Analytic Systems

The research theme Analytics Systems investigates utility determinants of analytic systems in daily practices within domains such as Health, Fisheries and Business from a people-process-technology perspective using an action research approach. We consider metrics such as effectiveness, efficiency and usability to determine a system’s societal impact. One novel aspect is its specific aim to collect these measurements from daily practices instead of from merely computational experiments. This, however, requires a significant software prototype engineering effort up front before an analytic system’s utility can actually be determined. A strategic secondary objective of this research is to improve transparancy in decision making processes.

We most prominently investigate Health Analytic Systems, i.e. Analytic Systems in daily practices within the Health domain.

The first completed PhD dissertation in Health Analytic Systems is from Michiel Meulendijk on the STRIP Assistant (e.g. Meulendijk et al, 2016). Current PhD projects in this research theme include Zhengru (Ian) Shen's STRIP Assistant 3.0 on prescriptive analytics in polypharmacy (e.g. Shen et al, 2016), Wienand Omta's HC StratoMineR on big data analytics in cell screening (e.g. Omta et al, 2016) and Raj Jagesar’s BeHapp passive mobile health analytics (e.g. Eskes et al, 2016).

Highlighted Papers 
Eskes, P., Spruit, M., Brinkkemper, S., Vorstman, J., and Kas, M. (2016). The Sociability Score: App-based social profiling from a healthcare perspective. Computers in Human Behavior, 59, 39-48.
Meulendijk, M., Spruit, M., Drenth-van Maanen, C., Numans, M., Brinkkemper, S., Jansen, P., and Knol, W (2015). Computerized decision support improves medication review effectiveness: an experiment evaluating the STRIP Assistant’s usability. Drugs & Aging, 32(6), 495–503.
Omta, W., Heesbeen, R. van, Pagliero, R., Velden, L. van der, Lelieveld, D., Nellen, M., Kramer, M., Yeong, M., Saeidi, A., Medema, R., Spruit, M., Brinkkemper, S., Klumperman, J., and Egan, D. (2016). HC StratoMineR: A web-based tool for the rapid analysis of high content datasets. ASSAY and Drug Development Technologies.
Shen, Z., Meulendijk, M., and Spruit, M. (2016). A federated information architecture for multinational clinical trials: STRIPA revisited. 24th European Conference on Information Systems. Istanbul, Turkey.