In this course, you’ll learn the foundational economic theories behind health care innovation and how to optimize your own health care practice or organization. Designed to help you gain a practical understanding of the theoretical frameworks of behavioral economics and operations management in the health care setting, this course will help you apply these frameworks to assess health care practices and apply innovation while managing risk. You’ll also explore the best practices for evaluating one’s innovative practices, using real-life examples of success to see the concepts in action. By the end of this course, you’ll have honed your skills in optimizing health care operations, and be able to develop the right set of evaluations and questions to achieve best innovative practices within your organization.
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Module 4
This module was designed to highlight the importance of behavioral economics in health care practice and how to utilize behavioral economic theory to optimize the operations of your health care organization. You’ll explore Expected Utility Theory and the different types of Prospect theory such as Reference Dependence, Diminished Sensitivity, and Loss Aversion in the context of health care. By studying real-life examples of Default Bias and Increased Cost Sharing case studies, you’ll establish a framework for health care interventions that will be effective and successful after implementation. By the end of this module, you’ll be better able to determine the theoretical basis for certain health care practices such as nudge units and whether such practices would benefit your organization.
Andrew M. Heller Professor at the Wharton School, Senior Fellow Leonard Davis Institute for Health Economics Co-Director, Mack Institute of Innovation Management The Wharton School
Amol S. Navathe, MD, PhD
Assistant Professor of Medical Ethics and Health Policy Department of Medical Ethics and Health Policy
David A. Asch, MD, MBA
Professor of Medicine and Professor of Medical Ethics and Health Policy Department of Medicine
Roy Rosin, MBA
Chief Innovation Officer Penn Medicine
Kevin Volpp, MD, PhD
Professor of Medicine, Division of Health Policy / Professor of Health Care Management Perelman School of Medicine / The Wharton School
In this session, we'll review some of the key behavioral biases that
are important enhancements of the standard economic view of human behavior.
These both more accurately describe what humans do and provide
a road map for how we might think about the design of interventions.
In standard economics, it's assumed that people make
optimal decisions based on their information, resources, and preferences.
This in some sense assumes a way of problems like obesity,
not a very satisfactory conclusion for
public health leaders or clinicians who
want to help people lower their future health risk.
Behavioral Economics helps us understand why people
do things that may seem to not be entirely rational,
and have trouble changing behavior even when their future selves would be better off.
Let's think for a moment about how the Science of Motivation has evolved.
In the past, people often assumed that if we just provided people with information,
if people know what to do, they would do it.
That unfortunately doesn't work very well.
And there are lots of examples of failed efforts to try to
provide people with information in the hope that it would change their behavior.
But for example, 70% of smokers in the US say they want to quit.
Only about 3% per year actually do,
even though the risks of smoking are widely known.
Because of frustration perhaps with standard information provision approaches,
a lot of health plans and employers have moved in the realm of Standard Economics,
providing economic incentives to people to do healthy behaviors.
The limitation for a lot of
those programs is that they assume people are perfectly rational,
and the size of the reward is all that matters.
What Behavioral Economics has mapped out are
ways in which people are predictably irrational.
Where decisions are affected by present bias,
loss framing, emotions, social context and inertia.
This means that the incentive delivery,
design, the choice environment are all critical.
We've gone over a lot of decision errors in recent lectures,
where we've highlighted that while people may be irrational,
they're rational in predictable ways.
By taking advantage of these typically decision errors,
we can steer people to healthier behaviors.
By way of quick review,
reference dependence refers to the concept that how people
evaluate a set of choices all depends on where they're starting.
Think about that example of somebody who has $4 million ,
but had a $1 million yesterday versus $7 million yesterday.
Framing, very important.
Choices can be presented to people in
different ways and whether they are presented as gains,
as losses, makes a huge difference.
The Endowment Effect; a very important concept,
which is a little bit of an interesting one because it surprises people
that having something in hand is so much more important in terms of motivating people.
But it relates to the notion that people really don't
like to lose what they already have.
