I last wrote a couple of weeks ago about Obama’s vision of comparative effectiveness and the healthcare reform bill. Since that report, the end of April saw a raft of first quarter financial results issued by pharmaceutical manufacturers. Whilst some reported fairly buoyant figures, these were offset by one common theme; the emerging financial impact of this landmark change in US legislation.
Over time, the healthcare reform bill is expected to have a positive impact on the pharmaceutical companies, as the coverage of health insurance increases across the US population, thus increasing demand for their products. However, this is not expected to come on-stream until at least 2014.
Although the healthcare reform bill was only passed at the end of March many pharmaceutical companies have revised their 2010 financial outlook downwards – and the blame has been firmly placed on the doorstep of the new legislation.
Lilly, as an example, ranked 11 amongst the pharmaceuticals in terms of turnover in 2009, reported “as a result of the new legislation, Lilly will incur substantial costs” in their 2010 1st quarter earnings reports. Lilly expect these “substantial costs” to be in excess of $435 million during 2010 – which represents approximately 2% of 2009 turnover. The company expects this negative impact to worsen to between $600m – $700m in 2011 – highlighting the further pain to come.
Another large US based pharma, Merck, anticipates that healthcare reform will adversely impact 2010 revenues by $170 million, rising to $300 – 350 million in 2011.
The world’s largest pharmaceutical company, Johnson & Johnson, estimates that the impact from the legislation will reduce sales by $400 – $500 million for the year, which represents less than 1% of 2009 turnover. Due to Johnson & Johnson’s diversified nature of the business, the impact is not as significant as in some of its competitors.
Whilst these three businesses reflect what is happening in the larger manufacturers, it demonstrates what is happening across the pharmaceutical industry. The large companies appear to be able to accommodate the loss in revenue, but how the smaller companies will cope with the reduction in revenue remains to be seen.
At the heart of the healthcare reform bill lies Obama’s vision of the role comparative effectiveness will play in sculpting the landscape of the future healthcare markets.
The financial losses discussed in this article clearly demonstrate the critical importance of comparative effectiveness across the board. This concept is not something that can be dismissed and swept under the carpet! All players in the healthcare industry – whether they be the drug suppliers, the healthcare providers or the insurers – must have a firm grasp on the basic concepts and language of comparative effectiveness as it WILL influence every pricing, marketing and purchasing decision the company makes. And it is not enough that only a selected few individuals within businesses hold this knowledge, cross-company training is vital.
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President Barack Obama’s political mantra on healthcare reform has comparative effectiveness research forming a substantial part of his strategy. In 2009′s economic stimulus plan, Congress approved $1.1 billion for comparative effectiveness research. This has been further bolstered through the Healthcare Reform Bill, passed on 23 March, by the establishment of a dedicated comparative effectiveness research (CER) institute – armed with a $500 million annual budget.
The passing of this legislation has naturally caused a huge amount of debate – with both those supporting and opposing the move clamouring for attention. Whilst some welcome the introduction of comparative effectiveness as the healthcare cost-saving opportunity that Obama purports, opponents, however, worry about its implications with regards to issues such as quality of care and insurance-coverage decisions.
Whichever side you find yourself on one thing is clear – the implications of Obama’s CER institute will be far-reaching and will have a significant impact. Comparative effectiveness will be at the heart of major healthcare decisions, whether you are a pharmaceutical supplier, healthcare provider or an insurer – or indeed any other kind of business in the healthcare arena.
So with comparative effectiveness very firmly in the spotlight and destined to stay there for some time, can you honestly say that your business understands the basic concepts that have suddenly become so critical in the US healthcare market place? You may – but do your non-health economist colleagues? And ask yourself, what could be the implications if they DON’T understand these concepts?
Rx Communications has been active in the field of health economics (HE) and CER for many years, and as such, is regarded as an expert in the field of HE and CER awareness and training.
The latest in our published series is :
Introduction to Comparative Effectiveness
Evidence Based Medicine
This short 60 pp guide explains these concepts in basic terms, covering the objectives of CER and providing a rapid read and understandable reference that you may like to pass to your colleagues.
