Economic evaluation is a common requirement in many countries for reimbursement and adoption decisions. The appropriate measurement of health outcomes is paramount to this appraisal process. However, controversy remains on the methodological underpinning of how health outcome measurements are obtained.
For instance, health technology assessment in England by the National Institute of Health and Care Excellence (NICE) favours the measurement of health gains in terms of health‐related quality of life using the EQ‐5D. Although valuations of the underlying health states by members of the general public (as opposed to patients) are preferred, most informative data about the health outcome are derived from patients' self‐assessments.
However, a patient's self‐assessment of their health state may be affected by factors other than changes to their objective health. A factor that is frequently cited in the literature is adaptation. Patients tend to self‐report better subjective health over the disease trajectory, even if more objective health measures suggest that their condition is not improving.
It has even been suggested that patients accommodate a chronic illness to a degree that the average health‐related quality of life value arising from their self‐reported measurement ends up being not inferior (and sometimes even superior) to that corresponding to healthy population norms.
Given that healthcare funding decisions are increasingly reliant on subjective health state measurements, it is critical that we fully understand the role that a chronic disease has on subjective health state measurement.
OHE’s Patricia Cubi-Molla, joint with Mireia Jofre-Bonet and Victoria Serra-Sastre from City, University of London, contribute to the adaptation literature with a new paper recently published in Health Economics. The paper hypothesizes, given an adaptation response, that there is a positive relationship between the length of time an individual suffers from an illness and the likelihood of reporting better health.
The issue of adaptation is analysed by estimating the effect of the presence of a long-standing illness and the time since diagnosis on the construct of subjective self-assessed health (SAH). The authors implement a dynamic ordered probit model controlling for health state dependence (i.e. an individual reporting better or worse health states by default). The empirical analysis uses the British Cohort Study (BCS70) which includes measures of both SAH and changes in the health state of the individuals, and information on the onset of chronic diseases and respondents’ experience of health shocks, as well as socioeconomic and demographic characteristics.
Their findings are supportive of the existence of adaptation. Time since diagnosis has a positive impact on self-assessed health, i.e. those who have had a chronic condition longer report better health than those more recently diagnosed. They also find that adaptation happens over relatively long durations, and does not have an equal impact across conditions. For instance, there is an adaptation effect for diabetes, asthma, migraines and upper respiratory tract infections, but no effect is found for depression or cancer.
This paper adds valuable insights to the understanding of the adaptation effect using innovative and robust methods. It links with other research undertaken at OHE that considers the role of age in health state valuation.
For more information please contact Patricia Cubi-Molla at OHE.
Posted in EQ-5D and PROMs, Health Statistics, Health Technology Assessment, Research | Tagged External publications