During the 2025 ECTRIMS, MS Nurse Pro held two nurse sessions, the second one with presentations from Noreen Barker, Christen Kutz and Stijn Denissen. They introduced how Shared Decision Making and new technologies, such as Artificial Intelligence, can improve treatment of Patients with Multiple Sclerosis.
You can find their presentation slides in our catalogue.
Otherwise known as SDM, it is a collaborative process where healthcare professionals incorporate the patient's values, preferences, and goals when making medical decisions. Its key features include:
Incorporating this concept can lead to better patient care through improving satisfaction and trust, enhancing adherence to treatment, reducing decisional regret and anxiety, and encouraging personalised care.
Devices, such as the MS-SUPPORT tool, an online, interactive, evidence-based decision aid developed in consultation with PwMS, can assist in the implementation of SDM. Its purpose is to generate a personalised summary of the patient's treatment goals, preferences, adherence, DMT use, and clinical situation, to be shared with their clinician before an appointment.
A study conducted by Col and colleagues looked at the efficacy of this tool and found that it successfully helped patients, a majority of whom (88%) strongly endorse it. As the results demonstrated, use of this tool increased adherence and improved mental-health in the short-term. Nevertheless, the paper has its limitation, like selection bias, response bias, social desirability bias and recall bias. Thus, for a more comprehensive view on the usefulness of SDM tools, further research is needed.
Specific research has also been conducted via collecting the opinion of women with MS who are (planning) pregnancy. The paper concluded that the MS-SUPPORT tool is generally user-friendly, but they also discovered difficulties in usability, such as filtering information and receiving contradictory recommendations. This shows that, while PDAs are useful for decision-making at initial diagnosis, work remains to be done in domains like pregnancy planning.
SDM aids:
Digital tools:
Treatment specific SDM aids:
The tool introduced in the previous section, MS-SUPPORT, is an example of a Patient Decision Aid (PDA). This umbrella term covers a variety of aids and tools:
A group of researchers, in collaboration with practitioners and various stakeholders developed the International Patient Decision Aid Standards (IPDAS). It is a common framework for PDAs regarding their content, development, implementation, and evaluation. First released in 2003, the resource is updated frequently to satisfy evolving medical standards.
The National Institute for Health and Care Excellence (NICE) also published a Standards framework for shared decision-making support tools. This document helps people using PDAs to determine their usefulness, and helps the developers of PDAs in conducting self-assessments as to the quality of their tools and processes. They proposed the following framework:
Is it worth incorporating PDAs into patient care? If you ask the scientific literature, it is going to tell you that it is very much worth it, though further research is necessary.
| Cochrane Library Review | Prototype Patient Decision Aid | CRIMSON Project | |
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Conclusions about PDAs from the literature:
Remainining challenges:
Shared decision-making in Multiple Sclerosis is portrayed as an ethical imperative. However, the question here is not whether SDM is ethical or moral, instead: does it actually work? In some instances, yes, because it helps decrease decisional conflict through higher self-efficacy and greater certainty and it does not increase neither anxiety nor depression rates. On the other hand, since 91% of patients prefer either autonomous or shared decision, there is no empirical evidence that PDAs are particularly effective for adherence and it resulted in clinical visits growing longer by an average of 2.55 minutes.
Consequently, improvements are needed, in which Artificial Intelligence can be of help. The literature reveals that there are 3 ways AI could aid decision-making:
The last finding is contested as other research found no difference in treatment quality between the algorithm and standard care.
Using AI for such personally sensitive topics also raises questions about potential risks. For instance, many of the models are black-box, meaning that their internal functioning is opaque. As with anything unknown, this can easily cause anxiety. Here, two approaches could provide a solution: a hybrid method where PDAs are concurrently used with clinicians during consultations or using explainable AI to counter the transparency problem.
Overall, AI is a technology that is going to continue influencing society, so for nurses to be able to use it as effectively and efficiently as possible, and be able to provide accurate advice to patients, they need to receive comprehensive trainings.
