December 31, 2017

The constraints to genomic editing

CRISPR… ¿debemos poner límites a la edición genética?

A new publication by Fundació Grifols highlights the potential constraints to genomic editing. It is a good moment to have a look at it. Savador Macip says:
Los peligros, pues, son muchos, tantos como las cosas buenas que la edición genética nos puede aportar. De alguna forma, recuerda la energía nuclear. Descubrir los secretos del átomo nos ha permitido acceder a una cantidad inimaginable de energía, que usamos diariamente, pero que se debe regular de una forma muy precisa para evitar accidentes terribles y contaminaciones no deseadas. Y, lo que es más peligroso aún, la misma información sirve para fabricar una de las armas más mortíferas que conocemos, capaz incluso de destruir el planeta. A otra escala, CRISPR/Cas9 podría tener efectos parecidos.

La ciencia no se detiene, siempre continúa avanzando, y la sociedad corre el peligro de quedarse atrás. Por ello es importante que los debates sobre hacia dónde queremos ir empiecen cuanto antes mejor y que en ellos participe una muestra amplia de la población, no solo los científicos. Para conseguirlo es necesario que el máximo número posible de gente esté bien informada acerca de los avances más recientes, que entienda su alcance y sus implicaciones y que haga el esfuerzo de contribuir en los debates. A la vez, los científicos deben salir a explicar qué está pasando en sus laboratorios y los políticos deben proporcionar plataformas necesarias para estas discusiones. Solo así nos aseguraremos de que estos descubrimientos son usados
A must read.

Side effects, a good film to watch

December 24, 2017

Diagnostic testing and outcomes

When diagnostic testing leads to harm: a new outcomes-based approach for laboratory medicine

There are five causes of testing-related diagnostic error:
  • An inappropriate test is ordered
  • An appropriate test is not ordered
  • An appropriate test result is misapplied
  • An appropriate test is ordered, but a delay occurs somewhere in the total testing process
  • The result of an appropriately ordered test is inaccurate
If we know that that these are the causes, are there any measures available?
In Lundberg’s model, the value of laboratory results is influenced by events
that occur before the sample reaches the laboratory and after the results are released
from it. His model encompasses the physician’s cognitive involvement at the start of
the process and at the end.

December 22, 2017

The weirdest financing of a health system in the world

Alternative Financing Strategies for Universal Health Coverage

This article from WHO by Joe Kutzin provides a deep analysis of the implications of financing universal coverage. Today I would like to highlight this statement:
There is a general trend toward greater diversification of revenue sources, including a diminishing role for payroll tax funding. This is a practical consequence of the “ideology” of UHC. With the move toward UHC, entitlement to health coverage is being delinked from employment, and from direct contributions more generally. On the practical side, wage-linked contributions cannot generate a sufficient revenue base, both in high-income countries (because of aging populations and macroeconomic concerns regarding increasing wage-based taxation) and also in low- and middle-income countries (LMICs) (because of low participation rates in formal sector employment).
Spain has decided exactly the opposite. Coverage entitlement comes from social security membership, while funds come from taxes. The weirdest financing of a health system in the world.

December 21, 2017

Now is the time for artificial intelligence in healthcare

Artificial intelligence in health care: within touching distance

Medical practice has so far been largely unchanged by the digital revolution that has disrupted so many other industries, but perhaps artificial intelligence (AI) will provide the improvements in medical care and research promised for so long.
A short editorial in Lancet highlights the importance of deep learning in healthcare.
In 2017, successful use of deep neural networks was reported for the analysis of skin cancer images with greater accuracy than a dermatologist and the diagnosis of diabetic retinopathy from retinal images. The inherent requirement for large-scale, high-quality, well structured data might ultimately limit the areas in which AI can bring benefits to health care.
 Jordi Parramon exhibition

December 14, 2017

The urgent need to define delivery models for genetic testing

Identification of Delivery Models for the Provision of Predictive Genetic testing in Europe: Protocol for a Multicentre Qualitative study and a systematic review of the literature

The increasing role of genomics in medical decision making requires a review on how services should be organised. Unless this effort is taken promptly, it will be much more difficult to adapt the messy organization to an efficient model for the delivery of services. This issues are explained in a recent article. The ten questions:

 The transfer of genomic technologies from research to clinical application is influenced not only by several factors inherent to research goals and delivery of healthcare but also by external and commercial interests that may cause the premature introduction of genetic tests in the public or private sector (i.e., introduction of a test despite insufficient evidence regarding its analytical validity, clinical validity, and utility). Furthermore, current genetic services are delivered without a standardized set of process and outcome measures, which are essential for the evaluation of healthcare services. It is important that only genetic/genomic applications with proven efficacy and effectiveness are delivered to populations, and particularly that technologies have favorable cost-effectiveness ratios