ABSTRACT
BACKGROUND: Although annual influenza vaccination could decrease the significant economic and humanistic burden of influenza in the United States, immunization rates are below recommended levels, and concerns remain whether immunization programs can be cost beneficial. The research objective was to compare cost benefit of various immunization strategies from employer, employee, and societal perspectives. METHODS: An actuarial model was developed based on the published literature to estimate the costs and benefits of influenza immunization programs. Useful features of the model included customization by population age and risk-level, potential pandemic risk, and projection year. Various immunization strategies were modelled for an average U.S. population of 15,000 persons vaccinated in pharmacies or doctor's office during the 2011/12 season. The primary outcome measure reported net cost savings per vaccinated (PV) from the perspective of various stakeholders. RESULTS: Given a typical U.S. population, an influenza immunization program will be cost beneficial for employers when more than 37% of individuals receive vaccine in non-traditional settings such as pharmacies. The baseline scenario, where 50% of persons would be vaccinated in non-traditional settings, estimated net savings of $6 PV. Programs that limited to pharmacy setting ($31 PV) or targeted persons with high-risk comorbidities ($83 PV) or seniors ($107 PV) were found to increase cost benefit. Sensitivity analysis confirmed the scenario-based findings. CONCLUSIONS: Both universal and targeted vaccination programs can be cost beneficial. Proper planning with cost models can help employers and policy makers develop strategies to improve the impact of immunization programs.
ABSTRACT
One objective of a disease management (DM) program is the reduction of members' claims costs. A considerable amount of effort has been dedicated to standardizing the outcomes of DM measurement. An area that has not received as much attention is that of random fluctuations in measured outcomes and the related issue of the validity of outcomes subject to random fluctuation. From year to year, large random fluctuations in claims costs can increase or reduce actual savings from a DM program. Sponsors of DM programs want to know how large a group or sample is necessary to prevent the effect of random fluctuations from overwhelming the effect of claims reductions. In this paper, we measure the fluctuations in calculated DM savings in a large commercial population using an adjusted historical control methodology--the methodology that has become the industry standard and which is codified by DMAA's Guidelines. We then determine the sample size necessary to demonstrate DM program savings at different levels of confidence and model the effect on fluctuations in observed outcomes under different methods of choosing trend, different levels of truncation, and for different estimates of program savings. Some groups, particularly employers, will be smaller than the minimum size required for credible outcomes measurement. For groups smaller than this minimum size, we suggest a utilization-based outcomes measure that can be used as a proxy. For both claims- and utilization-based calculations, we provide confidence intervals to be placed around savings estimates. We do this for group sizes ranging from 1000 to 100,000 members.
