Even Da Vinci Needs Evidence

A new study provides a framework of how policymakers can govern through evidence. In Governing through Evidence: A Study of Technological Innovation in Health Care (Journal of Public Administration Research and Theory, published online in advance on 25 March, 2013, DOI: 10.1093/jopart/mut016), Valentina Mele, Amelia Compagni (Department of Policy Analysis and Public Management) and Marianna Cavazza (Center for Research in Health and Social Care Management) investigate the role of evidence in governing the adoption of technological innovation in health care and identify the components of the process by analyzing the dynamics in Italy among regional policymakers, health care managers and clinicians.

In the health care system, the evidence-based paradigm (i.e. evidence provides indication of "what works") has been used not only in clinical decision making, but also in policymaking and management. Despite its growing importance, though, empirical investigation on how institutional arrangements may foster or prevent the implementation of evidence-based decisions is scant. The authors of the present study address this issue by focusing on the use of evidence to govern the adoption of highly innovative medical technologies. Through a multiple-case study, they analyze the case of the Da Vinci surgical robot acquisition since its first introduction in the Italian health care system in 1999.

The study of the dynamics among the actors involved in the process leads to the identification of four archetypes for governing technological innovation through evidence. These archetypes represent common conceptions of what "governing through evidence" means to policymakers and the other involved actors, and are associated to different institutional arrangements. Such classification has made possible, then, to understand that governing technological innovation through evidence rests on three pillars. The proposed framework highlights how policymakers, first, select and combine evidentiary bases (i.e. they identify the best available evidence), then they structure a new relational arrangement around evidence with those they aim to govern (i.e. health care managers and clinicians) and, finally, they standardize into institutional arrangements all those decisional criteria and procedures used to make the various forms of evidence explicit, understandable and replicable. The combination of these factors with the specific output sought by policymakers helps explain the different capabilities of institutional arrangements to govern in practice such a complex phenomenon.

Moreover, the case of the Da Vinci surgical robot provides other two important findings. That in governing a complex phenomenon scientific knowledge is not the only form of knowledge that can be employed by policymakers; and that, in contrast with previous studies, policymakers do not always search for extramural expertise or delegate decisions to private entities. To conclude, this study not only provides a useful framework for governing through evidence, but also has important implications for policymakers even beyond the health care domain.