Healthc Inform Res.  2013 Dec;19(4):286-292. 10.4258/hir.2013.19.4.286.

Contribution of Clinical Archetypes, and the Challenges, towards Achieving Semantic Interoperability for EHRs

• Tapuria A
• Kalra D
• Kobayashi

• KMID: 2229504
• DOI: http://doi.org/10.4258/hir.2013.19.4.286

Abstract

OBJECTIVES
The objective is to introduce 'clinical archetype' which is a formal and agreed way of representing clinical information to ensure interoperability across and within Electronic Health Records (EHRs). The paper also aims at presenting the challenges building quality labeled clinical archetypes and the challenges towards achieving semantic interoperability between EHRs.
METHODS
Twenty years of international research, various European healthcare informatics projects and the pioneering work of the openEHR Foundation have led to the following results.
RESULTS
The requirements for EHR information architectures have been consolidated within ISO 18308 and adopted within the ISO 13606 EHR interoperability standard. However, a generic EHR architecture cannot ensure that the clinical meaning of information from heterogeneous sources can be reliably interpreted by receiving systems and services. Therefore, clinical models called 'clinical archetypes' are required to formalize the representation of clinical information within the EHR. Part 2 of ISO 13606 defines how archetypes should be formally represented. The current challenge is to grow clinical communities to build a library of clinical archetypes and to identify how evidence of best practice and multi-professional clinical consensus should best be combined to define archetypes at the optimal level of granularity and specificity and quality label them for wide adoption. Standardizing clinical terms within EHRs using clinical terminology like Systematized Nomenclature of Medicine Clinical Terms is also a challenge.
CONCLUSIONS
Clinical archetypes would play an important role in achieving semantic interoperability within EHRs. Attempts are being made in exploring the design and adoption challenges for clinical archetypes.

Keyword

Electronic Health Records; Semantics; Health Information Management

MeSH Terms

Consensus
Delivery of Health Care
Electronic Health Records
Health Information Management
Informatics
Practice Guidelines as Topic
Semantics*
Sensitivity and Specificity
Systematized Nomenclature of Medicine

Figure

• 

  Figure 1 Example screen showing the main portion of an archetype for adverse reaction (to medication).

Reference

1. Kalra D. ISO/DIS 18308 Requirements for an Electronic Health Record reference architecture. Geneva, Switzerland: International Organization for Standardization;2010.

2. Kalra D, Lloyd D. ISO 13606 Electronic Health Record communication. Part 1: Reference Model. Geneva, Switzerland: International Organization for Standardization;2008.

3. Kalra D. ISO 13606 Electronic Health Record communication. Part 3: Reference archetypes and term lists. Geneva, Switzerland: International Organization for Standardization;2009.

4. Kalra D. ISO/TS 13606 Electronic Health Record Communication. Part 4: Security. Geneva, Switzerland: International Organization for Standardization;2009.

5. Kalra D. ISO/EN 13606 Electronic Health Record communication. Part 5: Interface specification. Geneva, Switzerland: International Organization for Standardization;2010.

6. Kalra D, Beale T, Lloyd D, Heard S. ISO 13606 Electronic Health Record communication. Part 2: Archetype interchange specification. Geneva, Switzerland: International Organization for Standardization;2008.

7. openEHR [Internet]. London: openEHR Foundation;2013. cited at 2013 Dec 1. Available from: http://www.openehr.org.

8. SemanticHealthNet [Internet]. [unknown]: SemanticHealthNet;2013. cited at 2013 Dec 1. Available from: http://www.semantichealthnet.eu.

9. Kalra D. Clinical foundations and information architecture for the implementation of a federated health record service [dissertation]. London: University College London;2002.

10. Smith R. What clinical information do doctors need? BMJ. 1996; 313(7064):1062–1068.

11. Patterson D, Ingram D, Kalra D. Information for clinical governance. In : Lugon M, Secker-Walker J, editors. Clinical governance: making it happen. London: The Royal Society of Medicine Press;1999.

12. Waegemann CP. Medical Record Institute's survey of electronic health record trends and usage. In : Proceedings of Toward an Electronic Health Record Europe '99; 1999 Nov 14-17; London, UK. p. 147–158.

13. Audit Commission for Local Authorities and the National Health Service in England and Wales. A spoonful of sugar: medicines management in NHS hospitals. London: Audit Commission;2001.

14. Kohn LT, Corrigan JM, Donaldson MS. To err is human: building a safer health system. Washington (DC): National Academies Press;2000.

15. Hammond WE, Pollard DL, Straube MJ. Managing healthcare: a view of tomorrow. Stud Health Technol Inform. 1998; 52(Pt 1):26–30.

16. Rothschild AS, Dietrich L, Ball MJ, Wurtz H, Farish-Hunt H, Cortes-Comerer N. Leveraging systems thinking to design patient-centered clinical documentation systems. Int J Med Inform. 2005; 74(5):395–398.

17. Martinez-Costa C, Menarguez-Tortosa M, Fernandez-Breis JT. An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes. J Biomed Inform. 2010; 43(5):736–746.

18. Rector AL, Nowlan WA, Kay S. Foundations for an electronic medical record. Methods Inf Med. 1991; 30(3):179–186.

19. Lopez DM, Blobel BG. A development framework for semantically interoperable health information systems. Int J Med Inform. 2009; 78(2):83–103.

20. Health Level Seven International. Using SNOMED CT in HL7 Version 3: Implementation Guide, Release 1.5 [Internet]. Ann Arbor (MI): Health Level Seven International;2009. cited 2013 Dec 1. Available from: http://wiki.hl7.org/index.php?title=Using_SNOMED_CT_in_HL7_Version_3;_Implementation_Guide,_Release_1.5.

21. Nightingale PG, Adu D, Richards NT, Peters M. Implementation of rules based computerised bedside prescribing and administration: intervention study. BMJ. 2000; 320(7237):750–753.

22. Bates DW. Using information technology to reduce rates of medication errors in hospitals. BMJ. 2000; 320(7237):788–791.