WASPSS: A Clinical Decision Support System for Antimicrobial Stewardship

  1. Cánovas Segura, Bernardo
  2. Morales, Antonio
  3. M. Juarez, Jose
  4. Campos, Manuel
  5. Palacios, Francisco
Libro:
Recent Advances in Digital System Diagnosis and Management of Healthcare

Ano de publicación: 2021

Tipo: Capítulo de libro

DOI: 10.5772/INTECHOPEN.91648 GOOGLE SCHOLAR lock_openAcceso aberto editor

Referencias bibliográficas

  • Aminov RI. A brief history of the antibiotic era: Lessons learned and challenges for the future. Frontiers in Microbiology. 2010;1(134):1-7
  • Clatworthy AE, Pierson E, Hung DT. Targeting virulence: A new paradigm for antimicrobial therapy. Nature Chemical Biology. 2007;3(9):541-548
  • Antimicrobial Resistance: Global Report on Surveillance—2014 Summary. Geneva: World Health Organization; 2014. Available from: http://www.who.int/drugresistance/documents/surveillancereport/en/. [Accessed: 28 August 2018]
  • Dellit TH, Owens RC, McGowan JE, Gerding DN, Weinstein RA, Burke JP, et al. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clinical Infectious Diseases. 2007;44(2):159-177
  • Doron S, Davidson LE. Antimicrobial stewardship. Mayo Clinic Proceedings. 2011;86(11):1113-1123
  • Nathan C, Cars O. Antibiotic resistance—Problems, progress, and prospects. New England Journal of Medicine. 2014;371(19):1761-1763
  • Magill SS, Edwards JR, Bamberg W, Beldavs ZG, Dumyati G, Kainer MA, et al. Multistate point-prevalence survey of health care-associated infections. New England Journal of Medicine. 2014;370(13):1198-1208
  • Schentag JJ, Ballow CH, Fritz AL, Paladino JA, Williams JD, Cumbo TJ, et al. Changes in antimicrobial agent usage resulting from interactions among clinical pharmacy, the infectious disease division, and the microbiology laboratory. Diagnostic Microbiology and Infectious Disease. 1993;16(3):255-264
  • Carling P, Fung T, Killion A, Terrin N, Barza M. Favorable impact of a multidisciplinary antibiotic management program conducted during 7 years. Infection Control & Hospital Epidemiology. 2003;24(9):699-706
  • Palacios F, Campos M, Juarez JM, Cosgrove SE, Avdic E, Cánovas-Segura B, et al. A clinical decision support system for an antimicrobial stewardship program. In: HEALTHINF 2016-9th International Conference on Health Informatics, Proceedings. Rome: SciTePress; 2016. pp. 496-501
  • Shortliffe EH. Computer-Based Medical Consultations: MYCIN. Elsevier; 1976
  • Ma M, Shahar Y, Shortliffe EH. Clinical decision-support systems. Biomedical Informatics. 2006;30:698-736
  • Kuperman GJ, Gardner RM, Pryor TA. HELP: A Dynamic Hospital Information System. Computers and Medicine. New York, NY: Springer; 1991
  • Evans RS, Pestotnik SL, Classen DC, Clemmer TP, Weaver LK, Orme JF, et al. A computer-assisted management program for antibiotics and other antiinfective agents. New England Journal of Medicine. 1998;338(4):232-238
  • Kahn MG, Sa S, Fraser VJ, Dunagan WC. An expert system for culture-based infection control surveillance. In: Proceedings of the Annual Symposium on Computer Applications in Medical Care. 1993. pp. 171-175
  • Doherty J, Noirot LA, Mayfield J, Ramiah S, Huang C, Dunagan WC, et al. Implementing GermWatcher, an enterprise infection control application. In: AMIA Annual Symposium Proceedings. 2006. pp. 209-213
  • Lamma E, Mello P, Nanetti A, Riguzzi F, Storari S, Valastro G. Artificial intelligence techniques for monitoring dangerous infections. IEEE Transactions on Information Technology in Biomedicine. 2006;10(1):143-155
  • Lo YS, Liu CT. 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. vol. 4. IEEE. 2010. pp. 449-453
  • Lovis C, Colaert D, Stroetmann VN. DebugIT for patient safety—Improving the treatment with antibiotics through multimedia data mining of heterogeneous clinical data. Studies in Health Technology and Informatics. 2008;136:641-646
  • Schober D, Boeker M, Bullenkamp J, Huszka C, Depraetere K, Teodoro D, et al. The DebugIT core ontology: Semantic integration of antibiotics resistance patterns. Studies in Health Technology and Informatics. 2010;160:1060-1064
  • Teodoro D, Pasche E, Gobeill J, Emonet S, Ruch P, Lovis C. Building a transnational biosurveillance network using semantic web technologies: Requirements, design, and preliminary evaluation. Journal of Medical Internet Research. 2012;14(3):e73
  • Leibovici L, Paul M, Nielsen AD, Tacconelli E, Andreassen S. The TREAT project: Decision support and prediction using causal probabilistic networks. International Journal of Antimicrobial Agents. 2007;30:93-102
