Improving the pharmaceutical regulation production function

Using Routinely Collected Data to Inform Pharmaceutical Policies

With the broadening of data available for officials to regulate markets, things could change. The issue is specially relevant for pharmaceuticals. Up to now if you want information about the market you have to use IMS data. Now governments that pay the drugs bill can use their own data to improve regulation. Better knowledge could represent better regulation if it is performed appropriately and on a timely basis. The OECD report tries to put all these elements together and highlight the opportunities ahead.

This report provides an overview of patient-level data on medicines routinely collected in health systems from administrative sources, e.g. pharmacy records, electronic health records and insurance claims. In total 26 OECD and EU member countries responded to a survey addressing the availability and accessibility of routinely collected data on medicines and their applicability to developing evidence. The report further explores the utility of evidence from clinical practice, looking at experiences and initiatives across the OECD and EU.

Governments will have to improve big data capabilities and add new talent.

Sorolla right now in London

Never ending health reforms

Reformas pendientes en la organización de la actividad sanitaria

A new issue of Cuadernos ICE shows the current state of the health system. You'll find an article that explains the main constraints to be overcome with all the details. Above all, in my opinion is the quality of institutions. The remaining articles are highly recommended as well.
We are living on a slippery slope and nobody cares about it, it seems that key decision makers have forgotten to read and accept facts as they are. I strongly suggest a reading of these articles. Something should be done to avoid having to rewrite the same a decade later, as it has happened. Maybe the reforms never end because they still have to start.
Take a chance, play your part. Don't wait too long.

PS. Facts (1) and (2)

You can cry a million tears 

You can wait a million years 

If you think that time will change your ways 

Don't wait too long

When your morning turns to night 

Who'll be loving you by candlelight

If you think that time will change your ways 

Don't wait too long

Maybe I got a lot to learn 

Time can slip away 

Sometimes you got to lose it all 

Before you find your way

Take a chance, play your part 

Make romance, it might brake your heart 

But if you think that time will change your ways 

Don't wait too long

It may rain, it may shine 

Love will age like fine red wine 

But if you think that time will change your ways 

Don't wait too long

Maybe you and I got a lot to learn 

Don't waste another day 

Maybe you got to lose it all 

Before you find your way

Take a chance, play your part 

Make romance, it might break your heart 

But if you think that time will change your ways 

Don't wait too long 

Don't wait 

Hmm... Don't wait

Compositors: Jesse Harris / Larry Klein / Madeline Peyroux

Definitely, this is the message

Revisiting the economic foundations of health insurance

Choose to Lose: Health Plan Choices from a Menu with Dominated Option

We know that more choice is not always better. Former posts have emphasized this issue. Loewenstein et al. provide remarkable evidence of what happens with health insurance:

Our findings offer perhaps the strongest evidence to date that insurance reveal as much or more about consumer understanding than about actual health-related risk preferences. In this sense, our setting provides a rare opportunity to conduct a specification check on
the standard insurance demand model absent search frictions.

Our findings challenge the standard practice of inferring risk preferences from insurance choices and raise doubts about the welfare benefits of health reforms that expand consumer choice.

If this is so, many books should be rewritten asap.

PS. G. Loeweinstein will be in Barcelona next week at Barcelona Jocs.

Van Gogh at Tate Gallery 

Pharma landscape

The Global Use of Medicine in 2019 and Outlook to 2023

The summary of IQVIA report:

• Global spending on medicines reached $1.2 trillion in 2018 and is set to exceed $1.5 trillion by 2023.
• Invoice spending in the United States is expected to grow at 4– 7% to $625–655 billion across all channels, but net manufacturer revenue is expected to be 35% below invoice and have growth of 3-6% as price growth slows on both an invoice and net basis.
• Net drug prices in the United States increased at an estimated 1.5% in 2018 and are expected to rise at 0–3% over the next five years.
• China reached $137 billion in medicine spending in 2018, but will see growth slow to 3-6% in the next five years as central government reforms to expand insurance access to both rural and urban residents, as well as expansions and modernizations of the hospital system and primary care services have been largely achieved and efforts shift to cost optimization and addressing corruption.
• Medicine spending in Japan totaled $86 billion in 2018, however spending on medicines is expected to decline from -3 to 0% through 2023, due to the effect of exchange rates and continued uptake of generics and offset by the uptake of new products.
• The number of new products launched is expected to increase from an average of 46 in the past five years to 54 through 2023, and the average spending in developed markets on new brands is expected to rise slightly to $45.8 billion in the next five years, but represent a smaller share of brand spending

Rescuing citizens from the "rule of rescue"

People feel a need to rescue identifiable individuals facing avoidable death or harm. This is a well known fact  explained in 1968 by the Nobel laureate Thomas Schelling from an economic perspective  and by Jonsen  in the bioethics context in 1986.