Status Quo Bias; very important,
underlies a lot of the work on defaults and
choice architecture which you're going to hear a lot more about,
but relates to the notion that people often stick with what they've already
been doing even when other much better alternatives present themselves.
Mental Accounting; People have lots of
different accounts for example in which they keep their money.
In essence it all should be a part of one mega account.
But people often make these decisions which don't make sense.
Saving money for a house or a car,
and then having a credit card with very high interest in a different account.
Loss Aversion: We talked about a bit.
The notion that the disutility of a loss is
much greater than the utility of an equivalent gain.
Non-linear Probability Weighting relates to the notion
that people overweight very small have probabilities near zero,
underweight probabilities near one.
Present-Biased Preferences.
People heavily discount the future to a much greater degree than typically makes sense.
And Anticipated Regret relates to the notion that people can anticipate the regret
they'll feel if the outcome isn't as desired and it relates to a choice they made.
This all leads to different Intervention Approaches.
When we think about Standard Economics,
we would think about only intervening when there is a clear market failure.
We used the example earlier of Externalities,
a behavior like smoking in
a small closed space like a room or an airplane that imposes costs on others.
Other examples of market failure would be Information asymmetries,
or markets that are imperfect,
where there's a monopoly and it makes sense for
the government to intervene and introduce competition.
Behavioral Economics, however opens up a whole another realm of possibilities,
where we'd consider intervening when there are what
George Loewenstein might call Internalities.
Behaviors that impose costs on one's own self in the long run,
and where if we accept people make a lot of decision errors,
we might consider helping people help their future selves.
A lot of interventions in Behavioral Economics are couched
around the notion of Libertarian or Asymmetric Paternalism.
There's no denying that a lot of these interventions are
paternalistic in the sense that we're trying to help provide
people with guidance towards achieving their goals and helping to steer them
towards goals we might view or the choice architect might view, as desirable.
However, they're asymmetric in a couple of important ways.
One is that we're helping those who make decision errors while not affecting
those who make deliberate well-informed decisions without decision errors.
We're also helping people without interfering with their freedom of choice.
In essence what we're trying to do,
is exploit biases that often lead to
self harmful behavior to how people engage in healthy behavior at higher rates.
One of the classic examples of this is food lay out in a cafeteria.
There are a lot of studies that show that the food that's
most easily accessible tends to be chosen most often.
So in a cafeteria that's typically the food in the middle of
the cafeteria, near the cashiers.
There's no denying that somebody needs to make
a decision about which food gets laid out where.
It could be the healthy food in the prime position.
It could be the most profitable food in the prime position.
It could be the most unhealthy food.
It could be done at random.
But here's a nice example of how people can be steered towards
healthier choices without limiting options for those who want to eat unhealthy food.
Nobody's removing them from the menu or the cafeteria.
We're not changing the differential prices,
we're just making it easier for those
who might be susceptible to these types of interventions
to make choices that they themselves might
view as consistent with their own long term goals.
In this session, we've reviewed several of
the key behavioral biases that make it difficult for people to behave fully rationally,
and discussed Asymmetric or Libertarian Paternalism as
a framework for thinking about potential Behavioral Economic Interventions.
The key thing to note is that these interventions ideally do not affect
freedom of choice for those who behave optimally or have strong preferences,
but rather make it easier for people who don't to make
decisions that may be more in keeping with their own long term best interest.
This is markedly different than a more heavy handed paternalistic approach.
Throughout this course, we'll use this notion of
light paternalism as a guide for thinking about how to
influence behavior choices in ways that preserve freedom of choice. Thank you.
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Christian TerwieschAndrew M. Heller Professor at the Wharton School, Senior Fellow Leonard Davis Institute for Health Economics Co-Director, Mack Institute of Innovation Management
Amol S. Navathe, MD, PhDAssistant Professor of Medical Ethics and Health Policy
David A. Asch, MD, MBAProfessor of Medicine and Professor of Medical Ethics and Health Policy
Roy Rosin, MBAChief Innovation Officer
Kevin Volpp, MD, PhDProfessor of Medicine, Division of Health Policy / Professor of Health Care Management
