We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrolment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modelling reveals large “choice inconsistencies” such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of “approximate inertia” where enrolees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrolees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or “choice overload”. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.
We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrolment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modelling reveals large “choice inconsistencies” such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of “approximate inertia” where enrolees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrolees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or “choice overload”. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.
Competition in health insurance markets may fail to improve health outcomes if consumers are not able to identify high-quality plans. We develop and apply a novel instrumental variables framework to quantify the variation in causal mortality effects across plans and measure how much consumers attend to this variation. We first document large differences in the observed mortality rates of Medicare Advantage plans in local markets. We then show that when plans with high mortality rates exit these markets, enrollees tend to switch to more typical plans and subsequently experience lower mortality. We derive and validate a novel “fallback condition” governing the subsequent choices of those affected by plan exits. When the fallback condition is satisfied, plan terminations can be used to estimate the relationship between observed plan mortality rates and causal mortality effects. Applying the framework, we find that mortality rates unbiasedly predict causal mortality effects. We then extend our framework to study other predictors of plan mortality effects and estimate consumer willingness to pay. Higher-spending plans tend to reduce enrollee mortality, but existing quality ratings are uncorrelated with plan mortality effects. Consumers place little weight on mortality effects when choosing plans. Good insurance plans dramatically reduce mortality, and redirecting consumers to such plans could improve beneficiary health.
Background: A growing body of scientific evidence suggests that face masks can slow the spread of COVID-19 and save lives, but mask usage remains low across many parts of the world, and strategies to increase mask usage remain untested and unclear. Methods: We conducted a cluster-randomized trial of community-level mask promotion in rural Bangladesh involving 341,830 adults in 600 villages. We employed a series of strategies to promote mask usage, including free household distribution of surgical or cloth masks, distribution and promotion at markets and mosques, mask advocacy by Imams during Friday prayers, role modeling by local leaders, promoters periodically monitoring passers-by and reminding people to put on masks, village police accompanying those mask promoters, providing monetary rewards or certificates to villages if mask-wearing rate improves, public signaling of mask-wearing via signage, text message reminders, messaging emphasizing either altruistic or self-protection motives for mask-wearing, and extracting verbal commitments from households. The primary objective was to assess which of these interventions would increase proper (covering nose and mouth) wearing of face masks, and secondarily, whether mask promotion unintentionally creates moral hazard and decreases social distancing. This analysis is part of larger study evaluating the effect of mask-wearing on transmission of SARS-CoV-2.
Results: There were 64,937 households in the intervention group and 64,183 households in the control group; study recruitment has ended. In the control group, proper mask-wearing was practiced by 13% of those observed across the study period. Free distribution of masks along with role modeling by community leaders produced only small increases in mask usage during pilot interventions. Adding periodic monitoring by mask promoters to remind people in streets and public places to put on the masks we provided increased proper mask-wearing by 29.0 percentage points (95% CI: 26.7% - 31.3%). This tripling of mask usage was sustained over all 10 weeks of surveillance, which includes a period after intervention activities ended. Physical distancing, measured as the fraction of individuals at least one arm’s length apart, also increased by 5.2 percentage points (95% CI: 4.2%-6.3%). Beyond the core intervention package comprised of free distribution and promotion at households/mosques/markets, leader endorsements plus periodic monitoring and reminders, several elements had no additional effect on mask wearing, including: text reminders, public signage commitments, monetary or non-monetary incentives, altruistic messaging or verbal commitments, or village police accompanying the mask promoters (the last not cross-randomized, but assessed in panel data). No adverse events were reported during the study period.
Conclusions: Our intervention demonstrates a scalable and cost-effective method to promote mask adoption and save lives, and identifies a precise combination of intervention activities that were necessary. Comparisons between pilots shows that free mask distribution alone is not sufficient to increase mask-wearing, but adding periodic monitoring in public places to remind people to wear the distributed masks had large effects on behavior. The absence of any further effect of the village police suggests that the operative mechanism is not any threat of formal legal sanctions, but shame and people’s aversion to a light informal social sanction. The persistence of effects for 10 weeks and after the end of the active intervention period, as well as increases in physical distancing, all point to changes in social norms as a key driver of behavior change. Our cross-randomizations suggest that improved mask-wearing norms can be achieved without incentives that require costly monitoring, that aesthetic design choices and colors can influence mask-wearing, and that surgical masks with a substantially higher filtration efficiency can be a cost-effective alternative to cloth masks (1/3 the cost) and are equally or more likely to be worn. Implementing these interventions – including distribution of free masks, and the information campaign, reminders, encouragement – cost $2.30-$3.75 per villager, or between $8 and $13 per person adopting a mask. Combined with existing estimates of the efficacy of masks in preventing COVID-19 deaths, this implies that the intervention cost $28,000-$66,000 per life saved. Beyond reducing the transmission of COVID-19, mask distribution is likely to be a cost-effective strategy to prevent future respiratory disease outbreaks.
Methods: We conducted a cluster-randomized trial of community-level mask promotion in rural Bangladesh from November 2020 to April 2021 (N=600 villages, N=342,126 adults). We cross-randomized mask promotion strategies at the village and household level, including cloth vs. surgical masks. All intervention arms received free masks, information on the importance of masking, role modeling by community leaders, and in-person reminders for 8 weeks. The control group did not receive any interventions. Neither participants nor field staff were blinded to intervention assignment. Outcomes included symptomatic SARS-CoV-2 seroprevalence (primary) and prevalence of proper mask-wearing, physical distancing, and symptoms consistent with COVID-19 (secondary). Mask-wearing and physical distancing were assessed through direct observation at least weekly at mosques, markets, the main entrance roads to villages, and tea stalls. At 5 and 9 weeks follow-up, we surveyed all reachable participants about COVID-related symptoms. Blood samples collected at 10-12 weeks of follow-up for symptomatic individuals were analyzed for SARS-CoV-2 IgG antibodies.
Results: There were 178,288 individuals in the intervention group and 163,838 individuals in the control group. The intervention increased proper mask-wearing from 13.3% in control villages (N=806,547 observations) to 42.3% in treatment villages (N=797,715 observations) (adjusted percentage point difference = 0.29 [0.27, 0.31]). This tripling of mask usage was sustained during the intervention period and two weeks after. Physical distancing increased from 24.1% in control villages to 29.2% in treatment villages (adjusted percentage point difference = 0.05 [0.04, 0.06]). After 5 months, the impact of the intervention faded, but mask-wearing remained 10 percentage points higher in the intervention group.
The proportion of individuals with COVID-like symptoms was 7.62% (N=13,273) in the intervention arm and 8.62% (N=13,893) in the control arm. Blood samples were collected from N=10,952 consenting, symptomatic individuals. Adjusting for baseline covariates, the intervention reduced symptomatic seroprevalence by 9.3% (adjusted prevalence ratio (aPR) = 0.91 [0.82, 1.00]; control prevalence 0.76%; treatment prevalence 0.68%). In villages randomized to surgical masks (n = 200), the relative reduction was 11.2% overall (aPR = 0.89 [0.78, 1.00]) and 34.7% among individuals 60+ (aPR = 0.65 [0.46, 0.85]). No adverse events were reported.
Conclusions: Our intervention demonstrates a scalable and effective method to promote mask adoption and reduce symptomatic SARS-CoV-2 infections.