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Q&A with Katherine Milkman: Keeping Your Resolutions

By | CHIBEblog
What are some common roadblocks to keeping new year’s resolutions? How can behavioral strategies remove them?

Self-control problems lead us to put off doing what we resolve to do better until later.  I’ll start the diet, but NEXT week.  I’ll go to the gym, but NEXT week.  Commitment devices are a terrific behavioral solution.  They involve signing up for some kind of punishment in the future (e.g., paying a fine, being ashamed in front of friends on social media) if we don’t actually do what we’ve resolved to do.  So I might sign up for a commitment device (say using stickk.com) and agree that if I don’t go to the gym twice next week, I’ll owe $25 to a charity I hate.  Now, when I feel the urge to procrastinate about

exercising, I’ll realize that putting it off will cost me $25 and I’m less likely to postpone that healthy behavior.  Another solution is just to make a plan about when, where and how you’ll follow-through.  This reduces forgetting and makes procrastination more awkward because procrastinating requires breaking an explicit commitment rather than a vague one.

Would you recommend that individuals pick one behavioral strategy (temptation bundling etc.) to set themselves up for success with their new year’s resolutions, or employ multiple strategies?

The more behavioral solutions the better, as far as I’m concerned.  It’s hard to stick to goals, and so we need help.  The more things we can line up that will help us – from social support (e.g., a friend to meet at a pre-scheduled time at the gym) to commitment devices (e.g., $25 to a charity you hate if you skip your workout) to temptation bundles (e.g., linking exercise with a guilty pleasure like watching the next episode in your favorite drama on TV) – the better our chances of success.

Is there a sweet spot in terms of number of resolutions to set for the year? Could setting more than a certain number of resolutions become an
impediment to keeping any?

Hmm.  That’s an interesting question.  There is research showing that planning the way to achieve too many goals can actually be harmful, so there may be a sweet spot for resolutions.  I normally set one or two, personally, but that’s not based on any hard data!

Are there particular types of resolutions that are best suited to certain behavioral strategies? If so, which ones?

The best resolutions are concrete, a little bit challenging but not impossible, and can be achieved by sticking to a straightforward set of actions.  Behavioral strategies will be most useful if it’s possible to make a plan that will facilitate reaching the goal and if it’s possible to use tactics like commitment devices and social support for motivation.  So, going to the gym twice a week is a great example of a good goal that’s well suited to behavioral strategies.  You can plan when you’ll get there, who you’ll work out with, and put money on the line that you’ll forfeit if you don’t make it.  A less fabulous goal would be to get healthier more often since it’s vague and less clear how to use behavioral tools to achieve this.

When It Comes to Calorie Consumption, Is Knowledge Power?

By | CHIBEblog

“The other day, I went to order lunch from a local chain restaurant. Half a turkey sandwich and a small cup of soup sounded like a good, appropriately sized, warm meal for a wintery day. As I placed my order, a kiosk tallied the calories right before my eyes: 400 for the sandwich and almost 300 for the soup…

Hmm. That seemed like a lot. Maybe, I thought, if I remove the bacon from the sandwich… and get a smaller soup…? “You know

calorie-count-menu

Image credit: Terrence Horan, MarketWatch

what? I’m sure it’s fine,” I told myself, and completed the order.

Over-consumption of calories has been a key driver of rising rates of obesity, and dining out is thought to play a significant role as people often substantially underestimate the calories in prepared foods. Restaurant menu labeling has been implemented in several cities and states and was included in the Affordable Care Act. By May 2018, chain restaurants, grocery stores, and other food establishments with 20 or more locations will be required to post calorie information on their menus. The hope is that making such information more visible will encourage consumers to choose – and restaurants to offer – lower-calorie items. But will it work?

We talked with Christina Roberto, PhD, director of the Psychology of Eating and Consumer Health (PEACH) Lab, about what the latest research shows on how knowing calorie information affects what people order and how much they consume.”


Q: Calorie labeling is relatively new. Has there been enough research to know if it works?

A: In short, the jury is still out on whether or the degree to which menu labeling encourages lower-calorie purchases and whether that will translate to a healthier population. But, there has been some research on the topic and we’re starting to learn more about how it affects consumer decision making in different settings like fast-food restaurants, cafeterias, and full-service chain restaurants.

We recently published a study that looked at all of the available research to date, and overall, although there’s little evidence to suggest that calorie labeling is leading to lower calorie purchases at fast-food restaurants, there are more promising findings that it may influence consumers at certain types of restaurants, such as full-service sit-down restaurants, coffee shops, and cafeterias.

Q: Why would that be?

A: it’s possible that calorie labeling may have more of an effect in certain settings because of the types of people who frequent those establishments, or differences in the psychology of ordering based on the restaurant setting.

