Research indicates that the text on many popular web sites is difficult to understand and consumers find that reading documents in electronic format is problematic. Since health information read online influences the patient-doctor relationship - e.g., treatments requested, or perceived patient value from a doctor's visit - it is important that this information be interpreted and remembered as completely and correctly as possible. Misunderstandings in health information may increase the risk of making unwise health decisions, which could lead to poorer health and higher health care costs. The goal of the project is to develop and test new technology that can present online health information that is easier to understand and remember. Prototypes will be developed that will visualize both the structure and content of web pages to increase understanding and retention without oversimplification. A small pilot study has shown positive effects of such a representation. The two prototypes will differ in how much content detail is included in the visualization. They will be evaluated for their effects on understanding and retention of information and compared with currently existing web sites. User behavior and preferences will also be captured and analyzed. Three user groups will participate in the development and evaluation of the prototypes: elderly consumers, Hispanic non-native speakers, and patients. These groups were chosen for their specific characteristics (age related problems, sub-optimal command of English, and patients' stress) that may require improved information presentation.

Medical/Health Lexicon with POS for GATE Users
We reformatted the UMLS Specialist Lexicon and combined it with the original GATE lexicon (17,831 entries). The final lexicon contains 271,157 items. For those words that appear in both lexicons, we used only GATE tags. For example, "where" is tagged as possibly an adjective, conjunction, or noun in the UMLS Specialist Lexicon, but only as a wh-adverb in GATE. In addition, we tuned the lexicon in a few cases to increase tagging performance: the tags for "cold" were swapped resulting in the entry cold NN JJ" instead of "cold JJ NN," for "elderly"' we added a NN tag.

Download GATE-UMLS-COMBO lexicon [4.1 MB] -- If you use this combined lexicon, please refer to G. Leroy, E. Eryilmaz, and B. T. Laroya, "Health Information Text Characteristics", American Medical Informatics Association (AMIA) Annual Symposium, Washington DC, November 11-15.

Consumer-friendly Labels
Increasing focus has been placed on bridging the gap between clinician and layperson communications. To utilize resources like the UMLS Semantic Network with laypeople requires that clinical terminology be replaced with labels that can be understood by people without medical training. We have generated two sets of labels for the Semantic Types and Semantic Groups; the first in conjunction with a medical librarian and the second validated by consumers themselves.

• Medical Librarian labels -- If you use these labels, please refer to T. Miller, G. Leroy, and E. Wood, "Dynamic Generation of a Table of Contents with Consumer-Friendly Labels", American Medical Informatics Association (AMIA) Annual Symposium, Washington DC, November 11-15.
• Consumer validated labels: [COMING SOON]

Consumer Health Vocabulary
We use the Consumer Health Vocabulary (CHV) to map difficult terms to easier variants. Acting as an intermediate, CHVs can assist us in bridging the gap between complex clinical language and language understood by laypeople. This CHV initiative is an ongoing collaboration among medical and informatics academics, clinicians, and practioners from around the world.

• Gondy Leroy
• Trudi Miller
• Elizabeth Wood
• Jie Fan

• A. Keselman, C. Arnott Smith, G. Divita, H. Kim, A. Browne, G. Leroy, Q. Zeng-Treitler, Consumer Health Concepts that do not Map to the UMLS: Where Do They Fit?, Journal of the American Medical Informatics Association (JAMIA), Forthcoming 2008.
• G. Leroy, T. Miller, G. Rosemblat, and A. Browne, "A Balanced Approach to Health Information Evaluation: A Vocabulary-based Naive Bayes Classifier and Readability Formulas", Journal of the American Society for Information Science and Technology (JASIST), Forthcoming 2008.[pdf]
• T. Miller and G. Leroy, "Dynamic Generation of a Health Topics Overview from Consumer Health Information Documents", International Journal of Biomedical Engineering and Technology. Forthcoming.[pdf]
• G. Leroy, "Improving Literacy with Information Technology," in Encyclopaedia of Healthcare Information Systems, N. Wickramasinghe and E. Geisler, Ed.: Idea Group, Inc, Forthcoming 2007.[pdf]
• T. Miller, G. Leroy, S. Chatterjee, J. Fan, and B. Thoms, "A Classifier to Evaluate Language Specificity of Medical Documents," Fortieth Annual Hawaii International Conference on System Sciences (HICSS), Waikoloa, Big Island, Hawaii, January 3-6, 2007, [pdf].
• T. Miller, G. Leroy, and E. Wood, "Dynamic Generation of a Table of Contents with Consumer-Friendly Labels", American Medical Informatics Association (AMIA) Annual Symposium, Washington DC, November 11-15, 2006 [pdf].
• G. Leroy, E. Eryilmaz, and B. T. Laroya, "Health Information Text Characteristics", American Medical Informatics Association (AMIA) Annual Symposium, Washington DC, November 11-15, 2006 [pdf].