Under competition, three essentially identical drugs may receive dramatically different labels, incremental cost-effectiveness ratio (ICER) justified pricing, and market positioning depending on their stratification approach. It appears superior to use an imperfect biomarker to none at all. It is less obvious whether patients, payers and firms prefer the same cut-off values for the companion diagnostic, or even whether each stakeholder a priori prefers the high, low or perhaps some other CDx cut-off value.The implications for regulating and financing of companion diagnostics are immediate. In Europe current legislation is as old as of 1998, the year that Herceptin entered into the market and the begining of stratified medicine. New regulation is still pending and there are no perspectives about a unified approach to lab tests assessment. European regulator is still on vacation.
The competing development teams may face a version of the game theory ‘prisoner’s dilemma’ in which the optimal result for patients and all firms would be to select a low or mid companion diagnostic cut-off value but the advantages of a potentially differentiating high efficacy claim may drive developers to select a high cut-off value. If all choose this approach, overall value may be reduced with many patients excluded from treatment. But the potential advantage of a higher cut-off value may prove too alluring, or the fear of a competitor selecting one, may drive all to do so. Each situation will depend on the specific facts of the indication, therapeutic, companion diagnostic and competitors
Consumers should celebrate that; the firms’ losses are their gains. But there is a catch. Comparison sites, whether for insurance or something else, introduce a new layer of costs, including their own splashy advertising campaigns. In theory, competition in the market for comparison sites ought to keep those costs down. But in a recent paper, David Ronayne of Warwick University argues that consumers often lose out from comparison sites. They earn a commission for each shopper who uses them to buy insurance. That referral cost is incorporated into the price the consumer ends up paying. If the increased costs outweigh the saving the comparison enables, consumers end up worse off.And the proposal:
How can you ensure the market for price comparison is competitive? Asking consumers to check multiple websites defeats the point of using them. One solution is to have only one site, but regulate it as a public utility. Alternatively, the government could run the site itself—much as the American government now runs comparison websites for health insurance under Obamacare.I think that this is the right approach, why not apply it here?
The main regulatory approaches are taxes, restrictions on the availability of SSBs in schools, restrictions on advertising and marketing, labeling requirements, and government procurement and benefits standards.On taxes:
Savvy regulatory design has tremendous potential. For example, there is growing evidence that taxes that are more salient to consumers, such as those included in a good’s posted price (rather than being levied at the register), are more likely to influence purchasing behaviorOn public procurement, a practical suggestion for immediate application:
Restrictions on which beverages may be purchased using government funds are a less visible form of regulation, but one with potential to change the consumption patterns of large numbers of people. Outside public schools, these standards are most germane in two areas: procurement standards for public institutions (e.g., government agencies, hospitals, and prisons) and restrictions on what recipients of government benefits for the indigent may buy with those funds.
The UK’s Government Buying Standards prohibit central government bodies from procuring SSBs larger than 330 ml and encourage the wider public sector to follow the guidelines. Massachusetts and many US counties and cities have adopted nutrition standards for government contracts, but most apply to a limited set of institutions, such as childcare facilities or youth centers.
Our analysis suggests that most companies have a considerable opportunity to get better at deploying capital and resources efficiently when sourcing innovation externally. In our experience, we have found that the best performers develop robust forecasts for the key assets, are fiscally disciplined, and set up their innovation-sourcing teams and transaction capabilities to ensure that the right internal expertise is brought to bear and to ensure smooth hand‑offs through the life cycle of a deal.The success lies within, the internal expertise is crucial. Have a look at the figure and you'll notice that the most efficient (defined as the commercial impact of the products acquired relative to capital deployed in M&As) is Roche. This is not by chance.
First, and foremost, introducing or increasing competition in the provision of health care services is a delicate policy exercise. The conditions for success and risks for failure need to be carefully assessed. In the right context, introducing competition may help to meet some health system objectives, although it is unlikely to contribute simultaneously and positively to all.Now it is crystal clear. The official has had a precise answer that it is exactly the opposite they were expecting. I've said the same in this blog several times. Take care.
Neither economic theory nor empirical evidence support the conclusion that competition should be promoted in all health services
Neither competition nor strict reliance on government regulation will solve all health system problems. Attempts to avoid or correct market failure can result in government failure and vice versa.
