Time Preferences and the Patient-doctor Interaction

Time Preferences and the Patient-doctor Interaction

Auteur : Alastair D. J. Irvine

Date de publication : 2018

Éditeur : Aberdeen University

Nombre de pages : 448

Résumé du livre

Patients' non-adherence to treatment is a widespread phenomenon in healthcare. Time preferences (how individuals value outcomes over time) are one cause for non-adherence. Using quasi-hyperbolic discounting, two options in the future are weighted consistently. However, when the early option becomes available the weighting changes. This creates the potential for non-adherence. The agency relationship that exists between patients and doctors implies hidden information. When the patient's time preferences are hidden from the doctor, the doctor must choose how to recommend treatments. Exploring how doctors make treatment decisions when time preferences are hidden from them, and how this impacts adherence, is therefore important. The first contribution of the thesis is to outline a model of the patient-doctor interaction incorporating quasi-hyperbolic discounting and hidden information. This shows that doctors should adapt to non-adherence when the probability a patient is present-biased is large enough. Secondly, a national survey of Scottish GPs explores whether doctors have different time preferences for themselves or their patients. Doctors do have the same private and professional time preferences, but value the health state differently between frames. Lastly, a laboratory experiment tests whether students in the role of a doctor adapt to non-adherence in the way predicted by the model. Students find the socially optimal level of treatment on average. Adaptation is stronger when using a performance payment, and results did not vary along demographic characteristics. The thesis highlights the importance of the patient-doctor interaction for generating nonadherence, not just patient preferences. It also shows that GPs' private time preferences may suitably substitute their preferences for patients. Finally, it points towards potential incentives for doctors to improve patient outcomes.

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