Public Health and behaviour change

Behavioral Epidemiology. Principles and Applications

It is quite surprising that a new book on Behavioral Epidemiology forgets Tversky and Kahneman, or Thaler. I couldn't find any reference to their works. After all these decades it seems that their works should be taken into account. Epidemiology and Public Health need to review its foundations, basically its rational decision making paradigm that has been their foundations.
I thought that this book could help, but finally I saw that only the first chapters are partially of interest. We'll have to wait.

Health in all policies narrative

Engagement of Sectors Other than Health in Integrated Health Governance, Policy, and Action

A good review on the topic is welcome. You'll find this article in Annual Reviews of Public Health. If health is created largely outside the health sector, engagement in health governance, policy, and intervention development and implementation by sectors other than health, is therefore important. I have reviewed this topic earlier, but I suggest a close look at it and its assumptions:

(a) Health is created largely outside the health care (or disease) sector; (b) the health care (or disease) sector, however, often carries social ownership of all health issues, even when they are beyond its control; (c) the health sector itself is a reproduction of (power) divisions in the public and private sectors and, while calling for integration, is itself fragmented; and (d) calls for broad social engagement with integrated research, policy, action, and governance for health may not align well with assumptions a–c.

The purpose of the article is to provide an evidence-based overview of how broad social engagement in health policy, action, and governance can be initiated, developed, and sustained.

 In Barcelona Caixaforum, right now.

Behavioral provider payment systems: the next step

Impact of Provider Incentives on Quality and Value of Health Care

Experimenting with incentives for quality is a risky task. The variable requires a precise measure and it must indicate the appropriate signal to the provider to have impact in decisions and behaviour. Usually, rational behaviour is assumed int the models. A recent review highlights this is issue:

Advocates of pay-for-performance in health care maintain that its early failures are the result of inadequate design, a failure to incorporate a more sophisticated understanding of provider motivation into program design (26). On the basis of evidence from early schemes and readings of economic and psychological theory, several researchers have produced blueprints for secondgeneration pay-for-performance frameworks. Their recommendations for designers include making rewards large enough to be meaningful; using penalties in addition to rewards; aligning incentives to professional priorities; using absolute rather than relative performance targets; providing frequent, discrete rewards or punishments; and making an explicit long-term commitment to incentives

But the authors admit that: " Some of these solutions are difficult to implement, are contradictory, or introduce further unintended consequences". And this paves the way to a pessimist view:

Programs are slowly becoming more sophisticated, but unless clear evidence for cost-effectiveness emerges soon, the incentive experiment may have to be abandoned. Many commentators see this abandonment as inevitable, believing incentive programs to be fundamentally flawed. Some concerns are technical in nature and relate to the difficulty of accurately defining and measuring the most important aspects of quality with the greatest impacts on patient outcomes

My impression is that the unit of analysis is usually wrong. Until we are not able to measure patient focused episodes of care properly, in a holistic way, will miss something. This should be the first concern. Of course, this is an overwhelming task, not an easy one.

Camille Pissarro in Sant Feliu de Guixols right now

Understanding The Value Of Innovations In Medicine

Video of the yesterday Health Affairs conference in Washington
Agenda and slides
Health Affairs site

Quite surprising the initial definition of value, quality over price?. It is not a ratio, it is the economic surplus, the worth created, one part for the producer and another for the consumer. But in healthcare the consumer is at the same time producer of surplus. This is unique. Maybe someday we should talk about how to split the value according to its contribution, and not only on value based payment.

How global health stands?

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The Global Burden of Disease (GBD) report shows in an aggregated way how is the world population health. It tries to give an index, and the summary would be:

The median health-related SDG index was 56·7 (IQR 31·9–66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6–88·9), Iceland (86·0, 84·1–87·6), and Sweden (85·6, 81·8–87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6–11·9), the Central African Republic (11·0, 8·8–13·8), and Somalia (11·3, 9·5–13·1) recording the lowest.

