Tag Archives: market access

The politics of market access

Market access is wrapped in the politics of health

The attention politicians and stakeholders pay to healthcare and its challenges is a keen driver of the ease or difficulty companies experience with drug regulation and market access and has implications through the development process to discovery. How this manifests itself, in part depends on a country’s investment in research infrastructure, availability of scientific talent, as well as the competency and experience of experts in the various regulators, whether HTA or pricing.

One thing that focuses political minds is a crisis in the healthcare system, whether a cluster of unexplained deaths, systematic abuse of payment systems, medical corruption, poor hospital management, declining outcomes, drug shortages, golly, the list goes on. What drives reform, well as Harold Macmillan is reported to have said, “events, dear boy, events”.

Can market access be sensibly undertaken without consideration of political forces? Those who see market access as simply planning will no doubt be surprised when their plans are overtaken by events.

Politics is the exercise of power

Like bankers who need to know their customers, market access specialists need to have deep knowledge of regulators, and the very functioning of government.

In many countries, payers and governments exert monopsony power; they are often the only game in town when it comes to purchasing anything healthcare, whether doctors, hospitals or medicines. And regulators are monopoly suppliers of regulation, whether pricing, reimbursement decisions or HTA. Together, whether in a coordinated way or not, they set the tone for how market access will actually work, quite independently of the actual demand on the clinical ground for a new medicine or therapy.

Sense-making of political forces is a core competency for market access

Public bodies do not exist in a vacuum, but are determined by how political concepts are implemented by governments. In the main, if you are into archetyping, there are broadly three views of how government decides how a healthcare system will work:

1. some things are properly done by non-publicly owned agents because they have proved competent (pharmacies); but this does not mean they are unregulated;

2. some things are a mix of public (hospitals in some cases) and private entities (doctors and general practitioners);

3. some things are generally accepted to be public responsibilities (public health).

Over time, of course, events dictate how governments interpret these three broad roles, and they will move things from one area to another as a function of reform or policy.

What we are seeing right now is the emergence of new ways for governments to regulate through the availability of big data and data analytics. These show up in indicators of hospital performance for instance, or activity based funding. The ability to measure these accurately is necessary.

With even greater power from the data analytics, e.g. machine learning, we can anticipate greater use of predictive modelling of features of healthcare systems. Two examples stand out for me.

The first is pharmacovigilance. A ‘smart (in artificial intelligence sense) regulator’ could directly monitor for adverse drug reactions; this would alter how regulatory action occurs and impact the speed of decision making on safety.

The second is drug pricing. ‘Smart drug pricing’ would enable reimbursement regulators (pricing authorities) to build predictive analytical pricing models of new medicines performance in clinical use to more precisely model value pricing. This would obviously alter the pricing dynamic.

Other factors come and go in terms of acceptability by governments, most notably the role of contestable markets themselves in healthcare. Some, such as Alain Enthoven, believed that competition in managed markets could be a driver of service quality, improve responsiveness to patients, for instance. The purchaser/provider split, so-called, is one approach to apply what I have called a ‘game theory’ approach to setting service standards and quality. Actually, there are two ways to characterise quality in healthcare. One is through (rigid) specification of standards (the Crosby model) and the other is through continuous quality improvement [CQI] (the Deming model); there are others such as 6-sigma, Lean/Toyota, etc., but they are in my view just variants of these two main ways of understanding quality.

A lower tolerance for risk will lend itself to rigid standard setting with a corresponding impact on how new medicines are viewed, e.g. greater need for evidence prior to adoption, versus a higher tolerance for risk through CQI with e.g. conditional approval.

Risk and salience are key factors in politics and hence in market access

Politicians respond to events that are widely salient, while civil servants are tasked with dealing with ‘technocratic’ or procedural matters. Counterfeit medicines, something I’ve worked on, can be either a risk that can kill people, or a factor in intellectual property and copyright. The former is politics, the latter is technocratic. Focusing on the second means dealing with settled matters and the interpretation of rules and regulations. A health crisis, for instance, lifts the event to wider salience amongst the public and in so doing can constrain the freedom of politicians to act or not, indeed, whether they can ignore the issue or delegate it to civil servants. A crisis also creates a window of opportunity though which new ideas and changes can flow – as they say, you shouldn’t waste a good crisis.

