Procurement is one tool for the public sector to acquire need-based, innovative and effective solutions. To succeed in purchasing services that succeed in improving patients’ outcomes and optimize cost of care, the process must be accompanied with tools for early decisional support. Documenting the effects of healthcare innovation is therefore fundamental when dealing with prioritizing adequate technology. The aim of the present study was to review the literature to identify early assessment methodology applicable to innovative procurement processes.

A scoping review was performed in January and February 2017 with the objective of selecting literature reporting on early assessment of health innovation. Methods for early assessment of health innovation were identified with the aim of investigating whether the methods change depending on where in the innovation process (development, introduction, and early diffusion) they are applied, and if the literature pointed to dominant methods. Next, critical elements of the innovative procurement process were identified, and methods relevant to the need-based phase of procurement were assessed.

In total 1064 articles met the search strategy. Based on predefined inclusion and exclusion criteria, thirty-nine articles were included in the study. When viewed in the light of innovative procurement, stakeholder insight was an important source of data in early assessment of potential benefits of health innovation. Such data can be applied in scenario analyses to provide necessary outcome overviews and to direct and accelerate the procurement process. Further, various simulation and analysis methods may be used in new ways to increase the impact of the scarce availability of data in early innovation phase.

The present review identified tools for early decisional support that address risks and step-wise healthcare management support. Information based on the present review will also be addressed in Panel 26 “Accelerating Value Based Health Care with Innovative Procurement and Early Decisional Support”