The quality of the data is a central criterion for the success of a publicly funded research project. This quality is all the more important as the information obtained from the data serves evidence-based decision-making in politics. In this case, the data will be provided to the Bavarian State Ministry of Health and Long-Term Care (StMGP) and the Bavarian State Government for healthcare planning in Bavaria.
To ensure a high quality of surveys and data, the digiDEM Bavaria project has established a close-knit quality management system with regular checks of survey and data quality. The project management is continuously working on improving and further developing the quality management system, particularly to take into account legal and technological developments.
Quality assurance measures
To ensure high survey and data quality, various measures are regularly implemented and documented.
As a first measure, participants in digiDEM Bayern will be contacted by phone at regular intervals. The focus of the telephone contact is on determining the participants' satisfaction with the survey. There is no conscious selection of participants to be called; rather, the random checks include all research partners in all Bavarian administrative districts involved in digiDEM Bayern.
As a second measure, a regular review of the completeness and plausibility of all data collected in digiDEM Bayern will be carried out. Data collection is performed using the REDCap registry software, which is widely used in the scientific community. This way, digiDEM Bayern staff have direct access to the pseudonymized data immediately after data entry and can check its completeness and plausibility. The results are documented in internal work systems.
Research Partner Profiles
As part of data collection, the digiDEM Bavaria project works closely with research partners. Research partners are institutions or individuals who are active in the care of people with cognitive impairments and/or their relatives. The following is a tabular overview of potential research partners:
| Category | Related facility types |
| Outpatient Services | Outpatient care service, support service, social services station |
| Pharmacies | |
| Doctors | Doctor, practice, clinic |
| Supported living facilities | Dementia-friendly shared living, assisted living |
| Expert bodies | Specialist center for family caregivers, Specialist center for elderly care |
| Memory clinics | Neurology, Memory Clinic, Outpatient Psychiatric Services |
| Individuals | Volunteers, freelance healthcare professionals |
| Daycare facilities | Daycare, support group, senior center, intergenerational center |
Criteria for selecting research partners
Research partners will be selected based on the criteria defined below:
- Access and contact for people with cognitive impairments and/or their caregivers.
- Professional background in caring for individuals with cognitive impairments and/or their caregivers.
- Experience in dealing with people with cognitive impairments and/or their caregivers.
- Volunteers recommended personally by regional project assistants and/or existing research partners.
Cooperation with the research partners is contractually regulated within digiDEM Bayern through a cooperation and data protection agreement. To ensure high quality of surveys and data, the research partners undergo systematic training before data collection begins. Upon completion of the training, the research partners receive a corresponding certificate. Additionally, research partners are required to undergo refresher training once a year.
The general cooperation criteria mentioned above will be checked during the training registration.
The results of the survey and data quality review will be communicated to the StMGP as a third-party funder for the digiDEM Bayern project in the form of regular reports. The continuous development and improvement of the QM system will also be implemented in coordination with the StMGP. This is particularly important to ensure the appropriate use of the funding provided by the StMGP from tax revenues.
