The Betsy Lehman Center: Do you see evidence that patients who have high-deductible plans delay or avoid treatment? Does the effect vary according to income level, age or other demographics?

Dr. Wharam: Until I saw results of our recent breast cancer study, I might have felt comfortable making some generalizations, but not now. To provide some context, we’ve done a few studies where the effects of the switch to high-deductible plans are more pronounced in some populations than in others, consistent with our expectations. In diabetes, for example, low-income patients have reductions in care, as well as adverse outcomes, when they switch to those plans. But higher-income patients don’t seem to be similarly affected.

Going into the breast cancer study, we thought we’d see a comparable pattern, but that’s not how it turned out. We found delays in diagnosis and treatment among breast cancer patients regardless of income level, and we saw similar findings when stratifying results by other demographic characteristics. The delay in breast cancer care seemed to cut across demographic groups, including women who lived in rural vs. urban communities and in predominantly white neighborhoods vs. non-white neighborhoods. 

The Betsy Lehman Center: To what degree do employers understand in advance how policies and plan design will affect patient care and outcomes?

Dr. Wharam: This is an important question. I started my research career wanting to create tools to help employers understand the real effects of these plans on workers — both health and cost outcomes. We still don’t have sophisticated tools, but my hope is that research, such as our diabetes and cancer studies, will convince employers and insurance companies of this need. 

Small employers are fighting for survival. It is very likely they are choosing high-deductible plans based on cost so they can continue to offer health insurance.

Large employers are in a better position, but even they don’t necessarily use sophisticated or reliable approaches to determine the effect of insurance choices. Some might get relatively good information from consulting companies, but I sense that their decisions are often driven by cost, hearsay or by a philosophical sense that people should have “skin in the game.” We are still influenced by the Rand Health Insurance Experiment, a landmark study from the 1970s and ‘80s. The Rand study was a rigorous but small, randomized trial with two important takeaways that people tend to remember: 1) high out-of-pocket costs reduced the use of all types of care for all types of people and 2) health outcomes did not change. This study actually did predict that people who are both sick and have low incomes would have worse outcomes in high-deductible health plans, but that more nuanced message, as well as other important details, seem not to be as well known. 

In our research, we find many things that support the Rand study’s findings and some that contradict, and we try to design studies that can answer questions that the Rand study could not. There is also patient-level and societal learning about high-deductible plans that could change effects compared with the Rand findings, and a vastly different health care environment now compared with the ‘70s and ‘80s.

Ideally, employers would have greater awareness of effects of benefit design, but I sense that the subtleties of how these health insurance plans actually work are underappreciated.

The Betsy Lehman Center: Do you see effects of cost-shifting on the patient-provider relationship? Should primary care providers be more proactive with patients who might, for example, delay diagnostic testing for cost reasons? 

Dr. Wharam: The datasets we use are not ideal for answering this question. However, in our research, we do see some evidence that cost is influencing the decisions patients make together with their providers. For example, people who come to the emergency room for care are less likely to be admitted if they have high-deductible plans. Busy ER docs are unlikely to know about the patient’s insurance status. It appears the patient’s awareness of cost is transmitted to the admitting physician; otherwise, why would admissions go down? 

One framework for thinking about high out-of-pocket costs is that these can cause side effects in the same way a drug can cause side effects. This has been termed “financial toxicity.” A patient who faces high cost might not accept or proceed with care recommended by the provider. Provider awareness of health insurance status does seem important. Increasingly, providers have care managers who look after certain vulnerable patients. Those teams should be aware of their patients’ insurance arrangements. That may be a way to reduce the potential for adverse outcomes among people with high-deductible insurance. 

Some researchers are using patient survey data to study behavior to learn why patients make certain decisions and to understand how high-deductible plans affect health outcomes. What we learn from survey data is different — more in-depth in certain realms — from what we learn from claims data and helps fill an important gap in the literature.

The Betsy Lehman Center: What are the synergies between population-level health services research and patient safety efforts? In what ways should the two disciplines be working together?

Dr. Wharam: As health services researchers, we’re very concerned about patient safety but we think about it in a different context. There’s always potential for health policies to harm patients. For example, there has been a lot of concern that 30-day readmission policies are having unintended consequences. 

I think collaboration between patient safety experts and health services researchers is a great idea. We’re going continue to work on understanding the true effects of insurance plans on health outcomes. We expect to report results about the effects of high-deductible plans on health outcomes such as stroke, myocardial infarction, amputations, and breast cancer survival in the next year or two. We’re finally getting to the point where we can look at these important morbidities and events and gain a robust understanding. We hope that policymakers and health insurers use these results to design smarter, more tailored health insurance arrangements — what we have called “population-tailored health insurance designs.” Ideally, health insurance would be designed and incentivized based on rigorous evidence about effects on patient outcomes and populations.