In every medication they may prescribe (this is

In a perfectly competitive market,
social welfare is maximized. According to Investopedia, a market that is
perfectly competitive has the following characteristics:

“1) All firms sell an identical product;

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2) All firms are price takers – they
cannot control the market price of their product;

3) All firms have a relatively small
market share;

4) Buyers have complete information
about the product being sold and the prices charged by each firm; and

5) The industry is characterized by
freedom of entry and exit” (Investopedia, Perfect
Competition).

Yet in the healthcare market, condition 4, which requires
complete information from all parties, is not met. There is market failure
because the supply and or demand curves are wrong, as some relevant information
has not been included. That relevant information is the missing information
from one or more sides — information asymmetry. This paper focuses on the
information asymmetry between 3 players: the patients, doctors, and
pharmaceutical companies.

Evidence:

            There are
various forms of information asymmetry present in the healthcare industry, one
being between physicians and pharmaceutical companies. Physicians are
responsible for prescribing medications for their patients, yet they do not
have the time and training to be familiar with all the benefits and side
effects of every medication they may prescribe (this is the role of
pharmacists). Pharmaceutical companies capitalize on this information asymmetry
by engaging in drug promotion. In 2012, the pharmaceutical industry spent more
than $27 billion on drug promotion, $15 billion of which was spent on detailing
(meaning face-to-face promotional activities like taking physicians to meals
and providing gifts), and $5.7 billion of which was spent on providing samples
of medications to physicians (Pew Charitable Trusts, 2013). While the main
benefit to detailing is that it allows information about prescriptions to be
spread quickly — as opposed to having a delay, with new treatment
recommendations taking more than 10 years to show up in medical textbooks
(Balas and Boren, 2000)– drawbacks include learning inaccurate information
about the sponsor’s and competitors’ drugs, costlier prescribing, and more
frequent use of brand-name drugs in classes with equally effective generic
drugs (DeJong and Dudley, 2017), which negatively affects cost (patients are
referred to costlier drugs) and quality (misinformation about competitor drugs
could lead to them not being prescribed when it might benefit the patient). In
fact, the recent opioid crisis exemplifies this problem. Ohio’s Attorney
General has filed a lawsuit against many pharmaceutical companies that
manufacture opioids, like Purdue Pharma, Teva Pharmaceuticals, and Johnson
& Johnson, for ” falsely denying or trivializeing the risks of opioids
while overstating the benefits of using them for chronic pain…to reverse the
popular and medical understanding of opioids”. The lawsuit also states that
these pharmaceutical companies engaged in behavior that Big Tobacco once used,
such as by “working together with those KOLs doctors who are “key opinion
leaders” and Front Groups professional societies and patient advocacy groups
to taint the sources that doctors and patients relied on for ostensibly
“neutral” guidance” to convince doctors and patients that “the compassionate
treatment of pain required opioids,” even though this went against medical
knowledge (State of Ohio ex rel. Mike DeWine, 2017). Pharmaceuticals were able
to leverage the information asymmetry and take advantage of doctor’s lack of
awareness to influence them to prescribe more opioids, increasing access to
opioids, raising the drug expenditures, and decreasing quality of care as
patients became addicted to opioids, ultimately contributing to America’s
opioid crisis.

            A second
example of information asymmetry exists between patients and the insurance companies,
in the form of adverse selection. A health insurance company who is extending
coverage to a patient would not know every detail of the patient’s health
history or expected future health expenditures, yet the insurance company must
charge a premium that should match the expected expenditures as closely as
possible. Only the patient himself knows how much health expenditures he is
expected to spend, so he can take advantage of this information asymmetry and
purchase insurance if the premiums would be lower than his expected
expenditures. Adverse selection occurs when the risk pool is filled with the
sickest people, causing premiums to rise, leading to the healthiest dropping
out. This cycle (termed the death spiral),
continues as the pool continues to get riskier, leading to increased premiums
and the healthiest forgoing insurance. Adverse selection was supported by a
study from David Cutler while looking at Harvard’s employer sponsored health
insurance trends. With a rise in premiums for the Blue Cross/Blue Shield PPO
program from $500 in 1994 to $2000 in 1996, they found that the people who left
were younger than those who stayed (by an average of 5 years) and 20% healthier
than the remainder, which meant the premiums would have to be increased again,
causing Harvard and Blue Cross/Blue Shield to dismantle the program (Cutler and
Zeckhauser, 1998). Adverse selection has negative effects on cost (by raising
premiums, potentially making health insurance less affordable for those who
need it the most) and restricting access (if health insurance is unaffordable,
patients would choose not to be insured and might not seek care when they need
it).

