Patients "Google" and Get More Out of Visits

Here is an interesting news piece about a study of patients "googling' to get information about their conditions before they go to a general practitioner and then feeling a set of more positive feelings about the experience of the visit with the general practitioner.

At first glance, I might have thought that patients googling would not help patient/provider relationships.  My intuition may have been that the process of obtaining information from the world wide web would have been seen as a substitute for positive patient/general practitioner interaction.  Instead, it seems to be complementary to and encouraging of positive interaction.

Patients have a choice--go to the general practitioner, invest their time in conversation with the GP, and come away with an experience that will guide their future health and well-being.  Alternatively, they can spend time before the visit gathering information (a use of a scarce resource), then engage in conversation with the general practitioner.  While my intuition may have been to think that patients would use the information as a substitute for interaction with the general practitioner.  What seems to happen is that the patients are taking the information and using the information to strengthen their interaction with their general practitioner.

This suggests that at least some patients see the value of the improved interaction with the physician as being more than the value of the time that it takes to search for information on the internet.  This suggests that the value of improved interaction must be substantial.

Of course, this is not just a patient issue. It is also a physician issue.  The physicians must believe that the information that patients bring to them is useful and does not interfere with the interaction.

The information from this new study may help patients and providers to plan better for more effective and more efficient interaction in the future.  

Obesity and the Public Interest

I am teaching a course on Coursera called "Principles of Obesity Economics" which is a mini-version of the online course that I typically teach at the Johns Hopkins School of Public Health each summer that is called "Obesity Economics".  The course has only been going for a day, but the preparation for it has actually demonstrated that as far as the "production of education" is concerned, there are interesting economies of scope from needing to prepare materials that are not interchangeable but that can be used with some variation in multiple settings.  But that is not the main point I want to make today.

When I typed in "Obesity Economics" as a search in google, I saw that several things with which my teaching is concerned and a blog entry at The Economist magazine.   In this entry, the author, discusses why American politics and culture makes it unlikely (in the author's opinion) that the United States will do anything that makes a serious impact on obesity in the next several decades.

That is an interesting conclusion in light of how much this gets talked about all the time.

The author concludes that the focus on individual rights to make decisions in their own self-interest and to focus only on their self-interest leads to high levels of obesity.  That is an interesting interpretation.  I am not sure I agree that this is the exact answer, but it is worth thinking about whether, from an economic perspective, there is reason to think that this might actually be the case.

Individual self-interest means that individuals maximize their own utility.  No one that I know wants to be obese.  Some people are more willing to accept it than others.  But does that necessarily mean that obesity should increase as much as it does.  That would suppose that people make poor decisions. Or that people don't have enough information to make decisions.  Or that people are given wrong information to make decisions.    Or that people don't look forward enough when making decisions.  Each of these might involve a government intervention.  Very little would necessarily need to be changed in terms of leaving individuals witha high degree of free choice of what they want to eat and when and how they want to use their energy and when.  Perhaps we could think a little harder about regulating business.  And perhaps that is truly the issue. Perhaps we do not need to be regulating or incentivizing individual behavior (although for all of America's focus on individual rights we still tend to think that we should not have to pay all of our own medical care costs so the responsibilities that come along with those rights don't necessarily seem to be taken as strongly). Perhaps we should regulate business more.  Although that does not seem to be a large part of American culture either.  And that may be the just as important a rate limiting factor to achieving goals having to do with weight control in the United States.

We would still have to justify it with a compelling public need or an example of a market failure, but the point of whom to target and how carefully to target them would seem to remain an open question.  

Hospitals Providing Formula

There is an interesting piece in the New York Times about hospitals ending the practice of sending formula home with mothers who are breastfeeding or ending the practice of sending mothers at home with formula at all.  There are a number of interesting economic questions here.

First, what is the role of a sample of formula in determining infant feeding practices.  This is particularly relevant for mothers who have decided to breastfeed at first.  On the one hand, it makes access to formula easier.  Less time required to obtain the first amount of formula that a mother will use to feed a child.  A lower price (zero beyond the hospital costs) than if the sample was not provided.  So, there is an economic logic to the idea that this might change mothers' behavior with respect to how they choose to feed their children.  Perhaps for any mothers who were truly at the margin about their decision to breastfeed, their decision might change.  Or, at the very least, their decision to stop breastfeeding might change to an earlier time than they had otherwise planned if the cost of switching to formula feeding is made lower than it would have been otherwise.

Even if the mother continues to breastfeed, one question would be how to measure the value of having the option of formula feeding readily available.  At least some mothers may assign a value to this even if they never choose to formula feed.  

Second, there is the question about whether it is acceptable to send formula home with mothers who are already formula feeding.  This does not seem like a question of promoting behavior change in this case.  Instead, the issue here is what brand the mother will choose.  Does the mother perceive the type of formula offered as an endorsement from the hospital.  In this case, is the hospital playing a role in essentially marketing a specific type of formula to the mothers.  If they are, is this a reasonable role for the hospital to play?

