Abstract
From a technological point of view two kinds of requirements must be taken into account when implementing Clinical Decision Support Systems (CDSSs) for antibiotic surveillance in a hospital. First, Artificial Intelligence (AI) technologies are usually applied to represent and reason about existing clinical knowledge, but also to discover new one from raw data. Second, at a global decision level, representative applications of Business Intelligence (BI) must be also considered. The present work introduces the design and implementation of a CDSS platform that integrates both AI and BI technologies to assist clinicians in the rational use of antibiotics in a hospital. The choice of a Hadoop based Big Data architecture provides a suitable solution for the problem of integrating, processing and analysing large sets of clinical data. The platform facilitates the daily follow-up of antibiotic therapies and infections while offering various decision support modules at both patient and global level. The system is being tested and evaluated in a university hospital.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Calloway, S., Akilo, H.A., Bierman, K.: Impact of a clinical decision support system on pharmacy clinical interventions, documentation efforts, and costs. Hosp. Pharm. 48(9), 744–752 (2013)
Cánovas-Segura, B., Campos, M., Morales, A., Juarez, J.M., Palacios, F.: Development of a clinical decision support system for antibiotic management in a hospital environment. Prog. Artif. Intell. 1–17 (2016). doi:10.1007/s13748-016-0089-x
Forrest, G.N., Van Schooneveld, T.C., Kullar, R., Schulz, L.T., Duong, P., Postelnick, M.: Use of electronic health records and clinical decision support systems for antimicrobial stewardship. Clin. Infect. Dis. 59(Suppl. 3), S122–S133 (2014)
Garcia-Caballero, H., Campos, M., Juarez, J.M., Palacios, F.: Visualization in clinical decision support system for antibiotic treatment. In: Actas de la XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2015), pp. 71–80 (2015)
Grover, M., Malaska, T., Seidman, J., Shapira, G.: Hadoop Application Architectures. O’Reilly, Beijing (2015)
Groves, P., Kayyali, B., Knott, D., Kuiken, S.V.: The ‘big data’ revolution in healthcare: accelerating value and innovation. Center for US Health System Reform, Business Technology Office (2013)
Hopkins, B.: The patterns of big data. Technical report, Forrester Research, Inc. (2013)
Khazaei, H., McGregor, C., Eklund, M., El-khatib, K., Thommandram, A.: Toward a big data healthcare analytics system: a mathematical modeling perspective. In: 2014 IEEE World Congress on Services (SERVICES), pp. 208–215 (2014)
Koller, W., Blacky, A., Bauer, C., Mandl, H., Adlassnig, K.P.: Electronic surveillance of healthcare-associated infections with MONI-ICU - a clinical breakthrough compared to conventional surveillance systems. Stud. Health Technol. Inform. 160(PART 1), 432–436 (2010)
Lamma, E., Mello, P., Nanetti, A., Riguzzi, F., Storari, S., Valastro, G.: Artificial intelligence techniques for monitoring dangerous infections. IEEE Trans. Inf. Technol. Biomed. 10(1), 143–155 (2006)
Leclercq, R., Cantón, R., Brown, D.F.J., Giske, C.G., Heisig, P., Macgowan, A.P., Mouton, J.W., Nordmann, P., Rodloff, A.C., Rossolini, G.M., Soussy, C.J., Steinbakk, M., Winstanley, T.G., Kahlmeter, G.: EUCAST expert rules in antimicrobial susceptibility testing. Clin. Microbiol. Infect. 19(2), 141–160 (2013)
Piddock, L.J.V.: The crisis of no new antibiotics–what is the way forward? Lancet. Infect. Dis. 12(3), 249–253 (2012)
Raghupathi, W., Raghupathi, V.: Big data analytics in healthcare: promise and potential. Health Inf. Sci. Syst. 2(1), 3 (2014)
Spellberg, B.: The antibiotic crisis: can we reverse 65 years of failed stewardship? Arch. Intern. Med. 171(12), 1080–1081 (2011)
Steurbaut, K., Colpaert, K., Gadeyne, B., Depuydt, P., Vosters, P., Danneels, C., Benoit, D., Decruyenaere, J., De Turck, F.: COSARA: integrated service platform for infection surveillance and antibiotic management in the ICU. J. Med. Syst. 36, 3765–3775 (2012)
Lo, Y.-S., Liu, C.-T.: Development of a hospital-acquired infection surveillance information system by using service-oriented architecture technology. In: 2010 3rd International Conference on Computer Science and Information Technology, pp. 449–453. IEEE (2010)
Acknowledgments
This work was partially funded by the Spanish Ministry of Economy and Competitiveness under the WASPSS project (Ref: TIN2013-45491-R) and by European Fund for Regional Development (EFRD, FEDER).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Morales, A., Cánovas-Segura, B., Campos, M., Juarez, J.M., Palacios, F. (2016). Proposal of a Big Data Platform for Intelligent Antibiotic Surveillance in a Hospital. In: Luaces , O., et al. Advances in Artificial Intelligence. CAEPIA 2016. Lecture Notes in Computer Science(), vol 9868. Springer, Cham. https://doi.org/10.1007/978-3-319-44636-3_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-44636-3_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44635-6
Online ISBN: 978-3-319-44636-3
eBook Packages: Computer ScienceComputer Science (R0)