Tag: health

Onwards and Upwards

It’s one of my favorite questions to ask whenever I talk about Gapminder in class:

Why did South Africa write the letter “U” over the last thirty years?

gapminder.org/tools

It’s one of my favorite questions to ask for two reasons, and both are related to each other. First, hardly anybody gets the correct answer. Second, the fact that hardly anybody gets it pleases me no end.

That’s an unusual thing for a teacher to say. How can absence of knowledge make the teacher happy?

But in this case, it really and truly is a wonderful thing. And the reason it is a wonderful thing is because AIDS today simply isn’t as big a concern as it used to be at one point of time.

One way to understand this chart is to come to the sobering conclusion that South Africa is only now getting back to life expectancy levels it last saw in the early 1990’s.

But hey, at least it’s getting back to those levels, huh?

And in more excellent news, we learn via Saloni Dattani’s awesome (and very, very welcome) blog post that life expectancy for folks with AIDS who are on AntiRetroViral (ARV) therapy is about as much as it is for folks who don’t have AIDS.

Or, in simpler terms, AIDS seems to be a solved problem.

For people with HIV on ART and with high CD4 cell counts who survived to 2015 or started ART after 2015, life expectancy was only a few years lower than that in the general population, irrespective of when ART was started. However, for people with low CD4 counts at the start of follow-up, life-expectancy estimates were substantially lower, emphasising the continuing importance of early diagnosis and sustained treatment of HIV.

https://www.thelancet.com/journals/lanhiv/article/PIIS2352-3018(23)00028-0/fulltext

The reason I say “seems to be”, rather than “is”, is simply because I do not know enough to be able to make a definitive statement. But this much I can say with confidence: this is definitely very good news.

And god knows we could do an extra large helping of good news.

Please, do consider subscribing to Saloni’s excellent blog!

About Life Expectancy

Quick post today, because I’m on the road – but an important post nonetheless. So important, in fact, that I hope to do a longer one in the near future.

But are you clear about what life expectancy means?

For example, here’s a chart from the World Bank, showing India’s life expectancy at birth in years:

Source: WDI

But what does this mean, exactly?

Does it mean that we should expect a baby born today to live until the age of 67?

But how could we possibly know what a baby born today is going to get in terms of healthcare? Scientific advancements are so rapid that we couldn’t possibly know this. So what does life expectancy at birth mean, then?

It turns out that there are actually two different definitions of life expectancy, and to understand ’em, you really should begin with this picture:

Source: https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference

Think of two groups of people. Let’s call the first group “Period”, and the second one “Cohort”.

Who is in the Period group? Everybody alive and in a particular region at a particular point in time. Say, for example, everybody alive in Bangalore in the year 2019.

Who is in the Cohort group? Everybody born in Bangalore in the year 2019, and this group tracked over time.

And, it turns out, you can define life expectancy for both groups.

So what is period life expectancy?

“Period life expectancy is calculated by assuming people will experience the current year’s mortality rates at each age at the corresponding ages in their lifetime.”

In practice, this is how it is calculated:

Imagine there are 1,000 infants (under one year old)5, and in a particular year, infants had a death rate of 5 per 1,000. This tells us that 995 of them would survive to the age of one.

Now, imagine these 995 have reached the age of one. Based on the death rate among one year olds in the same year, we can now estimate how many might survive to the age of two.

We can then carry on this calculation for the entire hypothetical cohort of 1,000 infants. Along with this, we can keep track of how many years each of them survived.

Then, we can calculate the average number of years lived by the entire group of 1,000 hypothetical infants. This is equal to the period life expectancy at birth.

This means period life expectancy is a summary measure of death rates in one particular year, rather than a prediction of how long people will actually live

https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference

This can be confusing, I agree. And what’s more, I remember the confusion I felt the first time I tried to make sense of this myself!

Try this: imagine 1000 babies born this year, in 2024. If the number of babies that make it to 2025 is (say) 995, then we ask how many of those 995 babies will make it to year 2 (2026).

How could we possibly know that, you might say, given all the potential advances that will happen in healthcare in 2024. Agreed! What we do is, we assume that the death rate for 1 year old babies in 2025 is what it was in 2024. Apply that death rate (the death rate for 1 year old babies in 2023) to our 995 babies in 2025. So how many remain?

Whatever your answer, those will be the number of two-year olds from this cohort in 2026. How many two-year olds are expected to pass away in 2026? Again, how could we possibly know? So we assume that the death rate of two year old babies in 2026 is the same as it was in 2024. Apply that death rate, and we now have an answer for how many three year olds (from this cohort) will be around in 2027.

And so on.

And that is what period life expectancy means. Read the definition again:

“Period life expectancy is calculated by assuming people will experience the current year’s mortality rates at each age at the corresponding ages in their lifetime.”

Period life expectancy, in other words, is not a forecast of how improvements in health will result in better life expectancy in the future. It is, instead, the exact opposite! It is a projection of current death rates for different age groups, applied to a group of people born today.