Another source of political change comes from rights-based challenges to health policy. While often seen as only of relevance within legal rule sets, (i.e. technocratic), they are about citizens’ or patients’ rights and access to treatment and therefore have high public salience. In the US, right now, there is a major political issue around the ‘deferred action’ programme which funds care for immigrants. Hitherto a technocratic issue, it is now widely salient (people in general are learning about it) and politicians (a.k.a. lawmakers) actions are now constrained, perhaps tellingly by moral factors. Other noteworthy historical examples are the Chaoulli case in Quebec and the various cases decided by the European Court of Justice on portability of healthcare benefits in the EU.

Politics and policy options determine how costs and benefits are distributed

Underlying political positioning is how policy implementation distributes the costs of a policy and the benefits of a policy (whether in time, money or resources). This type of analysis, from the work of the political scientists James Q Wilson, is revealing as it lays bear these underlying assumptions and the real world impact of a policy and its implementation. Examples where this approach is useful includes analysing drug rationing (approvals, defining treatment cohorts), price controls, reimbursement (or not) of branded generics, health technology assessments, and more generally the logic of market access. What we learn is where the costs sit and where the benefits sit, and importantly, who pays and who benefits. Such an analysis is profoundly revealing for identifying, for example free-riders, and the NIMBYs, two groups where there are often strong socio-political beliefs arising from political ideology transferred into policy.

Approaching market access purely as a technocratic exercise will under-power the associated solutions for market access initiatives. There is a good reason to know how and in what way the benefits of a new medicine are distributed (to whom and how), and what those costs are, whether measured in money, time, risk or opportunity. These considerations, drawn from the ability to apply relevant political analysis and insight, adds explanatory power and relevance, for instance, market entry strategies, or identifying gaps in evidence.

Real world data and evidence in healthcare: The market access challenge

We are in a new world when it comes to access to and the use of data and evidence. Real world data and evidence takes us from structured studies to the routine delivery of healthcare, actual use of a medicine, and the patient’s actual health status.

What is knowing this worth and to whom?

Real world data is best understood in the context of decision making, or choices and how they are made and the consequences that flow from these decisions. To illustrate:

  1. Patients get the wrong treatment, i.e. they are misdiagnosed. This is a particular issue for patients with rare diseases which experience not just being treated for the wrong condition (i.e. they are in the wrong treatment pathway).
  2. Clinical reasoning may be flawed. The main issue here is medical misdiagnosis, and clinical reasoning itself (backward/forward driven reasoning), and the rules for diagnosis, guidelines, the order items are listed in the differential diagnosis, and behavioural heuristics that impact clinical reasoning. Medical errors are more associated with backward-driven reasoning, using the hypothetico-deductive method; while forward-driven begins with data, with fewer errors. Other reasoning concerns include: doctors are reluctant to make a rare disease diagnosis, called the zebra retreat; inappropriate referral and diagnosing a mimic and sending the patient off to the wrong specialist, not listening to the parents of ill children, and so on.
  3. The treatment is the problem. Even if the treatment is diagnostically correct, the success or failure of that treatment often depends on whether the patient is adherent. It also depends on whether there are adverse drug events which alter patient acceptance of the medicine. Some patients may be non-respondent to the treatment, too.

What does that mean?

Enabling much of this is the use of computational methods, and machine learning, which uses real world data to enable precision medicine, case finding, precision cohort identification and treatable populations.

Regulators currently rely on industry reporting for adverse drug event reporting. RWD could enable regulators to directly monitor the market in real time and identify AD events. This would alter the pharmacovigilance system. In addition, they could gather data on off-label use (for and against) to assess the validity of treatment claims.

RWE may speed regulatory approval as the studies are tightly focused, don’t make expansive product claims and benefits are easier to demonstrate, thereby reducing regulatory risk.