For example, it could be that coffee chains, full-service sit-down chains, or fast-food outlets that market themselves as “healthy” attract consumers with higher incomes, education levels, and/or health consciousness who are more likely to pay attention to or be influenced by calorie labels. Some of the studies we looked at showed that awareness or use of menu labels is higher among certain consumers, such as women and those with higher incomes and health consciousness.

It’s also possible that calorie labeling doesn’t affect fast food patrons as much because they go to these restaurants already knowing what they want to order, while full-service sit-down patrons may spend more time reviewing the menu before making their decisions.

We also saw evidence that calorie labeling can promote lower-calorie choices in cafeteria settings. That could be because people eat there more regularly, like in a cafeteria in the work place, and are less likely to view the meal as a “treat” compared to dining out.

The bottom line is that we have some ideas about when calorie labeling may be more effective, but the mixed results we see, may be due in large part to issues with study design.

Q: Can you elaborate on that? Were there some studies that were more promising than others?

A: Yes, eighteen of the studies we examined evaluated calorie information in real-world restaurant settings. These varied greatly in design, with only one randomized control trial (RCT) and one quasi-real-world RCT. Seven studies used natural experiments evaluating menu labeling before and after implementation in an intervention and control city, while seven other studies only looked at changes before and after menu labeling was implemented in a city. Finally, two studies compared labeled versus unlabeled restaurant locations at the same point in time.

The strongest research design to evaluate menu labeling is a randomized controlled field experiment. Unfortunately, we were only able to find one of those, and the sample size was too small to be able to detect even moderate effects. But the study with the next strongest design found that calorie labeling was associated, on average, with a 15-calorie reduction per order at a coffee shop chain. And although there was only one real-world, full-service chain restaurant analysis with an adequate sample size, that study found that calorie labeling was associated with a 150-calorie reduction per order.

So the bottom line is that evaluations of menu labeling in different settings are mixed, but because much of the research is plagued by small sample sizes and sub-optimal study designs, what we really found is that there’s a considerable need for more research in this area. Data from RCT field experiments and natural experiments with large sample sizes testing menu labeling are needed, especially at full-service chain restaurants.

Q: As more restaurants are preparing to include calorie information on their menus, what, if anything, can be done to improve the impact labels have on decision making?

A: Well, presumably, making calorie information easier to understand and more accessible to a greater range of individuals would increase the reach and impact of the information. Some studies have shown, for example, that using traffic light systems to show which menu items are lower-calorie (indicated by green lights) and which are higher calorie (indicated by red lights) can cut the number of calories ordered by ten percent—but these types of labels don’t always outperform calorie information alone. We really need more real-world RCTs with large enough sample sizes to know for sure.

But rather than just focus on how calorie labels directly influence consumers, we were also interested in how labeling might influence what restaurants offer on their menus. Although the preliminary evidence suggests that calorie labeling regulations may be correlated with healthier restaurant offerings, the small number of studies and differences in study design make it difficult to draw conclusions at this point.


According to Roberto, research suggests that in order to return to 1970 levels of excess weigh in the population, adults need to consume 220 fewer calories daily, while children need to consume 165 fewer calories daily. Reducing consumer purchases in chain restaurants by even a small amount may help reduce this excess calorie intake.

This post originally appeared on the Penn Medicine News Blog.

David Laibson: Solving the Commitment Puzzle

By | CHIBEblog

CHIBE was pleased to welcome David Laibson, Phd as a keynote speaker on day two of our annual Behavioral Economics & Health Symposium, hosted jointly this year with the NBER Roybal Center for Behavior Change in Health and Savings. In his talk, Laibson presented attendees with a problem he calls the commitment puzzle, and a solution – private paternalism—that can help us keep the commitments we make to ourselves even in the absence of the ability to predict our own behavior.

The first digital pill: innovation or invasion?

By | CHIBEblog

The Food and Drug Administration (FDA) recently approved the first digital pill that tracks if patients have taken their medication. Our experts weighed in on the potential benefits of the new technology, as well as the potential for abuse.

(from left to right) Kevin Volpp, MD, PhD; Holly Fernandez Lynch, JD, MBe; Emily Largent, PhD, JD, RN; Robert Field, PhD, JD, MPH

The pill, a version of the antipsychotic Abilify used to treat schizophrenia and other mental illnesses, has an ingestible sensor that communicates with a wearable patch to record date and time of ingestion, as well as other physiological data. Patients can track their activity in a mobile application and permit their doctors and/or caregivers to view the information online.

Many hope the new technology will help to address the longstanding problem of medication nonadherence, which accounts for more than $100 billion in avoidable health care costs each year in the US. “Medication nonadherence is a huge public health challenge in the United States,” said Kevin Volpp, director of the Center for Health Incentives & Behavioral Economics (CHIBE), in an interview with The Philadelphia Inquirer. The new technology adds to a growing list of digital devices used to monitor medicine-taking, such as digital pill bottles. Previous research by Dr. Volpp has shown that automated reminders and physician notification via digital pill bottles are a promising means to help high-risk patients follow their prescribed medication regimen.

