Designing computer-based frameworks that facilitate doctor--patient collaboration.

A current trend in medicine involves establishing collaborative problem solving between patients and physicians in order to involve patients more in their own care. Neither diagnosis nor therapy can be completely successful unless the patient and the doctor understand each other and collaborate with each other in an effort to gauge the other's requests, needs and concerns. This is made even more difficult by the fact that there is often a big difference between the doctors and patients in terms of expectations, vocabulary used, and other factors. For diagnosis of many disorders, a detailed description of the problem and of the patient's history are required. For therapy, patients must understand how and when to take prescribed drugs, what changes to make in diet, exercise, or lifestyle and why they are important. This paper describes a model of asynchronous collaboration between people with very different knowledge of medicine in which a computer framework attempts to mediate between patients and physicians and reduce some of the differences in communication. It allows patients to pace themselves in familiarizing themselves with the relevant domain terms, some of the medical factors underlying the conditions under question, and the justifications and implications of the prescribed treatment plan. It also allows physicians to request more information of patients and gives patients contextual information to help them understand the underlying reasons for the questions. This framework has been partially implemented in the domain of migraines. As described in the paper, not only is the system designed to cooperate with the patient, but using the system also results in better mutual understanding between the doctor and the patient, thus leading to better collaboration between them.

Generating patient-specific interactive natural language explanations.

Patient compliance is a significant problem and is strongly correlated with the patients' understanding of their condition and prescribed treatment. Since doctors typically do not have large amounts of time to educate patients, and impersonal, voluminous patient handouts are largely ineffective, we propose the use of a sophisticated computer-based information system to generate tailored, interactive handouts to communicate with patients. Our system uses text planning and user modeling techniques to generate natural language descriptions of migraine, its symptoms, triggering factors and prescriptions. The system is capable of handling follow-up questions requesting further information, and generating responses in the context of previously supplied information--a capability unavailable in previous patient information systems. The system tailors its interaction to: (i) the class of migraine patients, (ii) the individual patient, and (iii) the previous dialogue. Preliminary evaluation of the system indicates that patients find it useful and informative. More extensive evaluation is in progress.