Risk-adjusted cost-effectiveness

 Health Technology Assessment With Diminishing Returns to Health: The Generalized Risk-Adjusted Cost-Effectiveness (GRACE) Approach

Cost-effectiveness analysis (CEA) embeds an assumption at odds with most economic analysis–that of constant returns to health in the creation of happiness (utility). We aim to reconcile it with the bulk of economic theory.

Therefore, 

 As health payers increasingly turn to CEA for value assessment, it becomes even more important to assure that it reflect the preferences of real people. Current models run an important risk by not considering the consequences of diminishing returns and risk aversion over health. Continuing to assume that the  incremental value of health is invariant to severity of illness endangers the foundations of CEA. The combination of the diminishing returns and severity of illness adjustments suggests that we are probably overvaluing treatments of low-severity illnesses (possibly by a factor of 2 or more) and undervaluing  treatments of very high-severity conditions (possibly by a factor of 5 or more).

This is solved by the GRACE framework that shows how to generalize traditional CEA models to incorporate the effects of diminishing returns to health improvements as severity of illness increases. This creates cost-effectiveness thresholds (stated as multipliers of consumption) that incorporate risk preferences both in consumption and in QoL and that increase with severity of illness.

 

Value based health care

 Building on value-based health care

A reminder:

Within the context of solidarity-based European health care systems and the mounting concerns about ensuring financial sustainability of universal health care, the European Commission Expert Panel on

Effective Ways in Investing in Health (EXPH) [3] proposed a comprehensive concept of value-based health care based on four pillars of value:

• achievement of best possible outcomes with available resources (technical value);

• equitable distribution of resources across all patient groups (allocative value);

• appropriate care to achieve each patient’s personal goals (personal value);

• contribution of health care to social participation and connectedness (societal value).

Examples of value-based health care initiatives identified by the EXPH that can contribute to more effective, accessible and resilient health care systems include: reallocation of resources through  disinvestment for reinvestment; addressing unwarranted variation, defined as variation in the utilization of health care services that cannot be explained; fighting corruption, fraud and misuse of public resources; increasing public value in biomedical and health research; regulatory policies aimed at improving access to high-value (but costly) medicines; incentives for fairer distribution; and more optimal use of resources.

A well known approach, opposite to creating value through market competition (Porter style). 

A value framework for diagnostic tests

 A Value Framework for the Assessment of Diagnostic Technologies: A Proposal Based on a Targeted Systematic Review and a Multistakeholder Deliberative Process in Latin America

Useful article, beyond the title, you'll find different value frameworks to apply to diagnostic tests and their proposal:

Table 4. Value framework proposed.

Essential/core
Criteria∗	Subcriteria∗
Clinical Benefit and Test Performance	Clinical consecuences of the use of the test
	Test performance
Safety and Unwanted consequences	Procedural safety
	Consequences of the wrong diagnosis
	Safety of test preparation
	Safety of test operators
Quality of scientific evidence
Economical aspects	Economic evaluation (clinical effectiveness and/or budget impact analysis)
	Other costs
Organizational aspects and feasibility within the clinical path	Impact on the health services provision system
	Impact on the path of patient care
High importance
Health priority of the health system
Disease burden
Equity	Neglected diseases test
	Test in communicable diseases and high prevalence
	Low access to health services
Ethical and legal aspect
Severity of the disease
Absence of alternative diagnostic technologies
Medium importance
Nonclinical benefits	Experience of who takes the test
	Value of the information
	Load on caregivers or family
	Preparation and/or care
	Number of results associated with the test
	Test processing time
	Self test
Environmental impact
Broader social impact
Low importance
Innovation

∗

See definitions of criteria and subcriteria in Appendix 3 (in Supplemental Materials found at https://doi.org/10.1016/j.jval.2020.11.008).

