SmartHealthNet

A digital care algorithm for patients, doctors, caregivers and therapists.

Jakob Tiebel

 

SmartHealthNet is a research project that brings together medical services, technical aids and all players involved in the care of neurological patients with digital support. The goal: individual, needs-based and coordinated care management of the people concerned.

In Germany alone, around 190,000 people suffer a stroke every year. 30 per cent of those affected experience a permanent disability. These people require medical treatment, physiotherapy and occupational therapy, speech therapy, special aids and social services. Unfortunately for patients, care processes are often very fragmented, inefficient and not very reproducible.

SmartHealthNet could change this situation in future. The aim of the project is to develop a service system that includes medical and digital services, rehabilitation technology and a digital management platform. This is intended to create a multi-faceted benefit, where doctors, providers and therapists receive more precise information and those affected receive personalised care.

  

„The algorithm is primarily based on data generated by the patient themselves“
Tom Kramer

SmartHealthNet is a federally funded research project. The model is intended to contribute to the future of medical care and can be applied to the care of many neurological diseases such as stroke, multiple sclerosis and amyotrophic lateral sclerosis.

  

„Care suggestions coming from the patient’s selfassessment help to make care in the assistive device field quicker and more suitable for requirements.“
Anja Weiss

The Berlin-based company Ambulanzpartner is the main initiator of the project. The sociotechnology service provider has been working for several years on a holistic concept for the care, research and networking of patients with rare, severe neurological diseases. The care algorithm developed as part of SmartHealthNet is intended to further improve the holistic concept in future.

The care algorithm developed as part of SmartHealthNet is primarily based on data that the patient generates themselves during care in the form of patient reported outcomes (PROMs). As presented in the article “Mobility training with ALS”, the care concept of Ambulanzpartner already takes into account the ability of patients to evaluate their health status and the care situation on the basis of patient-reported outcome measures (PROMS) and patient-reported experience measures (PREMS). To do this, they take part in surveys and enter the corresponding data into an app during the process.

  

„I hope that through the care algorithm, we can improve the care of ALS patients in Germany, Europe and around the world in a few years’ time.“
Prof. Dr. Christoph Münch Mitgründer und CEO Ambulanzpartner

The key advantage of the care algorithm is that the data patients generate via the PROMs has a direct impact on their care. Care suggestions resulting from entries in the app then directly contribute to the fact that, for example, care with an aid, such as the movement exerciser, can be carried out more quickly and in line with requirements.

Further potential lies in the linking of different data sources. For example, THERA-Trainer included data generated during training on the therapeutic movement exerciser in the algorithm during the project. In this way, PROMs can be supplemented in future with progress profiles and training data that the patient generates directly through the use of their assistive device.

  

„Initial experiences of use have been promising because the care algorithm gave suggestions on what aspects of care I can talk about with the patient.“
Dr. med. André Maier

So far, the care algorithm is still a research project and, for the time being, still pioneering work by Ambulanzpartner and participating consortium partners. In the long term, however, there is the potential to improve the care of neurological patients in Germany, Europe and worldwide through the use of this innovative approach.

  

  

„Readings from the app can provide important information on the course and dynamics of the ALS disease.“
Susanne Spittel

Care Algorithm SmartHealthNet:

https://l.ead.me/SmartHealthNet

Contact person:

Ambulanzpartner Soziotechnologie APST GmbH
Westhafen Straße 1
13353 Berlin
+49 (0)30-8103141 0
info@ambulanzpartner.de
www.ambulanzpartner.de

SmartHealthNet –
Conception, development and piloting of data-based case management

www.smarthealthnet.de

“This research and development project is funded by the Federal Ministry for Education and Research (BMBF) in the 'Innovations for the production, service and work of tomorrow' programme and is supported by Project Management Agency Karlsruhe (PTKA). Responsibility for the content of this publication lies with the author.”