Determinants of change in life expectancy

Contributions Of Public Health, Pharmaceuticals, And Other Medical Care To US Life Expectancy Changes, 1990-2015

Life expectancy in the US increased 3.3 years between 1990 and 2015, but the drivers of this increase are not well understood. We used vital statistics data and cause-deletion analysis to identify the conditions most responsible for changing life expectancy and quantified how public health, pharmaceuticals, other (nonpharmaceutical) medical care, and other/unknown factors contributed to the improvement. We found that twelve conditions most responsible for changing life expectancy explained 2.9 years of net improvement (85 percent of the total). Ischemic heart disease was the largest positive contributor to life expectancy, and accidental poisoning or drug overdose was the largest negative contributor. Forty-four percent of improved life expectancy was attributable to public health, 35 percent was attributable to pharmaceuticals, 13 percent was attributable to other medical care, and −7 percent was attributable to other/unknown factors. Our findings emphasize the crucial role of public health advances, as well as pharmaceutical innovation, in explaining improving life expectancy.

 A must read article. This is the kind of messages that can inform policymakers and redefine priorities. Unfortunately, there is no similar study for my country.

PS. If you want the same study over two centurys, check here

Vaquero at Marlborough

Professionalism, current challenges

 Medical Professionalism In An Organizational Age: Challenges And Opportunities

What strategies might organizations implement to make it more likely that clinicians can live up to the core responsibilities of professionalism?

This is the question. The answer in this article, at least in part.

 One useful beginning point is with institutional culture, “that which is shared between people within organizations… the shared way of thinking…the values, beliefs and assumptions.If the organizational culture does not support the responsibilities of professionalism, then people are able to fulfill them only through acts of personal heroism.

 Transparency is another controversial area where physician leadership might buttress professional responsibilities. Organizational policies vary considerably on how clinical data should be collected, identified, and shared.

Although it is simpler to identify the challenges and opportunities now confronting medical  professionalism than to propose effective responses to them, the approaches set forth here—with their focus on organizational culture, leadership, compensation, transparency, and doctor patient relationships—are intended to stimulate further discussion.

Matisse exhibition at Pompidou

 

Viruses are among us

Viruses, Pandemics, and Immunity 

A new book helps to explain our fight with infectious diseases. It splits it in two eras:

The first era of our eternal battle with infectious diseases ended with one of the major achievements of medicine, the vaccine against smallpox. We will tell the tale here of how this procedure, which ultimately eradicated the scourge of smallpox from the planet, was developed slowly by several cultures on different continents in an empirical way without any understanding of how or why it worked. In the second era we learned about the origins of infectious diseases and how to combat them.

And explains why we share our environment with viruses

 Viruses are very simple ancient organisms that have probably existed since life began. For reasons that will become clear in the next section, viruses cannot reproduce on their own. They have to colonize bacteria, plants, and animals (including humans) in order to replicate and propagate their species. Therefore, viruses have specialized skills that let them invade other species and replicate inside them. When a virus invades the human body and replicates, it can damage our cells and tissues. The immune system, about which we will learn in the next chapter, tries to kill viruses that invade us to prevent and combat viral infections. This war between viruses and our immune system has raged since time immemorial.

And this is our current fight with SARS-CoV2. Highly recommended.

 

 

Vaccine nationalism (2)

 Designing Pull Funding For A COVID-19 Vaccine

If somebody wants to avoid vaccine nationalism, then there is a need for a global mechanism of allocation. You'll find a specific proposal in Health Affairs about this issue. Unfortunately, it seems that nobody cares about its application.

In baseline simulations, the optimal pull program spends an average of $50 per dose to obtain an average of 2.2 billion doses—$110.4 billion in total. The size of our pull program is driven by the enormous estimated benefit from COVID-19 vaccination, leading the optimal program to induce nearly all firms to participate (average of 9.8 out of 10), installing nearly all  available capacity, and allowing more people to be vaccinated with less delay. To secure this level of participation requires the award to cover all but the most exorbitant cost draws. On average, 2.9 of the 10 candidate firms develop a successful vaccine, generating a social benefit (net of program costs) of $2.8 trillion.