Reimbursement regulators, providers and payers benefit from the potential to improve the quality of care as delivered to patients. This is enhanced by the development of more sophisticated decision support tools built on e.g. computational approaches or embedded in electronic record systems. This includes, for example, ‘red flagging’ tools to improve differential diagnosis, identify mimics, and trigger appropriate clinical suspicion as well as ‘referral filters’ to address inappropriate referrals, and so on. All these improve the value for money equation, and importantly reduce treatment risk, which drives avoidable costs out of the system.

Pharmaceutical companies can use this type of data to inform their drug portfolio development process. This would bring some order to research and development to improve internal priority setting and assessment of research targets in particular to avoid research bias (the impact of behavioural heuristics in R&D decision making for instance). The impact on trials cannot be ignored, use of synthetic control arms, improve precision of trial cohorts to remove the 80% or more of individuals who are not selected for a trial and perhaps save 60% or more of trial costs, and predict trial outcomes.

The evidence base for dossier submissions can be evidence informed with respect to the size of the treatable population, and patient response to treatment, reducing payer risk which manifests itself in refusing to reimburse.

The table suggests just a few changes from current market access to data-driven RWE market access.

Needless to say, this alters the underlying assumptions of pharmacoeconomics, medicines pricing and positioning.

I’ve summarised just a few points in the table below, to distinguish between what today could be called “Push market access”, a sales driven approach to placement, to a “RWD/RWD market access” with reduced risk and improved opportunities for demonstrating product value.

Stakeholder push’ Market Access RWD/RWE Market Access



Patient Risk of non-beneficial treatment Precise patient treatment cohorts

Risk of mis-/missed diagnosis, medical error Precision diagnosis with decision support tools



Clinician Uncertainty of benefits of treatment and the ‘halo’ of uncertainty inherent in clinical decision making Precision patient identification releases benefits through treatment targetting



Payers Pay for uncertain benefits Pay only for responders

Pay for treatment to non-responders Precision medicine to demarcate treatable population

Pay for non-adherent treatments Pay only for adherence, and risk reduction of non-adherence

Risk averse for uncertain treatable populations Risk managed for an evidence treatable population



Pharma industry Weak evidence for size of treatable population, with a “price per pill” Precision patient cohorts defines treatable population with cohort pricing

Missing Phase 4 evidence Good quality Phase 4 evidence

Risk of non-adherence, and non-responders Reduce risk through precision case finding

Missed patients Find the true treatable population

Drives costs into the healthcare system Removes costs from the healthcare system

Smart anti-counterfeiting: it is all in the system’s design

How can I be sure the medicine I take is genuine?

Counterfeit medicines are a global problem, with trade in the billions of dollars. The World Health Organization estimates 8-10% of all drugs supplied globally are counterfeit.
Counterfeits are a clear and present danger to human health. No country is immune from the risk. Fake medicines are hazardous, with documented toxicity, instability and ineffectiveness but few people are experts in pill authentication (even pharmacists get fooled). Counterfeit drugs are easier to make and fake than money. But there is little patients can do but rely on assurances by others that drugs are genuine. That may not be good enough.

The health and medicines regulators had for years believed there wasn’t a problem because there are few cases from their perspective. But today we know better and there have been efforts to address regulatory denial.

Counterfeit medicines are infiltrated into the supply and distribution of legitimate medicines by rogue, criminal organizations and individuals, who specifically target the weaknesses in supply chains, as well as human weakness (bribes and kickbacks) and gaps in healthcare payment systems.

Counterfeiting had originally been viewed as a patent issue legal advisors took a purely legalistic interpretation. It was not until the problem of counterfeiting was presented as a risk to human health and people’s lives that the dead end logic of patent protection was dropped. But why did the lawyers fail understand the context in which the problem existed? New legislation is always being introduced, such as the EU’s Falsified Medicines Directive, but the criminals will find a way to game this, even though this directive was apparently ‘gamed’ by developers using the French problem with the drug Mediator. However, gaming policy for developmental purposes also needs people to think like a criminal.