The biggest question overall may be whether the hospital has a role to play in shaping mothers' behavior rather than letting the mother make a choice for herself with the information she has available.  The hospital arguably has a role in providing information and helping the mother understand tradeoffs that she might need to make but what there is beyond that is uncertain.   

Non-Sedentary Economics

This week a study appeared on sedentary behavior and life expectancy.  The conclusions are that if sitting could be limited to less than 3 hours per day and watching television could be limited to less than 2 hours per day the life expectancy would increase.  The results were based on a meta-analysis, i.e, a study combining results from other studies, of five studies where people were asked about their behaviors like sitting and watching TV and then followed for some amount of time with mortality as an outcome.

A few thoughts on this issue.  First, the studies were not all US studies.  Is there reason to suspect that the effects of a sedentary lifestyle may not be the same everywhere?  Perhaps.  It may depend on the entire range of activities an individual undertakes.

Second, it is not clear whether the studies tested for any interaction terms.  The results have been interpreted as meaning that even people who exercise regularly are at risk if they also sit a lot or watch TV a lot.  The effects seem to be independent.  But what about a person who exercises regularly (perhaps even pretty hard) and also sits a lot.  Take myself.  Does running 25-45 miles per week (there is a lof of variation in my schedule depending on the temperatures, travel, vacation, work intensity, etc.) while sitting easily 8 hours a day at work, make a difference.  Perhaps the running has an independent effect (I sure hope it does). But do the two interact in more complex ways that are difficult to capture?  And how does sitting and working on a computer compare with watching TV? Or is watching different because one's body is more completely relaxed?  And what about those who multi-task rather than just "vegging out" in front of the TV?

Regardless of the study's limitations, (and the authors are up front about a number of others and no study is perfect), what if we take the results at face value?  First, is there a government role?  Is there a market failure for activity?  Is there a market failure with respect to TV watching?  Or are these just choices that people make that they should be allowed to make?  And what if people with jobs that are largely desk jobs want to change their behaviors?  what options do they have?  Is there any way to facilitate these individuals being productive while not sitting at work?  Is there suddenly going to be more of a market for the standing work desks?  And, if so, whose responsibility will it be to buy them?  The employer?  The employee?  Is there a place for government intervention here?


In the end, for me personally, there are a lot of tradeoffs and a lot of possible behaviors.  No easy answers. I'll just take my chances that my combination of activities, job responsibilities, food choices, and sleep quantities is right for me.  I suppose that is all most economists suggest--that people understand their choices, understand the implications of their choices, and are left as free as possible to make them.   

Income Inequality and Health

Some researchers hypothesize that there is a relationship between income inequality and health. The hypothesis suggests that in countries with less income inequality health outcomes will be better. This can provide an argument in favor of income redistribution from upper income individuals to lower income individuals. One interpretation would be higher taxes on higher income individuals with some type of extra support/benefits for lower income individuals.

Many of the studies that have supported this hypothesis have focused on cross-sectional data from multiple countries. One concern that other researchers raise is that when using this type of data, the countries with a great degree of income inequality also have more generous social support programs. In this case, it may not be the lower income inequality that actually results in better health outcomes. Instead, the argument may be in favor of more generous social programs--however we may find the resources for such programs Understanding what is only a correlation and contrasting that with causation is key.

One way to re-assess this question is to use panel data. A recent study by Dr. Mauricio Avendano at the London School of Economics tests this hypothesis. He used data over a number of years from the Organization on Economic Cooperation and Development (OECD). The data are advantageous for addressing the research question of interest to Dr. Avendano as he can look at how changes in income inequality over time within a country leads to any changes. He focused on infant mortality data. He did not find a strong relationship between income inequality and infant mortality.

So, does this completely rule out the possibility that programs leading to less income inequality will benefit health? No. But it does suggest that we should look harder for alternative hypotheses to explain what has been observed in cross sectional data and use this information to motivate policy. Policy that is based on correlations rather than causation is not likely to be efficient policy.

As with medicine, our focus in developing policies with respect to the economy and public health should be evidence based. This is simply one more study that suggests that the evidence to support specific programs that explicitly are aimed at reducing income inequality is not there. To clarify--it may be that the only way to find resources for more generous support programs would be to impose higher taxes on higher income individuals. That could result in less inequality in income that can be consumed. The key to the interpretation of Dr. Avendaon's finding is that while we could argue that reducing the income of high income individuals by a relatively small amount should not hurt them much while giving more resources to those with lower incomes should benefit them a lot may be true, there is nothing specifically about reducing income inequality itself that leads to better outcomes.

