Funding initiative of the ZD.B topic platform Digital Health/Medicine

Aim of the project

The aim of the project is the development and implementation of a digital platform for the transition management from hospital to short-term care facilities with the following digital functions and results:

• Improvement of the handover quality
• Input/overview of open places incl. occupancy-relevant information
• Transparent overview of the current short-term care market
• Fast, simple and intuitive usability
• Rights system for managing and editing data

In the course of the participatory development design, the project goals were continuously adapted to the results of the stakeholder and requirements analysis as well as to the continuous user dialogue based on a demonstrator.

Project description

The project addresses the transition of patients from inpatient care to continuing care arrangements at the interface between hospital and short-term care, which is an important health policy challenge in view of the increasing importance of chronic diseases, growing case severity, and changing care networks in long-term care.

Short-term care is offered in most cases as interspersed short-term care by inpatient nursing facilities, competing with demands for regular inpatient care as part of the nursing home's optimization decision. In this context, a bottleneck of available care capacities is evident in short-term care as well as in day care. Both the same-day information about the patient-individual care need and the concern about increased communication volume and thus additional transaction costs are clues to a potential acceptance problem both on the delivering and on the receiving side.

The project aims to optimize the supply interface between hospital and short-term care with the help of a digital platform to which both hospitals and care facilities have access, by increasing the quality of the transfer, reducing the costs of the institutions involved and speeding up the processes.

Backgrounded by the growing market of people in need of care and nursing, there is also a lack of a digital infrastructure that forms the basis for digital business processes in this segment. In this project, the basis of the infrastructure is to be created, on which further actors and processes can be mapped and new business models can be created.

Homepage

http://www.digitalcare.bayern/

Funding period

01.07.2017 - 31.05.2019

Project Management

Bruno Ristok C&S Computer und Software GmbH Wolfsgäßchen 1 86153 Augsburg Tel.: 0821-2582-0 Email: Contact by Mail Homepage: www.managingcare.de

Project partner

Fraunhofer Institute for Integrated Circuits IIS Nordostpark 84 90411 Nürnberg Homepage: www.iis.fraunhofer.de Task in the project: Fraunhofer IIS performed an analysis of process flows, expectations and demands on the system, as well as a demand-driven requirements analysis to determine the required functional scope, user interface design and data to be exchanged.

Research Institute IDC of the Wilhelm Löhe University of Applied Sciences Merkurstraße 41 90763 Fürth Prof. Dr. Jürgen Zerth Homepage: www.wlh-fuerth.de/idc Task in the project: The IDC of the Wilhelm Löhe University of Applied Sciences conducted a stakeholder analysis as part of the accompanying scientific research and investigated the acceptance of action and use as well as health-economic effects.

Aim of the project

DEVoTED is developing an empirical, data-driven and validated digital clinical decision support system (CDSS). This will allow physicians to assign patients to therapy resistance groups based on data as well as knowledge in order to make more targeted, personalized therapy decisions in routine medical practice. The system will support the assessment of the risk of treatment resistance in depression patients at the time of admission to the clinic, thereby reducing the number of unnecessary "trial-and-error" treatments, shortening the duration of treatment and reducing the risk of chronification. In addition to individual gains in quality of life and health, this results in a reduction of treatment and societal costs.

Project description

Therapy resistance is a relevant medical and macroeconomic problem in the care of patients with depression. In 2010, approximately 30 million patients were treated for depression in Europe, resulting in an overall cost of approximately €92 billion. According to the WHO, unipolar depression will soon be the main cause of disease burden in industrialized nations. Initial drug treatment (according to existing guidelines) is only successful in about 30% of those treated. In addition, existing guidelines are insufficient, and new research results are difficult for physicians to access and classify.

In DEVoTED, Biomax Informatics AG and the Max Planck Institute for Psychiatry with its affiliated clinic are developing a digital decision support system for the early detection of therapy resistance and thus for improving the choice of therapy in depression treatment. For this purpose, a data- and knowledge-based patient stratification for therapy resistance is performed. The criteria and models for stratification are based on literature research, expert knowledge as well as already existing extensive multidimensional data sets from own clinical studies. Data analysis and model development are performed by machine learning using artificial intelligence. The resulting statistical models and rule sets will be validated, integrated into a user-friendly web interface, and tested in routine medical practice at the clinic as well as with networked physicians in private practice.

Funding period

01.02.2018 - 31.01.2020

Project Management

Dr. Dieter Maier Biomax Informatics AG Robert-Koch-Str. 2 82152 Planegg Tel.: 089-8955740 E-mail: Contact by Mail Homepage: www.biomax.com

Project partner

Max Planck Institute of Psychiatry Kraepelinstr. 2-10 80804 Munich Homepage: www.psych.mpg.de Task in project: Expert interviews, data-driven patient stratification, clinical validation, test deployment in clinical practice

Aim of the project

My Bust Friend, a web-based software solution for breast cancer therapy support, is intended to accompany patients from the initial diagnosis, through treatment, into the period of aftercare and beyond. My Bust Friend informs, supports, motivates, empowers and reassures the patient. The goal is to improve treatment adherence as well as medication adherence in order to positively influence the patient's quality of life.