Their actual “lived and experienced” life expectancy may well be different, and usually is. See this in the case of France, for example:

Source: https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference

The TMKK, of course, is that we should expect to live, on average, for longer than the number indicated by our period life expectancy.

That just leaves us with two questions:

What is cohort life expectancy then? Well, it isn’t a forecast or a projection, it is an actual record of how many people born in a particular year make it to the next year, and the year after that, and the year after that… until eventually none are left.

Why does the blue line stop midway between 1900 and 1950? Well, you should be able to figure this out. And if you can’t, please do read the rest of Saloni Dattani’s excellent article!

Health in America (and Goodhart’s Law)

Is it better to spend a lot of money on healthcare, and not get great results, or it is better to not spend a lot of money on healthcare, and not get great results?

The United States of America tries to generate data that answers at least the first half of that question:

The country spends about $4.3trn a year on keeping citizens in good nick. That is equivalent to 17% of GDP, twice as much as the average in other rich economies. And yet American adults live shorter lives and American infants die more often than in similarly affluent places.

https://www.economist.com/business/2023/10/08/who-profits-most-from-americas-baffling-health-care-system

And if you are even remotely interested in the question of healthcare and how to get it to work for a country, you know, of course, about pharmaceutical firms and hospitals in America. But in a fascinating article, The Economist tells us about the middlemen in America’s healthcare system.

https://www.economist.com/business/2023/10/08/who-profits-most-from-americas-baffling-health-care-system

What do middlemen do? At their best, they can literally create markets. They can provide useful information to market participants, they can make markets more efficient by reducing search and transaction costs, they can lower risk and they can provide additional services. Has AirBnB made travel easier because of all of these factors? That’s what a middleman can do. So both this post and The Economist article aren’t a complaint about middlemen.

But that being said, the dose does make the poison. If middlemen make the markets more efficient, their revenue expressed as a percentage of national health expenditure shouldn’t be going up much, right? It certainly shouldn’t be nearly doubling!

So what’s going on?

  1. What does the healthcare market consist of? Doctors and patients, of course. But what connects, enables and facilitates interactions between both sides of the market? That’s the “plumbing” of this market – the middlemen. These are the insurance firms, the chemists, the drug distributors and the pharmacy benefit managers (PBM’s). As The Economist puts it, these entities don’t make drugs, and they don’t treat patients.
  2. And yet, they got to keep about 45% of America’s “health-care bill”. Those must be some fancy pipes!
  3. So here’s what happened. Back in 2010, the American government said to insurers that they could no longer eat away at all those dollars in America’s healthcare system. No more than 15% to 20% of collected premiums can end up in your pockets as profits. A measure (profitability) became a target (market efficiency to be defined by limiting profits).
  4. And in these parts, we know what comes next, correct?
  5. “But it imposed no restrictions on what physicians or other intermediaries can earn. The law created an incentive for insurers to buy clinics, pharmacies and the like, and to steer customers to them rather than rival providers. The strategy channels revenue from the profit-capped insurance business to uncapped subsidiaries, which in theory could let insurers keep more of the premiums paid by patients.”
  6. And well, these middlemen went out and bought these “uncapped subsidiaries” – some $325 billion worth of them. Or a 130 different mergers and acquisitions, if you like more than one metric.
  7. So now your healthcare market looks like this: patients go to get treated by doctors. Patients are “connected” to doctors via the plumbing provided by middlemen. But now, the plumbing “owns” the doctors!
  8. Which is when, as an economist, you should want to use the “i” word. What will be the incentive of the doctor? To give you the best treatment possible, or to reduce costs as much as possible for their corporate structure? If they can choose only one among these, which are they likely to choose?
    “For example, many studies have found that after hospitals acquire physician practices, prices increase but quality of care does not. A health-care company that controls many aspects of patient care could raise prices for rivals wishing to access its network. Some also worry about physicians being nudged towards offering the cheapest treatment to patients, lowering the quality of care.”
  9. One shouldn’t throw around such claims or hypotheses without backing it up with data. Is it actually the case that these middlemen are earning excess returns?
    “America’s health-care intermediaries are indeed unusually profitable. Research by Neeraj Sood of the University of Southern California and colleagues found that intermediaries in the health-care supply chain earned annualised excess returns—defined as the difference between their return on invested capital and their weighted-average cost of capital—of 5.9 percentage points between 2013 and 2018, compared with 3.6 for the S&P 500 as a whole.”
  10. Maybe these excess returns will attract competition, and maybe competition will make markets better? Paging Amazon!
    “Perhaps the biggest disruption to big health could come from Amazon. In 2021 its health-care ambitions suffered a setback owing to the closure of Haven Healthcare, a not-for-profit joint venture with JPMorgan Chase, the biggest bank in America, and Berkshire Hathaway, the biggest investment firm. Haven had aimed to cut health-care costs for the trio’s own staff. But despite Haven’s failure, Amazon is still expanding its health-care business. Last year it paid $3.9bn for One Medical, a primary-care provider. It runs Amazon Clinic, an online service offering virtual consultations, and RxPass, which lets members of its Prime subscription service buy unlimited generic drugs for a small fee. John Love, who heads Amazon’s pharmacy business, believes that the tech giant’s focus on customer experience, combined with its vast logistics network, makes it well-suited to shake up the industry.”
  11. But you’d be surprised at how complex any market can be. And healthcare markets are (trust me on this) a whole other story:
    “The entrenched firms have built their networks of doctors, hospitals, insurers and drugmakers over decades. Replicating that takes time and institutional knowledge. Mr Cuban admits that it is difficult to get drugmakers to list branded drugs on his pharmacy, as they are wary of upsetting the large pbms. And without branded drugs and the support of large health insurers, his firm’s reach remains small. The cap on insurers’ profits makes life tough for upstarts in that business, which struggle to compete against the negotiating power of the integrated giants.”
  12. Designing policy around healthcare markets is, as it turns out, quite the challenge. And it is very likely to be a case of one step forward and two steps back at worst, and two steps forward and one step back at best.
  13. But it is oh-so-important to take those steps, and having taken them, to ask if they are taking us in the right direction. Onwards!

