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The adaptive web

Personalized and Adaptive Systems For Medical Consumer Applications


Personalized and adaptive material have great potential for providing health-related information to medical consumers—to patients and to the general public. Health professionals have taken advantage of techniques such as mail merge to produce printed letters and leaflets that incorporate information for specific individuals. Adaptive and tailored messages have contributed to smoking cessation, increasing physical exercise, and improving diets, as well as helping patients to manage illnesses such as asthma and diabetes for themselves [3].

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. We have implemented an information system for cancer patients based on a psychologically motivated model of cancer patients' information needs at different times following diagnosis [1].

Tailoring the information presented to each patient can introduce some difficulties, which must be addressed in the design. To avoid confusing patients, adaptations must be embedded within a consistent interface. Although patients may benefit from interactive information, they often wish to print out information to read at their leisure and to share with their families. However, tailored material, which is easily presented on an interactive screen, may not be so easily reproduced as attractive and readable printouts. It is therefore important, but not always easy, to assess the benefits of tailored compared to generic information [4].

We are now undertaking a study to evaluate the psychological effectiveness of tailored information for patients with cancer, considering both online access and paper leaflets. We are examining both online access to information and the use of leaflets in the home (discussions with family and friends). We aim to model the latter as a function of three factors: whether the information is personalized based on the medical record; whether the patients select the information themselves; and whether the information includes anxiety management advice. In the study, all patients have an initial opportunity to browse the information online and then receive a printout to take home. The information presented to patients online, and the way the printouts are constructed, varies across groups. In this and other studies, we hope to identify where personalization will bring the greatest benefits to patients.

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References

1. Bental, D., Cawsey, A., Pearson, J., and Jones, R. Adapting Web-based information to the needs of patients with cancer. In Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (Trento, Italy, Aug. 2000), 27–37.

2. Jones, R., Pearson, J., McGregor, S., Cawsey, A., Barrett, A., Craig, N. et al. Randomised trial of personalised computer-based information for cancer patients. British Medical Journal 319 (1999), 1241–1247.

3. Patient Education and Counselling 36, 2 (Special Issue on Computer Tailored Health Education). Elsevier, Ireland, 1999.

4. Reiter, E., Robertson, E., Lennox, S., and Osman, L. Using a Randomised Controlled Clinical Trial to Evaluate a Natural Language Generation System. ACL Press, 2001.

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Authors

Diana Bental (diana@cee.hw.ac.uk) is a research associate in the Department of Computing and Electrical Engineering, Heriot-Watt University, Edinburgh, U.K.

Alison Cawsey (alison@cee.hw. ac.uk) is a lecturer in the Department of Computing and Electrical Engineering, Heriot-Watt University, Edinburgh, U.K.

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Figures

UF1Figure. Sample hypertext for a patient with diabetes.

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