Abstract
This chapter combines traditional performance management and system dynamics simulation modelling to address patients' mobility issues and pursue public value. The Italian case study is a first illustration of travelling flows' causal structure; however, the perspective is to introduce such methodological approach also at European level. After a literature review about the main factors inducing healthcare mobility, the phenomenon is explored in light of public management theories. Then, a model portrays the causal structure of the phenomenon in terms of system dynamics and performance management items. There follows a discussion of theoretical and managerial implications of the study, as well as ideas and issues for next research steps.
TopIntroduction
In the European Union, the free movement of people, goods and services is a driving force behind the pursuing of a sustained development, and a key EU priority is achievable and effective patients’ mobility (Forchielli & Fusco, 2008). Indeed, cross-border healthcare, facilitating the transfer of expertise and improving the choice for patients is a challenge to balance health care accessibility, quality, financial sustainability and equity (Wismar, Palm, Figueras, Ernst, & Van Ginneken, 2011). This could also compensate temporary imbalances between supply and demand, and incentive improvements in health care delivery in both sending and receiving countries, for example by creating pressure to reduce waiting times and revealing weaknesses in administrative processes, such as patient registration and data flows (Rosenmoller, McKee, & Baeten, 2006, p. 184).
The scale of cross-border healthcare is still relatively modest, accounting just for the 1% of the total EU healthcare expenditure (Van Ginneken & Busse 2011), but the attention to the phenomenon is growing, due to the relatively recent adoption of the European directive on the “Application of patients’ rights in cross-border healthcare” (2011/24/EU). This regulation triggers a series of issues, in particular for the coverage of the difference between home and destination countries’ medical tariffs, inducing patients to make healthcare choices according to pure economic convenience rather than quality (Simonetti, Ugenti, Casciello, & Tamburini, 2014, p. 641). For this reason, it is crucial to enforce local healthcare systems while providing the mobility option.
In effect, the mentioned Directive fosters coordination between Member States from a broader health system perspective (Clemens, Michelsen, Brand, 2014), whilst at State level, the European top down pressure may result in an opportunity to reform long-standing issues for which there was insufficient political will or technical resource in the past (EUPHA. O.5, 2014).
Therefore, innovative managerial tools are required for steering European healthcare systems to face the challenges above. Italy, with a public-regionalized healthcare system, has been already witnessing relevant patients’ flows from certain regions to others (in-border mobility). The Italian legislation states that the regional governments are in charge for health provision, ensuring at the same time the opportunity for patients to choose where to receive a public medical care.
As a result, the residential region will refund the destination regions for the health care provide to non-residents. Since there are constant patients’ outflows always generated by the same under-developed regions, such figures can represent indicators of low quality of the local healthcare offers.
In order to improve decision-makers’ strategic learning processes, the present chapter aims to contribute to the debate about how to provide sustainable care at a country level, and to hypothesize potential scenarios after the application of the new EU regulations.
For the purpose, the traditional performance management is combined with system dynamics simulation modelling. The proposed framework of analysis can be helpful to raise stakeholders’ awareness about the feedback structure responsible for the Italian inter-regional mobility flows, having relevant contact points with the cross-border dynamics. The structure of the chapter will be as follows: after this introduction about topic and aims of the study, the European and Italian legislations are introduced in combination with a critical literature review about the main factors affecting the attitudes of healthcare mobility. Then the patients’ flows are framed into the public management theories. Starting from that, there is the gradual introduction of the system dynamics model in conjunction to performance management items. The chapter ends with the proposal of a dynamic performance management framework, the discussion of the theoretical and managerial implications of the study, and a call for future researches.
Key Terms in this Chapter
End-Results: In a performance management system, variables expressing economic, competitive, or social objectives, able to affect the processes of accumulation/depletion of the strategic resources over the time.
Patients’ Mobility: The movements of patients outside their residential area. The phenomenon refers to patients entitled to access healthcare services by the affiliation to public health systems or private health insurers in privately funded systems.
Performance Drivers: In a performance management system, variables referring to the critical success factors outlining the capability of an organization, in relationship with the performance of external economies or counterparts to influence the end-results.
Stocks: Elements of a stock-and-flow structure representing the level of a resource within the system at a certain time.
Flows: Elements of a stock-and-flow structure representing the rate of change of a stock’s level expressed by quantities per units of time.
Strategic Resources: In a performance management system, variables able to influence the acquisition of other resources and the capacity of the organization to pursue economic, competitive, and social objectives.
System Dynamics: Computer-aided methodology able to represent the causal structure of a system through stock-and-flow feedback structures and computer simulations regarding the accumulation of materials, information, people, and money.
Auxiliary Variables: In a stock-and-flow structure, variable helping in calculus or acting as exogenous parameters or constants.