Alison Cawsey

Patient information systems that tailor to the individual

The potential of computers in patient education has been well described by Skinner et al. One of their recommendations was for more personalized systems. In this article we discuss how computer-based patient information systems can provide material that is tailored to the individual, giving a number of examples of systems developed in Scotland. We review some of the techniques used in developing tailored systems, and consider the evidence to date as to their efficacy.

Personalized and adaptive systems for medical consumer applications

We have developed a range of systems that synthesize text at a fine grain—down to phrases within individual sentences—in real time, using natural language generation techniques from artificial intelligence (see our review in [3] of other work using these techniques), and provide information that is most personally relevant to the patient. We use the patient’s own medical record as a basis for selecting, linking, and filtering information. In our systems for cancer and diabetes, we provide a summary of the patients’ medical record plus hypertext pages of more general information. Items from the medical record are automatically linked to the appropriate general pages, so patients have direct access to the most relevant information, whereas a nonpersonalized version would require users to search or navigate through many medical terms. Our systems can also select personal reminders to add to the general information based on the patient’s medical record, as depicted in the accompanying figure. In a randomized trial, we found cancer patients valued information that included details from their own medical records more highly than general information alone [2]. We use information associated with the patients’ medical records to filter out irrelevant material and allow patients to focus on the most relevant information, for example, to offer detailed information about a treatment only to those patients who are having that treatment. This is especially valuable when producing printed material where space is limited. Personalized and Adaptive Systems for

Generating Personalised Patient Information Using the Medical Record

This paper presents an approach for providing patients with personalised explanations of their medical record. Simple text planning techniques are used to construct relevant explanations based on information in the record and information in a general medical knowledge base. We discuss the results of the evaluation of our system with diabetes patients at three diabetes clinics in Scotland.

User modelling in interactive explanations

In this paper I consider how user modelling can be used to improve the provision of complex explanations, and discuss in detail the user modelling component of the EDGE explanation system. This allows a user model to be both updated and used in an explanatory dialogue with the user. The model is updated based on the interactions with the user, relationships between concepts and a reviseable expertise level. The model in turn influences the planning of the explanation, allowing a more understandable explanation to be generated. I argue that both user modelling and an “interactive” style of presentation are important for explanations to be acceptable and understandable, and that each reinforces the other.

Natural language generation in health care

Good communication is vital in health care, both among health care professionals, and between health care professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying, and even more convincing than the structured data, even when presented in tabular or graphic form. Documents may be automatically generated from structured data, using techniques from the field of natural language generation. These techniques are concerned with how the content, organization and language used in a document can be dynamically selected, depending on the audience and context. They have been used to generate health education materials, explanations and critiques in decision support systems, and medical reports and progress notes.

Adaptive information for consumers of healthcare

This chapter discusses the application of some of the technologies of the adaptive web to the problem of providing information for healthcare consumers. The particular issues relating to this application area are discussed, including the goals of the communication, typical content of a user model, and commonly used techniques. Two case studies are presented, and evaluation approaches considered.

Presenting tailored resource descriptions: will XSLT do the job?

Abstract The problem of finding relevant resources from those available across the World Wide Web is well recognised. Improved search engines provide part of the answer, but we also need to support the user in assessing for themselves the relevance of documents suggested by a search engine, prior to download. One way to do this is to provide them with descriptions tailored to their profile and query. This paper presents examples of how XSLT may be used to create tailored descriptions from RDF metadata, and explores whether XSLT is an adequate tool for this task.

Culture–personality based affective model

Bringing culture and personality in a combination with emotions requires bringing three different theories together. In this paper, we discuss an approach for combining Hofstede’s cultural dimensions, BIG five personality parameters and PSI theory of emotions to come up with an emergent affective character model.

Does writing a list help cancer patients ask relevant questions

We examined the use of written lists to give patients an opportunity to have their questions answered. Patients undergoing radical radiotherapy for cancer were given a sheet of paper with the simple prompt to write questions and give to the hospital doctor at their appointment 3 weeks later. At 3 months, patients were asked about their use and opinions of the written list. About half of the 478 patients attended with a written list. Fewer patients living in deprived areas used the list compared to more affluent areas. Doctors thought that 34% of patients would not otherwise have asked those questions and 91% of prompted discussions were a worthwhile use of time.

A Conversational Model for Health Promotion on the World Wide Web

In this paper we describe a new approach to computer-based health promotion, based on a conversational model. We base our model on a collection of human-human email dialogues concerning healthy nutrition. Our system uses a database of tips and small pieces of advice, organised so that support for the advice, and arguments against the advice may be explored. The technical framework and initial evaluation results are described.