Most measurements in long-term care focus on safety, the time needed, and the effects of treatments on a patient’s health. The way that patients and their caregivers experience the care provided and the relationship with the healthcare professional is often neglected despite this being crucial for the quality of this care. By measuring quality from the patient’s point of view we can better adjust the care based on actual needs and expectations. And if we can then make the results of the accountability of the quality of healthcare available to municipalities or health insurers, we can avoid unnecessary registration and save valuable time.



We are going to record the experiences of patients in different innovative ways. We will then try to get insight into the relationship between clients and healthcare professionals. Our focus is on using simple visual methods that can also be used for people with cognitive and communicative problems. We do this in different settings: home care, care for disabled people, and nursing home care.


We are living in a digital age and information is shared faster than ever before. Unfortunately, the sharing of medical data within the healthcare sector is not optimal, which means that care isn’t always adjusted to the patient’s personal situation. We want to make sure that patients, healthcare professionals, and researchers will have access to the right research data in the future and that they can easily share it as well.



We are going to develop a patient portal in South Limburg: the Personal Health Train. Health data will be contained in a fixed format and will be always be available. Furthermore, all relevant parties will be able to easily and quickly give support and advice. This is both handy and essential, especially for solving complex problems.

In order to create the Personal Health Train we need to:

  • Create data stations in the hospitals, the offices of general practitioners in Limburg, and for patients in Limburg.
  • Categorize questions in trains which then gather answers in the different data stations.
  • Create a railway so that trains can also actually travel.
  • Formulate house rules to find the right balance between openness and access on one hand and patient confidentiality on the other.


In the last few years, many measuring devices or wearables that can contribute to the health, vitality, and independence of people have been developed.

However, in practice this does not automatically result in:

  • The measurements being done in a safe and reliable way.
  • The results actually being usable for clients, citizens, and healthcare professionals.

By playing an active role in the further development and the application in healthcare in a number of promising wearables, we make sure that they can fulfil their potential and lead to more personalized care and a higher level of self-reliance for clients and citizens.



We will first focus on two wearables that have recently been developed by Maastricht University:

  • The Miss Activity® tracker, with an algorithm that can be adapted and personalized.
  • The Psymate® digital diary, where people can fill out questions at any moment.

With the help of our own knowledge and that of healthcare professionals, patients, and the industry, we are adapting the algorithm of the Miss Activity® for people who walk slowly due to chronic diseases or age, to make it easier for them to use. For the Psymate® it is especially important to get insight into the requirements and preferences of primary users such as general practitioners and mental healthcare institutions. We will also extensively test and monitor both wearables in daily practice.


Each year, the costs of care increase and the waiting periods grow longer. This doesn’t just apply to planning and performing medical interventions but also to making diagnoses. Currently, diagnoses are primarily made in hospitals. This is expensive and requires a great deal of time from both the patient and the healthcare provider. This sometimes means that it takes too long before a patient receives the care needed and might have additional consequences as well.

We take the diagnostics techniques from hospital environments and utilize them using high-tech detection methods at the patient’s home. This way, diagnoses retain their high quality but at significantly reduced costs. This helps us keep healthcare at an affordable price and the patient has more control over the whole process.



We will first develop two detection methods that are faster at detecting antibiotic-resistant bacteria and markers for coagulopathy. Conditions are easier to identify, treatments are faster and more effective, and the costs per analysis will decrease.