Predictive Health Technology and Policy Assessment of Socioeconomic Impacts

Impact evaluation of new policies, practices, and technologies is imperative for the effective and efficient provision of high quality health care. Traditionally the approaches for health technology assessment have focused on data collected from controlled trials. This has given the approach scientific rigor and precision. On the other hand, impacts to health and health care systems have far-reaching ripple effects in the society. Many of such impacts are not directly measurable in practice. They can be physically unmeasurable, too costly to measure, or the time delays from cause to effect are too long for practical purposes. This can leave loosely related data and expert opinion as the only sources from which to assess the impacts. In particular, for a future oriented assessment to inform a decision prior to a costly trial, a predictive approach not dependent on data collected in a trial is needed. Also, there can be significant indirect impacts from reactions to the primary impacts. To inform the decision makers, a systemic approach will provide a coherent holistic perspective encompassing both short and long-term impacts. We propose an approach using system dynamics to present such systemic structures and forecast their behavior by simulation. System dynamics is a proven technique to model complex systems to improve understanding of their behavior and evaluate intervention and policy alternatives. As a case example, we present a model considering traumatic brain injury and its socioeconomic costs. The model contains several feedback loops from which outcomes and secondary effects have amplified impacts.