Theory is one thing, implementation is a whole other story

In a paper written earlier this year, I and my co-author, Murali Neelakantan argued for unifying India’s (many) healthcare markets. Part of our proposal touched upon the need to unify a crucial aspect of these markets: procurement.

Furthermore, to ensure cost eff iciency and streamlined operations, the government will act as a monopsony buyer, procuring medical goods and services for all empanelled hospitals. This centralised approach will enable economies of scale, reduce costs, and guarantee steady demand for healthcare providers. By taking on the responsibility of procuring medical supplies, the government can negotiate better prices and allocation of resources within the healthcare system. We recognise that the healthcare requirements will vary across the country and even across states but we argue that there can be central procurement nevertheless. The local hospital or health authority will purchase based on the price notified by the central procurement agency.

https://ippr.in/index.php/ippr/article/view/213/92

It is one thing to say this as a theorist. As any public policy analyst will tell you, it is quite another to actually implement a scheme such as this. There will be teething troubles, there will be glitches. There will be leakages and pilferages. There will be stumbling blocks and unforeseen issues. Why, where will you start even, leave alone the question of actually making the whole thing work!

All good questions, of course. Entirely valid points. But we did point out that at least one state in India has already taken steps in this direction. Tamil Nadu already does centralized procurement of medicines, among other things worth emulating:

Another instance of successful healthcare reform at the state level can be found in Tamil Nadu, where the state government has implemented a range of innovative measures to improve the accessibility and affordability of healthcare services. These initiatives include the Tamil Nadu Medical Services Corporation (TNMSC), which centralises the procurement and distribution of drugs and medical equipment, resulting in more efficient and cost-effective processes (Parthasarathi and Sinha 2016).

https://ippr.in/index.php/ippr/article/view/213/92

But then, about two weeks ago, came news of a most excellent paper, written by CS Pramesh et al. Allow me to quote the abstract in its entirety:

In health systems with little public funding and decentralized procurement processes, the pricing and quality of anti-cancer medicines directly affects access to effective anti-cancer therapy. Factors such as differential pricing, volume-dependent negotiation and reliance on low-priced generics without any evaluation of their quality can lead to supply and demand lags, high out-of-pocket expenditures for patients and poor treatment outcomes. While pooled procurement of medicines can help address some of these challenges, monitoring of the procurement process requires considerable administrative investment. Group negotiation to fix prices, issuing of uniform contracts with standardized terms and conditions, and procurement by individual hospitals also reduce costs and improve quality without significant investment. The National Cancer Grid, a network of more than 250 cancer centres in India, piloted pooled procurement to improve negotiability of high-value oncology and supportive care medicines. A total of 40 drugs were included in this pilot. The pooled demand for the drugs from 23 centres was equivalent to 15.6 billion Indian rupees (197 million United States dollars (US$)) based on maximum retail prices. The process included technical and financial evaluation followed by contracts between individual centres and the selected vendors. Savings of 13.2 billion Indian Rupees (US$ 166.7million) were made compared to the maximum retail prices. The savings ranged from 23% to 99% (median: 82%) and were more with generics than innovator and newly patented medicines. This study reveals the advantages of group negotiation in pooled procurement for high-value medicines, an approach that can be applied to other health systems.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452934/ (Emphasis added)

There is an important difference between what was attempted here and what we are suggesting in our paper. Our paper talks of centralized procurement, while this paper speaks of implementing a pooled procurement approach. As they go on to say in their paper, “…centralized procurement systems require considerable administrative and managerial resources. A pooled procurement approach that is less resource-intensive and sustainable without significant investment is the WHO-suggested group contracting approach”.

