DataDonor

Abstract

The importance of value-based health care
Worldwide, health care systems are struggling to control costs while improving care outcomes. An ageing population, increase in chronic patients and shortage in care professionals result in high burdens on our health care systems. Current health care systems are organized around delivering quantity. When this is continued, health care costs will rise in an unsustainable pace and the quality of care will be affected. The concept of value-based health care proposes a paradigm shift where we move from organizing care based on volume to value. This concept suggests measuring value of health care based on outcomes achieved for the patient instead of volume delivered.

Assignment
Value-based health care (VBHC) is an evidence-based approach and can be used to improve individual and public clinical care. Longitudinal and systematic measuring and sharing of health data is essential to be able to track outcomes and improve clinical care accordingly.

Periodic patient health data can be used by care professionals to provide timely treatment interventions to patients. Additionally, patient health data can be used to build predictive models to support care professionals in providing more personalized treatment. For this, patient self-care supported by eHealth services is becoming increasingly important where the role of the patient shifts from being a ‘care user’ to a ‘care contributor’.

However, patients express concerns regarding the safety of eHealth services and are not thoroughly informed on how patient health data can improve both individual and public clinical care. Based on this, this thesis will answer the following research question:

How can care providers strategically obtain patient health data, in order to improve individual and public clinical care?

To answer this research question, a theoretical ecosystem which envisions a way of strategically obtaining patient health data to improve clinical care is developed and used during user research.

A theoretical ecosystem for the cardiovascular domain
Cardiovascular diseases (CVDs) are the main cause of death globally and the number of people living with chronic cardiovascular disease is increasing daily. Providing preventive care to those cardiovascular patients is key to manage the disease properly. Patient self-care, eHealth services and predictive models can have major implications on how cardiovascular care is managed and provided. Because the potential impact technology can have on improving clinical care for CVD, the theoretical ecosystem was designed for this domain.

The ecosystem is designed using insights from extensive preliminary research. It is a product service system which uses patient-generated health data from the telemonitoring service to better manage care and build predictive models to support cardiologists in providing tailored treatment. This ecosystem allows patients to receive personalized treatment and advice, have easier access to care and enables them to contribute to care easier.

Frisian Health Campus case
The theoretical ecosystem is used during a use case for Frisian Health Campus (FHC), a client of Deloitte. FHC is an initiative that aims to become a pivotal player in developing and supporting care innovations in the northern region of the Netherlands. In order to improve clinical care, they aim to connect various care providers in the region by developing a platform where patient health data is shared for research. Deloitte did extensive research to disclose what FHC is legally allowed to do with patient data on such a platform. However, they did not know what patients and care professionals think of such a platform and what is necessary to let patients share their health data with them. Therefore, the ecosystem that is designed was used to do research on the desirability of FHC’s envisioned data sharing platform.
User research and design challenge
In total 7 cardiovascular patients and 6 cardiologists were interviewed to gain a better understanding of how the theoretical ecosystem addresses drivers and needs of these users. It was found that patients are more than willing to share health data for research if privacy and security are guaranteed. This showed there is not a problem with the willingness to share health. Instead, barriers with keeping up the data flow were identified:

The desire to measure and share health data fades over time because patients find a balance in medication and lifestyle,
Measuring and sharing health data remind people they are a patient,
Patients are unaware of the value of their health data.

Results from user research resulted in the following design challenge:

To increase adherence of measuring and sharing health data, the design should let patients experience the value of health data and trigger personal drivers to periodically measure and share health data.

During user research, various alternative drivers to measure and share health data were found and are used to design behavioural interventions in the final concept. Three main triggers were identified. I would measure and share health data to:

Reassure my family and friends,
Contribute to care of other people,
Support my doctor in providing better care.

DataDonor
The final design, DataDonor, is a digital environment which consists of an informative website regarding the value of health data and a module that can be added to existing telemonitoring services to share health data for research. This way, patients and care professionals can use the initial telemonitoring service. Additionally, the module provides patients with information regarding the impact of their data donations on their care and that of others. To maintain measuring and sharing adherence, DataDonor adapts to personal drivers to measure and share health data over time.
By repositioning the role of a patient from being a ‘care user’ to a ‘care contributor’, patients are not reminded they are a patient when measuring and sharing health data but enable them to be a vital contributor to individual and public care.

Validation
DataDonor has been evaluated with patients, the client and health care experts to assess the concept on both a user and client level. These sessions resulted in relevant feedback and validation and are shared in chapter 7. However, to fully validate the effect of DataDonor, it should be tested over a longer period of time.

Conclusion
DataDonor is a digital environment supporting care providers to strategically obtain patient health data to improve clinical care. By guaranteeing secure and anonymous use of patient health data and by enabling patients to contribute to their own care and do good at the same time, patients can be triggered to share health data with their care providers. Additionally, by appealing to personal drivers to measure and share health data, DataDonor provides a solution that fit the needs of the patient, business and organization.