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Use case: PROSPECT: personalized health decision aid facilitated by the PHT

Development of a prostate cancer decision aid, with personalized content facilitated by the PHT.

Medical relevance

This personalized decision aid enables shared decision making by providing (personalized) information to patients, which enables them to choose, assisted by their physician, a treatment that suits them best.

Description

Patients with prostate cancer can choose between four treatment options with similar survival rates. However, without the right information, patients cannot decide which treatment fits the best with their personal life, wants and needs.

We previously developed a decision aid providing patients with structured information on all four treatment options. However, what may be relevant to one patient may not be relevant to another. For example, patients who are already incontinent will be more likely to develop more severe incontinence whereas others most likely will not become incontinent at all as result of treatment. Yet, all patients receive the same information. We therefore aim to develop a personalized decision aid for prostate cancer patients. Through artificial intelligence, patients will get personalized insight in their chances to develop specific side effects such as incontinence and erectile dysfunction. The personal health train will play a role in this project. It enables us to automatically send the information the AI models require to the tool. So, patients or physicians do not have to enter the relevant data manually.

Main results

We have developed a prostate care decision aid and are currently developing the user interface. We already developed several AI models that accurately predict incontinence and erectile dysfunction.

Lessons learned

The threshold for the use of technology by doctors and patients should be as low as possible. If it takes a lot of manual work, technologies will not be picked up and used in the clinic.

Follow up

We are aiming for proving the cost-effectiveness of personalized decision aids compared to usual care with a special emphasis on the personalized aspect of this particular decision aid.

Project details

Project leader

Rianne Fijten

Funders National Health Care Institute (ZIN)
Collaboration partners

Hogeschool Zuyd / Maastro / MUMC+ / Maastricht University / NKI/AVL / Radboud UMC

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