Sustainable Development Goals (SDG) were set by UN   and there are specific indicators for health. However the study takes into account 37 of the 50 indicators. I have explained before some technicalities about the use of DALYs for such studies. And you may know that I am concerned about its use. Today I would add a new concern, it is the projection to 2030 for all these indicators. In my opinions it is a useless effort. Nobody knows, nad using the past to project the future, it is exactly a guarantee of a mistake. However, The Lancet will publish your article.
Let's have alook at the expenditure side:

By comparing performance on the health-related SDG index in 2016 with total health expenditure and DAH (Development Assistace for Health) per capita received from 2010 to 2014,insights might be gleaned regarding the association between overall health funding and performance on the health-related SDG index and whether DAH is being directed toward those countries with the greatest need. Generally, total health expenditure is positively correlated with performance on the health-related SDG index; however, considerable variation exists at the same level of expenditure. For example, among countries with a health-related SDG index of 30 to 70, the association between total health expenditure per capita and performance varied massively, spanning at least a 7 times difference in spending with similar levels of performance on the health-related SDG index.

That's a lot of variation, it would require a closer look. And a clear prescription:

For countries that received DAH between 2010–14, some of the most pronounced differences in cumulative DAH per capita received in the 2016 index were in sub-Saharan Africa, with several countries in southern sub-Saharan Africa posting nearly 3 times more cumulative DAH per capita than a number of countries in central and western sub-Saharan Africa. Most notably, some of the poorest performers on the health-related SDG index, such as the Central African Republic, South Sudan, Somalia, and Niger, received relatively little DAH.

All in all, GBD is what we have, it has limitations but it allows to understand the situation. It is unnecessary to project the future, in my opinion. We have to work for the improvement of current population health.

PS. By the way, there is a ranking. You'll see that Spain has fallen from 7th to 23rd. Forget it. It is still worse but useless. The health variations inside Spain are so huge that the unit of analysis is wrong.

Olga Sacharoff

The long and bumpy road to CRISPR

A Crack in Creation:The New Power to Control Evolution

I've read the same book than Diane Coyle this summer. If you want a clear understanding of what's going on in genomic editing, it should be your first choice. A crack in creation is a description and analysis by Jeniffer Doudna the main researcher on the topic. For those that are excited by genome editingit is good to read this statement:

It’s easy to get caught up in the excitement. The fact that gene editing might be able to reverse the course of a disease—permanently—by targeting its underlying genetic cause is thrilling enough. But even more so is the fact that CRISPR can be retooled to target new sequences of DNA and, hence, new diseases. Given CRISPR’s tremendous potential, I’ve grown accustomed over the past several years to being approached by established pharmaceutical companies asking for my help in learning about the CRISPR technology and about how it might be deployed in the quest for new therapeutics.
But therapeutic gene editing is still in its infancy—indeed, clinical trials have only just begun—and there are still big questions about how things will progress from here. The decades-long struggle to make good on the promise of gene therapy should serve as a reminder that medical advances are almost always more complicated than they might seem. For CRISPR, too, the road leading from the lab to the clinic will be long and bumpy.
Deciding what types of cells to target is one of the many dilemmas confronting researchers—should they edit somatic cells (from the Greek soma, for “body”) or germ cells (from the Latin germen, for “bud” or “sprout”)? The distinction between these two classes of cells cuts to the heart of one of the most heated and vital debates in the world of medicine today.
Germ cells are any cells whose genome can be inherited by subsequent generations, and thus they make up the germline of the organism—the stream of genetic material that is passed from one generation to the next. While eggs and sperm are the most obvious germ cells in humans, the germline also encompasses the progenitors of these mature sex cells as well as stem cells from the very early stages of the developing human embryo.
Somatic cells are virtually all the other cells in an organism: heart, muscle, brain, skin, liver—any cell whose DNA cannot be transmitted to offspring.

Therefore, caution is required and ethical implications are huge as I've said before.
Highly recommended.

The priceless conundrum in healthcare

Pricing the Priceless: A Health Care Conundrum

Allocating resources in health care is a pivotal taks and three tools are used to solve it: market, government and professionalism. Briefly, in the market, prices paid would try to reflect information needed to take a decision for the supply side and demand side (hypotetically). Government allocates resources according to information of a benevolent ruler (biased and incomplete information). Professionals decide over the need of care according to "rules and guidelines" and specific patient situation (hypotetically).
As you may imagine, all these three approaches are used everyday in every health system in the world, and unfortunately they are imperfect, basically due to asymetric and incomplete information on one side, and incentives on the other.
Joseph Newhouse wrote a book fifteen years ago, that summarized many of these conundrums. The first is that we don't find prices, we find "administered prices" in health care, those set by insurers (private and public), and:

Setting administered prices is inevitably fraught with error, and because of lags in adapting to technological change, the extent of the error increases as pricing systems age.