  • Adlassnig KP, Blacky A, Koller W. Artificial-intelligence-based hospital-acquired infection control. Studies in Health Technology and Informatics. 2009;149:103-110
  • Steurbaut K, Colpaert K, Gadeyne B, Depuydt P, Vosters P, Danneels C, et al. COSARA: Integrated service platform for infection surveillance and antibiotic management in the ICU. Journal of Medical Systems. 2012;36:3765-3775
  • Beaudoin M, Kabanza F, Nault V, Valiquette L. An antimicrobial prescription surveillance system that learns from experience. AI Magazine. 2014;35(1):15-25
  • Evans RS, Olson JA, Stenehjem E, Buckel WR, Thorell EA, Howe S, et al. Use of computer decision support in an antimicrobial stewardship program (ASP). Applied Clinical Informatics. 2015;6(1):120-135
  • Simões AS, Maia MR, Gregório J, Couto I, Asfeldt AM, Simonsen GS, et al. Participatory implementation of an antibiotic stewardship programme supported by an innovative surveillance and clinical decision-support system. Journal of Hospital Infection. 2018;100(3):257-264
  • Sackett DL. Evidence-based medicine. In: Encyclopedia of Biostatistics. Chichester, UK: John Wiley & Sons, Ltd; 2005
  • WASPSS Project: Wise Antimicrobial Stewardship Support System. Available from: http://www.um.es/waspss/ [Accessed: 17 July 2019]
  • Cánovas-Segura B, Campos M, Morales A, Juarez JM, Palacios F. Development of a clinical decision support system for antibiotic management in a hospital environment. Progress in Artificial Intelligence. 2016;5(3):181-197
  • Cánovas-Segura B, Morales A, Juarez JM, Campos M, Palacios F. A lightweight acquisition of expert rules for interoperable clinical decision support systems. Knowledge-Based Systems. 2019;167:98-113
  • Canovas-Segura B, Zerbato F, Oliboni B, Combi C, Campos M, Morales A, et al. A process-oriented approach for supporting clinical decisions for infection management. In: 2017 IEEE International Conference on Healthcare Informatics (ICHI); IEEE. 2017. pp. 91-100
  • Morales A, Campos M, Juarez JM, Canovas-Segura B, Palacios F, Marin R. A decision support system for antibiotic prescription based on local cumulative antibiograms. Journal of Biomedical Informatics. 2018;84(July):114-122
  • Garcia-caballero H, Campos M, Juarez JM, 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, Albacete, Noviembre 9–12, 2015. 2015. pp. 71-80
  • Sendelbach S, Funk M. Alarm fatigue: A patient safety concern. AACN Advanced Critical Care. 2013;24(4):378-386
  • Leclercq R, Cantón R, Brown DFJ, Giske CG, Heisig P, Macgowan AP, et al. EUCAST expert rules in antimicrobial susceptibility testing. Clinical Microbiology and Infection. 2013;19(2):141-160
  • EUCAST Expert Rules Version 3.1. The European Committee on Antimicrobial Susceptibility Testing; 2016. Available from: http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf [Accessed: 28 August 2018]
  • Cánovas-Segura B, Campos M, Morales A, Juarez JM, Palacios F. Clinical decision support using antimicrobial susceptibility test results. In: Luaces O, Gámez JA, Barrenechea E, Troncoso A, Galar M, Quintián H, et al., editors. Advances in Artificial Intelligence: 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, Salamanca, Spain, September 14–16, 2016. Proceedings. 2016. pp. 251-260
  • Cánovas-Segura B, Morales A, Juarez JM, Campos M, Palacios F. Impact of expert knowledge on the detection of patients at risk of antimicrobial therapy failure by clinical decision support systems. Journal of Biomedical Informatics. 2019;94:103200
  • IOM (Institute of Medicine). Clinical Practice Guidelines We Can Trust. Washington, DC: The National Academies Press; 2011
  • Kish MA. Guide to development of practice guidelines. Clinical Infectious Diseases. 2001;32(6):851-854
  • Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PAC, et al. Why don’t physicians follow clinical practice guidelines? JAMA. 1999;282(15):1458
  • Cánovas-Segura B, Morales A, Lopez Martinez-Carrasco A, Campos M, Juarez JM, López Rodríguez L, et al. Improving interpretable prediction models for antimicrobial resistance. In: 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS). IEEE. 2019. pp. 543-546
  • Morales A, Cánovas-Segura B, Campos M, Juarez JM, Palacios F. Proposal of a big data platform for intelligent antibiotic surveillance in a hospital. In: Luaces O, Gámez JA, Barrenechea E, Troncoso A, Galar M, Quintián H, et al., editors. Advances in Artificial Intelligence: 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, Salamanca, Spain, September 14–16, 2016. Proceedings. 2016. pp. 261-270