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This booklet is packed with useful definitions, implications and examples. Information is clearly laid out in sections and tables and will give your colleagues a better understanding of your function and the likely implications of CER on your drug and device development activities.
The book also explores other relevant issues in CER such as study methodologies and their application in CER, the role and application of evidence based medicine and how to evaluate comparative effectiveness studies. ‘Comparative Effectiveness and Evidence Based Medicine’ is available to buy here at £15.99 (plus shipping).
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While outcomes for any given treatment differ significantly among patients, national healthcare systems continue to take a top down population perspective in reviewing not only epidemiologic data but to evaluating the effectiveness and cost-effectiveness of new medicines.
This top down approach, coupled with a growing need for cost containment, has recently caused many governments to institutionalise these practices through health technology assessment institutions. The purpose of these agencies is to promote better quality or value for money in the healthcare system; but this has led to medicines and technologies either being considered good (in other words, good for all) or they are deemed bad and are blacklisted.
Whether it be data from a randomised control trial, a comparative effectiveness study or a cost-effectiveness study, the focus is on the average patient’s health outcomes, where all individuals are treated equally (or to be more correct, identically). Variation is something that we consider only when it comes to statistical inference, viz. does the average effect differ from zero.
This is a major over simplification since patients do vary: their needs vary; their preferences vary; their circumstances vary and, most important, their outcomes vary. Even if you wanted to treat individuals equally on ideological grounds, these top down approaches ignore the risks and uncertainties in medical decision making. For example, rather than understanding risk in clinical trials, we attempt to make it go away by demanding larger and larger trials (a movement away from the individual, towards the population).
As technology progresses, we are increasingly aware that the variation in benefits and adverse consequences of many healthcare interventions are predictable. As our knowledge of genetics and proteinomics expands, our ability to predict these events grows exponentially. This has prompted many healthcare innovators to develop diagnostics to tailor medicines for particular patients – in what is often referred to as personalised medicine. Governments everywhere have been eager to support these start-ups, almost to the point of frenzy and with little accountability.
One key problem exists, however, in that these new technologies are incompatible with the fundamental principles of many national healthcare systems and with the top down evaluation that has been implemented. Hence a bottleneck is occurring – ironically with government playing a dual role of promoting and rationing medical technology. In order to alleviate this bottleneck, we either have to address the funding crisis through personalised approaches to healthcare finance (The Netherlands and Switzerland have attempted this) or we need to stop wasting money on research and development of personalised medicine technologies that are unlikely to be funded in the future.
Essentially this means that healthcare systems need to decide whether they want to focus on the mean (the average effects of medicine) or on the gene (by accommodating personalised medicine.
John Bridges, PhD, is Assistant Professor, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Senior Fellow at the Center for Medicine in the Public Interest and founding editor, The Patient: Patient-Centered Outcomes Research.
Pharmaceutical companies depend on data – and lots of it – to develop drugs and measure their effectiveness. And many patients are eager to supply that information if it might mean better treatments or better quality of life.
That’s the premise of PatientsLikeMe.com. Launched in 2006, it connects patients to other people dealing with the same life-altering disease. Not only does it allow users to share experiences and provide peer support, it also generates a goldmine of data by encouraging patients to track and quantify their symptoms, medications, and outcomes.
Today, the pharmaceutical industry relies on point-in-time, survey-driven information, explains David S. Williams III, the site’s co-founder and head of business development. In contrast, PatientsLikeMe provides a much wider range of data.
Pharmaceutical companies can monitor its forums for insight into patient perspectives or recruit its members for clinical trials. Most exciting, however, is the opportunity to examine real-world, long-term data on how patient attitudes, decisions, and outcomes change over the course of their disease.
You now have a different longitudinal way of looking at how patients interact with your medication that you never had before,” Williams says.
To date, nearly 20,000 people from around the world have joined PatientsLikeMe, which offers on-line communities for patients with ALS, multiple sclerosis, HIV, Parkinson’s, and a variety of mood conditions. Williams predicts those numbers will increase to one million patients and 200 communities by the end of 2011.