But note that they did not give up on centralized procurement – they thought it easier to begin with pooled procurement, before tackling the much bigger beast that is centralized procurement. (Also note that there is academic research on how centralized procurement can be of benefit, especially in developing nations.)

And they’re quite right, of course. Beginning at a relatively smaller scale and then attempting more ambitious targets is unglamorous, perhaps – but it is also a much more sensible way of doing things. These four paragraphs in particular make for fascinating reading in terms of actually working through the nitty-gritty of implementing pooled procurement. And if you are going to spend time reading those four paragraphs later, please also do spend time on Fig.2.

What were the key takeaways?

  1. Considerable savings, both on generic drugs, as well as on innovator drugs.
    “This outcome suggests that the concentration of demand significantly strengthened our negotiating power, while the centralized negotiation approach, combined with larger purchase quantities, allowed us to secure substantial price discounts.”
  2. Opportunity costs matter!
    “The potential impact of cost savings is huge, in not only improving the affordability of care and decreasing out-of-pocket costs for patients, but allowing for the re-allocation of drug procurement funds towards other initiatives to deliver high-quality care”
  3. Enforcement of quality standards became easier, because of pooled procurement.
    “These savings are notable because they were achieved without compromising on quality, due to strict standards imposed on both the drugs and the companies.”
  4. Pooled procurement helps individual patients across India, regardless of region-wise differences.
  5. Lower treatment abandonment rates (yay!), and therefore higher survival rates (double yay!).
  6. Lesser financial burden on the patients!

And to end, the paragraph that I hope will launch a thousand studies, and eventually, the implementation of centralized procurement of drugs and consumables in India:

Based on the success of our piloting of pooled procurement in the network, conducting such negotiations may be relevant at a larger scale for oncology drugs, such as through the national health authority, as that will enhance the bargaining power as well as have far-reaching impact on access and affordability across the entire national network. Negotiation on a national level could also address the challenges of vendor monopoly or patented drugs supplied by a single vendor. Furthermore, to determine the final price for innovator and single vendor drugs, a comprehensive evaluation of the available literature on efficacy and safety data is crucial. If a drug meets the threshold for significant clinical benefits, cost-effectiveness assessment using adaptive health technology can provide guidance for negotiating prices.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452934/

Too Much Government in Healthcare

This is a continuation of yesterday’s post, and in this post, I seek to come up with the best libertarian arguments for why healthcare markets should have as little government as possible.

Three questions for you to consider:

  1. When patients receive a healthcare service, how much should they pay for it?
  2. When doctors and other providers deliver a healthcare service, how much payment should they receive?
  3. How should these amounts be determined?

These questions aren’t mine. They’re taken from John C. Goodman’s book, “Priceless: Curing the Healthcare Crisis“. These are excellent questions, and as an economist, I do not find them remotely objectionable. Were I to analyze (or teach somebody how to analyze) a market for a good or service, this would be a very good place to begin.

You may be tempted to ask questions about externalities, moral hazard etc., and how these affect the provisioning and pricing within these markets, but I would argue that this really is the third question at play. In other words, I find this list fairly comprehensive.

What are the author’s own answers to these questions?

  1. Patients should pay a price for care equal to its marginal social cost.
  2. Providers should receive a price equal to the marginal social value their care creates
  3. Wherever possible, these prices should be determined in competitive markets.

Again, as an economist, I find this unobjectionable. Note that our concerns about different forms of market failures are accounted for by using the phrase “wherever possible”. Presumably, if markets are not competitive, price determination should happen by other means.

As an Indian economist, I need to ask what happens if patients are unable to pay a price for care equal to its marginal social cost. And I also need to ask what these other means for price determination might be, in case the market for healthcare isn’t competitive. Note that I don’t mean either of these as criticisms of what has been said. I simply wish to state that different countries will have different constraints and features, and at least in the case of India, I think both of these are truly important and relevant questions.

John Cochrane has a nice paper in which he answers the first of these questions:

“What about the homeless guy with a heart attack?”
Let’s not confuse the issue with charity. The goal here is to fix health insurance for the vast majority of
Americans –people who have jobs, people who buy houses, cars, and cell phones, people who buy
insurance for their houses and life insurance for their families.
Yes, we will also need charity care for those who fall through the cracks, the victims of awful disasters,
the very poor, and the mentally ill. This will be provided by government and by private charity. It has to
be good enough to fulfill the responsibilities of a compassionate society, and just bad enough that few will choose it if they are capable of making choices. I wish it could be better, but that’s the best that is
possible. For people who are simply poor, but competent, vouchers to buy health insurance or to refill
health savings accounts make plenty of sense

Cochrane, J. H. (2013). After the ACA: Freeing the market for health care. Available at SSRN 2213027. (pp 23-24)

In other words, government intervention is necessary, unless the provisioning is entirely and always possible via private charity. At least in India’s case, I feel fairly safe in assuming that private charity is simply not going to be enough, now or in the foreseeable future.

As regards the second question: why isn’t the market for healthcare competitive?

