Methods Inf Med 2011; 50(02): 180-189
DOI: 10.3414/ME09-01-0002
Original Articles
Schattauer GmbH

An Analysis Framework for Electronic Health Record Systems

Interoperation and Collaboration in Shared Healthcare
J. Bisbal
1   Department of ICT, Universitat Pompeu Fabra, Barcelona, Spain
,
D. Berry
2   Department of Control/Electrical Engineering, Dublin Institute of Technology, Dublin, Ireland
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received: 19. Januar 2009

accepted: 27. September 2009

Publikationsdatum:
18. Januar 2018 (online)

Summary

Background: The timely provision of complete and up-to-date patient data to clinicians has for decades been one of the most pressing objectives to be fulfilled by information technology in the healthcare domain. The so-called electronic health record (EHR), which provides a unified view of all relevant clinical data, has received much attention in this context from both research and industry. This situation has given rise to a large number of research projects and commercial products that aim to address this challenge. Different projects and initiatives have attempted to address this challenge from various points of view, which are not easily comparable.

Objectives: This paper aims to clarify the challenges, concepts, and approaches involved, which is essential in order to consistently compare existing solutions and objectively assess progress in the field.

Methods: This is achieved by two different means. Firstly, the paper will identify the most significant issues that differentiate the points of view and intended scope of existing approaches. As a result, a framework for analysis of EHR systems will be produced. Secondly, the most representative EHR-related projects and initiatives will be described and compared within the context of this framework.

Results: The main result of the present paper is an analysis framework for EHR systems. This is intended as an initial step towards an attempt to structure research on this field, clearly lacking sound principles to evaluate and compare results, and ultimately focusing its efforts and being able to objectively evaluate scientific progress.

Conclusions: Evaluation and comparison of results in medical informatics, and specifically EHR systems, must address technical and nontechnical aspects. It is challenging to condensate in a single framework all potential views of such a field, and any chosen approach is bound to have its limitations. That being said, any well structured comparison approach, such as the framework presented here, is better than no comparison framework at all, as has been the current situation to date. This paper has presented the first attempt known to the authors to define such a framework.

