Display options
Cite
Van de Velde S, Macken L, Vanneste K, et al. Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach. JMIR Med Inform. 2015;3(4):e33doi: 10.2196/medinform.4450.
Van de Velde, S., Macken, L., Vanneste, K., Goossens, M., Vanschoenbeek, J., Aertgeerts, B., Vanopstal, K., Vander Stichele, R., & Buysschaert, J. (2015). Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach. JMIR medical informatics, 3(4), e33. https://doi.org/10.2196/medinform.4450
Van de Velde, Stijn, et al. "Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach." JMIR medical informatics vol. 3,4 (2015): e33. doi: https://doi.org/10.2196/medinform.4450
Van de Velde S, Macken L, Vanneste K, Goossens M, Vanschoenbeek J, Aertgeerts B, Vanopstal K, Vander Stichele R, Buysschaert J. Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach. JMIR Med Inform. 2015 Oct 09;3(4):e33. doi: 10.2196/medinform.4450. PMID: 26453372; PMCID: PMC4704970.
Copy Download .nbib Format: NLM
Share it on

JMIR Med Inform. 2015 Oct 09;3(4):e33. doi: 10.2196/medinform.4450.

Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach.

JMIR medical informatics

Stijn Van de Velde, Lieve Macken, Koen Vanneste, Martine Goossens, Jan Vanschoenbeek, Bert Aertgeerts, Klaar Vanopstal, Robert Vander Stichele, Joost Buysschaert

Affiliations

  1. EBMPracticeNet, Leuven, Belgium. [email protected].

PMID: 26453372 PMCID: PMC4704970 DOI: 10.2196/medinform.4450

Abstract

BACKGROUND: The construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, began in 2011 to optimize quality of care by promoting evidence-based decision making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL MultiTerm terminology databases) from medical terminology databases, and support from online machine translation. This resulted in a validated translation memory, which is now in use for the translation of new and updated guidelines.

OBJECTIVE: The objective of this experiment was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator.

METHODS: We conducted a pilot study in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (1) by certificated junior translators without medical specialization using the hybrid method, (2) by an experienced medical translator without this support, and (3) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The human translation edit rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of translation acceptability and adequacy.

RESULTS: The average number of words per guideline was 1195 and the mean total translation time was 100.2 minutes/1000 words. No meaningful differences were found in the translation speed for new guidelines. The translation of updated guidelines was 59 minutes/1000 words faster (95% CI 2-115; P=.044) in the computer-aided group. Revisions due to terminology accounted for one third of the overall revisions by the medical proofreader.

CONCLUSIONS: Use of the hybrid human and computer-aided translation by a non-expert translator makes the translation of updates of clinical practice guidelines faster and cheaper because of the benefits of translation memory. For the translation of new guidelines, there was no apparent benefit in comparison with the efficiency of translation unsupported by translation memory (whether by an expert or non-expert translator).

Keywords: education, medical, continuing; evidence-based practice; practice guidelines as topic; technology; translations

References

  1. JAMA. 2002 Jun 5;287(21):2851-3 - PubMed
  2. Educ Health (Abingdon). 2007 Nov;20(3):82 - PubMed
  3. BMC Med Inform Decis Mak. 2008 Jul 28;8:34 - PubMed
  4. J Appl Psychol. 1948 Jun;32(3):221-33 - PubMed
  5. BMJ. 2010 Jan 29;340:c306 - PubMed
  6. J Med Internet Res. 2010 Jul 07;12(3):e26 - PubMed
  7. BMJ. 2011 Sep 23;343:d5856 - PubMed
  8. Implement Sci. 2013 Mar 23;8:35 - PubMed
  9. JMIR Res Protoc. 2013 Jul 10;2(2):e23 - PubMed
  10. Appl Clin Inform. 2013 Apr 10;4(2):170-84 - PubMed
  11. Stud Health Technol Inform. 2013;192:486-90 - PubMed
  12. PLoS Med. 2013;10(9):e1001516 - PubMed
  13. JMIR Res Protoc. 2014 Nov 18;3(4):e66 - PubMed
  14. J Eval Clin Pract. 2017 Feb;23(1):21-28 - PubMed
  15. BMJ. 1996 Jan 13;312(7023):71-2 - PubMed

Publication Types