THE IMPACT OF A VALUE-BASED INSURANCE DESIGN ON THOSE WITH MULTIPLE CHRONIC CONDITIONS.

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

Estimating preferences for medical devices: does the number of profile in choice experiments matter?

Background: Most applications of choice-based conjoint analysis in health use choice tasks with two profiles, while marketing studies routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on hearing aids. - Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys, and were randomized to choice tasks with two or three profiles. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analyses of individual-level models estimated with ordinary least squares. - Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P<0.0001). Pairs led to more variation, and were systematically biased toward the null because a third (32.2%) of respondents focused on only one attribute. This is in contrast to respondents in the triplet design who traded across all attributes. - Discussion: The number of profiles in choice tasks affects the results of conjoint analysis studies. Here triplets are preferred to pairs as they avoid non-trading and allow for more accurate estimation of preferences models

Estimating Patients' Preferences for Medical Devices: Does the Number of Profile in Choice Experiments Matter?

Background: Most applications of choice-based conjoint analysis in health use choice tasks with only two profiles, while those in marketing routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on measuring patient preference for hearing aids. Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys incorporating a conjoint analysis, but were randomized to choice tasks with two or three profiles. Baseline differences between the two groups were explored using ANOVA and chi-square tests. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analysis of individual-level models estimated with ordinary least squares. Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. The only significant difference between the groups was time to complete the survey (11.5 and 21 minutes respectively). Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P

Estimating preferences for medical devices:does the number of profile in choice experiments matter?

Background: Most applications of choice-based conjoint analysis in health use choice tasks with two profiles, while marketing studies routinely use three or more. This study reports on a randomized trial comparing paired with triplet profile choice formats focused on hearing aids. Methods: Respondents with hearing loss were drawn from a nationally representative cohort, completed identical surveys, and were randomized to choice tasks with two or three profiles. The primary outcomes of differences in estimated preferences were explored using t-tests, likelihood ratio tests, and analyses of individual-level models estimated with ordinary least squares. Results: 500 respondents were recruited. 127 had no hearing loss, 28 had profound loss and 22 declined to participate and were not analyzed. Of the remaining 323 participants, 146 individuals were randomized to the pairs and 177 to triplets. Pairs and triplets produced identical rankings of attribute importance but homogeneity was rejected (P<0.0001). Pairs led to more variation, and were systematically biased toward the null because a third (32.2%) of respondents focused on only one attribute. This is in contrast to respondents in the triplet design who traded across all attributes. Discussion: The number of profiles in choice tasks affects the results of conjoint analysis studies. Here triplets are preferred to pairs as they avoid non-trading and allow for more accurate estimation of preferences models

THE IMPACT OF A VALUE-BASED INSURANCE DESIGN ON THOSE WITH MULTIPLE CHRONIC CONDITIONS.

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

Evaluating consumer preferences for healthy eating from community kitchens in low-income urban areas : a discrete choice experiment of comedores populares in Peru

Many low-income individuals from around the world rely on local food vendors for daily sustenance. These small vendors quickly provide convenient, low-priced, tasty foods, however, they may be low in nutritional value. These vendors serve as an opportunity to use established delivery channels to explore the introduction of healthier products, e.g. fresh salad and fruits, to low-income populations. We sought to understand preferences for items prepared in Comedores Populares (CP), government-supported food vendors serving low-income Peruvians, to determine whether it would be feasible to introduce healthier items, specifically fruits and vegetables. We used a best-worst discrete choice experiment (DCE) that allowed participants to select their favorite and least favorite option from a series of three hypothetical menus. The characteristics were derived from a series of formative qualitative interviews conducted previously in the CPs. We examined preferences for six characteristics: price, salad, soup, sides, meat and fruit. A total of 432 individuals, from two districts in Lima, Peru responded to a discrete choice experiment and demographic survey in 2012. For the DCE, price contributed the most to individual's utility relative to the other attributes, with salad and soup following closely. Sides (e.g. rice and beans) were the least important. The willingness to pay for a meal with a large main course and salad was 2.6 Nuevos Soles, roughly a 1 Nuevo Sol increase from the average menu price, or USD $0.32 dollars. The willingness to pay for a meal with fruit was 1.6 Nuevo Soles. Overall, the perceived quality of service and food served in the CPs is high. The willingness to pay indicates that healthier additions to meals are feasible. Understanding consumer preferences can help policy makers design healthier meals in an organization with the potential to scale up to reach a considerable number of low-income families

No Man is an Island: The Impact of Neighborhood Disadvantage on Mortality

This study&#8217;s purpose is to determine if neighborhood disadvantage, air quality, economic distress, and violent crime are associated with mortality among term life insurance policyholders, after adjusting for individual demographics, health, and socioeconomic characteristics. We used a sample of approximately 38,000 term life policyholders, from a large national life insurance company, who purchased a policy from 2002 to 2010. We linked this data to area-level data on neighborhood disadvantage, economic distress, violent crime, and air pollution. The hazard of dying for policyholders increased by 9.8% (CI: 6.0&#8211;13.7%) as neighborhood disadvantage increased by one standard deviation. Area-level poverty and mortgage delinquency were important predictors of mortality, even after controlling for individual personal income and occupational status. County level pollution and violent crime rates were positively, but not statistically significantly, associated with the hazard of dying. Our study provides evidence that neighborhood disadvantage and economic stress impact individual mortality independently from individual socioeconomic characteristics. Future studies should investigate pathways by which these area-level factors influence mortality. Public policies that reduce poverty rates and address economic distress can benefit everyone&#8217;s health