Background: Value-based insurance designs establish cost-sharing levels to promote services perceived to be high value from the health insurer or policy maker’s perspective. However, it is unclear how people with multiple chronic conditions will react to changes in insurance design because they may not be willing or able to switch to lower cost prescription drugs. These individuals are the heaviest consumers of prescription drugs and may be more susceptible to short term complications from poorly managed conditions or from drug/drug interactions. This dissertation evaluates how adults with multiple chronic conditions respond to a change in insurance benefit design.
Methods: Data consists of drug and medical claims from Maryland’s high-risk pool for the years 2007-2011. High-risk pools offer insurance to those with preexisting conditions who were denied coverage on the individual market and who do not have access to employer-based insurance. An interrupted time series design with individual-level data exploits a co-pay change in 2010 that raised copayments on brand name medications while decreasing copayments on generic drugs. Outcomes include drug utilization, medical service utilization, drug and medical spending, generic substitution and whether the policy impacted medication adherence.
Results: The copayment policy change had a statistically significant impact on those with increasing numbers of chronic conditions, but the magnitudes are small. The use of both brand and generic drugs increased less than one drug fill per quarter across all numbers of chronic conditions following the policy change. The financial impact was greatest for those with the most chronic conditions—an over $150 increase in quarterly out-of-pocket spending for those with 10 or more chronic conditions. The use of generics increased for antidepressant drugs and decreased for hypertensive drugs. Overall, adherence levels remained unchanged.
Conclusions: This study finds little impact on the use of prescription drugs following a value-based insurance design initiative. Most of the impact is seen in those with the highest number of conditions who use more services and they experienced increased financial burden. Other insurance benefit design tools may be more effective in this population