“The people we’re attracting are that 5-15% of people in every single disease who will share their information openly. We know that target group exists,” he says. Once PatientsLikeMe proves that sharing medical information provides more collective benefit than keeping it private – establishing best care practices and accelerating research into treatments – he anticipates more people will overcome their privacy concerns.
But even data from the 5-15% segment alone has tremendous value, especially for a prevalent condition like heart disease. “The Framingham heart study has 5,000 people,” Williams points out. “We’re talking about building 200 Framingham heart studies in 200 different diseases.”
How reliable is the information generated by PatientsLikeMe? Although patients misinterpreting or misreporting information is a very real possibility, the aggregated data is structured to make outliers evident. Because these charts and graphs are posted on the site, patients have an opportunity to spot and correct mistakes themselves. If a patient sees that she is the only person who reported taking a particular medication for a particular purpose, for example, she may realize that she’s misunderstood why her doctor prescribed it.
Unlike most “health 2.0” businesses, PatientsLikeMe forgoes advertising in order to maintain high credibility with its members. Instead, revenues come from selling data to carefully screened partners that develop or sell drugs, devices, insurance or medical services aligned to the needs of patients.
While it’s a model that promises profitability, the ultimate goal is to benefit the patients themselves. As the site’s founders explain, “When patients share real-world data, collaboration on a global scale becomes possible. New treatments become possible. Most importantly, change becomes possible.”
Health clinics based in retail outlets, particularly drug stores, are changing the way primary care is delivered. Their proponents cite access, convenience, and price transparency as the major reasons for their popularity and growth. Further fueling this concept is the growing shortage of primary care doctors.
Staffed mainly by nurse practitioners, the clinics offer quick services for routine health conditions such as colds and sore throats that formerly would have taken patients to the office of a family physician or general internist.
The expansion of these clinics is nothing short of phenomenal. Their umbrella trade group, aptly titled the Convenient Care Association, estimates that there will be more than 700 of them by the end of this year, and some 2000 by the end of next year.
Initial concerns by medical associations that the clinics would be unregulated and provide mainly one-shot care other than continuity are largely dissipating.
For example, Minneapolis-based MinuteClinic – a subsidiary of CVS Caremark Corporation and the largest provider of retail-based healthcare in the US – now has full accreditation from the Joint Commission on Accreditation of Healthcare Organizations (JCAHO).
Its president, Michael Howe (pictured left), a former executive with Procter & Gamble, told HOC: “Our services complement primary care providers and our nurse practitioners make it a point to stress the importance of a regular medical exam with every patient they see.” He adds that “waiting times, compared with a doctor’s office, typically are about 15 minutes… and the average cost is about $60.”
The American Academy of Family Physicians (AAFP), rather than opposing the concept, has issued a set of standards for in-store clinics… and a former AAFP president serves on the company’s Clinical Quality Advisory Council.
A by-product of the clinics is that they have an impact on employee productivity because of the time saved in comparison with time spent in doctors’ waiting rooms.
In the United Kingdom, plans are in motion to formalise minor ailment clinics where pharmacists and nurse prescribers can serve to direct patients away from busy doctors’ offices.
The major UK pharmacist chain, Boots, is establishing walk-in clinics in concert with major supermarkets. However, such clinics have been slow to take off because they are limited by the National Health Service Primary Care Trusts’ budgets, since both doctors and pharmacists operating in these clinics will be seeking reimbursement for their prescribing.
The term “adherence” (or sometimes “compliance”) – the extent to which patients take their treatment as prescribed – has been understood to be a nagging clinical issue, but is now seen as a major cost driver in many therapeutic areas.
A recent report from the National Council on Patient Information and Education (NCPIE) in the United States reveals depressing statistics: 49% of those polled had forgotten to take a prescribed medication, 31% had not filled a prescription they were given, 29% had stopped taking a medicine before the supply ran out, and 24% had taken less than the recommended dosage.
A recent report in the Archives of Internal Medicine documents our failed efforts to improve adherence. Only about half of randomised controlled trials designed to improve medication adherence showed any consistent improvement in patient adherence, and less than one third of the studies demonstrated improvement in at least one clinical outcome. Non-adherence has even been referred to as the “other drug problem”.
