Exploring health-related quality of life in trauma patients beyond the borders of physical health:The promis of general health concepts in healthcare

The primary goal of this thesis was to evaluate the impact of minor and major traumatic injuries on significant health outcomes such as physical function, the ability to participate in social roles and activities and pain interference, by using patient reported outcomes. Furthermore, the needs for information and support of both patients and health care professionals after trauma were explored. The questions discussed in this thesis are divided into two main subjects. Part I describes the exploration of interest and usage of generic Patient-Reported Outcome Measures (PROMs) with regard to treatment and information provision to trauma patients. Part II inquires the implementation and results of Patient-Reported Outcomes measurement Information System computer adaptive testing questionnaires ‘physical function’, the ability to participate in social roles and activities and pain interference in daily practice in patients with a fracture. This thesis emphasizes that trauma patients are more than their isolated injuries. Also within trauma surgery, health status outside physical function should not be overlooked. Trauma surgeons agree that social and mental health is important to their patients, but many are struggling how to cope with problems they cannot solve. Exploring ways to support and inform trauma patients is essential, and e-health initiatives may play a role in meeting their needs. Learning and getting to know the patient by using PROMs can be helpful in monitoring, shared decision making and greater efficiency in outpatient clinics and generic questionnaires as PROMIS CAT could lower the burden for all medical specialties. After a widespread implementation of computer adaptive testing tools measuring quality of life and other relevant parameters, the expertise and authority of medical professionals should lead the way when necessary and self-adaptation and self-care should take back control when it is possible. Thinking even further and taking the rapid development of artificial intelligence into account, one might see a future where self-learning software tools use these acquired ‘big data’ to identify individual patients with an aberrant posttraumatic recovery, provide an early signal to both doctor and patient and even make a suggestion for a therapeutic intervention. However, this is a long journey of which this thesis is only a small step.