"My Disease Cost More Than Yours": It Really Depends on What is Counted

In the world of those who advocate for individuals who have a particular disease or condition, one thing that is often discussed is how much a disease costs.  In my casual observation as a scientist working with advocates, sometimes it seems like we get into a discusion of "My disease is bigger than your disease!"  Or, more appropriately, "My disease costs more than your disease and therefore deserves more attention."  Not quite like a schoolyard brawl. But definitely a sense of trying to get some attention based on the magnitude of the impact.

How do we measure the magnitude of the impact?  We often talk about direct costs (or how much we spend on medical care) and indirect costs (or measures having to do with productivity).  Sometimes, it is hard enough to measure the direct costs.  Who pays what?  How do we know how much they pay? IIs that is paid what it really costs?  How does the system (in the US or elsewhere) help to make it clear whether there is much of a relationship between what is paid and what it costs?

But that is the easy side.  Measuring lost productivity is even more complicated.  A key question that has been debated in the health economics community is whether to measure the value of the individual's time and the concept of potential productivity (often referred to as the "human capital approach") or whether to measure just the productivity lost by the firm (referred to as the "friction cost approach").

The conceptual model has been discussed in the literature extensively, but there is limited literature comparing estimates using the two approaches for the same disease with the same population.  A recent study by Paul Hanly and colleagues compared the estimates of the productivity cost of breast and prostate cancer using the two approaches.

It is at this point that we see that the numbers that are used by advocates greatly depend on what is being counted.  When counting all productivity costs over a lifetime, breast cancer has a far higher impact per person in Ireland than prostate cancer.  The breast cancer cases are younger, are likely earning more, and live longer with the impact of cancer.  However, with the friction cost approach, the two conditions are responsible for nearly identical productivity losses with prostate cancer having a slightly higher value.

In both cases, the wage is used rather than total compensation.  Total compensation includes things like employer sponsored health insurance premiums, payments to retirement accounts by the employer, etc.  Perhaps these are not issues in Ireland in the same way that they are in the United States, but they do need to be considered.

The next time you see that a given disease is costing a given country some enormous number of billions of dollars per year, be careful to stop and think "what is being counted," what should be counted, and how should we count it?  I find that I'm not ever sure of the answer to the last question.  And while the answer to the first one should be clear from reading a well-written scientific article, it may not be clear from reading a popular press interpretation.  Finally, the answer to the middle question may well depend on the policy context.  Let the user of results beware.  

Response Rates of Emergency Medical Services and Mortality

A recently published article looks at the association between reduced emergency medical system (EMS) response time and the mortality outcomes of patients.  You may be asking, "Well, why does it take a study to show that?"  It would seem logical and intuitive that faster response times are associated with better outcomes.  Many municipalities and others responsible for local EMS units have spent quite a bit of time and money trying to minimize response times.  If they did not lead to better outcomes why would we be doing such a thing?

In fact, there are many things in medical care where what is intuitive is what is done and there is not a strong evidence base to support the action.  There are many in the system who are trying to change this and move us to a more "evidence-based" medicine approach, but it takes a while.

How did this study address the question in a novel manner?  Sometimes, randomized trials are appropriate.  In this case it would be completely unethical to make it take longer to respond to some people at random.  The approach used is describe in the study's abstract which can be found here.  The author, Dr. Elizabeth Wilde, points out that some studies focusing on cardiac events have shown the expected relationship but that there was little evidence outside cardiac events and what evidence there was outside cardiac events suggested no relationship.  Why might there be no relationship when the data are analyzed?  That requires us to think about incentives and to think about who knows what.  If the caller indicates a dire emergency the dispatcher can (and has an incentive to) communicate this to the EMS unit.  This is a form of triage.  The researcher working with the data later has not idea how the dispatcher communicated with the EMS unit.  So, if the dispatcher consistently triages cases in ways that make the response times for more dire cases shorter, then those cases may do better than they would otherwise.  But if the original mortality rate for those cases was high, making it a little lower will just make it similar to the mortality rate for the ess severe cases that take longer.  Then, there will be no apparent relationship between the  time of response and the morality outcomes.

Dr. Wilde found a way to use some other data--the distance from the location of the person who called for EMS services to the nearest EMS unit--as a proxy for the response time.  People have used this type of proxy (or to use the technical term, instrumental) variable before--to show things like the effectiveness of more intense treatment for heart attacks. In that case, there was a similar concern about the severity of the condition being observable to the medical care provider but not the researcher.

In the end, Dr. Wilde found that a one minute increase in response time was associated with an 8% mortality increase one day after the incident and a 17% mortality increase 90 days after the incident.

So, now we have an evidence base for efforts to improve response time.  What is the most appropriate way to do that?  That is a separate economic, political, and normative question.  It could involve technology of locating individuals.  It could involve technology for traffic control?  It could involve enforcement of traffic rules.  Or it could involve a change in norms where people are more aware of the true costs of not moving out of the way of EMS vehicles as quickly as possible.

Regardless, the study by Dr. Wilde shows that every minute can be associated with increasing the potential to save more lives.