"A single death is a tragedy; a million deaths is a statistic." This quote reflects exactly what we are talking about. However, the issue is: Do you accept the rescue at any price with public money?

These previous posts of this blog: (1) and (2) explain the details. I'll not insist on what I've already said. I suggest you have a look at them.

Today you can asess these three facts:

1. A country spends 38m € in drugs for 249 patients in 2018. A lifetime treatment.

2. A country has a waiting list of 132.025 patients for surgery, 123.249 patients for diagnostic tests, and 424.715 patients waiting for a visit to the specialist. Total people waiting: 679.989 patients in a country with 7.543.825 inhabitants. 9% of the population is in the waiting list for a health service. However, 25% have voluntary duplicate insurance and could jump the list. Therefore the exact figure is 12% of inhabitants waiting.

3. A country knows that spending 10m € in addition every year can increase cardiac surgery by 600 interventions. This means 600 critical patients less in the waiting list. With 38m €, the number of cardiac interventions would be 2.280.

 Ask yourself what to do about it, what would you prefer to do with 38m€ every year ? Just apply them to 249 patients or to 2.280 (you are not on the waiting list, and we'll assume the same adjusted quality of life years for both cases). Anyway, it's too late to have your answer, the government has already decided for you, and maybe you don't agree with it, as I don't agree. The government prefers the rescue of 249 citizens.
Just to finish, check this final fact:

This country spends 1.192 € per capita of public budget on health. Another country under the same mandatory tax system is able to spend 1.635 €, 40% more !!!

More money allows to avoid such dilemmas for this country. Ask yourself if you want to stay in the former tax system that is damaging your health. Once you have the answer, you'll understand why this country wants to leave this unfair tax system as soon as possible.

Now at Brooklyn Museum

Pharma returns

Measuring the return from pharmaceutical innovation 2018

Key findings for top 12 biopharma companies in the Deloitte study.

• R&D returns have declined to 1.9 per cent, down from 10.1 per cent in 2010 - the lowest level in nine years
• Returns have been impacted by the growing cost of bringing a drug to market which now stands at $2,168 million – almost double the $1,188 million recorded in 2010
• Forecast peak sales have declined from last year to $407 million – less than half the 2010 value of $816 million

The growing cost of new drugs includes buying companies for their research (outsourcing research) instead of "producing" R&D within the company. The report will not tell you this minor observation.
Last February I said :

In drug industry the probability of R&D failure is 90.4%. We all know that in the drug costs we are paying also for failures, but we easily forget the figure.

You'll not find any reference to this minor issue. Is there any profitable industry with such a failure rate?

Caro Emerald

The bioethics of machine clinical decision making

Artificial intelligence (AI) in healthcare and research
Regulation of predictive analytics in medicine

This is what a brief note from Nuffield Council of Bioethics says about artificial intelligence in healthcare:

The use of AI raises ethical issues, including:

• the potential for AI to make erroneous decisions; 

• the question of who is responsible when AI is used to support decision-making; 

• difficulties in validating the outputs of AI systems; inherent biases in the data used to train AI systems; 

• ensuring the protection of potentially sensitive data; 

• securing public trust in the development and use of AI; 

• effects on people’s sense of dignity and social isolation in care situations; 

• effects on the roles and skill-requirements of healthcare professionals; 

• and the potential for AI to be used for malicious purposes.

A key challenge will be ensuring that AI is developed and used in a way that is transparent and compatible with the public interest, whilst stimulating and driving innovation in the sector.

This statement is naive.(From m-w, naive:  marked by unaffected simplicity : INGENUOUS). Up to now, have you seen any transparent algorithm available for imaging, triage or any medical app? For sure not. Therefore, the real key challenge is to stop introducing such algorithms -to ban apps- unless there is a regulatory body that takes into account the quality assurance or effectiveness side (sensitivity and specificity) and the required transparency for citizens.
Until now Nuffield has released only a brief. Let's wait for the report.
If you want a quick answer, check Science this week:

To unlock the potential of advanced analytics while protecting patient safety, regulatory and professional bodies should ensure that advanced algorithms meet accepted standards of clinical benefit, just as they do for clinical therapeutics and predictive biomarkers. External validation and prospective testing of advanced algorithms are clearly needed

 They explain the five standards and give rules and criteria for regulation. It is really welcome.

Berenic Abbot exhibition in Barcelona