I ran a simple Google search for “Assumptions of Competitive Markets“, and clicked on this link. Pick any other link that you prefer, but I would assume that the list won’t change all that much.

Competitive markets will have price takers, identical goods, a large number of buyers and sellers, easy entry and exit, and complete information. Some other websites may talk about zero search costs and zero transaction costs, but you can argue that this comes under complete information.

Is the market for healthcare in India competitive? Ask yourself which of these assumptions are met in the context of healthcare in India.

Where we lie on the spectrum between “hell yes” and “gawd no” may differ, but I think it is safe to say that most of us will be closer to “gawd no”. If your answer differs from this, I would love to know why.

But long story short, here would be my summarization of the libertarian approach to healthcare in the abstract:

As long as markets are competitive, and most people are above a certain income threshold, healthcare is best served by having as little government intervention in regulation and provisioning of healthcare as possible.

If that is not an acceptable statement for a libertarian approach to healthcare, please let me know how and why you would rephrase it.

If, on the other hand, it is an acceptable statement, then I have follow-up questions:

  1. If markets are not competitive, are we better off trying to make them competitive, or are we better off provisioning healthcare with government intervention? I ask this question specifically in an Indian context, but feel free to think about other nations while answering as well.
    Why does this matter? Because of opportunity costs. A resource that is spent on making markets competitive is a resource not spent on the provisioning of healthcare. Given the amount of poverty in India, this is an important question to think about.
  2. What is a good income threshold to keep in mind, and how do we know the answer is mostly correct?
  3. How many people need to be above this threshold for government to mostly withdraw from regulation and provisioning of healthcare?
  4. What does “as little government intervention as possible” mean? What should the government move out of first (regulation or provisioning), and why? Also, how?

I look forward to your answers!

Angus Deaton on Adam Smith and the Provisioning of Healthcare in America

Join me in staring at this chart. I have been doing so, on and off, for the past couple of days:

https://www.bostonreview.net/articles/how-misreading-adam-smith-helped-spawn-deaths-of-despair/

This is Figure 2 from a speech given recently by Angus Deaton at the Adam Smith Tercentenary celebrations at the University of Glasgow on June 8, 2023. I’ll have much more to say about the speech – that is the subject of today’s post – but for the moment, look at the chart.

It shows you life expectancy at age twenty-five in the United States of America (US) and Scotland (SCO). What does life expectancy at age twenty-five mean? Well, what does life expectancy at any age mean?

Life expectancy at a certain age is the mean additional number of years that a person of that age can expect to live, if subjected throughout the rest of his or her life to the current mortality conditions (age-specific probabilities of dying, i.e. the death rates observed for the current period).

https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Life_expectancy

In simple English, if you made it to the age of twenty-five as an American man in the year 1990, you could expect to live an additional fifty-one years from there on in (see the chart on the left).

Except for two problems.

The first problem is that the number, while indeed improving over time, started to drop off a little before 2020. A little before 2020, note, so this is not the pandemic we’re talking about.

And the second problem is a much bigger one. The red line in the chart on the left that I have been talking about is the red line at the top. That is the line for men in the United States with a BA degree.

The red line at the bottom of the chart – the life expectancy at age twenty-five for men in the United States without a BA degree – that red line is the one that I have not been able to stop thinking about. Here’s why:

  1. It is lower than the line for those with a BA throughout the entire period of analysis. US men without a BA degree have had lower life expectancy at twenty-five for the last thirty years.
  2. The life expectancy for this cohort at twenty-five started to drop off in 2010 – a full decade prior when compared to those with a BA degree.
  3. Not only has that drop-off not been arrested, it has accelerated a little before 2020. The data is probably even worse post 2020, but Angus Deaton has chosen to stop at 2020, since the topic of his speech isn’t the effects of the pandemic.

Outcomes over intentions, always remember. It doesn’t matter what the intentions were in 1990 or have been since then. Whatever they may have been (and are), the outcomes show that something, somewhere has gone wrong.

What has gone wrong? Can it be fixed? If so, how? Why should an Indian blogger care about this when there are so many other problems more specific to India?

I’ll answer each of these questions in turn, but I’ll begin with the last of these first.

Why should an Indian blogger care about this when there are so many other problems more specific to India?

For the same reason that an Indian blogger should care about what South Korea got right in the 1950’s when it comes to industrial policy. Because we should aim to try and replicate policies that have worked in other parts of the world, while being mindful of the opportunity costs of these policies. And by the same token, we should aim to try and avoid policies that have not worked in other parts of the world, while being mindful of the opportunity costs of not implementing those policies.

The second half of the last sentence in the paragraph above is quite something to think through, but we’ll get to it later on.

Being a student of the Indian economy requires you to be a student of economic policies the world over, and that over the years.

What has gone wrong?

Not just what has gone wrong, of course, but also why has it gone wrong.