This is reason why today we use the term payment systems instead of pricing. Payment systems try to combine different dimensions beyond price, sometimes volume, sometimes quality. Basically they want to correct the error of administered prices.
Unfortunately, the book finishes with a worrying  statement:

This is the conundrum of medical pricing; all arrangements that can be implemented have important drawbacks. Although variation in ideology plays a role in the payment methods that different countries use, the wide variation in institutional arrangements around the world as well as the ongoing efforts at attempting to reform and improve those arrangements in almost every country are consistent with that conundrum.

My impression differs a little bit, it is not and ideological issue. Payment methods differ because risk transfer may be possible or not. In a public system, finally the State assumes all the risk. In a private system, providers  market power may reduce the opportunities to transfer such risk.  Professionals in a public and private system don't assume financial risk, they decide but it is finally transferred to insurers and providers. Nowdays, the issue is still open for debate.

Pasimonious medicine

PRÁCTICAS CLÍNICAS EVITABLES: EL COSTE DEL DESPILFARRO

Tilburg and Cassel wrote in JAMA

Parsimonious medicine is not rationing; it means delivering appropriate health care that fits the needs and circumstances of patients and that actively avoids wasteful care—care that does not benefit patients

And Austin Frakt answered in his blog:

Perhaps the consequences of what they support with good intention will include rationing. Perhaps it’s hard to achieve parsimony with out at least a touch of it. If that’s the case, how much rationing will we tolerate to achieve some additional efficiency? Keep in mind, today we have a high level of rationing by ability to pay and a low level of parsimony. (in USA)

Unfortunately we don't now the level of parsimony in our health system. But if you want to know the size of the waste  in spanish health system, these are some figures for primary care:

El estudio APEAS cifraba en 10,1 por 1000 visitas los eventos adversos en atención primaria de los que un 7,3% graves y un 70,2% evitables (40), mientras que el ENEAS los cifraba en 9,3% por cada 100 hospitalizados, con un 16% graves y 42,8% evitables (41). Mientras que ambos estudios tendían a minimizar el impacto de estas cifras, los 300 millones de visitas no urgentes anuales en atención primaria resultarían en 3 millones de efectos adversos anuales, de los que casi 300.000 graves y al menos 2 millones evitables. En el caso de la hospitalización, los 5,2 millones de hospitalizaciones del año en que se realizó el ENEAS ofrecerían cifras de 450.000 efectos adversos anuales, de los que 90.000 serían graves y unos 200.000 evitables. Estas cifras situarían los eventos adversos derivados de la atención sanitaria como la probable tercera causa de morbi-mortalidad en nuestro país, tras las enfermedades cardiovasculares y el cáncer.

And regarding hospitalizations,

Diversos estudios publicados en la década del 2000 cifran en torno al 10-15% la cuota de este tipo de ingresos hospitalarios sobre el total de hospitalizaciones producidas en España en los años estudiados (42-46). Este porcentaje sería aún mayor para los ingresos por hospitalizaciones evitables en enfermedades crónicas estudiados más recientemente por el grupo Atlas de Variaciones en la Práctica Médica

And the figures for inappropriateness and low value care are more diffiuclt to estimate, though:

En España se han realizado numerosos estudios sobre utilización inapropiada de la hospitalización con cifras que sitúan este problema alrededor del 10% de las admisiones y el 30% del total de estancias hospitalarias

And only one example regarding pharmaceuticals

Añadir lapatinib a capecitabina en el tratamiento en segunda línea del cáncer de mama permite ganar, en promedio, 0,3 meses (10 días) de supervivencia con respecto al tratamiento previo con solo capecitabina, con un coste adicional de 18.298 € (60.996 € por mes de vida adicional) (59). Estas cifras implicarían que socialmente estamos dispuestos a pagar unos 732.000 euros por cada año de vida adicional ganado y, si se tiene en cuenta la baja calidad de vida de estos días ganados en la fase final de los procesos oncológicos, probablemente estaríamos hablando de cifras superiores a los 2 millones de euros por año de vida ajustado por calidad (AVAC o QALY) ganado con la incorporación de este tratamiento a este precio a la cartera de servicios.

If we as a society, we are not able to solve the rationing puzzle, then we could start by a more parsimonious medicine. You'll find more details in the chapter by S. Peiró in this book (p.273).
After reading this chapter, you'll be more concerned than before.