 
  • References

  • 1 Aamodt A, Nygård M. Different roles and mutual dependencies of data, information, and knowledge – An AI perspective on their integration. Data & Knowledge Engineering 1995; 16 (03) 191-222.
  • 2 Agrawal R, Grandison T, Johnson C, Kiernan J. Enabling the 21st century health care information technology revolution. Communications of the ACM 2007; 50 (02) 35-42.
  • 3 Anderson GF, Frogner BK, Johns RA, Reinhardt UE. Health Care Spending and Use of Information Technology in OECD Countries. Health Affairs 2006; 25 (03) 819-831.
  • 4 Andrew WF, Bruegel RB, Gasch AE. EHR Attributes and Subattributes. Healthcare IT 2007; 11 (1). Available from: http://health-care-it.advanceweb.com/resources/hx050104_p38_v2.pdf (accessed May 2008). Text: http://health-care-it.advanceweb.com/Editorial/Search/AViewer.aspx?AN=HX_07jan1_hxp41.html&AD=01–01–2007
  • 5 Beale T. Archetypes: Constraint-based domain models for future-proof information systems. Proceedings of Eleventh OOPSLA Workshop on Behavioural Semantics: Serving the Customer 2002 pp 16-32.
  • 6 Bernstein P, Melnik S. Model management 2.0: manipulating richer mappings. Proceedings of the 2007 ACM SIGMOD international conference on Management of data; 2007 pp 1-12.
  • 7 Bicer V, Kilic O. Dogac, Laleci GB, Archetype-Based Semantic Interoperability of Web Service Messages in the Health Care Domain. International Journal on Semantic Web and Information Systems 2005; 1 (04) 1-22.
  • 8 Bisbal J, Lawless D, Wu B, Grimson J. Legacy Information Systems: Issues and Directions. IEEE Software 1999; 16 (05) 103-111.
  • 9 Bisbal J, Berry D. Archtype Alignment: A two-level driven Semantic Matching Approach to Interoper-ability in the clinical domain. Proceedings of the International Conference on Health Informatics, HEALTHINF; 2009 pp 216-221.
  • 10 Blake JA, Bult CJ. Beyond the data deluge: Data integration and bio-ontologies. Journal of Biomedical Informatics 2006; 39 (03) 314-320.
  • 11 Bossen C. Evaluation of a computerized problem-oriented medical record in a hospital department: Does it support daily clinical practice?. Int J Med Inform 2007; 76 (08) 592-600.
  • 12 Brown SH, Lincoln MJ, Groen PJ, Kolodner RM. VistA – U. S. Department of Veterans Affairs national-scale HIS. Int J Med Inform 2003; 69 (03) 135-156.
  • 13 Covvey HD, Zitner D, Berry DM, Cowan DD, Shepherd M. Formal Structure for Specifying the Content and Quality of the Electronic Health Record. Proceedings of the 11th IEEE International Conference on Requirements Engineering; 2003 pp 162-168.
  • 14 Chaudhry B, Wang J, Wu S, Maglione M. et al. Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care. Annals of Internal Medicine 2006; 144 (10) 742-752.
  • 15 Dick RS, Steen EB, Detmer DE. editors. The Computer-Based Patient Record: An Essential Technology for Health Care. Revised edition. Institute of Medicine, National Academy Press; 1997
  • 16 Eichelberg M, Aden T, Riesmeier J, Dogac A, Laleci GB. A survey and analysis of Electronic Healthcare Record standards. ACM Computing Surveys 2005; 37 (04) 277-315.
  • 17 Eslami S, de Keizer NF, Abu-Hanna A. The impact of computerized physician medication order entry in hospitalized patients – A systematic review. Int J Med Inform 2008; 77 (06) 365-376.
  • 18 EU Commission, Communication from the Council, the European Parliament, the European Eco nomic and Social Committee and the Committee of the Regions.. “e-Health – making health-care better for European citizens: An action plan for a European e-Health Area”, Brussels, 30.4.2004, COM (2004) 356 final. http://europa.eu.int/information_society/doc/qualif/health/COM_ 2004_0356_F_EN_ACTE.pdf
  • 19 Ferraiolo DF, Kuhn DR, Chandramouli R. Role-Based Access Control. 2nd edition. Artech House Publishers; 2007
  • 20 Grimson J. Delivering the electronic healthcare record for the 21st century. Int J Med Inform 2001; 64: 111-127.
  • 21 Grimson J, Grimson W, Berry D, Stephens G, Felton E, Kalra D. et al. A CORBA-based integration of distributed electronic healthcare records using the Synapses approach. IEEE Transactions on Information Technology in Biomedicine 1998; 2 (03) 124-138.
  • 22 Goble C, Stevens R. State of the nation in data integration for bioinformatics. Journal of Biomedical Informatics 2008; 41 (05) 687-693.
  • 23 Häyrinena K, Sarantoa K, Nykänen P. Definition, structure, content, use and impacts of electronic health records: A review of the research literature. Int J Med Inform 2008; 77 (05) 291-304.
  • 24 Halamka JD, Mandl KD, Tang PC. Early Experiences with Personal Health Records. JAMIA 2008; 15: 1-7.