It is here that we get into the deep and tricky part of the ocean. Tricky because the diagnosis of a problem depends upon your ability to reason things through. Your ability to reason things through is in turn dependent upon:

  1. How well you know you know your facts
  2. How well you are able to analyze them in order to reach a conclusion
  3. How familiar you are with the developments within the subject being analyzed
  4. The tools and theories being used for analysis.

Let’s take the first three of these as a given in this specific instance, and so too the first part of the fourth. It is the second part of fourth point that Angus Deaton focusses upon.

What are we analyzing here? The fact that life expectancy at twenty-five for American men is declining, and that the decline is worse among men without a BA degree. What theory should we advance for trying to understand why this has happened?

There can be many, but let’s cleave them into two parts for now.

Theory 1: There is too little government support when it comes to the provisioning of healthcare in the United States of America.

Theory 2: There is too much government support when it comes to the provisioning of healthcare in the United States of America.

The good news is that one hundred percent of economists upon reading this have gone “Aha! Exactly!”

The bad news is that some of them said so upon reading Theory 1, and some of them upon reading Theory 2.

So which is it? Why so, and how do we know?

I wouldn’t be much of an economist if I didn’t have an answer to this question. But more importantly, I wouldn’t be much of a teacher if I didn’t give you an overview of both theories. That is exactly what I plan to do over the course of the next two days, so stay tuned.

Some Days Are Diamonds

… and as the poet tells us, some days are stones.

Today, in the case of yours truly, is one of the latter ones. The daughter has been sniffling, coughing and battling a fever for the last three days, and while she is now much better (thank god), she has now passed the fever on to me.

But that’s not the reason today is a stone. The reason today is a stone is because I didn’t schedule a post for 10 am today. I’ve been on a bit of a good run – best as I can tell, the last time I missed posting was on the 30th of October last year, and while that isn’t great if the aim is to post daily, it certainly is better relative to the recent past.

And naturally, this is not a streak I would like to give up on. The sensible thing to do is to have some buffer posts ready, that can be deployed on days such as these. If I’m not up to sitting in front of a computer, filtering stuff I’ve read and deciding what to write about – and I’m really not up to it today – then I should be able to dip into my pitaara and schedule something that I’ve written in the past.

The good news is that I have 12 drafts waiting that will turn into good posts whenever I get around to finishing them. The bad news is that not one of them is complete. I teach economics for a living, but my real calling is procrastination.

Today’s post was going to be my notes from having read an article that I both enjoyed reading closely, and discussing with my students in class at the Gokhale Institute. I’m teaching behavioral economics this semester, and the essay in question has a lot of great points to think about in the context of biases and irrationality. I may come back to it in a later blog post, but for now, I’ll link to it, and leave as a snippet this lovely excerpt:

I’ve been tweeting about irrationality since 2017, and in that time I’ve noticed a disturbing pattern. Whenever I post of a cognitive bias or logical fallacy, my replies are soon invaded by leftists claiming it explains rightist beliefs, and by rightists claiming it explains leftist beliefs. In no cases will someone claim it explains their own beliefs. I’m likely guilty of this too; it feels effortless to diagnose others with biases and fallacies, but excruciatingly hard to diagnose oneself. As the famed decision theorist Daniel Kahneman quipped, “I’ve studied cognitive biases my whole life and I’m no better at avoiding them.”

https://gurwinder.substack.com/p/why-smart-people-hold-stupid-beliefs

And may I just say that the universe is rather good at trolling? I followed the author of this essay that I’m talking about on Twitter, and here’s a tweet that he recently retweeted:

Yes, yes, ok, fine.

Visualization and the NFHS

A very quick post today, because the end of the year is proving to be anything but a holiday, alas.

My third post in the series about NFHS was going to be about a pet theme (and peeve) of mine: our inability to get better visualization for our data, and indeed better reporting of data in general. But there is good news on this front, finally – there is now an excellent resource that we can use to visualize the results of the NFHS-5 survey.

Here’s just one chart to whet your appetite: blood sugar level among adult women (high, or very high or taking medicine). Note that the chart for men is largely similar.

https://geographicinsights.iq.harvard.edu/nfhs-tracker-districts

This is great work, and kudos to everybody associated with this visualization project! 🙂

H/T: Shashank Patil

What is the story that NFHS-5 is telling us?

… is, if you ask me, a question that we should ask ourselves, rather than have this question be answered for us by somebody else.

What I mean by that is that I could tell you what I think of the results, or I could point you to articles written by others that tell you what they think of the results. But the results are out there for us to analyze, easily available and fairly readable in terms of accessibility.

Here is the India fact sheet, and here is where you can access data split by states.

I would recommend that you not take the easy way out, by reading what other folks have written. Sit instead, with these reports, and take a look at the big picture – the all India level data. Then begin with the Indian state that you call home, and check how it is doing. Compare India’s performance and your state’s performance with some states that you think ought to do well, and some that you think might be relative laggards on health parameters.

See if the data matches your intuition. And if it doesn’t, ask if you should suspect the data or your intuition (or both!). Begin to build, no matter how long it takes, a picture of India’s health status in your head.