Once a medicine has been factory sealed by the pharmaceutical manufacturer, there is no assurance that it will reach the patient unopened; a pharmacist and doctor can open it, and packages that cross borders are opened for repackaging and labelling. Indeed, there are companies with the licensed authority to repackage factory-sealed medicines with new labels in new languages. Unscrupulous distributors can conceal the illegal substitution of counterfeits within these apparently highly regulated systems. Many countries are net importers of medicines as they lack sufficient domestic manufacturing capacity or the medicine is complex and is manufactured in only a few places. This makes these countries vulnerable to supply chain interference.
While international trade in medicines trade has often focused on internet pharmacies, the real problem is that the online mail-order environment is a counterfeit drug delivery system into every home on the planet.

Healthcare systems themselves must address perverse incentives that drive criminal behaviour; keep in mind that criminals exploit weaknesses in supply chains, laws and regulations, and respond to unmet demand for a product (from toasters to cars, there are illegal markets everywhere and not just for drugs) resting on common incentives. A major driver for criminals is the existence of cash markets for their products (they tend not to take cheques), and one of the largest cash markets is people without adequate health insurance cover and reimbursement systems that do not cover the full cost of medicines, or fail to insulate patients from high drug costs. In addition, as information on medicines can now be widely salient through internet social media, a country failing to license a medicine that some people would value opens a door to counterfeiters to exploit a patient demand for that medicine.

What Cognology says.

Catching crooks with counterfeit drugs is also a problem of finding them. Using advanced intelligent technologies (cognologies as in the name of this blog) means that surveillance can be smarter and less distracted by false signals.

“I told you so”: post-Brexit access to medicines and medical device technologies

Continuing the theme of looking at life sciences, healthcare implications for the UK exiting the EU.

  1. The NHS, the UK’s public healthcare system, procures medicines in many cases through the benefits of the single market. While it is not clear what impact an exit will have on pricing itself, failure to ensure access to that single market will inevitably lead to the increase in drug costs. I’d hazard a guess of 10%. Given the difficult financing circumstances of healthcare expenditure in the UK, an increase of this magnitude, will have a knock-on effect on patients and their care.
  2. Apart from the price impact, UK patients may find access to medicines and medical devices restricted as the UK exits the wider European market overseen by the European Medicines Agency. The UK is not every companies’ first choice of a market to launch a new medicine or device, but with an exit, it clearly will drop further down the queue. Excluded from products launched in the rest of the EU, the UK can only wait for companies to ‘get around’ to including the UK.
  3. And apart from the loss of a degree of certainty of access to medicines and devices within the EU, a UK exit, the UK will need to introduce a separate regulatory scheme to replace the European Medicines Agency approach, adding costs and an additional regulatory hurdle for companies. The UK can, of course, try to harmonise itself with EMA, but in the end, departing EMA will reduce patient access to medicines.
  4. Is the UK market big enough to make a difference? Perhaps for some, but I suspect the economics coupled with the overall difficulty new products face contesting the UK market points to a general decline in product availability. At least with the EU, access to medicines and devices could be compared to other EU states; with an exit, the UK stands alone and does not look particularly welcoming.
  5. Of course, the NHS could have a rethink as is slowly underway and move to ensure access to new medicines and technologies. But that may require a different assessment whether the current way of financing the NHS itself is sustainable and that has really little to do with leaving the EU, although the EU does offer a safety value for patients denied care by the NHS. All this is now in jeopardy.
  6. The European Medicines Agency will need to leave the UK, and with it will go not just those jobs, but a whole domain of expertise. That expertise with EMA made the UK within the EU, one of two global centres of excellence in medicines regulation, along with the US FDA, Few people outside this area will appreciate the consequences of EMA departing, but it will be felt within pharmaceutical who maintain many high-paid and knowledgeable staff focused on medicines regulation. All this expertise goes and with it a capability within the UK that can never be regained. Whoever gets the agency, Sweden, Denmark, elsewhere, will be a net gainer of  talent from which to build tremendous domestic capabilities.

What Cognology says

Perhaps, I told you so?

Broken logic: NICE and the Cancer Drug Fund

Sir Andrew Dillon, the erstwhile leader of NICE as said that it is irrational for the Cancer Drug Fund to pay for drugs that NICE has turned down.

He’s right of course, it is irrational. But only if NICE’s logic is compelling.