How does the issue of adherence/compliance affect the field of health economics? The International Society for Pharmacoeconomic Outcomes and Research (ISPOR) has created the ISPOR Medication Compliance and Persistence Special Interest Group to study non-adherence in pharmacoeconomic evaluations.
JoAnne LaFleur, Research Assistant Professor at the Pharmacotherapy Outcomes Research Center, University of Utah College of Pharmacy (Salt Lake City, UT, USA) is a member of the ISPOR special interest group on adherence/compliance. She says there has been a surge in the last five years in measuring the cost outcomes of poor adherence.
She explains that medication costs are often much less expensive than the surgical or hospitalisation costs if the medications are not taken as directed and the clinical sequelae manifest. LaFleur also says that, in the US, a consistent problem has been that, with a few exceptions, the myriad health insurance plans don’t invest in programmes to improve adherence, in part because their pharmacy budgets are separate from the medical budgets. In fact, management of pharmacy coverage is often outsourced to other companies called pharmacy benefit managers. Thus, each group (pharmacy versus medical benefits) is not considering the ramifications of their decisions on the total healthcare cost, but rather only on their specific budgets.
According to David Nash, MD, MBA, Chairman of the Department of Health Policy at Jefferson Medical College (Philadelphia, PA, USA), who recently reviewed the Archives study, the only techniques that seem to have any impact on improving adherence are “once-a-day dosing and a rigorous reminder system to patients”.
For health economists, Dr. Nash sees three main issues regarding adherence and health economics:
In our next HOC article on adherence, we will discuss some of the challenges to including adherence in cost outcomes analyses, including effect of co-payment on adherence, as well as the use of accurate models of adherence in cost outcomes analyses – how closely do they reflect real life data?
As we provide and interpret pharmacoeconomic (PE) evaluation results for decision makers in different settings around the world, we should consider the standards being followed. And there are several of these: the ISPOR website presents a summary of international standards , grouping them into two broad categories: “PE guidelines” and “submission guidelines”.
Even the labels for the two types of guidelines suggest that there is likely to be significant variation. PE guidelines largely reflect the best technical approach for conducting an economic evaluation without a specific objective. In contrast, submission guidelines deal with a very specific objective of pharmacoeconomic evaluation—submission for formulary consideration or other coverage-related decisions.
Those reading manuscripts in peer reviewed journals or conducting studies that are intended for publication need to familiarise themselves with how the recommendations vary and what this implies for how peer reviewed work translates into actual decision making. For those who hope for a single set of standards for pharmacoeconomic evaluation, it may be disheartening to know that PE guidelines vary significantly among different countries.
Even so, PE guidelines are more likely to recommend the societal perspective (as primary), have longer time horizons, and recommend QALYs as the preferred outcome measure. Thus, without some analysis from a perspective that is less general than the societal perspective and employing less time than the ‘lifetime’ or similar horizon allowing for all effects of an intervention, the information presented in peer reviewed manuscripts will not be easily used for formulary decisions. This ultimately means analysts must perform more work in order to use the information for decision making. Additionally, the variation in standards makes reviewing international manuscripts all the more challenging.
All this variation may leave us longing for a single standard. While the community of researchers interested in and users of pharmacoeconomic evaluation might consider the pros and cons of a single standard, this would not unambiguously improve outcomes for the populations that are affected by formulary decisions as some of the variation reflects different national interests, and may be warranted.
Question: “How many people work in the public sector?”
Answer: “About half of them.”
It’s an old one, to be sure, but it has its echo in the fairly recently-coined word “presenteeism.” While absenteeism means not being at work at all; presenteeism means being at work, but not working; or at least not working to capacity.
That was the theme of a project presentation by 2008 MD/ MBA candidate Jeffrey Clough during Thomas Jefferson Medical College’s Health Policy Department’s Fellows’ Day. The project, funded by the Pharmaceutical Manufacturers and Research Association (PhRMA) and also involving Thomas Bunz, PharmD, as primary investigator, set out to examine the impact of pharmaceutical intervention in eight chronic disease entities: asthma, coronary artery disease (CAD), congestive heart failure (CHF), depression, diabetes, dyslipidaemia, hypertension, and migraine.