 Our mechanism offers two advantages over the free market. First, it dramatically lowers cost—by a factor of thirteen—by averting a bidding war. Given our program’s larger size compared with other policy proposals, it is ironic that its advantage would be to lower costs compared with the private market. Second, it allows for more efficient allocation, moving some vulnerable people in lowerincome countries up in the queue ahead of some from richer countries experiencing lower harm. A conjectured third benefit of our mechanism— enhancing investment in more candidates and more capacity—did not materialize in baseline simulations. Demand for a COVID-19 vaccine is so high that every firm in every simulation finds investing profitable under a free-market scenario. This third benefit does materialize in scenarios with substantially more per firm capacity than in the baseline.

 Eivissa, Francesc Català i Roca

 

Machine learning for clinical labs

 Machine Learning Takes Laboratory Automation to the Next Level

Good article on ML applications for microbiology lab.

There are two commercially available Food and Drug Administration (FDA)-approved microbiology laboratory automation platforms in the United States, namely, WASPLab (Copan Diagnostics Inc.) and Kiestra (Becton Dickinson) (6). Each system is highly customizable and consists of front-end processing, “smart” incubation according to laboratory protocol, and plate imaging. The processing unit performs medium selection, application of patient information and barcodes for tracking, medium inoculation, and plate streaking. Automation of these processes cuts down on and improves the consistency of repetitive tasks previously performed by technologists.

Image analysis software is not currently FDA approved, so the algorithm it deploys qualifies as a high-complexity laboratory-developed test when used to make definitive calls about microorganism presence/absence or culture significance. In this context, the end user need not understand the internal workings any more than they understand the inner workings of most computers. Additionally, as with most laboratory software, manufacturer assistance is provided in training the algorithm. Labs may, therefore, validate performance according to familiar sensitivity and specificity (for significant growth), precision and accuracy (for quantification), and procedural variation (coefficients of variation, Kappa statistics). As with any test, revalidation must be performed if components of the test change. The number of samples needed to train the algorithm (hundreds to thousands) will be algorithm dependent but easily available due to their common nature, facilitating both initial and revalidation using new plate images. Validation of machine learning image analysis for laboratory automation may, overall, be comparable to that performed for whole-slide imaging as used in histopathology, where the object of validation is a process as much as a machine (12) and where modest interobserver agreement may set a similarly modest benchmark for machine learning performance.

 Eivissa autèntica, Joaquim Gomis

Patient safety

 System governance towards improved patient safety: Key functions, approaches and pathways to implementation

A working paper by the OECD highlights the role of system governance in patient safety.

Safety in health is often considered as a dimension of quality of care and part of the overall performance of the health system. Similarities follow in the way safety and quality are governed. The OECD collects information on key health system characteristics every four years. The 2016 Health System Characteristics Survey provide the latest update of how OECD countries implement governance functions aiming to strengthen quality of health care services (Table A 3). OECD countries develop legislation and national and institutional regulations that define and ensure quality of care. Accreditation, inspections and audits are often used in monitoring compliance with national quality standards. 

The Health System Characteristics Survey created the basis for the development of the 2019 Patient Safety Governance Survey. The OECD distributed the survey to a network of country experts on safety governance and policies in the summer of 2019. With a response rate of 25 OECD countries, a set of semi-structured interviews were undertaken in the late 20192, creating a broad and robust knowledgebase of countries’ safety governance models.

Antonio Perrone

Tackling COVID-19

 Informe final del Grupo de Trabajo Mixto Covid-19

FEDEA has coordinated a group of 130 experts that have analysed current situation and options for the pandemic. I have participated in the health group. 

Health document

Abridged document.