Distributional cost-effectiveness

 Distributional Cost-Effectiveness Analysis. Quantifying Health Equity Impacts and Trade-Offs

Distributional Cost-Effectiveness Analysis Comes of Age

Distributional cost-effectiveness analysis (DCEA) provides information about the equity impacts of health technologies and programs and the trade-offs that sometimes arise between equity and efficiency. This field has now come of age with a growing applied literature,1 new training resources,2 and a formal professional network: a special interest group on equity-informative economic evaluation within the International Health Economics Association

The outline of the book:

Part One: Preliminaries

1:Introduction, Richard Cookson, Susan Griffin, Ole F. Norheim, Anthony J. Culyer

2:Principles of health equity, Richard Cookson, Anthony Culyer, Ole F. Norheim

3:Designing a distributional cost-effectiveness analysis, Richard Cookson, Susan Griffin, Ole F. Norheim, Anthony J. Culyer

4:Describing equity impacts and trade-offs, Richard Cookson, Susan Griffin, Ole F. Norheim, Anthony J. Culyer

5:Introduction to the training exercises, Richard Cookson, James Love-Koh, Colin Angus, James Lomas

Part Two: Simulating Distributions

6:Health by disease categories, Kjell Arne Johansson, Matthew M. Coates, Jan-Magnus Økland, Aki Tsuchiya, Gene Bukhman, Ole F. Norheim, Øystein Haaland

7:Health by social variables, James Love-Koh and Andrew Mirelman

8:Costs and health effects, Colin Angus

9:Health opportunity costs, James Love-Koh

10:Financial protection, Andrew Mirelman and Richard Cookson

Part Three: Evaluating Distributions

11:Dominance analysis, Owen O'Donnell and Tom Van Ourti

12:Rank-dependent equity weights, Owen O'Donnell and Tom Van Ourti

13:Level-dependent equity weights, Ole F. Norheim, Miqdad Asaria, Kjell Arne Johansson, Trygve Ottersen and Aki Tsuchiya

14:Direct equity weights, Mike Paulden, James O'Mahony and Jeff Round

Part Four: Next Steps

15:Uncertainty about facts and heterogeneity of values, Susan Griffin

16:Future challenges, Richard Cookson, Alec Morton, Erik Schokkaert, Gabriela B. Gomez, Maria Merritt, Ole F. Norheim, Susan Griffin, and Anthony J. Culyer

The business of vaccines

 Covid-19 and the business of vaccines

The FT explains the business models behind vaccines and asks if the Covid-19 pandemic will fundamentally change the vaccine market. This short documentary features global experts including Bill Gates, the CEOs of Moderna and Gavi, and the lead scientist behind the Oxford/AstraZeneca vaccine

The low marginal benefit of ultra-expensive drugs

 Assessing the Added Therapeutic Benefit of Ultra-Expensive Drugs

In US:

The number of ultra-expensive drugs and Medicare beneficiaries taking these drugs has grown significantly, resulting in a very high concentration of Medicare Part D spending on ultraexpensive drugs. Between 73% and 85% of these drugs assessed in France, Canada, or Germany received a low added  therapeutic benefit rating. Policy reforms to address drug prices in the United States should consider developing an assessment framework for added therapeutic benefit to incentivize and reward the development of drugs that offer a significant clinical improvement over the current standard of care. In the interim, use of international assessments would be possible.

However, it may seem weird to our eyes, but:

 Medicare Part D in particular has a problem with ultra-expensive drugs, since it pays nearly 80% of the cost of these drugs, and by law Medicare cannot directly negotiate the price for these drugs with the drug companies

Public funding without the possibility to set the contract for low marginal benefit drugs! The result:

Medicare Part D spending on brand-name drugs for these ultra-expensive drugs increased from 1.5% in 2012 to 19% in 2018

The answer is change the law and set benefits package according to added value. 

Helen Clockburn collection MOMA

The long and bumpy road to CRISPR (3)

 CRISPR People. The Science and Ethics of Editing Humans

A book on the ethics of CRISPR, without a clear prescription, only a review of He horrendous experiment and a personal view of the current situation.

This has been a cautionary tale about scienceand scientists. People can overreach. He Jiankui, driven as far as I can tell by what Macbeth called “vaulting ambition, which o’erleaps itself,”1 and aided by a serious lack of scruples, behaved terribly. He put three lives at needless and reckless risk (and tried to do the same to more). The story is also a cautionary tale for Science. He Jiankui damaged Science by reinforcing the Victor Frankenstein image—the mad, uncontrolled scientist. Most scientists, and hence most science, are much more rule bound, constrained by the needs of getting and keeping jobs, tenure, and most importantly grants, as well as wrapped, in most countries, in many bureaucratic threads of control. But He happened, and Science needs both to act to minimize the harm he has caused and to be seen to be doing so.