However, the digital pill goes a bit further, explained Holly Fernandez Lynch, assistant professor of medical ethics and health policy, in an interview with Wharton Business Radio. “What’s new about [the digital pill] is this is something you swallow, and it’s less easy to game the system.” An electronic pill bottle records that the bottle is opened, but not whether the medication has been taken. This technology is the next step to avoid that kind of gaming.

In the same interview, Robert Field, professor of law and professor of health management and policy at Drexel University, highlighted the pill’s potential to address other public health issues in which medication adherence plays a large part, including antibiotic resistance, infectious diseases (specifically, tuberculosis), and AIDS (antiretroviral drugs). In addition, Fernandez Lynch and Field both agreed that clinical trials are among the most exciting new uses for the digital pill; it could help researchers determine whether a new medication is not effective, or if subjects simply aren’t taking it.

Despite these possible benefits, our experts also expressed concerns about the new technology. One point of debate is whether Abilify is the right product to start with, explained Fernandez Lynch. On one hand, missing a dose of medication for patients with schizophrenia has serious clinical implications, and reminders could be critical.  On the other hand, there are also concerns about whether that population has the capacity to consent to this type of medication. Although wearing the patch is voluntary, this may be especially problematic if insurers begin to tie copays and/or benefits to use of the digital pill. For example, if an insurer refuses to cover the drug if a beneficiary doesn’t wear the patch, Fernandez Lynch said, “then we have to start asking: ‘Is it still voluntary? When does it no longer become voluntary?”

Privacy is also a concern, explained Emily Largent, assistant professor of medical ethics and health policy, in a radio interview with The Takeaway. “Because mental health is stigmatized, we’re worried about this particular group of patients being the first group going out,” she said. However, Dr. Largent noted that the new technology has protections built into it to avoid an invasion of privacy.  “The monitoring is not continuous, as the sensor is digested and excreted. The patch can be removed and needs to be replaced every seven days anyhow. And patients can instantly remove physicians and family members from seeing their data if they don’t want them to. Patients still have a fair amount of control,” she explained.

The FDA expects an uptick in proposals for new digital pills that treat other conditions. Ultimately, our experts agree that this is an exciting new advance in medication-monitoring technologies. However, it will only work if clear protections are put in place to prevent abuse and the data are used in a way to collaboratively problem-solve with patients for their benefit rather than punishing them for their decisions.

This post originally appeared on Health Policy$ense.

LDI Symposium Highlights Promising Behavioral Solutions to Public Health Challenges

By | CHIBEblog

Earlier this month, our founding partner, the Leonard Davis Institute of Health Economics, celebrated 50 years of research with a symposium drawing together some of the brightest minds in health policy. At a panel focused on the potential for behavioral science to influence health care, CHIBE Director Kevin Volpp, MD, PhD joined External Advisory Board member Robert Galvin, MD, Internal Advisory Board member Barbara Kahn, PhD, MBA, MPhil and renowned Duke University behavioral economist Peter Ubel, MD to outline behavioral solutions that address premature mortality in the United States. The panel, moderated by Internal Advisory Board member David Asch, MD, MBA highlighted the ways in which health care delivery systems and employers can leverage behavioral insights to promote health.

Humans have bounded rationality in predictable ways. In his talk, Dr. Volpp described program designs that take advantage of our typical decision errors to help make it easier for individuals to engage in healthier behaviors. Policies such as changing the default prescription option in electronic health records to a generic medication and using an enhanced active choice automatic refill program for prescriptions can boost health while cutting down on unnecessary costs.

Another area ripe for behaviorally-informed policy change is menu presentation of health information. Dr. Ubel explained that the location of calorie labels impacts how we eat in often unexpected ways. When calorie information is placed on the side of the menu where we begin reading (left for English, right for Hebrew), we curb our consumption. In another experiment, Dr. Ubel found that surcharges for unhealthy menu items are much less effective at shifting our eating habits than labels listing those same foods as “unhealthy” or approaches that combine the labels and the surcharges.

Dr. Kahn described the many exciting ways in which Amazon has been transforming retail. She highlighted principles that could be applied to health care, including the importance of both minimizing pain points and creating experiences that exceed expectations. Dr. Kahn also described ways in which data can be seamlessly collected about a person’s preferences, and how this creates many ready opportunities for personalization that could be applied in health care settings.

After years of experience working directly with CEO’s to develop employee health policies, Dr. Galvin brought a unique perspective to the panel. Workplace wellness programs can place employers in an uncomfortable role, while at the same time, employees frequently have little interest in getting healthier. Dr. Galvin suggests that, in addition to focusing on benefit design, employers should carefully consider environmental changes to the workplace that promote a healthier lifestyle. This can include behaviorally-informed placement of healthier foods on the work site and the incorporation of standing desks or other movement that disrupts sedentary jobs. Employers are already comfortable making work sites safer and “greener,” so making these environments healthier is a logical next step.

