, (Eds.), Evaluation for 21st century. A handbook. Sage, Thousand Oaks, pp. 1–26.
  • Hyytinen, K. (2017), Supporting service innovation via evaluation: a future oriented, systemic and multi-actor approach, Doctoral thesis, Aalto University, Espoo
  • Iivari, M., Francis Gomes, J., Pikkarainen, M., Häikiö, J., Ylén, P. (2017), Digitalization of Healthcare: Use of data in policy making, Proceedings of the XXVIII ISPIM Innovation Conference, Austria