Garry Winogrand

Responsible corporate governance

A Skeptical View of Financialized Corporate Governance

Corporate governance practices need to improve, though the approach to fix it is still a work in progress. The last recession gave us multiple examples of irresponsible corporate governance, but few actions have been taken to reverse the trend. A recent article shows how this misallocation of risk and resources should be addressed:

Effective governance requires that those in control are accountable for actions they take. However, those who control and benefit most from corporations' success are often able to avoid accountability. The history of corporate governance includes a parade of scandals and crises that have caused significant harm. After each, most key individuals tend to minimize their own culpability. Common claims from executives, boards of directors, auditors, rating agencies, politicians, and regulators include "we just didn't know," "we couldn't have predicted," or "it was just a few bad apples." Economists, as well, may react to corporate scandals and crises with their own version of "we just didn't know," as their models had ruled out certain possibilities. Effective governance of institutions in the private and public sectors should make it much more difficult for individuals in these institutions to get away with claiming that harm was out of their control when in reality they had encouraged or enabled harmful misconduct, and ought to have taken action to prevent it.

 Public and private organizations are affected and these are the author's "skeptical" suggestions:

The key to improving corporate governance is to increase transparency, create better internal and external control and accountability, and address distortions and inefficiencies through effective laws and regulations.

Society should demand such change, though laws in regulations are not enough. As Foucault reminds us from roman culture, infamia is a crucial measure. Nowadays,  power and money through the media are able to stop infamia too often.

Bjork digital now in Barcelona

Health care priorities in practice

Implementation of the 2013 amended Patients’ Rights Act in
Norway: Clinical priority guidelines and access to specialised
health care

Norway decided to update their system to set health care priorities. In 2013, the Patient Rights Act was amended to simplify the priority setting process for specialized elective health care and to improve access to care. And now, this is what they have:

Priority for treatment is now determined by only two criteria: 1) clinical effectiveness; and 2) cost-effectiveness of the intervention. There are 33 clinical priority setting guidelines organised by medical specialty, which help hospitals evaluate whether individual patients have a right to access care.
The revised guidelines define and score a total of 556 condition-intervention pairs, and will give all patients who are evaluated as having a need for specialist elective healthcare the right to access these services

Health policy must define priorities, it is not only a professional issue. Unfortunately by now, in our country are quite far from Norway, geographically and politically.

People on the waiting list? In Catalonia there are 736.000 citizens (10% of population) waiting for an appointment, test or hospitalization. SOMEBODY SHOULD SOMETHING

Weegee by Weegee in Barcelona

A quantum leap in biomedicine

Correction of a pathogenic gene mutation in human embryos

Today you should have a look at Nature. The reason is genome editing of human embryos. Although a chinese team performed something similar in 2015, right now the details are clearly explained. The trial has been developed to fix a mutation that causes hypertrophic cardiomyopathy.If you don't want to read the whole article, check the news. Genome editing is gaining momentum as I said some months ago, it is closer than you may think.


PS. Why FBI is concerned about CRISPR? The answer in FT Big Read
PS. The news in FT.
PS. A useful article from Nature 2015:

Genome editing: 7 facts about a revolutionary technology

What everyone should know about cut-and-paste genetics.

• Lucy Odling-Smee,
• Heidi Ledford
• & Sara Reardon

30 November 2015

Article toolsediting is in the spotlight again as a large international meeting on the topic is poised to kick off in Washington DC. Ahead of the summit, which is being jointly organized by the US National Academy of Sciences, the US National Academy of Medicine, the Chinese Academy of Sciences and Britain’s Royal Society and held on 1–3 December, we bring you seven key genome-editing facts.

Yorgos Nikas/Science Photo Library

Human embryos are at the centre of a debate over the ethics of genome editing.

1. Just one published study describes genome editing of human germ cells.

In April, a group led by Junjiu Huang at Sun Yat-sen University in Guangzhou, China, described their use of the popular CRISPR–Cas9 technology to edit the genomes of human embryos. Only weeks before the researchers’ paper appeared in Protein & Cell¹, rumours about the work had prompted fresh debate over the ethics of tinkering with the genomes of human eggs, sperm or embryos, known collectively as germ cells. Huang and colleagues used non-viable embryos, which could not result in a live birth. But in principle, edits to germ cells could be passed to future generations.

2. The law on editing human germ cells varies wildly across the world.

Germany strictly limits experimentation on human embryos, and violations can be a criminal offence. By contrast, in China, Japan, Ireland and India, only unenforceable guidelines restrict genome editing in human embryos. Many researchers long for international guidelines, and some hope that the upcoming summit in Washington DC could be the start of the process to create them.