Improving the relatively poor health outcomes of the United States will take time. However, small, behaviorally-informed changes in our offices, restaurants and health care policies can contribute to producing significant improvements.

Wharton-Sirius Radio Previews Issues From Upcoming LDI 50th Anniversary Symposium

By | CHIBEblog

The Department of Health and Human Services’ proposal to eliminate or scale back the Affordable Care Act’s “bundled payment” programs seems counter to early research findings that document the cost savings and improved outcomes achieved by those new payment models, according to University of Pennsylvania health services researcher Amol Navathe.

Navathe, MD, PhD, was one of three Penn faculty members appearing on the Wharton/Sirius “Business of Health Care” radio show to discuss their own areas of research as a prelude to the upcoming two-day Leonard Davis Institute of Health Economics 50th Anniversary “Shaping the Future of Health Care” Symposium. That event brings together more than four dozen top health care research and policy experts from Penn and around the country at a time when federal policies related to issues like bundled payments, the opioid crisis and insurance exchanges are in political flux.

Bundled care and payment research
An Assistant Professor of Health Policy and Medicine at Penn’s Perelman School of Medicine and an LDI Senior Fellow, Navathe heads a research team studying Medicare joint replacement procedures done in the bundled manner.

The “bundled” payment model requires that all services related to a specific kind of surgery be centrally coordinated and billed as a single episode of care — as opposed to the traditional fragmented system of à la carte treatments and billing.

“On the somewhere between $20,000 and $30,000 cost of a hip or total knee replacement,” said Navathe, “we’re seeing up to a 20% savings, depending on which health system we’re looking at. Those are big dollars.” The Penn research also found bundled payment joint replacement patients had fewer post-surgical complications or hospital readmissions.

When they were scaled up after their launch, ACA Medicare bundled payment programs were made mandatory — hospitals in the designated markets have to change their joint replacement procedures and billing practices in order to qualify for reimbursement. But the latest CMS  proposal alters that, making bundled services voluntary in some markets, thus enabling hospitals to return to their traditional billing methods. The proposed rule would also cancel mandated bundle programs for other types of Medicare surgeries that were slated to launch soon.

Catalyzing change
“If we really want to make a dent on health care spending in the long run,” Navathe said, “we have to think about how to scale these programs more broadly. Mandating them is a way to catalyze change and that’s probably the most compelling reason to do it. If we go with the self-selection of volunteering, we may end up getting particularly inefficient providers volunteering to be a part of this. A voluntary approach also makes it harder to study and ultimately understand what the real impact of bundled payments is.”

Sirius show host Mitchell Goldman, MBA, noted that Navathe is one of 250 Senior Fellows at the half-century-old LDI who investigate and analyze how the U.S. health care delivery system is organized, financed, managed, and quality controlled. For the last 50 years, the multidisciplinary research and findings of institute’s experts have informed a broad spectrum of policy issues at the federal and state government level as well as throughout the health care business.

Zachary Meisel, a Penn Medicine emergency physician, LDI Senior Fellow and Associate Professor at Penn’s Perelman School of Medicine.

The opioid crisis
Another part of the Wharton/Sirius radio show was a discussion about the opioid crisis with researcher and Penn Medicine emergency physician Zachary Meisel. Underscoring the importance of such opioid-related research, Meisel’s appearance came as the CDC was releasing the first governmental statistics for 2016 drug deaths detailing a dramatic year-to-year increase in overdose mortalities.

LDI Senior Fellow Meisel, MD, MPH, is an Associate Professor at Penn’s Perelman School of Medicine and also Director of the Policy and Dissemination core for the National Institute on Drug Abuse-funded Center for Health Economics of Treatment Interventions for Substance Use Disorder, HCV, and HIV (CHERISH).

Physician behavior
Physician prescribing behavior is now widely recognized as a major driver of the current opioid misuse epidemic and both federal agencies and professional medical organizations are working to establish clearer guidelines for the use of opioid-based pain management medications.

Supported by a $2.1 million grant from the Patient-Centered Research Institute (PCORI), Meisel heads a team analyzing the kinds of storytelling methods that can best motivate physicians to more effectively score and understand the potential risks in opioid prescribing.

“We know that there are evidence-based guidelines around opioid prescribing and that ER physicians have not done a great job in actually following the evidence-based guidelines over the years,” said Meisel. “We looked at whether or not stories and narratives may help physicians to be more adherent to a prescribing guidelines and found that, yes, they can.”

Executive Director Daniel Polsky discusses LDI’s upcoming 50th Anniversary “Shaping the Future of Health Care” symposium. Foreground: Rebecka Rosenquist, LDI Assistant Director of Health Policy.

