The document discusses a proposed solution to increase patient empowerment by making medical information more accessible and understandable. It describes a language interpretation engine that can analyze medical texts and generate simplified interpretations by automatically identifying and explaining medical terminology. The system was integrated into an existing tele-care system and showed promising accuracy rates in initial tests, though further testing is still needed. The goal is to help patients better understand their health by clarifying complex terminology.

1. Patient Empowerment by Increasing Information Accessibility I n a Telecare System Vasile Topac* E - mail: vasile.topac @aut.upt.ro Vasile Stoicu Tivadar* E - mail: vasile.stoicu [email_address] * “Politehnica” University of Timi şoara Department of Automation and Applied Informatics Timi şoara, Rom ânia

3. Study no.1 (study of accessibility of web page with medical information) “ … On existing consumer health Web pages. We found that only 4% of pages were classified at a layperson level, while the remaining pages were at the level of medical professionals. This indicates that consumer health Web pages are not using appropriate language for their target audience ” * - So 9 6% of pages were above layperson level! * Trudi Miller; Gondy Leroy; Samir Chatterjee; Jie Fan; Brian Thoms , A Classifier to Evaluate Language Specificity of Medical Documents, in HICSS 2007. 40th Annual Hawaii International Conference on System Sciences , 2007 Problem

4. "For twenty-three million Americans who speak English less than "very well," language barriers lead to lower quality of and worse access to health care. ... millions of patients with limited English proficiency forced to accept a lower quality of care than English speakers receive." *. Problem Study no.2 (study of accessibility of information for people with limited English proficiency in USA) * Mara K. Youdelman, The Medical Tongue: U.S. Laws And Policies On Language Access , Journal, 27, no. 2, 424-433; 2008 - Therefore several states have lows facilitating medial language access!

8. TELEASIS architecture: Our Case

9. - Sequences for accessing interpreted medical data: Patients accessing interpreted medical data

10. - Sequences for accessing interpreted medical data: We’ll focus on the Language Interpretation Engine Patients accessing interpreted medical data

11. Example Original Text: “ Aspiration of the marrow has been primarily utilized for cytologic assessment, with analysis directed toward morphology and obtainment of a differential cell count” Interpreted Text: “ Aspiration of the marrow has been primarily utilized for cytologic assessment (cytologic assessment = cells evaluation) with analysis directed toward morphology and obtainment of a differential cell count” - Example of how the interpretation is done by the Language Interpretation Engine:

20. Thank you! Contact: vasile.topac aut.upt.ro The article: http://www.ncbi.nlm.nih.gov/pubmed/21893834