Advertisement

Using ontologies to integrate and share resuscitation data from diverse medical devices

      Abstract

      Objective

      To propose a method for standardised data representation and demonstrate a technology that makes it possible to translate data from device dependent formats to this standard representation format.

      Methods and results

      Outcome statistics vary between emergency medical systems organising resuscitation services. Such differences indicate a potential for improvement by identifying factors affecting outcome, but data subject to analysis have to be comparable. Modern technology for communicating information makes it possible to structure, store and transfer data flexibly. Ontologies describe entities in the world and how they relate. Letting different computer systems refer to the same ontology results in a common understanding on data content. Information on therapy such as shock delivery, chest compressions and ventilation should be defined and described in a standardised ontology to enable comparison and combining data from diverse sources. By adding rules and logic data can be merged and combined in new ways to produce new information. An example ontology is designed to demonstrate the feasibility and value of such a standardised structure.

      Conclusions

      The proposed technology makes possible capturing and storing of data from different devices in a structured and standardised format. Data can easily be transformed to this standardised format, compared and combined independent of the original structure.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Resuscitation
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Christie A.
        • Mickey S.E.
        • Johan H.
        • Thomas D.R.
        Incidence of EMS-treated out-of-hospital cardiac arrest in Europe.
        Resuscitation. 2005; 67: 75-80
        • Rea T.D.
        • Eisenberg M.S.
        • Sinibaldi G.
        • White R.D.
        Incidence of EMS-treated out-of-hospital cardiac arrest in the United States.
        Resuscitation. 2004; 63: 17-24
        • Cummins R.O.
        • Chamberlain D.A.
        • Abramson N.A.
        • et al.
        Recommended guidelines for uniform reporting of data from out-of-hospital cardiac arrest: the Utstein Style.
        Circulation. 1991; 84: 960-975
        • Jacobs I.
        • Nadkarni V.
        • Bahr J.
        • et al.
        Cardiac arrest and cardiopulmonary resuscitation outcome reports: update and simplification of the Utstein templates for resuscitation registries. A statement for healthcare professionals from a task force of the international liaison committee on resuscitation (American Heart Association, European Resuscitation Council, Australian Resuscitation Council, New Zealand Resuscitation Council, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Council of Southern Africa).
        Resuscitation. 2004; 63: 233-249
        • Herlitz J.
        • Svensson L.
        • Engdahl J.
        • Silfverstolpe J.
        Characteristics and outcome in out-of-hospital cardiac arrest when patients are found in a non-shockable rhythm.
        Resuscitation. 2008; 76: 31-36
        • Friedman M.
        • Barnes V.
        • Whyman A.
        • et al.
        A model of survival following pre-hospital cardiac arrest based on the Victorian Ambulance Cardiac Arrest Register.
        Resuscitation. 2007; 75: 311-322
        • Nichol G.
        • Steen P.
        • Herlitz J.
        • et al.
        International Resuscitation Network Registry: design, rationale and preliminary results.
        Resuscitation. 2005; 65: 265-277
        • Morley P.T.
        Monitoring the quality of cardiopulmonary resuscitation.
        Curr Opin Crit Care. 2007; 13: 261-267
        • Kramer-Johansen J.
        • Edelson D.P.
        • Abella B.S.
        • Becker L.B.
        • Wik L.
        • Steen P.A.
        Pauses in chest compression and inappropriate shocks: a comparison of manual and semi-automatic defibrillation attempts.
        Resuscitation. 2007; 73: 212-220
        • Olasveengen T.M.
        • Wik L.
        • Kramer-Johansen J.
        • Sunde K.
        • Pytte M.
        • Steen P.A.
        Is CPR quality improving? A retrospective study of out-of-hospital cardiac arrest.
        Resuscitation. 2007; 75: 260-266
        • Olasveengen T.M.
        • Wik L.
        • Steen P.A.
        Quality of cardiopulmonary resuscitation before and during transport in out-of-hospital cardiac arrest.
        Resuscitation. 2008; 76: 185-190
        • Sunde K.
        • Eftestøl T.
        • Askenberg C.
        • Steen P.A.
        Quality assessment of defibrillation and advanced life support using data from the medical control module of the defibrillator.
        Resuscitation. 1999; 41: 237-247
        • Eftestol T.
        • Sunde K.
        • Ole Aase S.
        • Husoy J.H.
        • Steen PA
        Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest.
        Circulation. 2000; 102: 1523-1529
        • Eftestol T.
        • Sunde K.
        • Steen P.A.
        Effects of interrupting precordial compressions on the calculated probability of defibrillation success during out-of-hospital cardiac arrest.
        Circulation. 2002; 105: 2270-2273
        • Eftestol T.
        • Wik L.
        • Sunde K.
        • Steen P.A.
        Effects of cardiopulmonary resuscitation on predictors of ventricular fibrillation defibrillation success during out-of-hospital cardiac arrest.
        Circulation. 2004; 110: 10-15
        • Gundersen K.
        • Kvaløy J.T.
        • Kramer-Johansen J.
        • Theresa M.O.
        • Eilevstjønn J.
        • Eftestol T.
        Using within-patient correlation of samples to improve the accuracy of shock outcome prediction for cardiac arrest.
        Resuscitation. 2008; 78: 46-51
        • Risdal M.
        • Aase S.O.
        • Kramer-Johansen J.
        • Eftestol T.
        Automatic identification of return of spontaneous circulation during cardiopulmonary resuscitation.
        IEEE Trans Biomed Eng. 2008; 55: 60-68
        • Skogvoll E.
        • Eftestol T.
        • Gundersen K.
        • et al.
        Dynamics and state transitions during resuscitation in out-of-hospital cardiac arrest.
        Resuscitation. 2008; 78: 30-37
        • Eilevstjønn J.
        • Eftestøl T.
        • Aase S.O.
        • Myklebust H.
        • Husøy J.H.
        • Steen P.A.
        Feasibility of shock advice analysis during CPR through removal of CPR artefacts from the human ECG.
        Resuscitation. 2004; 61: 131-141
        • Berman J.J.
        • Bhatia K.
        Biomedical data integration: using XML to link clinical and research data sets.
        Expert Rev Mol Diagn. 2005; 5: 329-336
      1. OWL Web Ontology Language Guide. 2004 (Accessed 2008, at http://www.w3.org/TR/owl-guide/).