‘Narrow networks’ research
The third expert on the show was Daniel Polsky, PhD, who is the Executive Director of LDI as well as a Professor of Health Care Management at the Wharton School and Professor of Medicine at the Perelman School of Medicine. A major part of his most recent research focuses on the “narrow networks” strategies of limited provider coverage used by insurers to lower premium costs.

And, as head of LDI, Polsky said he is focused on both the continued expansion of LDI’s collaborative research activities and capabilities as well as telling the story of the organization’s 50-year history as a pioneer in the field of health services research. He pointed out that the upcoming October symposium is the latest demonstration of how LDI has long functioned as a hub of interdisciplinary research aimed at improving the U.S. health care delivery system.

Campus-wide collaboration
“LDI originally began as an effort to bring together the expertise of Penn Medicine and Wharton School business researchers to address the dramatic demands of the new Medicare and Medicaid systems in the 1960s,” he said. “Since then, LDI has greatly expanded to include experts from the other schools across the campus. For instance, scientists from the School of Nursing are a huge part of our Institute.”

“And,” he continued, “all of these disciplines are working together to address the problems of health care that constitute one of the today’s most pressing national concerns.”

This post originally appeared on the Leonard Davis Institute blog.

Got Behavioral Science Results? Help Us Build a Resource for All

By | CHIBEblog

It’s been more than three months since the launch of the Behavioral Evidence Hub, a community-driven collection of behavioral interventions proven to create impact. Jointly launched by CHIBE,  Innovations for Poverty Action (IPA), and ideas42, the B-Hub (as it’s affectionately called) has been visited by people in more than 125 countries since May. We’ve also published even more projects by more contributors and added new domains to accommodate the diversity of interventions submitted.

So, what’s next? That’s where you come in.

If you build it they will come…so we did.

As a community-driven resource, the B-Hub relies on contributions from a myriad of people in order to offer the most comprehensive collection of designs and guidelines out there. Valuable behavioral insights are often buried in academic journals or behind paywalls where many people who could harness them for social impact may never lay eyes on them. The B-Hub is a space we carved out to gather findings into a single resource for applied behavioral science strategies, sharing actionable guidelines between those who do experimental work and those seeking proven, innovative solutions.

Problem-solvers from around the world come to the B-Hub to browse usable strategies for tackling any number of pervasive problems in a wide range of domains such as financial wellbeing, college completion, and long-term health. Contributors maintain the resource’s continuous growth while expanding the reach of their work by putting results in front of a wider audience of practitioners.

Who can submit to The B-Hub?

Everyone is invited to submit content that meets the eligibility requirements. The B-Hub currently includes work from a variety of different partners, including individual academic researchers, governments, nonprofits and NGOs.

Is my research or project eligible?

There are four key attributes that tie all B-Hub entries together. Everything published on the B-Hub is:

Behavioral. At its core, the B-Hub is all about human behavior
Applicable. We want studies that can be applied somewhere else
Rigorous. The most reliable solutions are tested with trusted experimental methodology
Effective. It has to work. Tests should show a statistically significant quantitative effect

What is the commitment?

First, fill out the submission form. After you submit it, a member of the B-Hub team will reach out for more details about the work you want to publish. If it meets the requirements above, the next step will be to complete a brief write-up of your work, including details about the challenge you faced, the design you created, the impact it had, and any implementation guidelines you can offer to others.

Project pages are usually between 700-1500 words. While researchers will take the lead on writing their own summaries, the B-Hub editorial team will provide support as necessary—because we don’t want hassle factors to get in the way of sharing your insights with the world.

Why does my contribution to the B-Hub matter?

We know overloading people with generalized information won’t inspire action. That’s why B-Hub visitors are guided through each project step-by-step, including details on the context of the problem tackled, specifics and visuals from the designs, and guidelines from the original researchers and/or implementers on how the solution was carried out. Although what works in one context isn’t guaranteed to lead to success in another, collecting real-world examples in an open-source, community resource can lead to their adaptation to new situations—and new lessons learned.

The B-Hub does more than bring behavioral findings into the real world. It is a database of what works and how for practitioners, and it is an accessible platform outside of journals for researchers to disseminate findings seamlessly with other problem-solvers across the globe. More connection equals more knowledge sharing, which equals more social good.

Have more questions about the B-Hub? Email info@bhub.org.

This post originally appeared on ideas42.

Celebrating LDI’s 50th Anniversary

By | CHIBEblog

Origins of the Leonard Davis Institute of Health Economics

With a gift from Leonard and Sophie Davis, the University of Pennsylvania established the Leonard Davis Institute of Health Economics (LDI) in 1967, two years after Congress enacted Medicare. It was created to fill fundamental gaps in the evidence base that could inform policies critical to the financing and management of the nation’s increasingly costly and complex health care system. Today, LDI is considered one of the world’s leading university-based programs of its kind.

LDI and its senior fellows are among the pioneers in interdisciplinary health services research and have helped guide health policies at all levels of government and the private sector. More than 200 LDI senior fellows work to improve the health of the public through studies on the medical, economic and social issues that influence how health care is organized, financed, managed and delivered.

