Grant: Collaborative Research and Development Grants

Present-day health-information material is often limited in its effectiveness by the need to address it to a wide audience.  What is generally produced is either a minimal, generic document that contains only the information common to everyone, or a maximal document that tries to provide all the information that might be relevant to someone (and hence much that is irrelevant to many). But material that contains irrelevant information, or omits relevant information, or that for any other reason just doesn't seem to be addressed to the particular reader is likely to be discounted or ignored, with consequent problems in motivation for compliance with medical regimens, health-related lifestyle improvements, and so on. Recognizing this, health educators have paid much attention to methods of identifying different segments of their audience and their differing needs and constructing material accordingly, but at some level, the material remains generic.  An effective means of providing patient-centric health care would be through the personalization of health information: with individually tailored information, the patient would be both better-educated about their specific condition and better able to make informed decisions. The goal of our research is to develop Natural Language Generation tools and methodologies that can be used to deliver health educational materials tailored to the needs of the individual patient in a timely and accessible manner through Web-based systems.  Our initial domain of application is reconstructive breast surgery, but the Natural Language software tools and authoring methodologies we will produce will be generally applicable to all medical interventions.