The project’s methodology involved searching literally thousands of articles using key words relating to the eight diseases and their connection to absenteeism and presenteeism. These eventually reduced to about 300–400 applicable or usable ones. The goal was to condense this wealth of information and make it understandable. With healthcare costs being such a major issue, the project’s findings would have an effect on decision making; in other words, which drugs can save money in productivity and worker satisfaction.
The two researchers found that from an employer or payer standpoint the impact more than compensated for the cost of medications in diseases such as asthma or where younger patients were more heavily involved; the return on investment was less or minimal in diseases such as CHF that primarily affect older patients.
Jeffrey Clough points out, though, that for some diseases an employer would likely see a return on investment (ROI) quickly in direct medical costs (e.g. diabetes, asthma) and in others there would be no ROI (e.g. dyslipidaemia); still others, he says, could yield a positive ROI if productivity costs are included (e.g. depression, migraine). The key point for decision makers, he emphasises, is not to evaluate medication costs as a single item but to think of all costs that could be affected.
There are ways to measure presenteeism, Mr Clough and Dr Bunz agree, but no standardised way to determine costs. How, for instance, can you assess the cost in lowered productivity of an arthritic patient’s ability with a computer?
PhRMA was allowed to comment and review at various stages in the genesis of the 10,000 word project; but the researchers emphasise that they have the final say. They believe that their work will be published in a peer-reviewed journal within the next six months. PhRMA will work with employers to show how if you use available pharmaceuticals appropriately you can improve outcomes economically as well as clinically.
The theme of this year’s international ISPOR meeting – held on May 20–23 in Arlington, Virginia, USA – was “new tools, new audiences for health outcomes research.”
In his valedictory address, retiring ISPOR president Dr Michael Drummond told some of the 1600 registrants to the meeting that the organisation now has more than 3300 members in 80 countries. Forty nine percent of those come from the US and 35% from Europe, while industry accounts for 38% of the membership, he said, with healthcare research and academia each accounting for 28%.
This year’s meeting attracted 64 podium presentations and 524 posters. The organisation’s forward planning strategy – Impetus 2010 – includes research excellence, promoting education, reaching out to decision-makers, and international growth.
In a plenary session titled ‘How should the media convey information about new medical technologies?’ a former JAMA editor Drummond Rennie said that “while the drug industry does exceedingly good trials,” the press is often shrill in its Pharma bashing. Peter Littlejohns of NICE agreed, saying that the press too often sensationalises healthcare issues, takes a personalised angle, quotes from so-called experts, and often presents a negative slant.
Ex-national public radio journalist Snigda Prakash said that in the Vioxx case Merck had hidden adverse cardiovascular data, and, she said, an editor of the New England Journal of Medicine said he’d been ‘hoodwinked’ in connection with the journal’s Vioxx article. A pharmaceutical industry questioner from the floor noted that the media seldom report the great advantages of drugs and the good work done by the pharmaceutical industry. Ms. Prakash said the line between advertising and editorial has become blurred. And Dr. Rennie added that better ways need to be found to educate the public about adverse effects of drugs – a move that would also be helpful to the industry.
In a session on the economics of personalised medicine, a panellist defined this as “doctors customising medical care to a person’s genetic code for better diagnosis, more effective treatment and fewer side effects.” Another panellist spoke of raising the bar – the impact of heightened awareness of the need for health economics data in the absence of regulatory mandates. The managed-care revolution in the US created a demand for evidence-based formulary placement and the need to establish the value of a new medicine, said another. Applying evidence-based criteria to high technology, he said, if the answer is No to the questions of clinical effectiveness, safety, and improved value then the drug or the technology should not be adopted; if the answer is yes, and there is no comparable product, it should be adopted.
In a session on the relevance of cost-effectiveness information for clinicians, Dr. Alan Detsky said there’s a need to teach clinicians how to make decisions based upon rational thinking. Cost-effectiveness analysis is a linear programming technique developed to maximise good health outcomes, he said. Cost consequence analysis, he added, is the cost of the prescription, the cost of effects and the cost of side effects. Those doing such analyses may be biased, he said, and concluded “two economists debating is like watching the passive aggressive Olympics.”