Ramon Andrade 3Dciencia

The CRISPR-Cas9 system makes editing genomes cheap and easy.

3. You don’t have to be a pro to hack genomes.

The CRISPR–Cas9 technology has made modifying DNA so cheap and easy that amateur biologists working in converted garages or community laboratories are starting to dabble.

4. Cas9 is not the only enzyme in town.

A key ingredient in the CRISPR–Cas9 system is the DNA-cutting enzyme Cas9. But in September, synthetic biologist Feng Zhang at the Broad Institute of MIT and Harvard in Cambridge, Massachusetts, reported the discovery of a protein called Cpf1, which may make it even easier to edit genomes².  (Zhang is one of those who pioneered the use of CRISPR-Cas9 for genome editing in mammalian cells).

BGI

A gene-edited micropig created by the BGI in Shenzen, China. 

5. Pigs are on the front line of genome-editing experiments.

Dogs, goats and monkeys are all part of the growing CRISPR zoo. But pigs in particular have been at the heart of several eye-catching announcements — from micropigs that weigh about six times less than many farm pigs, to super-muscly pigs, to a pig whose genome has been edited in 62 places (the aim being to produce a suitable non-human organ donor).

6. Gates, Google and DuPont want a piece of the genome-editing action.

In August, several high-profile investors, including the Bill & Melinda Gates Foundation and Google Ventures, pumped US$120 million into the genome-editing firm Editas Medicine of Cambridge, Massachusetts. Big Agriculture is following suit: DuPont forged an alliance with the genome-editing firm Caribou Biosciences of Berkeley, California, in October, and announced its intention to use CRISPR–Cas9 technology to engineer crops.

Eloy Alonso/Reuters/Corbis

Microbiologists Emmanuelle Charpentier and Jennifer Doudna.

7. The CRISPR–Cas9 system is at the centre of a patent row.

Zhang was granted a US patent on CRISPR–Cas9 in April 2014. But several months before he filed his application in 2012, molecular biologists Jennifer Doudna at the University of California (UC), Berkeley, and Emmanuelle Charpentier, now at the Max Planck Institute for Infection Biology in Berlin, had filed their own patent. UC Berkeley has since requested that the United States Patent and Trademark Office determine who should get credit for harnessing the CRISPR–Cas9 system, in particular for its application in human cells. And a similar debate is playing out in Europe, where oppositions to a patent that Zhang and his colleagues won in February have been filed. All three scientists co-founded companies that make use of CRISPR–Cas9.

Measuring quality of episodes of care

Episode-Based Approaches to Measuring Health Care Quality

I have always thought that all the efforts to link payment to performance need to define first what is the unit of analysis. In my opinion, episode is the crucial one. Unfortunately there are very few settings that are measuring episodes. If performance and value is not linked to the episode, then forget about the impact, it may be anything.
A new article emphasizes the need for episodes in measuring quality, and provides a useful framework:

Episode-based measures could assess changes in health outcomes (“delta measures”), the amount of time during an episode in which a patient has suboptimal health status (“integral measures”), quality contingent upon events occurring previously (“contingent measures”), and composites of measures throughout the episode.

After reading this article somebody should do something (...) on current and available measures of quality.

Parov Stelar new album

Beyond health gain:the value of knowing in precision medicine

Value assessment in precision cancer medicine

Towse and Garrison provide a clear picture of the economics of using drugs with companion diagnostics (precision medicine) in the Journal of Cancer Policy. Three main issues arise:

A. Reducing or avoiding the adverse effects associated with treatment (including the medical and nonmedical costs of man-aging them).
B. Reducing or avoiding time delays in selecting the most appropriate intervention
C. Enabling a treatment effective only in a small fraction of the population to be made available or more widely available.

But there are also psychological gains (difficult to estimate) related to the value of knowing:

