Informing Investment to Reduce Inequalities: A Modelling Approach.

BACKGROUND: Reducing health inequalities is an important policy objective but there is limited quantitative information about the impact of specific interventions. OBJECTIVES: To provide estimates of the impact of a range of interventions on health and health inequalities. MATERIALS AND METHODS: Literature reviews were conducted to identify the best evidence linking interventions to mortality and hospital admissions. We examined interventions across the determinants of health: a 'living wage'; changes to benefits, taxation and employment; active travel; tobacco taxation; smoking cessation, alcohol brief interventions, and weight management services. A model was developed to estimate mortality and years of life lost (YLL) in intervention and comparison populations over a 20-year time period following interventions delivered only in the first year. We estimated changes in inequalities using the relative index of inequality (RII). RESULTS: Introduction of a 'living wage' generated the largest beneficial health impact, with modest reductions in health inequalities. Benefits increases had modest positive impacts on health and health inequalities. Income tax increases had negative impacts on population health but reduced inequalities, while council tax increases worsened both health and health inequalities. Active travel increases had minimally positive effects on population health but widened health inequalities. Increases in employment reduced inequalities only when targeted to the most deprived groups. Tobacco taxation had modestly positive impacts on health but little impact on health inequalities. Alcohol brief interventions had modestly positive impacts on health and health inequalities only when strongly socially targeted, while smoking cessation and weight-reduction programmes had minimal impacts on health and health inequalities even when socially targeted. CONCLUSIONS: Interventions have markedly different effects on mortality, hospitalisations and inequalities. The most effective (and likely cost-effective) interventions for reducing inequalities were regulatory and tax options. Interventions focused on individual agency were much less likely to impact on inequalities, even when targeted at the most deprived communities.

Economic analysis of a randomized phase III trial of gemcitabine plus vinorelbine compared with cisplatin plus vinorelbine or cisplatin plus gemcitabine for advanced non-small-cell lung cancer (Italian GEMVIN3/NCIC CTG BR14 trial).

BACKGROUND/OBJECTIVE: Non-platinum-based chemotherapy is a potential alternative to platinum doublet therapy for advanced non-small cell lung cancer in selected patients. We determined the cost-effectiveness of gemcitabine/vinorelbine (GEMVIN), versus cisplatin/gemcitabine (PG) or cisplatin/vinorelbine (PV), from a government payer perspective. METHODS: Results from a randomized trial of GEMVIN versus PG or PV demonstrated no significant difference in global quality of life (primary endpoint) or overall survival between regimens, but superior progression-free survival for platinum-based regimens. A cost analysis was conducted using direct medical costs of treatment, grade 3 or 4 toxicity management, and investigations for the mean number of cycles per study arm. Costs were calculated using Canadian dollars in 2005, and then in 2013 after drug patent expiry. RESULTS: In 2005, GEMVIN was the most expensive regimen ($6868), and PV the least expensive ($4650), with an incremental cost of GEMVIN over PV of $2218. Diagnostic and administration costs did not differ significantly among regimens; GEMVIN had the lowest toxicity costs. The principal cost driver in 2005 was the cost of chemotherapy. In 2013, toxicity and administration costs emerged as major drivers; GEMVIN was less costly than PV and PG, (cost savings of $413 over PV). CONCLUSION: Despite similar outcomes, GEMVIN was more expensive than PV or PG in 2005 because of higher chemotherapy costs. By 2013, after chemotherapy drug patent expiry, GEMVIN became the least costly regimen. Economic considerations in oncology change over time, and should be revisited in policy decisions based on cost.

The burden of endometriosis: costs and quality of life of women with endometriosis and treated in referral centres.

BACKGROUND: This study aimed to calculate costs and health-related quality of life of women with endometriosis-associated symptoms treated in referral centres. METHODS: A prospective, multi-centre, questionnaire-based survey measured costs and quality of life in ambulatory care and in 12 tertiary care centres in 10 countries. The study enrolled women with a diagnosis of endometriosis and with at least one centre-specific contact related to endometriosis-associated symptoms in 2008. The main outcome measures were health care costs, costs of productivity loss, total costs and quality-adjusted life years. Predictors of costs were identified using regression analysis. RESULTS: Data analysis of 909 women demonstrated that the average annual total cost per woman was €9579 (95% confidence interval €8559-€10 599). Costs of productivity loss of €6298 per woman were double the health care costs of €3113 per woman. Health care costs were mainly due to surgery (29%), monitoring tests (19%) and hospitalization (18%) and physician visits (16%). Endometriosis-associated symptoms generated 0.809 quality-adjusted life years per woman. Decreased quality of life was the most important predictor of direct health care and total costs. Costs were greater with increasing severity of endometriosis, presence of pelvic pain, presence of infertility and a higher number of years since diagnosis. CONCLUSIONS: Our study invited women to report resource use based on endometriosis-associated symptoms only, rather than drawing on a control population of women without endometriosis. Our study showed that the economic burden associated with endometriosis treated in referral centres is high and is similar to other chronic diseases (diabetes, Crohn's disease, rheumatoid arthritis). It arises predominantly from productivity loss, and is predicted by decreased quality of life.