In her inaugural address as ISPOR president, Diana L. Brixner, R.Ph, PhD, executive director of the University of Utah’s Pharmacotherapy Outcomes Research Center, said ISPOR “should glance back, reach outward, and press forward.” She noted the enormous growth, particularly internationally, of the organisation. Founding ISPOR Executive Director Marilyn Dix Smith, Ph.D., said the organisation’s revenue is more than $3 million with a net surplus of $700,000. She said she welcomes ideas for worthwhile projects for the organisation.
ISPOR’s flagship publication Value in Health attracted some 271 submissions in the past year, said its editor Dr Josephine Mauskopf… and the organisation’s website attracts some 1.5 million hits a month.
Next year’s international conference will be held in Toronto.
There is increasing pressure to describe the benefits of new treatments in terms of increased productivity in the work-place, and many clinical studies are now attempting to include some measurement of improved productivity as a secondary endpoint.
Whilst many trials have indeed shown that effective medical intervention can decrease illness-associated loss of work time, it does not necessarily follow that an effective treatment will always improve a standard measure of productivity.
Laura Pizzi and colleagues from Jefferson Medical College have constructed a simple model of employee behaviour based on economic theory which can predict the effect of a treatment on time worked.
Their model suggests that a medicine might only decrease loss of work time if its use is associated with increased job satisfaction but has little effect on non-work or leisure time.
In addition the model highlights the fact that work hours are influenced by several variables such as wages, the comparative cost of other goods, job characteristics and health status. These variables might work to make an effective therapy either increase or decrease productivity.
This work illustrates the need for a greater understanding of the effect of many different social and economic factors on productivity and the importance of considering these factors when designing and interpreting clinical trials.
Pizzi LT, and Gagne JJ. Pills and productivity: what economic theory tells us about employees work behaviours. ISPOR Connections, February 15, 2007, Vol.13, No.1
The chance to generate new knowledge, to resolve healthcare problems, to benefit mankind – perhaps even to acquire in the process a Nobel Prize and a measure of immortality – ought to make healthcare research a popular, even glamorous endeavour.
But it’s rarely perceived that way. What’s vital, says one ranking academic, is for would-be researchers to develop a “constructive discontent” about the state of knowledge in their particular field.
Another notes rather dryly that research is “narrow, slow, dirty, and inadequately funded, while offering few opportunities and while being conducted by sterile, reference quoting people.”
In fact, the stereotype of the researcher as a determined individualist working in solitary confinement may once have been true; these days, though, with research becoming ever more sophisticated, collaboration is essential. In fact, a large part of investigation is communication with other people.
The fact is, though, that there is money for well-planned, exciting, meaningful and original research. Still, some potential researchers are confused about the application process, or about which of the several agencies they should approach. Some may even be deterred by a notion that the scramble for financing is fiercely competitive, so they have to learn where to begin.
Getting started involves fuelling your idealism and scientific curiosity as early as possible. What that means is being acutely observant, asking intelligent and appropriate questions, gathering all the clues or data and drawing valid conclusions to solve a given mystery.
This begins with an unsolved problem… followed by asking the right questions about it, then developing a working hypothesis and a well reasoned theoretical answer. After that come the protocol, design, method, subjects and equipment for the investigation. And finally the data can be interpreted to answer the original question.
Good clinical investigation can elucidate the cause of the disease, reveal areas of inadequate knowledge and persuade a researcher to ask the basic question and thus get into the research cycle with experimental work. As the president of a British pharmaceutical company is reputed to have said: “You can’t ask mice if they’ve got headaches.”
Nonetheless, research isn’t simply about hard data. Many great discoveries owe themselves to serendipity – to chance, to lucky breaks. One example is Minoxidil. Originally discovered and used as an antihypertensive, it turned out to generate hair growth in its users… and became in addition a blockbuster treatment for baldness. Even so, as has often been said, serendipity comes to the prepared mind, to the researcher who expects the unexpected.
In essence, then, you’ll need to make the theory fit the facts, not the facts fit the theory; you’ll need a thirst for knowledge, and what one prominent researcher calls “a spirit of discontent.” And you’ll need partners.
