Connect
MJA
MJA

Developing a national emergency department data reference set based on SNOMED CT

David P Hansen, Madonna L Kemp, Sandra R Mills, Megan A Mercer, Paul A Frosdick and Michael J Lawley
Med J Aust 2011; 194 (4): S8. || doi: 10.5694/j.1326-5377.2011.tb02934.x
Published online: 21 February 2011

Abstract

Data quality and patient safety

Appropriate and clear communications are a major contributor to patient safety within health care environments,4 and this includes information captured for future use in electronic systems. With the advent of electronic health records, the recording of clinical data within EDs is becoming increasingly important, with patient information from the ED visit being included in hospital admission notes and discharge summaries. Current ED data collections focus more on performance data rather than providing efficient and consistent information on the condition diagnosed and the treatment phase of the patient. With about three out of five presentations to Australian EDs leading to a hospital admission,5 recording information on diagnosis is vital in determining and communicating the treatment pathway for a patient through the ED and beyond, in both primary and secondary health care settings.

Contrasting ICD-10-AM and SNOMED CT

Diagnostic classifications such as ICD-10-AM typically do not offer the detail required to adequately record patient data for meaningful use in an actual situation at the point of care. In contrast, the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) is a large and comprehensive clinical terminology that enables consistent documentation, exchange and aggregation of data on clinical encounters, and facilitates representing clinically relevant information in electronic health records.6 SNOMED CT has a hierarchical structure made up of concepts and descriptions for these concepts as well as the relationships between them.

As a standard, SNOMED CT complies with Cimino’s seminal desiderata for 21st century medical terminology,7,8 and has been recognised as the most comprehensive clinical terminology available.9 It has been adopted as the principal clinical terminology supporting 15 of the world’s leading national e-health implementation programs.10 The Australian version of SNOMED CT, termed SNOMED CT-AU, which is maintained and distributed by the National E-Health Transition Authority (NEHTA), has one key difference — the identification of content suitable for the Australian health system.

The following example highlights the difference between how a condition such as “Osteoarthritis of knee” is defined using ICD-10-AM and SNOMED CT. In ICD-10-AM, “Osteoarthritis of knee” is represented as “M17.9 – Gonarthrosis, unspecified” in the section “Diseases of the musculoskeletal system and connective tissue” under the heading “Arthropathies”.2 However, in SNOMED CT, this condition is explicitly represented by a series of “IS A” relationships, defining the parent and ancestor concepts, to give greater knowledge of the disorder. Its position within the hierarchy, with parent concept “Arthropathy” and ancestor concepts including “Disorder of musculoskeletal system” and “Joint finding”, is shown in the Box(A). Concepts in SNOMED CT may be fully modelled as shown in the Box(B): in this case, “Osteoarthritis of knee” has an additional relationship “Finding site” with value “Joint structure”. These definitional characteristics of SNOMED CT are what make it more suitable for clinical use and for computer-based systems.

The Australian ED reference set (EDRS)

The Snapper platform is being used by NEHTA to develop the EDRS, and the first version based on SNOMED CT-AU has recently been released. The SNOMED CT-AU concepts in the EDRS will be used in future ED data collections and contribute to national ED data, including the NNAPEDCD.

The first version of the EDRS contains 4000 concepts sub-divided to support entry to the diagnosis and presenting problem sections of current information systems. There are still another 3000 terms that could be added to the reference set, but these will require additional modelling and clinical validation.

To ensure the clinical relevance of the EDRS content, inclusions are chosen by a committee of senior ED clinicians from each state and territory, chaired by the ED clinical policy leader at the Australian Government Department of Health and Ageing.

  • David P Hansen1
  • Madonna L Kemp1
  • Sandra R Mills2
  • Megan A Mercer2
  • Paul A Frosdick2
  • Michael J Lawley1

  • 1 Australian e-Health Research Centre, CSIRO ICT Centre, Brisbane, QLD.
  • 2 National E-Health Transition Authority, Sydney, NSW.


Correspondence: David.Hansen@csiro.au

Competing interests:

The CSIRO has received licence fees from the International Health Terminology Standards Development Organisation and NEHTA for use of the Snapper software. NEHTA is funded by the Australian Government Department of Health and Ageing.

  • 1. Australian Institute of Health and Welfare. National non-admitted patient emergency department care data service. http://www.aihw.gov.au/hospitals/napedc_database.cfm (accessed Feb 2010).
  • 2. International classification of diseases and related health problems, 10th revision. Volume 2. Second revision. 2.1 Purpose and applicability. http://www.who.int/classifications/icd/ICD-10_2nd_ed_volume2.pdf (accessed Nov 2010).
  • 3. Johnston T, Endo T. Data quality issues impacting on reporting on presentations to emergency departments in Queensland hospitals: data quality issues in emergency department data, 2007–08 update. Technical report — emergency department data report #2. Brisbane: Health Statistics Centre, Queensland Health, 2009.
  • 4. Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital-based and primary care physicians. JAMA 2007; 297: 831-841.
  • 5. Australian Institute of Health and Welfare. Australian hospital statistics 2007–08. Chapter 5: Non-admitted patient care. Canberra: AIHW, 2009. (AIHW Cat. No. HSE 71; Health Services Series No. 33.) http://www.aihw.gov.au/publications/hse/hse-71-10776/hse-71-10776-c05.pdf (accessed Dec 2009).
  • 6. International Health Terminology Standards Development Organisation. SNOMED Clinical Terms (SNOMED CT) International release, January 2009. http://www.cap.org/apps/docs/snomed/documents/january_2009_release.pdf (accessed Dec 2009).
  • 7. Cimino JJ, Hripcsak G, Johnson SB, Clayton PD. Designing an introspective, multi-purpose controlled medical vocabulary. In: Kingsland LC, editor. Proceedings of the 13th Annual Symposium on Computer Applications in Medical Care; 1989 Nov 5-8; Washington, DC. Washington, DC: IEEE Computer Society Press, 1989: 513-518.
  • 8. Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med 1998; 37: 394-403.
  • 9. Elkin PL, Brown SH, Husser CH, et al. Evaluation of the content coverage of SNOMED CT: ability of SNOMED clinical terms to represent clinical problem lists. Mayo Clin Proc 2006; 81: 741-748. http://www.mayoclinicproceedings.com/content/81/6/741.full (accessed Sep 2010).
  • 10. International Health Terminology Standards Development Organisation. Members of IHTSDO. http://www.ihtsdo.org/members (accessed Sep 2010).
  • 11. Rosenbloom ST, Brown SH, Froehling D, et al. Using SNOMED CT to represent two interface terminologies. J Am Med Inform Assoc 2009; 16: 81-88.

Author

remove_circle_outline Delete Author
add_circle_outline Add Author

Comment
Do you have any competing interests to declare? *

I/we agree to assign copyright to the Medical Journal of Australia and agree to the Conditions of publication *
I/we agree to the Terms of use of the Medical Journal of Australia *
Email me when people comment on this article

Online responses are no longer available. Please refer to our instructions for authors page for more information.