This study has demonstrated two important results. Firstly, that stable schizophrenia has the lowest impact on quality of life (highest utility value) and 'relapse' has the highest impact on quality of life (lowest utility value) of the health states measured. This is unsurprising, as these two states represent the extremes in schizophrenia-related health effects. The results also consistently showed 'EPS' to have the second-greatest impact on quality of life, followed by diabetes, while there was little difference between the quality of life impacts of 'weight gain', and 'hyperprolactinemia'.
The second key result is that the actual utility values varied considerably according to the population from which the values were derived. Utilities derived from patients were, on average, 0.077 points higher than those derived from the lay population. This indicates that patients are less willing to trade years of life to avoid schizophrenia-related health states. This is likely to be the result of a shift in psychological expectations, which includes a shift in the weight placed on different aspects of quality of life and a changed view of what matters in life. General population respondents are less likely to understand these shifts, tending to focus on the transition to the state rather than its longer term consequences, and therefore underestimate the ability of a patient experiencing the disease to adapt to their health state [8, 24]. Other research indicates that general population respondents focus more on the negative aspects of a health state than the remaining positive aspects . Together, these would lead to lower utility values from the general population than a patient population. These general observations, support schizophrenia-specific work that has pointed to the importance of self-experience and a model of recovery in this disease [26, 27] which supports the general concept of adaptation.
The study results confirms the earlier work of Voruganti et al.  and Adams et al.  suggesting that stable patients are capable of participating in studies designed to elicit the quality of life impact of schizophrenia and its treatment. Despite differences in utility values, patients and laypersons took the same amount of time to complete the interview and interviewers reported no problems in understanding of the study tasks among either population. It is important in health services research to gain the perspectives of all participants, and this study shows that a well-designed, sensitively administered interview is able to elicit health-related utilities from patients as well as laypersons that can be used to inform decision makers about the quality of life impact of schizophrenia. It is likely that differences in the results reflect differences in perspective, rather than an inability of patients to provide appropriate responses.
The key potential problems in any health-related utility study (which limits the transferability of results) relate to the description of the health states and time period used as the benchmark in the time trade-off procedure. In the current study, the health state descriptions were developed after review of the published literature and consultation with clinical experts, and finalised following pilot studies with both patients and lay groups. Further, the mean utility values for stable disease – at 0.919 for patients and 0.865 for laypeople – were higher than hypothesised. However, the result from the EQ-5D patient scores was very similar to the utility for stable disease among laypeople. As noted previously, the utilities derived from EQ-5D scores are based on lay values. Hence, the similarity of the two results indicates that laypeople value the patient mapped functionality of their condition from EQ-5D at a very similar level to how laypeople value the stable schizophrenia health state described in Table 1. This provides a good indication that the health state descriptions are consistent with clinical reality and mitigates any concerns over the use of a convenience sample of laypersons in this study.
This study was designed to assess the impact on quality of life of key adverse events associated with the newer antipsychotics. Previous studies had shown that schizophrenia relapse has a substantial impact on quality of life, as does EPS. These results were supported in this study. However the adverse events primarily associated with the newer antipsychotics – hyperprolactinemia, weight gain and diabetes – have a lower impact on quality of life than EPS and relapse. There are two ways in which adverse events such as hyperprolactinemia, weight gain and diabetes – with the lower measured impact on quality of life – can affect the results of an economic evaluation. Firstly, such events are likely to influence the desire of patients and their families to continue with medication, and may cause patients to discontinue, with the associated increase in relapse. This would ensure that more time was spent in the relapse state with its substantial impact on quality of life. Secondly, the duration of these adverse events is also important. The impact of relapse on quality of life is substantial but relapse is a relatively transitory condition. Conversely, weight gain and diabetes show a smaller impact on quality of life than relapse, but are more sustained. The overall net effect of these quality of life differences could be determined through the use of the commonly employed outcome measure in health economic evaluations: the Quality Adjusted Life Year (QALY) which takes into account both the quality of life effects and the duration of that effect.
There are two main implications that flow from the results reported here. Firstly, that treatment-related adverse events all have a measurable impact on a patient's quality of life. While EPS and relapse have the greatest impact on quality of life, events such as hyperprolactinemia, weight gain and diabetes noticeably reduce patient quality of life compared with schizophrenia patients who do not suffer from these adverse events. These results offer the potential to minimise the net effect of disease and treatment on patient quality of life and quality-adjusted life years in economic analyses. Secondly, that the differences in valuations provided between patients and lay persons can be substantial in a disease such as schizophrenia and this could impact the cost-effectiveness of different treatment options for patients. Only by employing the sorts of estimates provided in this study in future cost-effectiveness models can the potential importance of these differences be fully determined.