LDI is one of the first university programs to successfully cultivate collaborative scholarship among typically disparate disciplines. LDI is a cooperative venture among Penn’s health professions, business and communications schools (Medicine, Wharton, Nursing, Dental Medicine, Law School and Annenberg School for Communication) and the Children’s Hospital of Philadelphia, with linkages to other Penn schools, including Arts & Sciences, Education, Social Policy & Practice and Veterinary Medicine.

Mr. Davis, who died in 2001 at the age of 76, received an honorary Doctor of Laws degree from Penn in 1972 (Almanac January 30, 2001).

LDI Leadership

Robert D. Eilers, founding director of LDI, emphasized the Institute’s educational component. He created an MBA major in 1970, which was the first MBA program in health care management. He later added undergraduate and doctoral concentrations in order to train managers and analysts of health care systems. Dr. Eilers consulted with the Nixon Administration and helped draft the HMO bill that passed in 1973.

LDI’s other past executive directors included: Samuel P. Martin III, 1974-1978; William P. Pierskalla, 1978-1983; John C. Hershey, 1983-1984; Mark V. Pauly, 1984-1989; J. Sanford Schwartz, 1989-1998; and David A. Asch, 1998-2012. Daniel E. Polsky has led LDI since 2012.

Dr. John Eisenberg was founding chief of Penn’s Division of Internal Medicine, 1978-91 and was one of the first Robert Wood Johnson Clinical Scholars at Penn. In 1997 he became director of the federal Agency for Health Care Policy and Research and shepherded its transition to the Agency for Healthcare Research and Quality (AHRQ) as it is known today.

LDI Highlights

In 1976, LDI established the National Health Care Management Center, the first federally funded research center devoted to the management and organization of health care.

LDI hosted the Philadelphia Commission on AIDS in 1987 to help address Philadelphia’s growing AIDS crisis.

LDI launched the Summer Undergraduate Minority Research (SUMR) pipeline program in 1999 to address health disparities.

In 2008, the Institute founded the Center for Health Incentives and Behavioral Economics, one of just two NIH-funded centers dedicated to behavioral economic research in health.

LDI contributed to the UPHS Center for Innovation in Health Care Financing, which test how insights from behavioral economics and health economics can improve patient health and reduce the rate of growth in health care costs in 2011.

In 2012, LDI was involved in the establishment of the Penn Medicine Center for Health Care Innovation, which develops and tests new health care delivery strategies for better outcomes and value.

Today, LDI hosts 250 senior fellows and receives $100 million annually in research grants. LDI researchers publish more than 800 articles in peer-reviewed journals each year. LDI focuses on four key areas: improving health care delivery, optimizing insurance markets, motivating healthy behaviors and reaching vulnerable populations.

LDI forms collaborations to work toward measurable results, with organizations ranging from universities to companies to the federal government. It also provides seed funding to help launch early research careers.

LDI’s motto is: Research to Improve the Nation’s Health System: Theory Driven; Data Tested; Policy Focused

50th Anniversary Symposium 

LDI is Penn’s hub of health system-related research, policy analysis and education. Penn LDI’s 50th Anniversary Symposium, Shaping the Future of Health Care will be held on campus on October 5-6. Two Penn LDI alumni: Katrina Armstrong and Patrick Conway, who have been ‘firsts’ in their fields, will receive the John M. Eisenberg Pioneer Award. LDI alumni social events will be held on October 4. Symposium registration includes the 50th Anniversary Dinner Celebration on October 5. The event will include a celebration in which former LDI executive director Mark Pauly will be honored for his career of scholarship and mentorship.

LDI is highlighting the pioneering people, events and publications that marked turning points in its history and in health policy on Twitter using the hashtag #PennLDI50.

For information, visit https://ldi.upenn.edu/50th-symposium

This post originally appeared on the University of Pennsylvania Almanac.

The 50-state Laboratory: How Can Behavioral Science Bolster Vaccination Policy?

By | CHIBEblog

Vaccinating kids saves a lot of lives and a lot of dollars. High rates of vaccine coverage assure community protection (“herd immunity”), and in the United States we achieve this by requiring children to be fully vaccinated by the time they start school. Taken together, these requirements are often called the “immunization schedule.” We’ve mandated school-entry immunization for so long that it at times seems like a given, but many other countries don’t have similar mandates. They suffer from lower vaccine coverage and more disease.

But what happens when parents in the U.S. don’t want their children to be vaccinated? All 50 states have legalized medical exemptions: Some kids, due to medical contraindications like immunosuppression or severe allergy, cannot safely be vaccinated. Most states also make some provision for nonmedical exemptions: These might be religious, philosophical, or “personal belief” objections to the required immunization schedule.

