Health plan choices
Estimates of total cost remain among the most important ways to convey a plan’s value for consumers. We also see many other opportunities to help consumers understand the value of different plan designs and compare them.
In reviewing these plan designs, we identified some key aspects that can be simplified for consumers.
Pre-deductible coverage is a major driver of how consumers experience plans with higher deductibles, like the deductibles in many in Silver and Bronze plans in the Marketplaces. Consumers who choose a plan without understanding the nature of the deductible can easily find themselves with high medical costs, leaving them questioning the value of having insurance. Conversely, if a consumer knows about and uses pre-deductible coverage, they may well be satisfied with a plan even if it has a much higher deductible than they thought they could accept.
Pre-deductible coverage is also an important differentiator of value in out-of-pocket estimates among plans with otherwise similar benefit designs. Plans with more generous pre-deductible coverage will have lower out-of-pocket estimates, and when pre-deductible coverage is highlighted, this can help guide consumers toward plans that more tangibly provide value to consumers.
Consumers are very concerned about their healthcare costs, but they have varying – and often low - levels of understanding what plan designs mean for them in terms of out-of-pocket costs. However, we have learned from research we conducted with experts at Duke and Penn that consumers concepts out-of-pocket costs don’t always match estimates that are calculated in online tools. Consumers may be looking for something that gives them a precise prediction of what their costs will be; such a prediction is obviously not possible under an insurance plan.
At the same time, consumers understandably want to know costs for predictable events like filling a prescription on a monthly basis. Although this seems simple, in practice the vagaries of drug pricing make it very difficult to provide accurate predictions. We are working on ways to incorporate drugs costs into plan selection that handle this variability without having drug prices that aren’t accurate (for that particular plan at a particular pharmacy).
Some plans offer low copays and coinsurance for ambulatory services like doctor visits and drugs, while adding hefty cost-sharing for hospital stays – we routinely see $1500 copays for a hospital visit alongside low copays for primary care visits.
In other cases, plans may have a “base benefit” of a high coinsurance for specialty drugs (e.g. 40%), but that skimpy benefit is offset by a cap of $150. We are exploring ways to better represent this sort of benefit information to reduce complexity and make the info more applicable to the consumers’ situation.
Starting in 2016, we partnered with Dave Chandrasekaran to publish a summary of Marketplace plans in range of states. You can see examples here. Visualizing data in this way helps clarify the tradeoffs in benefits between different plans. We plan to expand on this kind of comparison to help illuminate this type of tradeoff.
Working with researchers at and UPenn and Duke we interviewed 33 Navigators about the use of decision support tools in Marketplace enrollment.
Help Consumers Shift to a Value-Oriented mindset
A significant body of academic research (Baker, Monheit, Bialowoski, Han, and many others) on consumers shopping for health plans indicate that behavioral factors like poor self-confidence in financial choices, low patience for hassles, present-focused thinking, or fear of high health lead consumers to suboptimal choices. Our focus groups and other detailed plan selection work with consumers have illustrated how important it is to help consumers get into a frame of mind where they can make value-oriented choices
We believe that several approaches may be useful:
• Using messaging that changes people’s mental/emotional frame of reference toward thinking through what they want and value. Nearly all consumers can do this for products such as cars – even those who have never owned a car. For insurance, this might take the form of thinking about their children and their desire to protect their children.
• Connect plan choice consumers’ specific health goals and needs. This might take the form of asking about diseases and using this to shape their out-of-pocket estimates, or other profiling of plans based on diseases.
• Help consumers overcome “inertia” through targeted prompting. This might include email or phone interventions, similar to the Covered California pilot of targeted calls to help consumers Yin reviews, .
Help consumers shop for provider networks
Provider networks are perhaps the most important part of a insurance plan, as they are the gate between consumers and accessing healthcare with insurance coverage. Our tools were first in the nation to display a localized measure of network breadth within the plan shopping experience. While we originally developed this measure an effort to signal to consumers that plan might have a very narrow network, we believe there is a great deal more that needs to be done. As groundwork, there are many improvements needed to this data, from creating a standardized identifiers for networks,
Problems of accuracy in provider directories have been extensive discussed in both health policy fora and in the peer reviewed literature for a number of years. Although progress has been made on availability of provider-network data (such as through ACA JSON files and the Provider Directory API requirements), there are still numerous challenges for consumers in obtaining a definitive answer whether a doctor is or is not covered or not covered by their health plan. To address this, we have proposed a standard, consumer-friendly identifier for networks.
As a simple example, a diabetic person who uses an insulin pump has almost no way to know which insurance companies offer coverage of that insulin pump.
In addition, we are advocating for data transparency for Federal Employee Health Benefits program plans.