Information asymmetry also impacts
the relationship between the patient and the physician, which is complicated by
the principal-agent problem. As Robert Evans writes in Strained Mercy: The Economics of Canadian Health Care, a perfect
agent is “one who makes the same decisions that the patient would have made if
the patient possessed the same information and expertise as the agent.”
However, Evans continues by writing “The ‘perfect agent’ would need a split
brain, one half advising the patient solely in the patient’s interest, the
other half reacting… in a self-interested, own-welfare maximising way” (Evans,
1984). The physician is not a perfect agent because while he is suggesting
treatment plans that would benefit the patient, he’s also the provider of care
at the same time, which means he is incentivized to maximize his revenues.

Since physicians in the US are paid generally by fee-for-service, meaning they
receive money for every procedure or test, the physician may be incentivized to
perform more procedures or tests than is medically necessary. Such behavior is
termed “physician-induced demand,” and one study confirmed that such a problem
exists. In Thomas Rice’s “The Impact of Changing Medicare Reimbursement on
Physician-Induced Demand,” Rice examined the responses of physicians to a
change in Medicare reimbursement in Colorado between fiscal year 1976 and 1977,
in which some physicians received increased Medicare reimbursements while
others received decreased Medicare reimbursements. The researcher examined the
trends in variables such as the relative-value units (RVUs) per medical or
surgical service (as a measure of the intensity of services provided), the
number of services provided (looking at the average number of services provided
per patient), and the number of ancillary services provided (like x rays or
other laboratory tests). The study found the following results:

“The results show that
declining medical reimbursement rates result in increases in the intensity
of medical services provided, and that declining surgical reimbursement
rates result in increases in the intensity of surgical services provide.

Decreases in both medical and
surgical reimbursement rates result in increased provision of surgical
services to Medicare patients.
 Declining laboratory reimbursement rates
result in the ordering of more laboratory RVUs per medical service.”

Thus, the researchers suggest that there is a “negative
relationship between the changes in reimbursement rates and changes in demand
inducement,” so physicians were motivated to increase their fees by performing
more intensive and frequent services. However, the researchers acknowledge that
such changes could have also been the result of an increase in patient-demand.

A decrease in reimbursement would likely mean a decrease in patient copayments
as well, which would shift the demand curve to the right since for any given
price level, the patient would demand more services. However, the researcher
notes that this isn’t a strong counter-argument, because a patient would not
know they have the ability to change factors like the intensity of their
treatment, and for tests, they are all pretty much determined by the physician
(Rice, 1983). This information asymmetry can also be problematic when
physicians are practicing defensive medicine, which is a “deviation from sound
medical practice that is induced primarily by a threat of liability,” which may
include additional testing, referring patients to another provider, or refusing
to treat certain patients. In one study, researchers distributed a
questionnaire to physicians in Pennsylvania and asked how often they engage in
the following 4 types of assurance behavior:

“(1) order more tests than medically
indicated;

(2) prescribe more medications than
medically indicated;

(3) refer to specialists in
unnecessary circumstances; and

(4) suggest invasive procedures
against professional judgment.

And how often they engage in the 2 types of avoidance
behavior:

(1) avoid conducting certain
procedures/interventions; and

(2) avoid caring for high-risk
patients”

93% of respondents reported they sometimes or often engaged
in at least 1 of the 6 forms of defensive medicine detailed above, with some
types of physicians engaging in certain behaviors more often than others — for
example, 70% of emergency physicians surveyed reported they often ordered more
diagnostic tests than were medically indicated (Studdert et al., 2005). This
type of defensive medicine can have mixed impact on quality. As the study
mentions, most of the assurance behaviors aren’t harmful to patients and
could’ve offered marginal benefits. But for behaviors that were more invasive,
like ordering biopsies when unnecessary, there could be more harm than good,
such as making the patient more distressed or the additional risk of the biopsy
itself. Regarding cost and access, the study found that the cost of defensive
medicine could be substantial (since these are additional services being
provided), but may be covered by insurance companies, so the ultimate cost to
the consumers might not be that much. The study found that avoidance behavior
could lead to reduced access for patients, as physicians who want less
expensive malpractice insurance may choose to not perform more risky or
difficult procedures. The researchers note that access could be particularly
harmed if rural doctors practiced avoidance behavior, since there is already a
shortage of providers in those areas, so patients may have a harder time
finding a physician for their needs (Studdert et al., 2005). Because patients
are also not medically trained, this also makes judging the differences between
physicians harder, and so patients rely on heuristics like price as a judge of
quality. In an experiment where volunteers were given placebo pain-reduction
pills, with one group being told the pill was being sold at a regular price of
$2.50 while the other group being told the pill was being sold at a discount
for $0.10, the researchers found that after both groups received electric
shocks, the pain reduction was greater for the group with the regularly priced
pills than for the discounted pills (JAMA, 2008). Although this study is
specific to medication, perhaps the results may be extrapolated to treatments,
especially given the fee-for-service incentive structure. For example, if a
physician recommends a higher-cost treatment, like surgery (because the
physician will receive more revenue from performing that), the patient in his
or her lack of medical knowledge, may agree to this procedure because 1) the
physician recommends it, and 2) the price is a proxy for quality so patients
may believe the higher-cost treatment will be more effective. However, this
experiment shows that such information asymmetry could have negative impact on
cost (by moving patients towards higher cost treatments) and quality (the
treatment might just be pricier but not much more effective). Although the
patients trust the doctors to recommend them the best treatment, such
information asymmetry can distort the relationship and lead to less than
optimal outcomes for the patient.