  • 25 HL7 Entity Identification Service (EIS) Draft Standard for Trial Use.. Release 1 98pp. Available from: http://www.hl7.org/dstucomments/index.cfm , accessed on 9/06/2008
  • 26 Hull R, Zhou G. A framework for supporting data integration using the materialized and virtual approaches. ACM SIGMOD Record 1996; 25 (02) 481-492.
  • 27 Iakovidis I, Dogac A, Purcarea O, Comyn G, Laleci GB. Interoperability of eHealth Systems – Selection of Recent EU’s Research Programme Developments. Proceedings of the International Conference eHealth: Combining Health Telematics, Tele-medicine, Biomedical Engineering and Bioinformatics to the Edge. 2007
  • 28 Ingram D. GEHR: The Good European Health Record. In: Laires MF, Ladeira MJ, Christensen JP. editors. Proceedings of Health in the New Communications Age. Amsterdam: IOS Press; 1995
  • 29 IOM 2001 Commitee on Quality of Healthcare in America Institute of Medicine.. Crossing the quality chasm: A New health system for the 21st century. National Academic Press; 2001
  • 30 IOM 2003, Committee on Data Standard and Patient Safety, Key Capabilities of an Electronic Health Record System
  • 31 ISO 2004, TC 215.. Health Informatics – Electronic Health Record – Definition, Scope and Context. ISO/DTR 20514.
  • 32 Jha AK, DesRoches CM, Campbell EG. et al. Use of Electronic Health Records in U. S. Hospitals. The New England Journal of Medicine 2009; 360: 1628-1638.
  • 33 Kaelber DC, Bates DW. Health information exchange and patient safety. Journal of Biomedical Informatics 2007; 40 6)(Suppl. 1) S40-S45.
  • 34 Kaelber DC, Jha KA, Johnston D, Middleton B. et al. A Research Agenda for Personal Health Records (PHRs). JAMIA 2008; 15: 729-736.
  • 35 Kimball R, Ross M, Thornthwaite W, Mundy J, Becker B. The Data Warehouse Lifecycle Toolkit. 2nd edition. John Wiley & Sons; 2008
  • 36 Kohn LT, Corrigan JM, Donaldson MS. editors. To err is human: Building a safer health system. National Academic Press; 2000
  • 37 Kossmann D. The state of the art in distributed query processing. ACM Computing Surveys 2000; 32 (04) 422-469.
  • 38 Kukafka R, Ancker JS, Chan C, Chelico J, Khan S, Mortoti S. et al. Redesigning electronic health record systems to support public health. J Biomed Inform 2007; 40 (04) 398-409.
  • 39 Laleci G, Dogac A, Olduz M, Tasyurt I, Yuksel M, Okcan A. SAPHIRE: A Multi-Agent System for Remote Healthcare Monitoring through Computerized Clinical Guidelines. In: Annicchiarico R, Cortés U, Urdiales C. editors. Agent Technology and e-Health. Springer-Verlag; 2008
  • 40 Martínez-Costa C, Menárguez-Tortosa M, Fernández-Breis JT, Maldonado JA. A Model-driven Approach for Representing Clinical Archetypes for Semantic Web Environments. J Biomed Inform 2009; 42 (01) 150-164.
  • 41 McKee M. Reducing hospital beds: What are the lessons to be learnt?. European observatory on health systems and policies policy brief. 2004; 6. WHO. 2004
  • 42 Moreau L, Groth P, Miles S, Vazquez-Salceda J, Ibbotson J, Jiang S. et al. The provenance of electronic data. Communications of the ACM 2008; 51 (04) 52-58.
  • 43 Noy NF. Semantic integration: a survey of ontology-based approaches. ACM SIGMOD Record 2004; 33 (04) 65-70. Special section on semantic integration.
  • 44 PriceWaterHouseCoopers.. The economics of IT and hospital performance. PriceWaterHouse-Coopers’ Health Research Institute; 2007
  • 45 PriceWaterHouseCoopers.. Research rewired: Merging care and research information to improve knowledge discovery. PriceWaterHouseCoopers’ Health Research Institute; 2008
  • 46 Spil TAN, Katsma CP. Balancing Supply and Demand of an Electronic Health Record in the Nether-lands; Not too open systems for not too open users. Proceedings of the 40th Annual Hawaii International Conference on System Sciences; 2007 pp 134-134.
  • 47 Uslu AM, Stausberg J. Value of the electronic patient record: An analysis of the literature. J Biomed Inform 2008; 41 (04) 675-682.
  • 48 Weed LL. Medical records that guide and teach. The New England Journal of Medicine 1968, 278 (11): 593-599 and 278 (12): 652-657. Published also in MD Computing 1993; 10 (02) 100-114.
  • 49 Whitten P, Mylod D, Gavran G, Sypher H. Most wired hospitals rate patient satisfaction. Communications of the ACM 2008; 51 (04) 96-102.
  • 50 World Health Organization.. Working together for health:. world health report, 2006
  • 51 Yoder J, Johnson R. The Adaptive Object-Model Architectural Style. Proceedings of 3rd IEEE/IFIP Conference on Software Architecture: System Design, Development and Maintenance 2002. Kluwer; 2002 pp 3-27.