The healthcare funding conundrum (once again)

Fiscal Sustainability of Health Systems. Bridging Health and Finance Perspectives

Forget economic forecasts, most of them have failed many times. You don't need to be precise about the size of the GDP devoted to health in 2030, it will definitely be more expenses than now. The OECD tries in a new report to review these forecasts and to spread fear in the near future. I think that our societies before the great recession, were able to manage to some extent fiscal deficits. Now it is different, the size of the deficit for future generations is unacceptable.
The report reviews former approaches to supply side and demand side measures for cost-containment. A well known story on the macro-prescription for governments.  My view is not reflected in the document. I have highlighted many times the importance of organizational change, the micro-perspective, i.e. the changes in the structure of incentives and coordination mechanisms in the health system.
This is the most challenging effort for any government, because organizational change and prioritisation represents an attempt to modify the current status quo. Governments are affraid of it, but in my opinion somebody has to handle this conundrum and tell  the population exactly that unless we change current health care organizations, taxes will not be sufficient to pay the bill. Then two options will be open to us: out of pocket or no access. This is the message that this report is unable to explain clearly and now it's time for somebody to disseminate it.

PS. Read the Fiscal Sustainability of Health Systems: Policy Brief 

Measuring population health

Morbilidad, utilización de recursos y costes sanitarios en la comarca del Baix Empordà

In this blog I've explained many times that if I had to pick one health system as a benchmark I would say that it is  Serveis Sanitaris Integrats del Baix Empordà (SSIBE). This is my choice. I've been contributing over the last decade to understand what has happened to the morbidity, utilization and costs of this population.
Now, you have all this research effort in a PhD Dissertation by J. M. Inoriza, a must read. I strongly recommend you to have a look at it. Congratulations to all contributors.

Health policy: what works?

Successes and Failures of Health Policy in Europe. Four decades of divergent trends and converging challenges

Three questions to answer:

• Do differences in rates of disease reflect differences in related policies?
• What would a country gain if it implemented the policies of the best performing country?
• Which social, economic and political factors influence a country's success in health policy?

And the (partial) answer is in chapter 14 of the book:

Gains in health since 1970 for the causes analysed in this chapter have clearly been enormous. While not all of these declines can be attributed to health policies, part of the decline in all these causes can  be, as shown in the previous chapters. For example, some of the declines in lung cancer and  ischaemic heart disease can be attributed to tobacco control; some of the declines in external cause mortality among children to injury prevention, and some of the declines in death rate from RTIs to road safety measures, and so on. It is impossible to estimate the specific contribution of preventive health policies to these declines, but even if these accounted for only half or a quarter of the cause-specifi c declines, the successes would be immense. At the same time, not all countries have been  equally successful in bringing down mortality from these preventable causes, as shown again by the calculations.

The book was released in 2013 with data from 5 years before, an update would be necessary. Anyway, a close reading is required.

The modeling approach to health decisions

Applying Modeling to Improve Health and Economic Policy Decisions in the Americas: The Case of Noncommunicable Diseases

On the role of modeling in health, this OECD report says:

In the health sector, the purpose of modeling is to structure evidence on clinical and economic outcomes in a form that can inform decisions about clinical practices and health care resource allocations. Models synthesize evidence on health consequences and costs from many different sources, including clinical trials, observational studies, insurance claim databases, case registries, public health statistics, and preference surveys. A model’s logical, mathematical framework permits the integration of facts and values and links these data to outcomes that are of interest to health care decisionmakers

I agree. The report shows some examples of aggregated modeling without panel microdata. If you compare this approach with David Eddy one, Archimedes models, it is exactly the opposite. And my opinion is in favour of Archimedes, as you can check in my previous posts. The most useful approach to modeling is the one that allows improve decisions at micro level, physician and patient.

PS. An innovative approach with practical implications in SSIBE, Palamós.

 Bonnard exhibition in Madrid.

The size of income inequality (2)

Source: World Economic Forum: Inclusive Growth and Development Report 2015

Epigenetics contribution to clarify disease mechanisms

Epigenetics at the Crossroads of Genes and the Environment

You may find an updated definition of epigenetics in this JAMA article:

 Epigenetics refers to information transmitted during cell division other than the DNA sequence per se, and it is the language that distinguishes stem cells from
somatic cells, one organ from another, and even identical twins from each other. Examples include (1) DNA methylation, a covalent modification of the nucleotide cytosine, that is copied during cell division at CpG dinucleotides by the maintenance enzyme DNA methyltransferase I; (2) posttranslational modifications of nucleosome proteins about which the DNA double helix is wrapped; and (3) the density of  nucleosomes and higher-order packaging of chromatin within the nucleus, including its relationship to the nuclear lamina.

If this is so, why is the message of predictive genetics so widespread?. I've insisted on this issue before.

 The field of epigenetics and epigenetic epidemiology have much to do to improve measurement of epigenetic marks, inform natural variation in such marks, and the biological and population level relationships between genes, environment, and epigenetics. This is an important emerging area as it holds promise for better risk prediction in precision medicine as well as for clarification of disease mechanisms among the existing opaque landscape only partially informed by traditional genetic and environmental studies to date.

 A short and relevant article that provides hints for further reading.

PS. Epigenetic phenomena, from Nature.

Ownership and access to medical data

Unpatients—why patients should own their medical data

Eric Topol says in Nature Biotechnology:

Today, in the United States, health data live in a plethora of places, from electronic health record (EHR) systems, insurance claims databases, siloed personal health apps, research and clinical trial databases, imaging files and lots of paper. Although seemingly everywhere, any true semblance of an overarching organization or standardization of medical data are lacking, whether at the individual or societal level

His proposal is straightfoward: the ownership of the clinical record is of the patient. This situation is completely different in our country. We have public centralised repositories and the patient is the owner. There is still a lack of coordination and many things to solve, however the basics are covered in the publicly funded System, that's not the case in the private sector.

In contrast to the legal and technical difficulty an individual faces to obtain all his or her own medical data is the relative ease with which hackers have managed to breach ~100 million patient records in the first half of 2015

And his proposal:

 We must begin talking about creating a health data resource in a much broader and more universal context, controlled by the individuals who supply the data. This is a unique moment where we may be able to provide for personal control and, at the same time, create a global knowledge medical resource.

Sounds interesting, though methodology is crucial for success.


PS. Hacking electronic records:

The timeline for electronic medical data hacks in the United States of over 1 million individuals