Improving Decision-Making for Clinical Research and Health Administration

This chapter presents a health decision-support system called DISEArch that allows the identification and analysis of relevant EHR for decision-making. It uses structured and non-structured data, and provides analytical as well as visualization facilities over individual or sets of EHR. DISEArch proves to be useful to empower researchers during analysis processes and to reduce considerably the time required to obtain relevant EHR for a study. The analysis of semantic distance between EHR should also be further developed. As with any information systems project, a conversation needs to be put in place to realize the full potential that IT-based systems offer for people, in this case within the medical domain. It is a mutual learning experience that requires constant translations, frequent prototype discussions, grounding of new IT-based support in current practices and clear identification of existing problems and future opportunities that are opened up in order to enrich the momentum of the project, enlarge the community of early adopters and guaranteeing the continued financial, scientific and administrative support for the project from management stakeholders. Our experience is very positive and we intend to further pursue this approach and extract lessons learned for similar projects.