Policy
Implementations:

            The above
market failures can be mitigated through public and private policies.

            For the
information asymmetry between physicians and pharmaceutical companies, public
solutions involving regulation would be most effective. In a recent statement,
the FDA Commissioner said the department was “actively exploring the question
of whether, in the future, there should be mandatory provider education”
regarding opioids (Fox, 2017). This would bridge the knowledge gap about
opioids so that physicians can prescribe them more responsibly, instead of
being swayed by pharmaceutical representatives. The government can also
increase regulations on the prescription method of drugs, and the FDA
Commissioner also expressed the importance of having shorter durations of prescriptions:

“When opioid prescriptions are written, they should be done
so for shorter durations of use. I believe there are still too many 30-day
prescriptions being written for conditions like dental procedures or minor
surgery, which should require very short-term use, if they require an opioid
prescription at all.” (Fox, 2017).

It’s also possible for the private sector to increase
education about the drugs being prescribed, such as the health insurance
company setting their own quantity limits on the prescriptions for
reimbursement or by sending representatives to talk to physicians who appear to
be over-prescribing certain drugs to increase their education.

            For
information asymmetry between the patient and insurance companies, one  public solution to reduce the risk in the
risk pool is to have an individual mandate requiring everyone to purchase
health insurance, such as the one through the Affordable Care Act. Another
public solution is for the government to use tax revenue and insure high-risk
individuals, leaving the healthier population to purchase health insurance
through the regular employer-sponsored health insurance or through the
exchanges, so that premiums remain low for lower-risk individuals, which will incentivize
them to purchase insurance.

            The best
way to resolve information asymmetry between patients and doctors is for both
parties to be equally informed, though granted, in some cases, it’s impossible
to do so — for example, there’s no way for a regular person to get as much
knowledge as a doctor, who has gone to medical school. But nevertheless,
information is valuable. As pointed out in one study examining
physician-induced demand, if a patient’s education level was secondary level or
above, they were prescribed a significantly smaller amount of drugs than those
who were illiterate or had less than a primary school education. The researcher
suggests that higher-educated patients were able to influence the providers,
reducing the likelihood of physician-induced demand (Nguyen, 2011). Given the
relationship between education and drug prescription likelihood, a public
policy solution is to promote education among the masses, such as through
providing free education up to the secondary level or providing scholarships or
loans for college and beyond. A private solution is to also encourage education
of employees, such as by providing scholarships to employees who are seeking to
further their education. Another public or private solution is to educate
patients on illnesses and potential treatments, so the patients can have an
idea of what treatments are out there before consulting with the doctor. This
could take the form of pamphlets distributed by governmental agencies that are
placed in the waiting rooms, websites that provide information on diseases and
treatments (like through the American Cancer Society’s website), or through the
use of support groups (where patients can get advice from other patients and
know what to expect from their treatments). These solutions would empower the
patient to play a greater role in what treatments they receive so that they
don’t have to rely as much on the physician as their agent. To provide more
information on patient quality and reverse the trend of using price to signal
quality, a private solution is for more transparency about doctors and outcomes
so that potential patients have more information to base their decision on.

This is already being done in many places, as one can Google a doctor and see
ratings on sites like healthgrades.com, ratemds.com, or on health insurance
websites, but many doctors are not included. Health insurance companies could
easily overcome this issue by requiring its insurees to fill out a quick survey
about the doctor (asking questions about the quality of the doctor and care provided)
before paying the claim and then aggregating those responses on a database.

            Conclusion:

The healthcare market is complex,
with many players who have different relationships with each other. In such an
environment, information asymmetry has been a challenging issue plaguing the
market, which has had negative implications for patient cost, quality, and
access. Being able to mitigate this market failure will be an important step in
making the market run more efficiently for all players. 

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