Estimating a preference-based index for a menopause specific health quality of life questionnaire.

BACKGROUND: The aim of the study was to develop a menopause-specific, preference-based health-related quality-of-life (HRQoL) index reflecting both menopausal symptoms and potential side-effects of Hormone Replacement Therapy (HRT). METHODS: The study had three phases: the development of a health state classification, a prospective valuation survey and the estimation of a model to interpolate HRQoL indices for all remaining health states as defined by the classification. A menopausal health state classification was developed with seven dimensions: hot flushes, aching joints/muscles, anxious/frightened feelings, breast tenderness, bleeding, vaginal dryness and undesirable androgenic signs. Each dimension contains between three and five levels and defines a total of 6,075 health states. A sample of 96 health states was selected for the valuation survey. These states were valued by a sample of 229 women aged 45 to 60, randomly selected from 6 general practice lists in Sheffield, UK. Respondents were asked to complete a time trade-off (TTO) task for nine health states, resulting in an average of 16.5 values for each health state. RESULTS: Mean health states valued range from 0.48 to 0.98 (where 1.0 is full health and zero is for states regarded as equivalent to death). Symptoms, as described by the classification system, can be rank-ordered in terms of their impact (from high to low) on menopausal HRQoL as follows: aching joints and muscles, bleeding, breast tenderness, anxious or frightened feelings, vaginal dryness, androgenic signs. Hot flushes did not significantly contribute to model fit. The preferred model produced a mean absolute error of 0.053, but suffered from bias at both ends of the scale. CONCLUSION: This article presents an attempt to directly value a condition specific health state classification. The overall fit was disappointing, but the results demonstrate that menopausal symptoms are perceived by patients to have a significant impact on utility. The overall effect is modest compared to the more generic health state descriptions such as the EQ-5D. The resultant algorithm generates a preference-based index that can be used economic evaluation and that reflects the impact of this condition.

Modeling pandemic preparedness scenarios: health economic implications of enhanced pandemic vaccine supply.

Influenza pandemic planning is a complex, multifactorial process, which involves public health authorities, regulatory authorities, academia and industry. It is further complicated by the unpredictability of the time of emergence and severity of the next pandemic and the effectiveness of influenza epidemic interventions. The complexity and uncertainties surrounding pandemic preparedness have so far kept the various stakeholders from joining forces and tackling the problem from its roots. We developed a mathematical model, which shows the tangible consequences of conceptual plans by linking possible pandemic scenarios to health economic outcomes of possible intervention strategies. This model helps to structure the discussion on pandemic preparedness and facilitates the translation of pandemic planning concepts to concrete plans. The case study for which the model has been used shows the current level of global pandemic preparedness in an assumed pandemic scenario, the health economic implications of enhanced pandemic vaccine supply and the importance of cell culture-based influenza vaccine manufacturing technologies as a tool for pandemic control.