1. Reduction in uncertainty reflecting the idea that a companion diagnostic, by increasing the certainty of a patient’s response to a medicine—would be more valuable to individual patients and hence they (or their payer) would be willing to pay more for the combination. Furthermore, as noted above, at the population level, greater certainty could lead to greater uptake and improved compliance.
2. The value of hope is the notion that in some circumstancesindividuals become risk-seekers in the sense that they would be willing to pay more for access to a technology with a long tail indicating that some patients have a much longer survival time than current therapy, even though the average life expectancy may be no greater, or even less, than standard therapy.
3. Real option value for which the best example is that if  a treatment can extend life, this opens up possibilities for individ-uals to benefit from future advances in medicine. Hence, they(or their payer) should be willing to pay more than simply theamount they would pay for a gain in life expectancy alone, ascalculated under conventional methods, because it provides the option of benefiting from further treatments.
4. Insurance value is related to the idea that insurance tocover innovations provides peace of mind, not just by protectingagainst catastrophic financial loss but also by protecting fromcatastrophic health loss. The focus is usually only on financial protection, in the form on an Extended Cost-effectiveness Analysis. Lakdawalla et al. point out that greater value comesfrom the reassurance value of knowing of the existence of a treatment, or even of incentives to develop such a treatment.
5. Scientific spillovers arise because the benefit of scientificadvances cannot be entirely appropriated by those making them. Improving knowledge creates opportunities for additional innovation by others. For example, proving that a particular agentworks on a hypothesized pathway in a particular cancer means that the general understanding of that cancer is enhanced and thus further research can explore other pathways in the same cancer. This creates a commons problem with potential underinvestment, implying that patients may wish to reward developerswith higher prices to encourage knowledge generation.

The authors back value based pricing for drugs and companion diagnostics, just at the same time that The New York Times casts some shadows over this option.

Cantut - El Pomeró

Precision medicine: a deep breakthrough in life sciences paradigm

Bioscience - Lost in Translation? How precision medicine closes the innovation gap

It is not so easy to translate knowledge into practice, and this is the case of biosciences into clinical applications. However, recently this trend is accelerating and precision medicine is emerging. A new book gives us the highlights to understand precisely what's going on: Bioscience - Lost in Translation? How precision medicine closes the innovation gap.

Richard Barker (the author of 2030 - The future of medicine) says:

The classic definition of diseases has been in terms of the symptoms they cause and/ or where in the body they appear. This was the best that medicine could do when external observation of the patient was the only or primary means of diagnosing disease. The  powerful new tools of molecular biology are reinterpreting disease in terms of aberrant,
defective, or unbalanced molecular mechanisms at the cellular, organ, or organism level. Molecular level diagnosis becomes a real possibility. Such an approach brings effective therapy immediately closer. Molecular diagnostics can separate diseases with similar symptoms but different underlying causes— and often suggest a different starting point for intervention.

If this is so, what should we do?

The seven changes of mindset and of practice are:
1. Advance the molecular definition of disease and the application of systems biology. We need a more decisive move from a classic definition of diseases— in terms of the symptoms they cause and/ or where in the body they appear— to a definition in terms of aberrant, defective, or unbalanced molecular mechanisms at the cellular level. And we need to marry this with a recognition that singular target- based innovation rarely works: we need a systems biology approach.

2. Partner academia and industry in more collaborative, impact- oriented research. We need to extend the ‘open innovation’ approach in which academia and companies invest together and share IP. We need to define new pre- or non- competitive spaces, especially in work on disease mechanisms and disease models. And we need to provide for new types of links and incentives to break down the barriers between these two worlds. 

3. Move decisively to a more adaptive approach to development, trial and approval design. We need to build on successful experiments in more flexible trial design, development pathways, and regulatory appraisal to a globally accepted adaptive approach. This involves collaborative design of the evidence package needed to secure approval and reimbursement, and greater teamwork through the process. 

4. Create new reward and financing vehicles for leading edge innovation. We need to move from reward systems based purely on unit sales of products, irrespective of outcome, to rewarding innovators for positive outcomes, patient by patient. We also need to design financing mechanisms that bridge between cost- effectiveness and affordability. We must be able to accommodate high- cost precision therapies that offer cures and so generate long- term returns for the system.

5. Engineer tools and systems for faster and better innovation adoption and adherence. We need to move from reliance solely on promotion to doctors and passive patient participation to a disciplined approach to establishing new pathways of care. These will be based on modern behavioural science, clinical decision support, and other digital technologies.

6. Develop an infrastructure for real- world data- driven learning. We now have the opportunity to study in large populations how lifestyle and treatment choices lead
to outcomes, learning from every patient as if in a clinical trial. New analytical tools will empower this.

7. Bring patients into the mainstream of decision- making and engage them  hole heartedly throughout the process. It is time to move from a process and mindset in which patients are regarded as passive subjects for clinical trials and recipients of products and procedures. Their input and engagement needs to be sought along the whole innovation chain: on treatment benefits, acceptable risks, optimal clinical trial design, adherence support, and outcomes.

Highly recommended.