Methods Inf Med 2008; 47(04): 364-380
DOI: 10.3414/ME0480
Original Article
Schattauer GmbH

Service-oriented Subscription Management of Medical Decision Data in the Intensive Care Unit

S. Van Hoecke
1   Department of Information Technology, Ghent University, Gent, Belgium
,
J. Decruyenaere
2   Department of Intensive Care, Ghent University Hospital, Gent, Belgium
,
C. Danneels
2   Department of Intensive Care, Ghent University Hospital, Gent, Belgium
,
K. Taveirne
1   Department of Information Technology, Ghent University, Gent, Belgium
,
K. Colpaert
2   Department of Intensive Care, Ghent University Hospital, Gent, Belgium
,
E. Hoste
2   Department of Intensive Care, Ghent University Hospital, Gent, Belgium
,
B. Dhoedt
1   Department of Information Technology, Ghent University, Gent, Belgium
,
F. De Turck
1   Department of Information Technology, Ghent University, Gent, Belgium
› Author Affiliations
Further Information

Publication History

Received: 16 February 2007

accepted: 09 January 2008

Publication Date:
18 January 2018 (online)

Summary

Objectives: This paper addresses the design of a platform for the management of medical decision data in the ICU. Whenever new medical data from laboratories or monitors is available or at fixed times, the appropriate medical support services are activated and generate a medical alert or suggestion to the bedside terminal, the physician’s PDA, smart phone or mailbox. Since future ICU systems will rely ever more on medical decision support, a generic and flexible subscription platform is of high importance.

Methods: Our platform is designed based on the principles of service-oriented architectures, and is fundamental for service deployment since the medical support services only need to implement their algorithm and can rely on the platform for general functionalities. A secure communication and execution environment are also provided.

Results: A prototype, where medical support services can be easily plugged in, has been implemented using Web service technology and is currently being evaluated by the Department of Intensive Care of the Ghent University Hospital. To illustrate the platform operation and performance, two prototype medical support services are used, showing that the extra response time introduced by the platform is less than 150 ms.

Conclusions: The platform allows for easy integration with hospital information systems. The platform is generic and offers user-friendly patient/service subscription, transparent data and service resource management and priority-based filtering of messages. The performance has been evaluated and it was shown that the response time of platform components is negligible compared to the execution time of the medical support services.