To be successful you must be highly professional: develop your methodology to a fine pitch, and know unerringly what’s relevant. The professional sets out to answer a question; the amateur sets out to prove something.
Finally, make sure that some proportion of your reading relates to research articles – not just reviews, but specific reports of research activity in areas where you have a particular interest. Go to it!
Rx Communications and Greenflint had great pleasure in attending the 9th annual European meeting of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), 28–31 October in Copenhagen.
Our booth featured Rx sister company Greenflint, whose models are designed to help in early-stage decisions, cutting costs, making strategic decisions during development, and developing a promotional message.
With red clay, attendees were asked to create a communication tool, and with the green clay, to model their favourite thing.
This creative challenge produced, amongst other entries, a dove carrying an olive branch, a football match between Copenhagen and England, ‘probably’ Denmark’s best export (the famous lager), and a Christmas tree.
All entries and winners for both competitions can be viewed at the Rx and Greenflint websites.
The theme of the congress was ‘Asking critical questions’. The first plenary session was introduced by Bengt Jønsson, PhD, who initiated the discussion on the use of health technology assessment (HTA) as a basis for reimbursement and priorities in health care.
Richard Bergström, MScPharm, presented the HTA principles adopted by EFPIA and industry’s perspective on promoting good use of HTA. Audun Hågå, MSc, discussed priority decisions from a government perspective focusing on Nordic countries. One key message was the need for increased communication between industry and payers, and a decision on the best practices for Europe.
The second plenary session was a debate between Professor Paul Glasziou, PhD, FRACGP, and Ivar Sonbo Kristiansen, MD, PhD, MPH, moderated by Kjeld Møller Pedersen. This session examined questions surrounding evidence based medicine (EBM).
Dr Kristiansen questioned the use of EBM in health policy; he urged the audience to be more humble in interpreting the results of randomised clinical trials (RCT), and suggested that EBM does not improve patients’ health.
The speaker questioned the Cochrane collaboration, suggesting it is an anti-industry movement that should be consulted with caution. Professor Glasziou retaliated by providing examples of when an RCT is required, although he agreed that RCTs are not always the best approach, suggesting that the best study design depends on the type of question one is attempting to answer.
With regards to the Cochrane collaboration, Professor Glasziou explained the background and stressed that the collaboration is not anti-industry, and when used properly is a good tool to aid physicians in choosing the correct medication for their patients.
The third plenary session addressed the societal value of the QALY. Professor Dorte Gyrd-Hansen, PhD, gave a critical view demonstrating that the task of performing a linear translation from QALYs to willingness to pay (WTP) is theoretically and empirically unattainable.
The speaker stressed that we need to think carefully about study design and interpretation of results. Professor Martin Buxton, BA (Soc Sci), argued that ‘social’ WTP values are interesting but of no immediate relevance.
The speaker stressed that a health system is responsible for the entire population and a WTP threshold needs to be set. This threshold should ensure that technologies adopted are always more valuable than other new alternative and any displaced activities.
In addition to these plenary sessions, there were 28 thought-provoking workshops, 6 issue panel presentations, 64 contributed presentations, and almost 600 posters.
Health economists interacting with colleagues and clients often need to have a global perspective, which means not limiting one’s view to what is going on in one’s own country… and that goes beyond economics.
So, how does a health economist develop a holistic and global perspective?
Keep up with academic and trade journals covering economic topics that are not limited to your own country; be sure to read non-economic articles too. For example, a health economist who has become expert in infectious disease might include clinical epidemiology articles relevant to infectious disease in your country and in others.
However, to interpret data effectively and make predictions you will need to go beyond just economic and clinical epidemiology. Read about sociologic and political issues related to infectious disease.
While these other disciplines don’t always look at issues in exactly the same way as economists do, the ideas that come from the other disciplines may help you to understand how people think about infectious disease and how policy makers are likely to use clinical epidemiology data and economic data together to make policy.
Remember that as health economists we are interested in how people make decisions. There is no better way to find out how people make decisions than to cultivate a global approach both geographically and professionally.