Reports From the Field

Simple Patient Care Instructions Translate Best: Safety Guidelines for Physician Use of Google Translate

Journal of Clinical Outcomes Management. 2018 January;25(1)

References

1. Hummel J, Evans P. Providing clinical summaries to patients after each office visit: a technical guide. Qualis Health 2012. Accessed 14 Mar 2016 at http://hit.qualishealth.org/sites/default/files/hit.qualishealth.org/Providing-Clinical-Summaries-0712.pdf.

2. Neuberger M, Dontje K, Holzman G, et al. Examination of office visit patient preferences for the after-visit summary (AVS). Persp Health Infor Manage 2014;11:1d.

3. Kruse CS, Bolton K, Freriks G. The effect of patient portals on quality outcomes and its implications to meaningful use: a systematic review. J Med Internet Res 2015;17:e44.

4. Schoonover, K. Using a medical interpreter with persons of limited English proficiency. J Clin Outcomes Manage 2016;23:567–75.

5. Shin HB, Bruno R. Language use and English-speaking ability: 2000. Census 2000 Brief. Accessed 9 Nov 2017 at https://census.gov/content/dam/Census/library/publications/2013/acs/acs-22.pdf.

6. Lewis MP, Simons GF, Fennig CD, editors. Ethnologue: languages of the Americas and the Pacific. 19th ed. Dallas: Sil International; 2016.

7. Pavlik V, Brown AE, Nash S, et al. Association of patient recall, satisfaction, and adherence to content of an electronic health record (EHR)-generated after visit summary: a randomized clinical trial. J Am Board Fam Med 2014;27:209–18.

8. Johnson M, Schuster M, Le QV, et al. Google’s multilingual neural machine translation system: enabling zero-shot translation. Accessed 9 Nov 2017 at https://arxiv.org/pdf/1611.04558.pdf.

9. Patil S, Davies P. Use of Google Translate in medical communication: evaluation of accuracy. BMJ 2014;349:g7392.

10. Kaliyadan F, Gopinathan Pillai S. The use of Google language tools as an interpretation aid in cross-cultural doctor-patient interaction: a pilot study. Inform Prim Care 2010;18:141–3.

11. Zhang Y, Zhou S, Zhang Z, et al. Rumor evolution in social networks. Physical Review E 2013;87.

12. Shingenobu T. Evaluation and usability of back translation for intercultural communication. In: N. Aykin, editor. Usability and internationalization. Global and local user interfaces. UI-HCII 2007, Lecture Notes in Computer Science, vol 4560. Springer, Berlin, Heidelberg.

13. Kincaid JP, Fishburne Jr RP, Rogers RL, et al. Derivation of new readability formulas (automated readability index, fog count and Flesch reading ease formula) for Navy enlisted personnel. Naval Technical Training Command Millington TN Research Branch. 1975. Accessed 7 May 2016 at http://www.dtic.mil/dtic/tr/fulltext/u2/a006655.pdf.

14. Kwiecien R, Kopp-Schneider A, Blettner M. Concordance analysis—part 16 of a series on evaluation of scientific publications. Dtsch Arztebl Int 2011;108:515–21.

15. Goodall N. Ethical decision making during automated vehicle crashes. Transportation Research Record: Journal of the Transportation Research Board 2014;2424:58–65.

16. Kalra N, Groves D. The enemy of good: estimating the cost of waiting for nearly perfect automated vehicles. Santa Monica, CA: RAND Corporation, 2017.

17. Wu DT, Hanauer DA., Mei Q, et al. Assessing the readability of ClinicalTrials.gov. J Am Med Inform Assoc 2016;23:269–75.

18. Responses to: Use of Google Translate in medical communication: evaluation of accuracy. BMJ 2014;349:g7392 Accessed 10 Dec 2017 at www.bmj.com/content/349/bmj.g7392/rapid-responses.

19. Nápoles AM, Santoyo-Olsson J, Karliner LS, et al. Inaccurate language interpretation and its clinical significance in the medical encounters of Spanish-speaking Latinos. Med Care 2015;53:940–7.

Conclusion

This study suggests that 9 times out of 10, the quality of machine translation using Google Translate is acceptable in terms of quality and safety. Currently, machine back translation may fail to reveal a relatively poor translation from English to Spanish. This study showed that increasing sentence complexity, as measured by the reading level index, was associated with a significant (P < 0.05) increase in unsafe machine translation. Similarly, including medication instructions in machine translations were associated with increased risk (P < 0.05) of machine translation safety error in this study.

A simple way to improve communication now would be to display the reading level to authors of patient communication content in real time, and limit the dictionary of acceptable words to forbid the use of known ambiguous terms or forbidden abbreviations. This would teach authors to use simple language, and increase the chance that translation (either human or machine) would be effective. This preliminary study suggests that keeping medication dosing instructions in a structured format is advisable, as is keeping sentences simple. As with spoken language [4], starting with clear, simple to understand English instructions provides the best machine translations into Spanish.

The Clinical Machine Translation Study Group: Todd W. Altenbernd, Steven Bedrick, Mark D. Berg, Nerida Berrios, Mark A. Brown, Colleen K. Cagno, Charles B. Cairns, Elizabeth Calhoun, Raymond Carmody, Tara F. Carr, Clara Choo, Melissa L. Cox, Janiel Cragun, Rachel E.M. Cramton, Paola Davis, Archita Desai, Sarah M. Desoky, Sean Elliot, Mindi J. Fain, Albert Fiorello, Hillary Franke, Kimberly Gerhart, Victor Jose Gonzalez, Aaron John Goshinska, Lynn M. Gries, Erin M. Harvey, Karen Herbst, Elizabeth Juneman, Lauren Marie Imbornoni, Anita Koshy, Lisa Laughlin, Christina M. Laukaitis, Kwan Lee, Hong Lei, Joseph M. Miller, Prashanthinie Mohan, Wayne J. Morgan, Jarrod Mosier, Leigh A. Neumayer, Valentine Nfonsam, Vivienne Ng, Terence O'Keeffe, Merri Pendergrass, Jessie M. Pettit, John Leander Po, Claudia Marie Prospero Ponce, Sydney Rice, Marie Anoushka Ricker, Arielle E. Rubin, Robert J. Segal, Aurora A.G. Selpides, Whitney A. Smith, Jordana M. Smith, William Stevenson, Amy N. Sussman, Ole J. Thienhaus, Patrick Tsai, J. Daniel Twelker, Richard Wahl, Jillian Wang, Mingwu Wang, Samuel C. Werner, Mark D. Wheeler, Jason Wild, Sun Kun Yi, Karl Andrew Yousef, Le Yu.

Corresponding author: Joseph M. Miller, MD, MPH, Department of Ophthalmology and Vision Science, University of Arizona, 655 North Alvernon Way, Suite 108, Tucson AZ 85711, jmiller@eyes.arizona.edu.

Financial disclosures: None.