gms | German Medical Science

16. Deutscher Kongress für Versorgungsforschung

Deutsches Netzwerk Versorgungsforschung e. V.

4. - 6. Oktober 2017, Berlin

May I suggest…? – The Intervention-Management-System (IMS) of the DelpHi-MV trial

Meeting Abstract

  • Henriette Rau - Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Greifswald, Germany
  • Daniel Fredrich - Institut für Community Medicine, Universität Greifswald, Universitätsmedizin Greifswald, Körperschaft des öffentlichen Rechts, Greifswald, Germany
  • Kerstin Albuerne - Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Greifswald, Germany
  • Jochen René Thyrian - Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE), Greifswald, Germany
  • Wolfgang Hoffmann - Universitätsmedizin Greifswald, Greifswald, Germany

16. Deutscher Kongress für Versorgungsforschung (DKVF). Berlin, 04.-06.10.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocV182

doi: 10.3205/17dkvf006, urn:nbn:de:0183-17dkvf0061

Published: September 26, 2017

© 2017 Rau et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



Background: In the context of complex health care situations, individual unmet needs are to be identified and covered via interventions, e. g. by a general practitioner (GP). For this purpose, a so-called intervention management system (IMS) was developed for the GP-based, randomized, controlled DelpHi-MV (dementia: life- and person-centered help in Mecklenburg-Western Pomerania) intervention trial [1]. The IMS shall support the integrated care of community-dwelling people with dementia (PWD) and their caregivers at the PWD’s home.

Research Aim: Aim of the IMS development was to assess the individual characteristics of the PWD and their caregivers by using a specific set of standardized questionnaires and, thereby, identifying unmet needs according to the “DelpHi-standard”. This computer-assisted assessment includes a knowledge database of guidelines for dementia care as well as relevant geriatric diagnostics, care, and treatment options to facilitate the selection of specific activities (“intervention modules”) for meeting the identified needs [2].

Methods: Within the DelpHi-MV intervention trial, the individual PWD’s characteristics are assessed by means of standardized questionnaires and the use of evaluated, valid instruments such as the DemTect (dementia detection), CERAD (Consortium to Establish a Registry for Alzheimer's Disease), NP (Neuropsychiatric Inventory) or B-ADL (Bayer Activities of Daily Living Scale). Data is collected via electronic case report forms (eCRF), which were filled in by study nurses at the PWD’s home using a tablet-PC. The collected data was then basis for searching the knowledge database regarding the following health care dimensions: 1) medical treatment and care management, 2) medication management, and 3) support as well as counseling for the PWD and their caregivers. If unmet needs are identified, the study nurse creates a list with corresponding intervention modules as recommendations for the GP using the IMS. The list is available in a printable as well as electronic format (PDF). Each activity, which is classified as valid by the GP, is marked accordingly in the IMS and its implementation is automatically tracked with a success monitoring. The interventions are implemented by the study nurse herself and/ or by other involved professionals.

The IMS was integrated as an additional module into an existing mobile information capture system (MINCA) [3], which provides eCRFs for on- and offline processing. As budget, human resources and IT infrastructures are limited resources in many research projects, the filter function of the IMS knowledge database was created as an example from two free of charge and open-access components: 1) Drools and 2) Guvnor. These enable the easy creation and management of rules to filter the knowledge database by people with little IT knowledge via an appropriate user interface. Additionally, a so-called Reminder module was implemented to support study nurses in keeping track, and scheduling the suggested intervention modules to meeting the identified needs of PWD and their respective care givers.

Results: The intervention management system (IMS) was developed within the DelpHi-MV intervention trial and has been successfully used since 2013. Currently, the IMS contains 386 rules, which lead to pre-filtered lists for activities to meet individual needs, and serve as basis for case-related consultation between the study nurses and the GP as well as for success monitoring. The exemplary implementation with the two free of charge and open-source components Drools and Guvnor enabled us to gain experience with regard to the possibilities and limitations of such knowledge databases and the rules engine, which will be taken into account in further developments.

Discussion: The IMS is built as a module so that it can be integrated into existing eCRF systems. The integration of Drools and Guvnor as a knowledge database and a rule-executing instance was carried out as an example to enable implementation and administration of rules for non-IT experts with little programming knowledge. The integration of additional tools or the exchange of the selected components is technically possible, when needed.

Practical implications: Currently, the IMS supports the improvement of complex care situations in PWD and their respective caregivers by facilitating the systematical identification of unmet needs according to the “DelpHi-standard” [2]. Additionally, it supports study nurses in assembling specific intervention modules for people with dementia at home to the GP. The IMS is under constant development and, therefore, will be also able to support various other complex care situations in geriatrics in the near future.


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Meyer J, et al. A mobile and asynchronous electronic data capture system for epidemiologic studies. Comput Methods Programs Biomed. 2013;110(3):369-379.