A global consensus is a chimera. Seven and a half billion people are not going to agree on this issue—nor will the fraction of those who understand it. Neither will the roughly 200 countries of the world, at least at anything other than a lowest common denominator. Not all countries have agreed to various nuclear weapons or climate change treaties in spite of the apparently obvious need for them. If somehow something close to unanimity were achieved, it would probably be at the cost of precision. Thus, the Council of Europe enacted a convention that banned human cloning, but effectively left open the then-hot question whether it covered just reproductive cloning or “research cloning” (of human embryos for only ex vivo use) by not defining a “human being.” It also left the implantation and enforcement of such a ban up to the member nations, some of whom were probably happy, for political reasons, to sign it but will have little interest in enforcing it. 

And this is the controversial position of the author:

 One might argue that human germline genome changes are irreversible, or less reversible, than some other interventions. But is that true? A mistaken genome change could presumably be reedited, in a living person or in that person’s germline (or embryos), to reverse the error. Or it could be selected against in the individual’s offspring, through PGD or otherwise. It could be too late to avoid harm to the edited person, but that mistake will not have to pass on from generation to generation. Human germline genome editing does raise important questions about safety, coercion, equity, diversity, and  enhancement. These are not unique to editing the human germline genome. They also apply to somatic cell DNA editing, to new drugs, to smartphones, to climate change, and to many other changes from technologies. Questions about reversibility also apply; the social effects of cell phones are probably less reversible than genome edits. The fact that a technological change is in “the human germline genome” should have no special ethical weight.

Really? Security in CRISPR is not unique???

Changing the production function of diagnostic tests (2)

 The Cas proteins behind CRISPR diagnostics

CRISPR diagnostics explained in few words: 

There are many protein tools in the CRISPR toolbox. Each is suited to a particular suite of uses. For example, the common CRISPR protein Cas9 is well suited for genome editing. It is not suited for CRISPR diagnostics. In this blog post, we’ll introduce you to the proteins behind CRISPR diagnostics: Cas12, Cas13, and Cas14.

 CRISPR diagnostics have two key components:

• Protein-guide molecule complexes. These first cut specific nucleic acid sequences that the user wants to detect. After cutting a user-specified sequence, these complexes non-specifically cut other nucleic acids.
• Modified nucleic acids (reporters). These produce a visual signal when cut. They are only cut if the user-specified nucleic acids are cut first. These modified nucleic acids make it easy to observe when the user-specified nucleic acids have been detected (cut).

COVID epistemology

 Why Does the Pandemic Seem to Be Hitting Some Countries Harder Than Others?

And there lies an epidemiological mystery. The usual trend of death from infectious diseases—malaria, typhoid, diphtheria, H.I.V.—follows a dismal pattern. Lower-income countries are hardest hit, with high-income countries the least affected. But if you look at the pattern of covid-19 deaths reported per capita—deaths, not infections—Belgium, Italy, Spain, the United States, and the United Kingdom are among the worst off.

This is the unfixed conundrum explained by Siddhartha Mukherjee in The New Yorker, And no clear answer, you may read the whole article to confirm it.

 The covid-19 pandemic will teach us many lessons—about virological surveillance, immunology, vaccine development, and social policy, among other topics. One of the lessons concerns not just epidemiology but also epistemology: the theory of how we know what we know. Epidemiology isn’t physics. Human bodies are not Newtonian bodies. When it comes to a crisis that combines social and biological forces, we’ll do well to acknowledge the causal patchwork. What’s needed isn’t Ockham’s razor but Ockham’s quilt.

Above all, what’s needed is humility in the face of an intricately evolving body of evidence. The pandemic could well drift or shift into something that defies our best efforts to model and characterize it. 

 

Great documentary, on Knoedle gallery fake art

CRISPR: from lab to the clinic

 This is the year that CRISPR moves from lab to clinic

Jennifer Doudna says:

In 2021, researchers will use CRISPR to enhance our medical response to the Covid-19 pandemic. Teams will continue to collaborate and bring to market vital CRISPR-based diagnostic tools that are accurate, rapid and painless. One currently being developed and scaled by Mammoth Biosciences, a company I co-founded, along with partners at the University of California, San Francisco and the pharmaceutical company GSK, can detect and indicate the presence of SARS-CoV-2 RNA in a similar fashion to a pregnancy test.

