Calvin Ackley

This paper studies the impact of a preferred network design on procedure-level spending for lab services. This plan structure, termed the "Site of Service" design, employes a two-tiered cost-sharing schedule for lab tests: patients incur no out-of-pocket costs at preferred providers but face a deductible at non-preferred providers. Using event-study methods and administrative data on two large carriers, I find that these tiered incentives lead to a considerable reduction in the price paid per lab, with effect size ranging from 14% to 36% across groups and time. I find that the preferred provider program generates savings both by steering consumers towards less expensive providers and by putting downward pressure on negotiated prices. Notably, I present explicit causal evidence linking the preferred network to substantial negotiated price cuts. I find that these price dynamics account for about half of the overall program savings while the steering mechanism accounts for the remainder.

In this paper, I study tiered cost sharing, an innovative incentive structure designed to steer patients toward low-cost providers using large out-of-pocket price differentials. Using administrative data from New Hampshire, where two large insurers utilize tiered pricing programs, I estimate the effects of tiering on choices and spending for common gastrointestinal endoscopic procedures. I first conduct a difference-in-differences analysis using the rollout of one insurer’s tiered option. I then develop and estimate a demand model to explicitly compare the tiered design with other common plans. Both the reduced form and structural models imply that the tiered plans are associated with 4.5%–6.3% less in mean per-episode spending than high-deductible and coinsurance-based plans, and do not affect the likelihood of seeking care. I find evidence that the savings is in part due to a salience or “simple pricing” effect whereby patients respond to tiered out-of-pocket prices but not to traditional deductibles or coinsurance rates.

The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.