School-entry mandates and exemptions from those mandates are determined by states, so we essentially have a 50-state laboratory for studying the effects of exemption laws on parent responses, vaccine coverage, and disease outbreaks. In recent years, parents have been increasingly hesitant to vaccinate their children, and outbreaks of vaccine-preventable diseases have risen. (Remember the Disneyland measles outbreak?) In response, many states are rethinking when and how they allow vaccine exemptions.

Vaccine exemption law is fertile ground to apply behavioral science to public policy.

In 2017, 17 states considered more than 40 changes to their state’s exemption regime. Were behavioral insights in evidence in most of these proposed bills? A little bit. Could there be more? For sure. Vaccine exemption law is fertile ground to apply behavioral science to public policy. Below are four behavioral principles relevant to exemption legislation, along with some examples of current and proposed exemption laws that leverage these insights:

#1: Add hassle factors

Many proposed revisions invoke the idea of making easier to adhere to immunization schedules (opting in) than to get an exemption (opting out). This makes sense: We know from prior studies that states with tougher exemption requirements (for instance, needing a health care provider to sign the exemption form versus the parent just signing the form themselves) have lower exemption rates. In the 2017 legislative session, Iowa proposed that religious exemption seekers provide an affidavit signed by the applicant’s religious leader confirming that immunization conflicts with specific religious tenets. This should prevent people from abusing the religious exemption to circumvent vaccine mandates.

Minnesota proposed several additional requirements for exemption. These include a statement from the child’s physician confirming the applicant and guardian have received information about the health risks of failing to vaccinate and an acknowledgement that the student may be prohibited from attending school in the case of an outbreak. This last requirement is particularly good at making the benefits of vaccination salient—it helps the parent visualize a future exclusion from school.

If some hassle is good, is more hassle better? Idaho currently requires parents to write a short statement explaining or justifying their exemption request. My research team hypothesized that while this might add some hassle factor, the act of writing the statement might equally serve to reinforce anti-vaccine beliefs (and we’re testing that in an online experiment; stay tuned for the results). How about the ultimate hassle: No nonmedical exemptions at all? This was proposed in the Arizona legislature, and was actually passed and implemented in California following the Disneyland outbreak. This might not work, due to increased reactance to this issue when the nonmedical exemption option is withdrawn altogether.

#2: Design incentives for maximum impact

Much of the recent work on behavioral economics and health has focused on optimally designed incentives (financial and non-financial) for healthy behaviors. Could this work in exemption laws? One of several proposed bills in the New York state legislature would eliminate the dependent tax deductionsfor taxpayers who fail to comply with immunization requirements for their dependents (with the savings going to the Department of Health for vaccine education).

The problem here is a licensing effect. Once parents can effectively “pay to not play,” exemption become more of a consumer choice than a moral obligation. And are parents the right place to apply incentives (whether carrots or sticks)? Insurance companies already reward physician practices (through quality bonuses) for vaccine coverage rates in their patient panels. Exemption laws could build in similar rewards for school districts that reduce exemption rates or maintain low or zero exemption rates over time.

#3: Make vaccine education count

Educating parents about the benefits of vaccination and the harms of not vaccinating has long been promoted as a key strategy to promote vaccine acceptance—with little evidence to support its effectiveness. Optimism about vaccine education is evident in a proposed bill in Connecticut, requiring parents who seek an exemption to provide evidence of participation in a “science-based” education module. (Washington state already requires this; you can complete their required education module yourself here).

A required education module can serve as an effective hassle factor, but in order to actually persuade a vaccine-hesitant parent to get their kid vaccinated and not require an exemption, the educational content needs to be “behavioral science-based.” How? One strategy is to increase the salience of the real risks of contracting vaccine-preventable diseases. This can help counter risk compensation (parents don’t think their kid will contract a vaccine-preventable disease) and ambiguity aversion (parents prefer known risks of not vaccinating to unknown risks of vaccinating). However, increasing the salience of the potential harm (versus risk) of vaccine-preventable diseases may backfire with vaccine-hesitant parents. A lot more research is needed on when the backfire effect kicks in and how to avoid or circumvent it.

#4: Leverage social norms and peer pressure

Fortunately, the vast majority of parents fully vaccinate their kids. Exemption rates are low in many schools, districts, counties, and states. Exemption laws can leverage this strong social norm by making exemption data publicly available and by mandating school-level reporting. A proposed law in Texasrequires school districts to report data on requested, granted, and denied exemptions to the state’s Department of Health, which will make the data public on the department website. Schools also must notify parents and guardians upon request if any student in the school is exempted. New Yorkproposed a similar reporting requirement. In addition to confirming the social norm for complete vaccination, these publicly available data also permit the identification of exemption outliers or “hotspots.” As with educational interventions and incentives, some caveats about licensing and backlash are warranted.

