News

Helping match patients with mental health professionals: Advancing the MatchMind Project

Helping match patients with mental health professionals: Advancing the MatchMind Project

This collaborative initiative is coordinated by the Mental Health Cluster of Catalonia with the participation of the Cluster Innovative Solutions for Independent Living (SIVI), our partner INTRAS Foundation and the companies ITA Clinic, MEDEA MIND and ISALUS.

 

We continue to make progress in the exciting journey in which we have been immersed for some months now, the MatchMind Project: Algorithm for personalising the assignment of patients to mental health professionals.

 

This collaborative initiative is coordinated by the Mental Health Cluster of Catalonia with the participation of the Cluster Innovative Solutions for Independent Living (SIVI), our partner INTRAS Foundation and the companies ITA Clinic, MEDEA MIND and ISALUS.

 

Together, we have embarked on the innovative development of a matching system between patients and professionals to improve the results of the therapeutic process.

 

This system will use clinical and demographic variables of the patient, together with the therapeutic style, personality, area of experience, as well as other variables of the professionals with the aim of assigning each patient to the most suitable professional.

 

To this end, we will develop two evaluation protocols (one for patients and the other for professionals) where the most relevant variables for the selection of the professional will be evaluated. The information collected by these protocols will feed a personalisation algorithm, in charge of matching patients and professionals based on their data.

 

A glimpse into the soul of MATCH MIND:

At its core, MATCH MIND aims to develop software for matching new patients to psychotherapists based on data from both patients and therapists. The central hypothesis of the project is that optimally matching patients and professionals based on clinical variables will improve satisfaction levels, treatment adherence, therapeutic alliance and motivation to change, ultimately improving therapeutic efficacy.

 

In summary, knowing the serious consequences of these disorders, not only on the people who suffer from them but also on their environment, we consider the main targets of the project to be the affected patients and their families. Once the system’s maximum performance has been achieved, the solution can be extended to any psychotherapy device in both the public and private networks. Due to the incidence currently observed, the influx of new mental health patients is a challenge for those responsible for mental health units. The tool will streamline these services by assisting in the key process of assigning patients to professionals, minimising the likelihood of errors in this process, and as a result optimising the use of resources by increasing the accuracy of resource allocation.

 

Exploring the frontiers of research:

In the initial phase, we were immersed in developing the assessment protocols for patients and professionals, as well as the first version of the matching algorithm between patients and professionals, followed by the development of the software where the assessment protocols, the matching algorithm and the dashboards where the results of the matching will be visualised will be implemented. The pilot system will soon be implemented in several test centres.

 

Technological innovation and beyond:

MATCH MIND explores the integration in a software by means of three dashboards (one for the patient, one for the professional and one for the clinic administration), where the algorithm’s decision and the reasons for it will be presented in a simple and attractive way. Finally, the information collected by the system will be stored to train the future Artificial Intelligence algorithm that will be developed in later phases. With this supervised algorithm, it will be possible to make more complex predictions about the personalisation of treatments for different mental health problems.

 

A promising future:

This project will continue with a second phase of development and validation of an Artificial Intelligence algorithm for assigning the most appropriate professional for each patient. The main objective is to research and develop more complex algorithms based on artificial intelligence, which will improve the accuracy of the recommendations.

 

This project has been funded by the AEI (Innovative Business Associations) grant line of the Ministerio de Industria, Comercio y Turismo of the Spain Government.

NEWS​

Related News

Evondos Anna in Siun Sote, Finland: Technology brings quality home care to sparsely-populated areas

9 Apr 2024
In Siun Sote, it is believed that medicine-dispensing robots will increasingly establish themselves as part of future home care. In North Karelia, dem...

ECHAlliance Announces Reciprocal Agreement with AgeTech Atlanta

8 Apr 2024
ECHAlliance and AgeTech Atlanta forge a Foundation Partnership to drive AgeTech Innovation and Excellence

Digital Health Collaboration: ECHAlliance Session at Africa-Europe Science Forum

8 Apr 2024
Connecting the Dots: ECHAlliance Hosts session on Digital Health Collaboration at Africa-Europe Science Collaboration and Innovation Forum

New Foundations 2024

8 Apr 2024
New Foundations is a key driver in progressing our strategic priorities by enabling awardees to pursue research, networking or dissemination activitie...

Neurotech Entrepreneurship to Validate Emerging Innovations (NERVE)

8 Apr 2024
The NERVE (Neurotech Entrepreneurship to Validate Emerging Innovations) program is Canada's single largest award that catalyzes early stage entreprene...

Horizon Europe Pump Priming Programme

8 Apr 2024
The programme supports individual UK SMEs wanting to explore and access Horizon Europe collaborative research and innovation opportunities.

Become a member

Join ECHAlliance to amplify your organisation’s message, grow your networks, connect with innovators and collaborate globally.
 
First name *
Last Name *
Email Address *
Country *
Position *
First name *
Last Name *
Email Address *
Country *
Position *