 CRISPR will also have an important effect on the way we treat other diseases. In 2021, we will see increased use of CRISPR-Cas enzymes to underpin a new generation of cost-effective, individualised therapies. With CRISPR enzymes, we can cut DNA at precise locations, using specifically designed proteins, and insert or delete pieces of DNA to correct mutations.

This is precisely what is going on. 

 

COVID-19 innovation response

 The COVID-19 Innovation System

EIT Community COVID-19 Response

 The COVID-19 innovation system represents a departure from business as usual. Considering the remarkable progress to date, especially on vaccine development, this raises the question of whether this model is useful only for crisis times, or whether biomedical innovation policy in “normal” times might productively incorporate some elements of the COVID-19 model as well.

The largest funding response has been from the US government. Roughly $14–$15 billion of the $4 trillion allocated to the COVID-19 response was for R&D for vaccines and treatments.8,9 Though this increased US federally funded biomedical R&D by about one-third (compared to previous NIH funding; see “NIH Data” in the online appendix),10 it is small compared with the potential value of these interventions for ameliorating or preventing the disease and securing a return to normalcy

 

 

 

Profit over health

CODE BLUE.  Inside America’s Medical Industrial Complex

An interesting and persusive book by Mike Magee, an insider talking about details of how to create the worst health care system in developed countries and how to avoid it!. A clear message for European countries and current misguided policies. 

Ten Reasons Why Consolidating Oversight under a Single Centralized Authority Works So Well:

  1. It provides unimpeded universal access to coverage.

  2. It lowers administrative costs by at least 50 percent, and overall health care expenses by 15 percent, according to an extensive economic health policy research study published in BMC Health Services Research in 2014.15

  3. It is portable, allowing people to change jobs or geographic locations without worry.

  4. It can emphasize prevention by promoting health planning and budgeting priorities.

  5. It provides a standard basic benefit package for all, with flexibility for an individual to purchase additional services through private supplemental insurance.

   6. It offers a wider choice of doctors and hospitals, with coverage guaranteed, and limits “balanced billing” on essential services that are covered.

  7. It prohibits insurers from obstructing access to care with administrative obstacles to payment.

  8. By prioritizing care, the system increases wellness, therefore decreasing the cost of sickness.

  9. It forces transparent budgeting for outcomes, with a clear definition of goals and priorities, and promotes performance-based payments.

 10. It inserts public oversight of patient databases, preventing MIC use of data to maximize profits by steering patient choices and managing opaque MIC profit sharing

 

COVID-19 and the surge of populism

 Populism and the Politicization of the COVID-19 Crisis in Europe

Chapter 3. Spain: Is Ideology Back in Populist Discourse? by Jaume Magre, Lluís Medir, and Esther Pano

Risk stratification, objective and subjective

 Risk Stratification: A Two-Step Process for Identifying Your Sickest Patients

A proposal in two steps:

Step one involves sorting patients into one of three risk groups (high, medium, and low) based on objective data, which we take from claims or our electronic health record (EHR). We make our determinations based on the presence or absence of such factors as chronic conditions, advanced age, multiple comorbidities, physical limitations, substance abuse, a lack of health insurance, low health literacy, frequent hospitalizations or emergency department (ED) visits, recent major surgery or brain trauma, polypharmacy, or difficulty following a treatment plan. Some EHRs will calculate a risk score automatically based on this data. In either case, it is important to adjust the score based on additional, subjective considerations, which are the focus of step two.

In step two we assign each patient to one of six risk levels based on how physicians and staff answer the following questions:

• Is the patient healthy with no medical problems? If so, are his or her biometrics in or out of range?
• Does the patient have chronic conditions but he or she is doing well?
• Does the patient have chronic conditions that are out of control but without complications?
• Does the patient have complications of chronic disease or high-risk social determinants of health? (If you or your care team are unsure how to assess or address a patient's social determinants of health, the AAFP's EveryONE Project1 includes tools and resources.)
• Is the patient potentially in danger of dying or being institutionalized within the next year?

I missed any reference to morbidity and episode measurement. My impression is that objective measure is the first mandatory step through groupers, and risk stratification improves with subjective sources of information. And levels can be allocated through probabilistic fuzzy systems.