Our 50-state laboratory will gear up again in the next legislative sessions—that’s good news for public health and policy researchers interested in conducting observational studies of changes in state exemption laws. But there’s also an opportunity to be more proactive: Legislative staff can deploy evidence from behavioral science when drafting new exemption laws. My research team and I are busy drafting evidence-based model legislation templates so that legislators don’t have to start from scratch when designing new exemption laws. We hope to push the field from outdated, ineffective, or politically-motivated approaches to crisp, simple legislative strategies that use behavioral insights to keep kids healthy.

This post originally appeared on Behavioral Scientist.

Closing the Scholarship-Policy Gap with Strategic Science

By | CHIBEblog

This summer the Trump administration announced further delays in (1) implementing calorie labels on restaurant menus across the nation and (2) rolling out a new nutrition facts label. Both policies are designed to increase nutrition transparency and arm consumers with important health information when making decisions. This signals little interest from the current administration in promoting sound, common-sense nutrition policies. It also highlights a need, more than ever, for scientists to communicate with policymakers at the federal, state, and local levels, to encourage evidence-based policymaking.

Most of the time, scientists generate their research questions based on what they think is interesting and important.

This approach can obviously yield valuable discoveries, but it also means that scientists don’t always have answers to the questions that urgently plague policymakers. Unfortunately, most scientists and policymakers rarely talk, let alone work together to formulate a program of research.

My own research focuses on investigating the consequences of food policies and interventions on dietary habits and health. During my graduate education, I studied with Kelly Brownell at the Yale Rudd Center for Food Policy and Obesity. Working with Kelly, I learned to embrace a different approach to science, one that aims to work with policymakers and influencers to identify and answer the research questions that they most need answered. We call this approach Strategic Science, because it involves being strategic in our selection of research topics and questions so as to increase the effectiveness of behavioral policies.

In this blog post, I describe our four-step model of Strategic Science that we’ve used in our own work.

Step One: Identify and connect with change agents. Change agents are individuals or institutions in a position to make or influence policy. A change agent might be a government policymaker, regulator or legal official, the press, an advocacy group, a non-profit organization (e.g., World Health Organization), or citizens who influence decision makers.

Step Two: Develop strategic research questionsStrategic Science is meant to complement traditional scientific inquiry by soliciting input from change agents when a scientist is crafting a research question. The goal of these conversations is to identify strategic questions, not generate strategic answers or advocate for a position. Instead, the scientist and change agent partner to identify research questions that will advance scientific knowledge, while providing change agents with policy-relevant information.

Step Three: Rigorously answer the strategic research question. This step is a scientist’s bread and butter—conduct rigorous research in an objective manner.

Step Four: Communicate research results to change agents. Strategic Sciencerequires a commitment to not only publishing in peer-reviewed journals, but making the research accessible to change agents. This might be done through policy briefs and short descriptions that explain the methods, results, and relevance of the research in a clear and concise manner. Once the initial relationships are formed with change agents, it’s much easier to communicate the work back to them later.

I recently used this Strategic Science approach when California introduced a bill to place warning labels on sugary drink containers. At the time, there were virtually no data on how such a policy might influence consumers. After learning about the policy, I became curious about whether graphic warning labels that displayed visual images of the health harms associated with over-consuming sugary drinks would be more influential than the text-based warning labels that the bill proposed. But the immediate policy need was to do a timely study that could inform the current debate on sugary drink warning labels. I connected with a prominent advocacy group in California that had worked on this issue. Those conversations made me realize that it would be most valuable to the policy debate if I focused my investigation on the study of labels that could be realistically implemented in the immediate future. This meant that graphic warning labels were out, and our team instead designed online experiments to test whether different kinds of text-based warning label messages would be differentially effective. That research revealed that such text-based labels are able to educate consumers about the health harms of sugary drinks and may influence parent and adolescent purchases in a way that calorie information alone probably would not. It also revealed that the precise wording of the text messages that were under consideration did not matter much.

I’m still pursuing research on graphic warning labels, but the conversation with policy influencers shaped the immediate questions I sought to answer so that I could provide timely and relevant data to inform a current policy debate. The jury is still out on whether text-based warning labels would influence consumers’ actual purchases—a great deal more research in the real-world is needed to answer that question—but our initial work suggested that this is a reasonable policy to begin exploring and testing in localized settings.

We need more scientists engaging in Strategic Science to generate innovative policy ideas and help close the scholarship-policy gap, but to achieve this, academic institutions need to work to make this easier. First, academic institutions need to do more to incentivize faculty to engage in this type of research, as it requires time to foster relationships and communicate results. Second, academics need more institutional infrastructure and staff support to help them identify and connect with change agents and communicate their research. Third, it requires funders to rapidly provide funding to scientists partnered with change agents so they can address time-sensitive policy questions. Just as a doctor may generate research ideas from talking with patients, more scientists need to be having conversations with change agents who can help ensure science is asking questions that can lead to better, more evidence-based policies.

This post originally appeared on LDI Health Policy$ense.