Abstract
The underlying idea in this work consists on providing added values utilities that allow exploiting the Electronic Health Record (EHR) as something more than a simple information record. The key for providing added value to the clinical information systems is to exploit the synergy “Information + intelligence + ubiquity”. Based on this idea, we propose a distributed architecture that deals with: 1) Database and an integration layer to exploit the data stored and its integration with external information system, 2) Tools for support the medical knowledge management, 3) Tools for supervision and analysis of the health care quality (based on EBM and Clinical Guidelines) 4) Intelligent Assistance Tools.
This work has been supported by the Spanish MEC under the national project TIN2006-15460-C04-01, PET2006-406 and PET2007_0033.
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Campos, M., Juárez, J.M., Palma, J.T., Marín, R.: Temporal data mining with temporal constraints. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds.) AIME 2007. LNCS (LNAI), vol. 4594, pp. 67–76. Springer, Heidelberg (2007)
Chen, J., He, H., Jin, H., McAullay, D., Williams, G., Kelman, C.: Identifying risk groups associated with colorectal cancer. In: Williams, G.J., Simoff, S.J. (eds.) Data Mining. LNCS (LNAI), vol. 3755, pp. 260–272. Springer, Heidelberg (2006)
DeClercq, P.A., Blom, J.A., Korsten, H.H.M., Pasman, A.: Approaches for creating computer interpretable guidelines that facilitate decision support. Artificial Intelligence in Medicine 31, 1–27 (2004)
Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From Data Mining to Knowledge Discovery: An Overview. In: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press (1996)
Field, M.J., Lohr, K.N.(eds.): Guidelines for clinical practice: from development to use. National Academy Press, Washington (1992)
Gunter, T.D., Terry, N.P.: The emergence of national electronic health record architectures in the United States and Australia: models, costs, and questions. J. Med. Internet Res. 7(1), 3 (2005)
Guil, F., Juárez, J.M., Marín, R.: Mining Possibilistic Temporal Constraint Networks: A Case Study in Diagnostic Evolution at Intensive Care Units. In: Proc. of the Intelligent Data Analysis in Biomedicine and Pharmacology, IDAMAP 2006, Verona, Italy, pp. 7–12 (2006)
Hung, S.Y., Chen, C.Y.: Mammographic case base applied for supporting image diagnosis of breast lesion. Expert Systems with Applications 30(1), 93–108 (2006)
Juarez, J.M., Guil, F., Palma, J., Marin, R.: An uncertain temporal similarity proposal for temporal CBR. In: Roth-Berghofer, T.R., Göker, M.H., Güvenir, H.A. (eds.) ECCBR 2006. LNCS (LNAI), vol. 4106, pp. 210–219. Springer, Heidelberg (2006)
Knaup, P., Wiedemann, T., Bachert, A., Creutzig, U., Haux, R., Schilling, F.: Efficiency and safety of chemotherapy plans for children: Catipoa nation wide approach. Artificial Intelligence in Medicine (24), 229–242 (2002)
Montani, S., Terenziani, P., Bottrighil, A.: Exploiting decision theory for supporting therapy selection in computerized clinical guidelines. In: Proc. of the 10th Conference on Artificial Intelligence in Medicine, pp. 136–140 (2005)
Powell, J., Buchan, I.: Electronic Health Records Should Support Clinical Research. J. Med. Internet Res. 7(1), 4 (2005)
Sackett, D.L., Rosenberg, W.M., Gray, J.A., Haynes, R.B., Richardson, W.S.: Evidence based medicine: what it is and what it isn’t. BMJ (British Medical Journal) 312(7023), 71–72 (1996)
Shortliffe, E.H.: MYCIN: rule-based computer program for advising physicians regarding antimicrobial therapy selection. Ph.D. thesis, Stanford University (1974)
Terenziani, P., Montani, S., Bottrighi, A., Molino, G., Torchio, M.: Clinical guidelines adaptation: managing authoring and versioning issues. In: Proc. of the 10th Conference on Artificial Intelligence in Medicine, pp. 151–155 (2005)
Toma, T., Abu-Hanna, A., Bosman, R.: Predicting mortality in the intensive care unit using episodes. In: Proc. of the 1st International Work-conference on the Interplay between Natural and Artificial Computation, pp. 447–458 (2005)
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Campos, M., Morales, A., Juárez, J.M., Sarlort, J., Palma, J., Marín, R. (2009). Intensive Care Unit Platform for Health Care Quality and Intelligent Systems Support. In: Corchado, J.M., Rodríguez, S., Llinas, J., Molina, J.M. (eds) International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008). Advances in Soft Computing, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85863-8_43
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DOI: https://doi.org/10.1007/978-3-540-85863-8_43
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