Ask questions about India’s population, its split by gender, ask about our obesity rates and split those up by states. Ask about whether men are doing better than women on some parameters, and if so which – and eventually, why. Ask if there are major changes between the 4th and the 5th round, and ask if the rate of improvement between the 4th and the 5th is different from the rate of improvement between the 3rd and the 4th. Then ask if these numbers are comparable at all, given that there is a difference of ten years in the latter case, but only 5 in the former.

Try to come up with a list of ten points at the all-India level that seem noteworthy to you. And once you’re done with the list, then take a look at what the newspapers and columnists and op-eds are saying.

Is the story that you have come up with similar to theirs? If not, why? Might it be because they’ve done a better job in highlighting relevant material, or might it because they’re biased in some ways? Do you think they’re biased because of what they’ve written in the past, or because their interpretation of NFHS-5 differs from yours, or both? What is the probability that you are biased against them, rather than they being biased while writing whatever it is that they have written? How can one tell, really?

The bottom-line is this: if you consider yourself a student of economics, don’t form your opinions and biases by mirroring and mimicking the opinions and biases of folks you like. Begin with the data, form your own opinions, and then test them against those of others. Defend your ideas and conclusions by pitting them against those of others, and by engaging in respectful debate.

It’s a good way to study our country! 🙂

Update: Please take a look at this excellent Twitter thread about the history of NFHS. H/T: Sumita Kale.

Understanding the idea behind the NFHS

Why should you, as an informed citizen of this country, be aware of how well India is doing in terms of health?

The question isn’t rhetorical. For its own sake is a more than good enough answer, of course, but here are additional reasons for keeping track of how well we’re doing as a country in terms of health:

  • If you think that the Solow model is a good way to start to think about the long term growth prospects of our nation, then thinking about the health of that workforce is important
  • If you think it is possible that different states may have different health outcomes, it makes sense to try and understand whether this is the case.
  • It also makes sense to dig into the data and try and understand the particulars of these differences. (A state may do poorly on life expectancy in comparison to other states, for example, but better along other dimensions. Why might this be so is an excellent question to ask, and this is just one of many possible questions.)
  • This is true for many other ways to “slice” this data. Are there different outcomes by, say, gender? By urban/rural divide?
  • The answers to each of these questions is important because it helps us understand how to build a framework to answer the mot important question of them all: if we have to improve India’s health, where should we start?

And for all of these reasons (and so many more) it makes sense for all of us to be aware of the results of the NFHS survey.

What is the NFHS Survey?

The National Family Health Survey (NFHS) is a large-scale, multi-round survey conducted in a representative sample of households throughout India. The NFHS is a collaborative project of the International Institute for Population Sciences(IIPS), Mumbai, India; ICF, Calverton, Maryland, USA and the East-West Center, Honolulu, Hawaii, USA. The Ministry of Health and Family Welfare (MOHFW), Government of India, designated IIPS as the nodal agency, responsible for providing coordination and technical guidance for the NFHS. NFHS was funded by the United States Agency for International Development (USAID) with supplementary support from United Nations Children’s Fund (UNICEF). IIPS collaborated with a number of Field Organizations (FO) for survey implementation. Each FO was responsible for conducting survey activities in one or more states covered by the NFHS. Technical assistance for the NFHS was provided by ICF and the East-West Center.

http://rchiips.org/nfhs/about.shtml

Why is the NFHS important?

Why do we have something like NFHS? To obtain data on health and nutrition, disaggregated to the level of districts. We want to take stock of developmental targets at a single point in time and wish to track improvements (or deterioration) over time.

https://www.newindianexpress.com/opinions/columns/2021/dec/13/nfhs-andwhy-surveys-are-better-than-asking-a-cab-driver-2394809.html

How often is the NFHS carried out?

That’s a little tricky to answer, but I can tell you that there have been five rounds so far. The first one was in 1992-93, the second in 1998-99, the third in 2005-06, the fourth in 2015-16 (and this decade long gap is why this question is a little tricky to answer) and the fifth in 2020-21.

OK, so we can use this data to see how health in India has evolved over time?

Um, not exactly:

To gauge improvements over time, ideally, we should have what statisticians and economists call a panel. In a panel, across time, questions are asked to the same individuals/households. For something like NFHS, that’s not possible. In addition, for NFHS-5, compared to NFHS-4 (2015–16), additional questions have been asked. For those questions, gauging improvements over time is naturally impossible.

https://www.newindianexpress.com/opinions/columns/2021/dec/13/nfhs-andwhy-surveys-are-better-than-asking-a-cab-driver-2394809.html

Then what can we use the data for?

Especially because the answer to the first question in this series included this: “wish to track improvements (or deterioration) over time.”

Well, yes, it did. And we do use this data to see how health in India has evolved over time. But it’s not a perfect comparison, because we aren’t tracking the same households over time, and it therefore isn’t an apples to apples comparison. But the perfect shouldn’t be the enemy of the good, especially in public policy! The fifth round has in fact been structured in such a way so as to make the results as comparable as possible.

