Healthy Decisions: Towards Uncertainty Tolerance in Healthcare Policy

The pace of innovation in healthcare is accelerating, and society demands innovative healthcare programmes to become available as soon as possible. Therefore, decisions regarding the use and reimbursement of new programmes need to be made when scientific evidence is by definition still scarce and effectiveness and cost effectiveness are (highly) uncertain. Dealing with uncertainty in healthcare decision making is challenging. First, since not all uncertainties are easily incorporated, generally only some uncertainty is explicitly characterised and presented in assessments [1]. As a consequence, researchers focus on quantifiable uncertainties such as measurement error. The logic of quantification, or ‘‘mathematics of certainty’’ [2], may result in ignoring important uncertainties which are hard or impossible to quantify (such as degree of generalisability of effectiveness to different populations and long-term consequences), causing pseudo-certainty of the results generated. Second, decision makers traditionally resort to science for certainty. Being transparent about uncertainty conflicts with this notion of scientific certainty and is perceived by decision makers as complicating decision making. At the same time, the steep rise in healthcare expenses, combined with the ongoing economic crises, necessitates painful and far-reaching decisions on the allocation of healthcare resources. These decisions are often based on model-based assessments of the comparative (cost)effectiveness of the innovative programme [3]. To account for timely and optimal decisions in the long run, it is crucial that all relevant uncertainties are incorporated in the assessments [4]. These uncertainties need to be identified as soon as possible, before the assessment is performed. This allows for transparent decision-making processes leading to defensible decisions and maintaining or increasing public trust in research results as well as policymaking bodies [5]. Moreover, allowing relevant uncertainties to be neglected in the assessments may stimulate companies to not collect evidence, in order to increase the chances of reimbursement for their product [6]. What is— and, hence, also what is not—assessed sets the agenda and frames the debate [4]. In this commentary, we argue that knowledge and concepts on dealing with uncertainty from other scientific disciplines, such as environmental science and risk governance, can improve the handling of uncertainty in J. P. C. Grutters (&) Department for Health Evidence (HEV 133), Radboud University Medical Centre, PO Box 9101, 6500 HB Nijmegen, The Netherlands e-mail: janneke.grutters@radboudumc.nl