Provider competition can contribute to improving value in health service delivery, but details about where, when and how to introduce competition are critical. Competition in health care provision will not solve all health system problems and may have adverse effects.
Competition is unlikely to achieve improvement in all aspect of health system performance at the same time. It will not solve all the trade-offs policy makers face between different, sometimes conflicting, health system objectives.
Competition can at the same time increase the number of services provided and billed, creating uncertainty in relation to overall health care costs. That is, the introduction of competition may well result in increased costs and add to fiscal pressures. Increased costs may, or may not, be justified by additional health benefits to the population (or some parts of the population).
As competition is an instrument, sound policy evaluation studies are needed to assess and judge its effects. Such empirical studies are currently rare and even absent in some countries.
The introduction of competition has uncertain effects on equity of access to health care, as it is conditional on the effects above and on the heterogeneity of patients. Empirical work has found that the introduction of competition among hospitals, in the UK, produced little or no result in equity terms. This limited evidence does not allow for general presumptions about the effects of competition on equity of access to health care.
RWE is drawn from robust anonymous patient-level data using sound scientific and commercial analytics. It is not about amassing "Big Data" so much as performing targeted analyses on ever expanding healthcare datasets.Its impact could be large if drug prescription decisions and pricing takes into account the outcomes from the "patient journey" as they say. This is a new paradigm with uncertain spillovers. The true evidence based medicine with the power of big data. We must be aware of it and follow it closely.
While RWE is known to complement data from Randomized Clinical Trials (RCTs), its real potential is in moving decisions away from perceptions and broad extrapolations to the actual facts about patient journeys and outcomes. With innovations in data and technology, RWE is replacing other information sources such as non-behavioral primary market research (PMR), standard market reports, consumption/market data purchases, observational studies, and even selected spending on RCTs.
Three principles stand out as providing the direction for new approaches to understanding behavior and designing and implementing development policy. First, people make most judgments and most choices automatically, not deliberatively: we call this “thinking automatically.” Second, how people act and think often depends on what others around them do and think: we call this “thinking socially.” Third, individuals in a given society share a common perspective on making sense of the world around them and understanding themselves: we call this “thinking with mental models".In chapter 8 you'll find the application to health issues. A clear warning:
Telling people that there is a way to improve their health is rarely sufficient to change behavior. In general, successful health promotion campaigns engage people emotionally and activate or change social norms as much as they provide information. The message disseminated should be that others will support you or even applaud you if you do it, not just that something is good for you. Successful campaigns address many or most of the following: information, performance, problem solving, social support, materials, and media . A campaign should tell people that a behavior will improve their health (information), demonstrate and model the behavior (performance), reduce barriers to its adoption (problem solving), create a system for supporting people who choose to adopt it (social support), provide the materials necessary to begin adoption (materials), and provide a background of support through in-person, print, radio, television, and other approaches (media).As you may imagine, this is much more difficult than simply giving information. This is precisely the greatest challenge.
Three general recommendations flow from our arguments and related synthesis of existing evidence on broad benefits of vaccination. First, many economic evaluation studies of vaccinations should be redone to capture the full benefits generated by the vaccination in question. Second, the evidence to date on the full value of vaccination has been focused on measuring the total social benefits generated. It would also be useful to explore the distribution of vaccination’s benefits among different possible beneficiaries. Third, the primary empirical evidence on broad vaccination benefits will need to be considerably expanded and improved
| Perspective | Benefit categories | Definition | |
| Broad | Narrow | Health care cost savings | Savings of medical expenditures because vaccination prevents illness episodes |
| Care-related productivity gains | Savings of patient’s and caretaker’s productive time because vaccination avoids the need for care and convalescence | ||
| Outcome-related productivity gains | Increased productivity because vaccination improves physical or mental health | ||
| Behavior-related productivity gains | Vaccination improves health and survival, and may thereby change individual behavior, for example by lowering fertility or increasing investment in education | ||
| Community health externalities | Improved outcomes in unvaccinated community members, e.g., through herd effects or reduction in the rate at which resistance to antibiotics develops | ||
| Community economic externalities | Higher vaccination rates can affect macroeconomic performance and social and political stability | ||
| Risk reduction gains | Gains in welfare because uncertainty in future outcomes is reduced | ||
| Health gains | Utilitarian value of reductions in morbidity and mortality above and beyond their instrumental value for productivity and earnings | ||