PhD defence L. (Lisa) Hoogendam

Below is a brief summary of the dissertation:

Shared decision-making leads to care that is better aligned with patients’ values. However, this method of decision-making is not always used. This thesis investigates how we can use personalized outcome information to help patients with hand and wrist conditions, particularly with thumb base osteoarthritis, and their healthcare providers make joint treatment decisions. 
First, we investigated what patients consider to be a relevant improvement or ‘good outcome’. For common hand and wrist conditions, the Minimally Important Change (MIC) and Patient Acceptable Symptom State (PASS) have been established for this purpose.
Next, treatment outcomes for thumb base osteoarthritis were investigated. Non-surgical treatment (such as hand therapy) showed long-term effects, and surgery is only necessary if symptoms persist. In addition, we found that various complications occur after surgery, varying in severity. Providing non-surgical treatment first, and consider surgery only when symptoms persist appears to be the most cost-effective strategy for thumb base osteoarthritis. Furthermore, psychological factors, such as expectations and perception of illness, were strongly related to treatment outcomes and satisfaction. Positive expectations prior to treatment relates to better outcomes, which supports the importance of good expectation management.
Finally, we developed prediction models that can help patients understand their chances of a relevant symptom improvement after treatment. These models proved to be reliable, usable in clinical practice, and may improve the quality of decision-making.
In conclusion, this thesis demonstrates data-driven applications to assist patients with hand and wrist conditions and their healthcare providers in their shared decision-making regarding treatment options.