The problem for Sir Andrew, and like-minded people, is that there is another logic that trumps NICE’s rational world. Don’t get me wrong. NICE performs a useful, but technocratic, function with analytical assessments that any rational person would indeed want to know. Where we part company is believing that NICE’s logic is the final word on the matter. Which it isn’t.

Tasked, perhaps unenviably, with parsing the performance of medicines and clinical practice, cannot also mean that they are above challenge. Many of NICE’s rulings fly in the face, not of logic, but of our beliefs as humans. It is why we do things when the odds are against us, because not to do so would be wrong. If we think of the challenges NICE faces as wicked problems, that is complex problems with a multiplicity of solutions, it becomes self-evident that their logic is just one way of deciding and choosing. We could use other rules, other criteria. The Cancer Drug Fund is just such an approach. It is another matter whether we should have in place alternative funding approaches that individuals can avail themselves of (such as co-payments or co-insurance); for extraordinarily costly therapies, co-funding would not apply, so we’ll back to the problem anyway.

NICE has a troublesome relationship with the notion of ‘rule of rescue’ and so has decided to ignore it. There replacement, the “end-of-life premium” is really just a reweighting of the logic they use.

You see, the rule of rescue is what we might call a meta-rule — it is a rule that tells us if other rules are working properly, and importantly, as a moral imperative which tells us what to do. The rule is often invoked in a particular form: that people facing death should be treated regardless of cost. The rule as originally formulated is really about assisting identifiable individuals facing avoidable death (Jonson, 1986); the bioethicists and economists have shifted this to a cost-effectiveness approach, making it one about trade-offs instead.

The problem for healthcare systems is that all patients are becoming identifiable as medicines become personalised (medicines may become orphan drugs). The problem for the NHS is that it does not allow such people to rescue themselves because it prohibits any sort of co-funding or other arrangements. The only option is an opt-out (and private medical insurance has rules about pre-existing conditions). Given the funding priorities of the NHS, we should be reflecting not so much on how to make the pot bigger, but on using the money that is available better (there will never be enough money), and ways to introduce practical co-funding.

Since individuals have no other options in the NHS, the rule of rescue as a moral imperative will be violated and we will act, not out of analytical error (i.e. make a technical mistake), but unethically. You see, the NHS must be the healthcare system of last resort and therefore of rescue, otherwise, identified individuals are destined to a death sanctioned by public policy and is that a policy or healthcare system worth having?

We have seen a similar challenge to NHS/NICE logic recently with the King family and proton beam therapy, and the NHS will also use NICE logic to determine access. Whether beams or drugs, it is the same argument.

But why cancer? The main public policy question is why should cancer patients be given preferential treatment as against any other deserving group? This may in part be driven by the often astronomical costs of new cancer therapies themselves, which demarcate cancer patients decisively from equally deserving patients with less cost-contentious therapies. I have just finished some work on motor neuron disease, for which there is one specific medicine and life expectancy from diagnosis is 3 to 5 years, with median survival rates that are measured in months. NICE reportedly is developing guidelines for this disease. Costs are considerable, and at least in the UK, highlight the bureaucratic illogic of separate healthcare and social care, but that is another story.

What Cognology says

The moral dilemma that the economists at NICE are trying to reduce to an equation is whether a new therapy is extending life, or delaying death. The Oregon approach collapsed when the hard choices emerged and people were unable to resolve this dilemma, which is not a quantitative issue, but one of how we value our humanity. Kierkegaard’s Concluding Unscientific Postscript speaks of the leap to faith as involving self-reflection and the emergence of scepticism. It is worrisome that NICE is so confident.

Further reading

Cookson R, McCabe C, Tsuchiya A. Public healthcare resource allocation and the Rule of Rescue. J Med Ethics. 2008 Jan 7 [cited 2014 Sep 4];34(7):540–4.

Jonsen, AR 1986, Bentham in a box: technology assessment and health care allocation, Law, Medicine and Health Care, Vol 14, pp172–4.
Richardson J, McKie J. The rule of rescue, working paper 112, Centre for Health Program Evaluation, Monash University