Capturing Valuation Study Sampling Uncertainty in the Estimation of Health State Utility Values Using the EQ-5D-3L.

OBJECTIVES: Utility scores associated with preference-based health-related quality-of-life instruments such as the EQ-5D-3L are reported as point estimates. In this study, we develop methods for capturing the uncertainty associated with the valuation study of the UK EQ-5D-3L that arises from the variability inherent in the underlying data, which is tacitly ignored by point estimates. We derive a new tariff that properly accounts for this and assigns a specific closed-form distribution to the utility of each of the 243 health states of the EQ-5D-3L. METHODS: Using the UK EQ-5D-3L valuation study, we used a Bayesian approach to obtain the posterior distributions of the derived utility scores. We constructed a hierarchical model that accounts for model misspecification and the responses of the survey participants to obtain Markov chain Monte Carlo (MCMC) samples from the posteriors. The posterior distributions were approximated by mixtures of normal distributions under the Kullback-Leibler (KL) divergence as the criterion for the assessment of the approximation. We considered the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm to estimate the parameters of the mixture distributions. RESULTS: We derived an MCMC sample of total size 4,000 × 243. No evidence of nonconvergence was found. Our model was robust to changes in priors and starting values. The posterior utility distributions of the EQ-5D-3L states were summarized as 3-component mixtures of normal distributions, and the corresponding KL divergence values were low. CONCLUSIONS: Our method accounts for layers of uncertainty in valuation studies, which are otherwise ignored. Our techniques can be applied to other instruments and countries' populations. HIGHLIGHTS: Guidelines for health technology assessments typically require that uncertainty be accounted for in economic evaluations, but the parameter uncertainty of the regression model used in the valuation study of the health instrument is often tacitly ignored.We consider the UK valuation study of the EQ-5D-3L and construct a Bayesian model that accounts for layers of uncertainty that would otherwise be disregarded, and we derive closed-form utility distributions.The derived tariff can be used by researchers in economic evaluations, as it allows analysts to directly sample a utility value from its corresponding distribution, which reflects the associated uncertainty of the utility score.

Effectiveness of an intervention to facilitate prompt referral to memory clinics in the United Kingdom: Cluster randomised controlled trial.

BACKGROUND: Most people with dementia do not receive timely diagnosis, preventing them from making informed plans about their future and accessing services. Many countries have a policy to increase timely diagnosis, but trials aimed at changing general practitioner (GP) practice have been unsuccessful. We aimed to assess whether a GP's personal letter, with an evidence-based leaflet about overcoming barriers to accessing help for memory problems-aimed at empowering patients and families-increases timely dementia diagnosis and patient presentation to general practice. METHODS AND FINDING: Multicentre, cluster-randomised controlled trial with raters masked to an online computer-generated randomisation system assessing 1 y outcome. We recruited 22 general practices (August 2013-September 2014) and 13 corresponding secondary care memory services in London, Hertfordshire, and Essex, United Kingdom. Eligible patients were aged ≥70 y, without a known diagnosis of dementia, living in their own homes. There were 6,387 such patients in 11 intervention practices and 8,171 in the control practices. The primary outcome was cognitive severity on Mini Mental State Examination (MMSE). Main secondary outcomes were proportion of patients consulting their GP with suspected memory disorders and proportion of those referred to memory clinics. There was no between-group difference in cognitive severity at diagnosis (99 intervention, mean MMSE = 22.04, 95% confidence intervals (CIs) = 20.95 to 23.13; 124 control, mean MMSE = 22.59, 95% CI = 21.58 to 23.6; p = 0.48). GP consultations with patients with suspected memory disorders increased in intervention versus control group (odds ratio = 1.41; 95% CI = 1.28, 1.54). There was no between-group difference in the proportions of patients referred to memory clinics (166, 2.5%; 220, 2.7%; p = .077 respectively). The study was limited as we do not know whether the additional patients presenting to GPs had objective as well as subjective memory problems and therefore should have been referred. In addition, we aimed to empower patients but did not do anything to change GP practice. CONCLUSIONS: Our intervention to access timely dementia diagnosis resulted in more patients presenting to GPs with memory problems, but no diagnoses increase. We are uncertain as to the reason for this and do not know whether empowering the public and targeting GPs would have resulted in a successful intervention. Future interventions should be targeted at both patients and GPs. TRIAL REGISTRATION: Current Controlled Trials ISRCTN19216873.