City Research Online

Abstract

Healthcare funding decisions in the UK rely on health state valuations of the general public. However, it has been shown that there is disparity between the valuation of the impact of hypothetical conditions on health and the reported health by those experiencing them. Patients' adaptation to health states is among the most common explanations for this discrepancy. Being diagnosed with a disease appears to affect individual perception of health over time so that better subjective health may be reported over a disease trajectory. This paper examines adaptation to health states using a longitudinal dataset. We use four waves of the British Cohort Study (BCS70), which tracks a sample of British individuals since birth in 1970 and contains information on self-assessed health (SAH), morbidity, and socioeconomic characteristics. We implement a dynamic ordered probit model controlling for health state dependence. Results are supportive of the existence of adaptation: Time since diagnosis has a positive impact on SAH. Moreover, adaptation happens over relatively long durations. We do not find significant results proving different adaptation paths for patients reporting prior better SAH. The analysis by specific conditions generally supports the existence of adaptation, but results are statistically significant only for a subset of conditions.

Publication Type:	Article
Additional Information:	This is the peer reviewed version of the following article: Cubí-Mollá P, Jofre-Bonet M, Serra-Sastre V. Adaptation to health states: Sick yet better off? Health Economics. 2017, which has been published in final form at http://dx.doi.org/10.1002/hec.3509. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Publisher Keywords:	Self-Assessed Health, Dynamic Ordered Probit, Adaptation, Long-Standing Illness
Subjects:	H Social Sciences > HB Economic Theory
Departments:	School of Policy & Global Affairs > Economics
SWORD Depositor:	Symplectic Administrator

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