Project description

The disease breast cancer presents every patient with special problems and challenges. The app My Bust Friend supports women in self-managing their breast cancer disease. With the help of the app, she receives sound medical information and explanations about treatment and aftercare. The app creates an individual therapy roadmap and takes the patient by the hand to guide her through the treatment jungle and aftercare, as well as making the world of medical terminology understandable and approachable. The app provides motivational support for taking medication and leading a healthy lifestyle, as well as tips for coping with side effects, stress and emotional strain. This is expected to increase treatment adherence (50% of women in standard care do not complete the recommended cancer medication), improve quality of life, and also improve prognosis. Parallel to the market launch, this is to be validated in prospective clinical studies.

Should the expected effects be scientifically proven, My Bust Friend is also a profitable tool for health insurance companies to improve the care of their insured. In addition, the web app can support the work of physicians and nurses in the care of breast cancer patients. The app can also collect outcome data and transmit it to cancer registries and breast centers, thus facilitating the benchmarking required by the authorities. Meine Busenfreundin is being developed as a progressive web app for the German-speaking market, within a collaborative project between university, industry and start-up. It is innovative and offers high commercialization potential.

Homepage

www.meinebusenfreundin.de

Funding period

01.09.2018 - 31.08.2020

Project management

Marko Wilhelm Meine Busenfreundin GmbH Tel.: 089-4142455714 E-Mail: Contact by Mail

Project partner

TELUM GmbH Business IT Solutions Welfenstraße 22 81541 München Homepage: https://www.telum.de Task in the project: Technical development and project management

Clinic and Polyclinic of the Hospital rechts der Isar Munich Ismaninger Straße 22 81675 Munich Homepage: http://www.frauenklinik.med.tum.de Task in the project: Conduction of studies, content design

Aim of the project

The aim of the R&D project is to couple the cutting-edge technology of digital pathology, digital diagnostics, as well as immunotherapy of cancer in an innovative but cost-effective and easily integrable way in order to make this technology accessible to clinical as well as research institutions and pharmaceutical companies, thus enabling fast, cost-effective and safe diagnostics for the benefit of patients. Therefore, the scientific and technical working objectives of this project are to develop a novel computer-assisted in vitro diagnostic system for quantifying the local immune status of gastroesophageal tumors and their spatial microenvironment as an example of individualized diagnosis, prognosis, and therapy decision-making for cancer immunotherapy in the spirit of precision medicine.

Project description

For the realization of digital pathology in clinical routine, the technical and organizational requirements with current products and the associated costs are very high. Thus, the adaptation of digital pathology into clinical practice falls far short of its potential. In contrast, work objectives of this project consist of the development of a novel prototyped computer-assisted in vitro diagnostic (CAD-IVD) system for real-time digitization of histological slides using interactive low-cost stitching microscopy. Quantification of the local immune status of gastroesophageal tumors and their spatial microenvironment supports individualized immunotherapy.

The new approach goes beyond the principle of conventional image-based CAD systems by integrating software-based diagnostic and therapy decision support with the corresponding in vitro diagnostic in one system. The potential of the approach lies in the optimal adaptation of biomarkers and analysis technology, the low usage barriers for practical application, and the opportunities for successful commercialization arising from attractive business models based on this hybrid foundation of hardware, software and biomarker kits. The system combines the patented ISTIX® technology (Fraunhofer IIS) for real-time digitization of histological slides using low-cost interactive stitching microscopy with the patented Definiens Tissue Phenomics® technology from the field of artificial intelligence. Medical supervision of the project is provided by the Institute of Pathology of the University Hospital Erlangen in cooperation with the Institute of Pathology of the Bayreuth Hospital.

Funding period

01.05.2018 - 30.04.2020

Project management

Dr. Maria Athelogou Principal Scientist & Scientific Alliances Manager Definiens AG Bernhard-Wicki-Str. 5 80636 Munich Tel.: 089 231180 8014 Mobile: 0179 4958091

Project Partner

Volker Bruns Group Manager Medical Image Processing Fraunhofer IIS Am Wolfsmantel 33 91058 Erlangen Homepage: https://www.iis.fraunhofer.de/

Prof. Dr. med. Arndt Hartmann, Dr. med. Carol Geppert (MIAC) Institute of Pathology University Hospital Erlangen Krankenhausstrasse 8-10 91054 Erlangen Tel.: 09131 8524723 Homepage: http://www.pathologie.uk-erlangen.de/

Prof. Dr. med. M. Vieth (Associate Partner) Institute of Pathology Klinikum Bayreuth GmbH Preuschwitzer Str. 101 95445 Bayreuth Tel.: 0921 400 5602 Homepage: https://klinikum-bayreuth.de/einrichtungen/kliniken/pathologie/