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2006 Winner

Development and evaluation of a decision aid for shared decision-making in patients with metastatic neuroendocrine tumours using decision analysis techniques

Applicant:

Adil Ahmed
Research Registrar
Gastroenterology Dept
North Hampshire Hospital NHS trust, Basingstoke
& Honorary Registrar Kings College Hospital, United Kingdom

Abstract:

Shared decision making, is where patients and health professionals join in both the process of decision-making and ownership of the decision made. Patient involvement in decision-making increases adherence to treatment choices and improves satisfaction and the appropriateness of interventions. Decision aids do a better job than standard care in improving patient’s knowledge about options and create more realistic expectations. They enhance active participation in decision making, lower decisional conflict and decrease the proportion of people remaining undecided.

Neuroendocrine tumours (NET’s) originate from neuroendocrine cells and present with hypersecretory syndromes characterised by flushing, diarrhoea and wheezing. In patients with incurable tumour there are several treatment options with risks and benefits varying from patient to patient. Decision making here is extremely difficult necessitating constant up-to-date medical evidence. The analytical process needed for tailoring it to individual patient is complex. Patient involvement in such a process is all the more difficult.

Decision analysis is a process that offers an explicit and systematic approach to decision making. It has already been used in a variety of health care settings including breast and ovarian cancer.

We aim to develop a computerised decision aid which will offer a decision analysis based opinion/recommendation as to the optimal course of action for patients with incurable metastatic NET’s. We will use the decision aid to elicit patient preferences regarding the available treatment options. This will be synthesised using decision analysis techniques with the up-to-date medical evidence already loaded in the decision aid. The decision aid recommendation will thus form a platform for the shared decision-making.

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