 
  • References

  • 1 Morris AH, Gardner RM. Principles of Critical Care, chapter on Computer applications. In: Hall J, Schmidt G, Wood L. (eds). New York: McGraw-Hill; 1992. pp 500-514.
  • 2 Weed LL. Clinical Judgment Revisited. Methods Inf Med 1999; 38 (Suppl. 04) 279-286.
  • 3 Hoste EAJ, Clermont G, Kersten A, Venkataraman R, Angus DC, De Bacquer D, Kellum JA. RIFLE criteria for acute kidney injury are associated with hospital mortality in critically ill patients: a cohort analysis. Critical Care 2006; 10: R73.
  • 4 Georgieva M, Milanov S, Milanov M, Gyurov E. Clinical pulmonary infection score (CPIS) dynamics in polytrauma patients with ventilatorassociated pneumonia. Critical Care 2004; 8 (Suppl 1): p 212.
  • 5 Kajdacsy-Balla Amara AC, Andrade FM, Moreno R, Artigas A, Cantraine F, Vincent J. Use of the Sequential Organ Failure Assessment score as a severity score. Intensive Care Med 2005; 31: 243-249.
  • 6 Decruyenaere J, De Turck F, Vanhastel S, Vandermeulen F, Demeester P, De Moor G. On the Design of a Generic and Scalable Multilayer Software Architecture for Data Flow Management in the Intensive Care Unit. Methods Inf Med 2003; 42: 79-88.
  • 7 De Turck F, Decruyenaere J, Thysebaert P, Van Hoecke S, Volckaert B, Danneels C, Colpaert K, De Moor G. Design of a flexible platform for execution of medical decision support agents in the Intensive Care Unit. Elsevier Journal of Com-puters in Biology and Medicine 2007; 37 (Suppl. 01) 97-112.
  • 8 Lenz R, Kuhn KA. Intranet Meets Hospital Information Systems: The Solution to the Integration Problem?. Methods Inf Med 2001; 40 (Suppl. 02) 99-105.
  • 9 Fieschi M, Dufour JC, Staccini P, Gourvernet J, Bouhaddou O. Medical Decision Support Systems: Old Dilemmas and new Paradigms ?. Methods Inf Med 2003; 42: 190-198.
  • 10 Greenes RA. Clinical Decision Support. The Road Ahead. Elsevier Inc., 2007
  • 11 Chen HT, Ma WC, Liou DM. Design and Implementation of a Real-Time Clinical Alerting System for Intensive Care Unit. Proc AMIA Symp 2002; pp 131-135.
  • 12 Wakai K, Kawamura T, Endoh M, Kojima M, Tomino Y, Tamakoshi A, Ohno Y, Inaba Y, Sakai H. A scoring system to predict renal outcome in IgA nephropathy: from a nationwide prospective study. Nephrol Dial Transplant 2006; 21 (10) 2800-2808.
  • 13 Adrie C, Cariou A, Mourvillier B, Laurent I, Dabbane H, Hantala F, Rhaoui A, Thuong M, Monchi M. Predicting survival with good neurological recovery at hospital admission after successful resuscitation of out-of-hospital cardiac arrest : the OHCA score. Eur Heart J 2006; 27 (23) 2480-2485.
  • 14 Chen J, Chung J, Wong T, Fan KL, Pun CO. Early detection of pulmonary hypertension with heart sounds analysis pilot study. Stud Health Technol Inform 2006; 122: 112-116.
  • 15 Trivedi MH, Kern JK, Marcee A, Grannemann B, Kleiber B, Bettinger T, Altshuler KZ, McClelland A. Development and Implementation of Computerized Clinical Guidelines: Barriers and Solutions. Methods Inf Med 2002; 41 (Suppl. 05) 435-442.
  • 16 The World Wide Web Consortium (W3C).. http://www.w3c.org
  • 17 Van Hoecke S, Haerick W, De Jans G, De Turck F, Laermans E, Dhoedt B, Demeester P. Design and Implementation of a Secure Media Content Delivery Broker Architecture, The 2005 International Symposium on Web Services and Applications (ISWS’05). Las Vegas, USA: 2005
  • 18 Steurbaut K, Van Hoecke S, Colpaert K, Danneels C, Decruyenaere J, De Turck F. Granularity of Medical Software Agents in ICU – Trade-off Performance versus Flexibility. Proceedings of the First International Symposium on Intelligent and Distributed Computing (IDC’07). Craiova, Romania: 2007
  • 19 Hoste EA, Kellum J. Acute Kidney Injury: Epidemiology and Diagnostic Criteria. Current Opinion in Critical Care 2006; 12 (Suppl. 06) 531-537.
  • 20 Van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R. Intensive insulin therapy in the critically ill patients. N Engl J Med 2001; 345 (19) 1359-1367.
  • 21 Rady MY, Johnson DJ, Patel BM, Larson JS, Helmers RA. Influence of individual characteristics on outcome of glycemic control in intensive care unit patients with or without diabetes mellitus. Mayo Clin Proc 2005; 80 (12) 1558-1567.
  • 22 Ewart GW, Marcus L, Gaba MM, Bradner RH, Medina JL, Chandler EB. The critical care medicine crisis: a call for federal action: a white paper from the critical care professional societies. Chest 2004; 125 (Suppl. 04) 1518-1521.
  • 23 Kelley MA, Angus D, Chalfin DB, Crandall ED, Ingbar D, Johanson W, Medina J, Sessler CN, Vender JS. The critical care crisis in the United States: a report from the profession. Chest 2004; 125 (Suppl. 04) 1514-1517.
  • 24 Irwin RS, Marcus L, Lever A. The critical care professional societies address the critical care crisis in the United States. Chest 2004; 125 (Suppl. 04) 1512-1513.
  • 25 Levy M. Computers in the intensive care unit. Journal of Critical Care 2004; 19 (Suppl. 04) 199-201.
  • 26 Andrews T, Cubera F, Dolakia H, Goland J, Klein J, Leymann F, Liu K, Roller D, Smith D, Thatte S, Trickovic I, Weeravarana S. Business Process Execution Language for Web Services. 2003
  • 27 The OWL Services Coalition.. OWL-S: Semantic Markup for Web Services. Technical White paper (OWL-S version 1.1), 2004