title: Modeling workflow to design machine translation applications for public health practice.
abstract: OBJECTIVE
  Provide a detailed understanding of the information workflow processes related to translating health promotion materials for limited English proficiency individuals in order to inform the design of context-driven machine translation (MT) tools for public health (PH).
  
  
  METHODS
  We applied a cognitive work analysis framework to investigate the translation information workflow processes of two large health departments in Washington State. Researchers conducted interviews, performed a task analysis, and validated results with PH professionals to model translation workflow and identify functional requirements for a translation system for PH.
  
  
  RESULTS
  The study resulted in a detailed description of work related to translation of PH materials, an information workflow diagram, and a description of attitudes towards MT technology. We identified a number of themes that hold design implications for incorporating MT in PH translation practice. A PH translation tool prototype was designed based on these findings.
  
  
  CONCLUSIONS
  This study underscores the importance of understanding the work context and information workflow for which systems will be designed. Based on themes and translation information workflow processes, we identified key design guidelines for incorporating MT into PH translation work. Primary amongst these is that MT should be followed by human review for translations to be of high quality and for the technology to be adopted into practice.
  
  
  CONCLUSIONS
  The time and costs of creating multilingual health promotion materials are barriers to translation. PH personnel were interested in MT's potential to improve access to low-cost translated PH materials, but expressed concerns about ensuring quality. We outline design considerations and a potential machine translation tool to best fit MT systems into PH practice.
authors.affiliation: University of Washington Northwest Center for Public Health Practice, 1107 NE 45th Street, Suite 400, Box 354809, Seattle, WA 98105, USA; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA; Department of Health Services, University of Washington, Seattle, WA, USA. Electronic address: amturner@uw.edu.
authors.forename: Anne M
authors.initials: AM
authors.lastname: Turner
authors.affiliation: University of Washington Northwest Center for Public Health Practice, 1107 NE 45th Street, Suite 400, Box 354809, Seattle, WA 98105, USA.
authors.forename: Megumu K
authors.initials: MK
authors.lastname: Brownstein
authors.affiliation: Department of Health Services, University of Washington, Seattle, WA, USA.
authors.forename: Kate
authors.initials: K
authors.lastname: Cole
authors.affiliation: Public Health - Seattle & King County, Seattle, WA, USA.
authors.forename: Hilary
authors.initials: H
authors.lastname: Karasz
authors.affiliation: Department of Electrical Engineering, University of Washington, Seattle, WA, USA.
authors.forename: Katrin
authors.initials: K
authors.lastname: Kirchhoff
mesh_terms: D022126:Access to Information; D000465:Algorithms; D003142:Communication; D001330:Electronic Data Processing; D017144:Focus Groups; D006266:Health Education / Q000379:methods*; D006293:Health Promotion; D006297:Health Services Accessibility; D006801:Humans; D007802:Language; D000069550:Machine Learning; D011635:Public Health Administration; D040442:Public Health Informatics; D015980:Public Health Practice; D011785:Quality Assurance, Health Care; D014175:Translating; D014861:Washington; D057188:Workflow
keywords: Human centered design; Natural language processing; Public health informatics; Public health practice; Workflow