      2. W3C. Owl Web Ontology Language. 2004 (Accessed 2008, at http://www.w3.org/TR/owl-features/).

        • Shabo A.
        • Rabinovici-Cohen S.
        • Vortman P.
        Revolutionary impact of XML on biomedical information interoperability.
        IBM Syst J. 2006; 45: 361-372
        • Zweigenbaum P.
        MENELAS: an access system for medical records using natural language.
        Comput Methods Programs Biomed. 1994; 45: 117-120
      3. U.S. National Library of Medicine. Unified medical language system (Accessed November 2008, at http://www.nlm.nih.gov/research/umls/).

        • Rector A.L.
        • Nowlan W.A.
        The GALEN project.
        Comput Methods Programs Biomed. 1994; 45: 75-78
        • Pisanelli D.M.
        • Gangemi A.
        • Steve G.
        An ontological analysis of the UMLS methathesaurus.
        Proc AMIA Symp. 1998; : 810-814
      4. International Health Terminology Standards Development Organisation. SNOMED (Accessed November 2008, at http://www.ihtsdo.org/snomed-ct/).

        • Dieng-Kuntz R.
        • Minier D.
        • Ruzicka M.
        • Corby F.
        • Corby O.
        • Alamarguy L.
        Building and using a medical ontology for knowledge management and cooperative work in a health care network.
        Comput Biol Med. 2006; 36: 871-892
        • Prcela M.
        • Gamberger D.
        • Jovic A.
        Semantic web ontology utilization for heart failure expert system design.
        Stud Health Technol Inform. 2008; 136: 851-856
        • Smith B.
        • Ashburner M.
        • Rosse C.
        • et al.
        The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration.
        Nat Biotechnol. 2007; 25: 1251-1255
        • Kumar V.S.
        • Narayanan S.
        • Kurc T.
        • Jun K.
        • Gurcan M.N.
        • Saltz J.H.
        Analysis and semantic querying in large biomedical image datasets.
        Computer. 2008; 41: 52-59
      5. W3C. XML Tutorial (Accessed 13 November 2007, at http://www.w3schools.com/xml/).

        • Martin D.
        • Paolucci M.
        • Wagner M.
        Bringing Semantic annotations to web services: OWL-S from the SAWSDL perspective.
        in: Proceedings of the 6th international semantic web conference, Busan, Korea, 11–15 November2007
        • Pei M.
        • Nakayama K.
        • Hara T.
        • Nishio S.A.N.S.
        Constructing a global ontology by concept mapping using Wikipedia hhesaurus.
        in: Proceedings of the 22nd international conference on advanced information networking and applications—workshops, 2008, AINAW2008: 1205-1210
        • Bloehdorn S.
        • Haase P.
        • Sure Y.
        • et al.
        Ontology evolution.
        in: Davies J. Studer R. Warren P. Semantic web technologies: trends and research in ontology-based systems. West Sussex, Wiley2006: 51-70
      6. Energistics - WITSML Home Page (USA). WITSML overview (Accessed 4 December 2008, at http://www.witsml.org/witsml/Default.asp).