How many households are covered?

NFHS-5 fieldwork for India was conducted in two phases, phase one from 17 June 2019 to 30 January 2020 and phase two from 2 January 2020 to 30 April 2021 by 17 Field Agencies and gathered information from 636,699 households, 724,115 women, and 101,839 men

http://rchiips.org/nfhs/NFHS-5_FCTS/India.pdf

What questions are asked in this survey?

That’s a great question to ask!

Four Survey Schedules – Household, Woman’s, Man’s, and Biomarker – were canvassed in local languages
using Computer Assisted Personal Interviewing (CAPI).

In the Household Schedule, information was collected on all usual members of the household and visitors who stayed in the household the previous night, as well as socio-economic characteristics of the household:

water, sanitation, and hygiene; health insurance coverage; disabilities; land ownership; number of deaths in the household in the three years preceding the survey; and the ownership and use of mosquito nets.

The Woman’s Schedule covered a wide variety of topics, including the woman’s characteristics, marriage, fertility, contraception, children’s immunizations and healthcare, nutrition, reproductive health, sexual behaviour, HIV/AIDS, women’s empowerment, and domestic violence.

The Man’s Schedule covered the man’s characteristics, marriage, his number of children, contraception, fertility preferences, nutrition, sexual behaviour, health issues, attitudes towards gender roles, and HIV/AIDS.

The Biomarker Schedule covered measurements of height, weight, and haemoglobin levels for children; measurements of height, weight, waist and hip circumference, and haemoglobin levels for women age 15-49 years and men age 15-54 years; and blood pressure and random blood glucose levels for women and men age 15 years and over. In addition, women and men were requested to provide a few additional drops of blood from a finger prick for laboratory testing for HbA1c, malaria parasites, and Vitamin D3.

http://rchiips.org/nfhs/NFHS-5_FCTS/India.pdf

Whoa, that’s… a lot!

Indeed it is! If you haven’t clicked through to those PDF’s that have been linked to in the previous question, take the time out to go and do so. Conducting one of these surveys isn’t easy. All of these, and across these numbers (636,699 households, 724,115 women, and 101,839 men) is pretty tough, and kudos to the team that did the work.

So how are these households selected?

Another excellent question. From the interview manual (and if you are a student of statistics, this manual ought to be mandatory reading):

All 29 states and seven union territories (UTs) will be included in NFHS-5. NFHS-5 will provide
estimates of most indicators at the district level for all 707 districts in the country as on 1 March
2017.

For NFHS-5, the sample consists of approximately 30,456 clusters (small geographically defined
areas) throughout the country. The households in each of these clusters have recently been listed or
enumerated. A sample of households was then scientifically selected to be included in NFHS-5 from
the list in each of the clusters. Each of these households will be visited and information obtained
about the household using the Household Questionnaire. Women and men within these households
will be interviewed using an Individual Questionnaire. Women age 15-49 years will be interviewed
using the individual Woman’s Questionnaire. Men age 15-54 years will be interviewed using the
individual Man’s Questionnaire. We expect to complete interviews with about 7,45,488 women and
1,19,501 men in 670,032 households in this survey.

http://rchiips.org/NFHS/NFHS5/manuals/NFHS-5%20Interviewer%20Manual_Eng.pdf

And how are the surveys conducted?

During NFHS-5 fieldwork, you will work in a team consisting of one field supervisor, three female
interviewers, and one male interviewer. Each team will be provided with a vehicle and driver for
travelling from one Primary Sampling Unit (PSU) to another to conduct the fieldwork.
In addition, the team will include two health investigators. These individuals will be responsible for
drawing blood from eligible persons for testing for anaemia status, blood pressure, and blood glucose. In
addition, the health investigators will collect blood drops from a finger stick on filter paper cards,
which will be tested for malaria, HbA1c, and Vitamin D3 in ICMR laboratories. They will also be
responsible for the anthropometric measurements of eligible women, men, and children. The supervisors
will also receive some biomarker training so that they can supervise the health investigators and assist
them as needed. All interviewers will be trained to assist the health investigators in taking the
anthropometric measurements(height, weight, and waist and hip circumference measurements).
Each team supervisor will be responsible for his/her team of interviewers and health investigators.
The specific duties of the supervisor are described in detail in the Supervisor’s Manual.

http://rchiips.org/NFHS/NFHS5/manuals/NFHS-5%20Interviewer%20Manual_Eng.pdf

This PDF, the one that I have excerpted from, is 182 pages long. I am not for a moment suggesting that all of you must read every single word. But I’ll say this much: if you are currently studying either statistics or economics, you should go through it more than once. It is one thing to learn from textbooks, and quite another to understand the on the ground realities.

In tomorrow’s post, let’s dig in and take a look at the data itself, and see what the NFHS-5 results tell us about our country’s health.