David Williams has posted Health Wonk Review: Back to School Daze at Health Business Blog
David debuts the fall season with a serious roster of posts, just the thing to get us back to business.
According to two researchers, the answer is no. As they write at Stat:
As we wrote recently in Science, three key barriers are impeding the drive toward truly transformational precision medicine: researchers often don’t rigorously test the biological theories that supposedly explain why a targeted treatment should work; they haven’t fully determined the accuracy of the diagnostic tests used to figure out if a patient is a good candidate for the therapy; and there’s little coordination between investigators, which has led to inefficient research.
Can you give me an example of the problem?
An evaluation of 33 studies of ERCC1 and lung cancer chemotherapy showed so much heterogeneity in the diagnostic methods and scoring rules that the results are essentially incomparable. So after more than a decade of research, we still don’t know if measuring ERCC1 makes a difference. Nevertheless, numerous ERCC1 test kits are commercially available, and are being used to help “guide” lung cancer chemotherapy.
Precision medicine is still a laudable goal. Finding the best treatment on average is less useful than finding the best treatment match for each patient. However, rigorous science needs to back up any claims that treatments are more or less effective for specific biomarkers or lab values.
Precision medicine is still the future…the future may just be a few more years away than we had previously hoped.
Step therapy is good in theory, but often not in practice. In step therapy, patients are required to try one drug first–typically a low cost and/or high-value treatment–before moving on to more expensive alternatives. In theory, this is a great idea. The first drug patients should try should be the highest value one.
In practice, however, step therapy does not always work out as planned. Stat describes some of these issues. Broadly, step therapy doesn’t work due to asymetric information. Typically there is private information that patients and physicians have that insurers do not have. For instance, how does one define whether a patient “failed” a therapy. Clinically this may be easy to do in many cases, but for payers this information is difficult to observe.
The practical issues described above highlight some shortcomings when step therapy is administered well. Oftentimes, however, it is not.
Dr. Kenneth B. Blankstein, an oncologist in Flemington, N.J., is treating a woman for lung cancer. She responded well to the first chemotherapy drugs he prescribed. When her health was stable, he gave her a “temporary break” from chemo to spare her some of its side effects.
But when he tried to return her to the treatment, the insurer balked, saying that the “temporary break” was evidence that the treatment had failed. Despite Blankstein’s protests, the insurer said she would have to move next to Tarceva, another treatment.
“She had under a 5 percent chance of a response on Tarceva,” he said. “Yet they insisted, so we had to.”
More broadly, Blankenstein summarizes the problem with step therapy as follows.
“The patient’s being told to use a drug we know isn’t going to work, but we have to use it anyway for someone with terminal illness? To me that’s just insane, but it’s the way they do things…It’s taken away clinical judgment. It’s managing by algorithms.”
According to an article in the American Psychological Association webpage, the answer is likely ‘yes’.
Originally intended as a day for relaxation and celebration of the American worker, Labor Day today is very different from the first Labor Day in 1882. Back then, a largely industrial and agricultural workforce could disconnect from work on Labor Day without the possibility of being disturbed by work-related cell phone calls, reading e-mails on-the-go or being summoned to rush back to the office. In today’s 24/7 society, work frequently intrudes in to employee’s personal lives during evenings, weekends, vacations and holidays. In fact, 83 percent of email users admit to checking their email daily while on vacation.
Constant work can have an adverse effect on individual’s health:
“While technology has undoubtedly improved our lives in the last 125 years, constant use of technology can add to the stress levels of an already overworked nation” says Dr. Russ Newman of the American Psychological Association.
However you spend your day, please enjoy your Labor Day.
The Healthcare Economist has been published in this month’s edition of Pharmaceutical Commerce. The article, titled Value frameworks are here: What to do about them?, provides a brief overview of the existing value frameworks and describes what steps life sciences company can take to evaluate the value of their innovations.
When using real-world data, researchers must always deal with a key issue: selection bias. To get around this bias, many health care researchers use an instrumental variable that can predict the explanatory variable of interest (e.g., receipt of a specific treatment) but is not correlated with patient outcomes (e.g., mortality). A commonly used IV is patient distance from a provider; distance from a provider would certainly affect receipt of specific services that provider specializes in, but it may not be correlated with outcomes.
An interesting editorial by Soumerai and Koppel (2016), note the following, however:
Like any cross-sectional analysis, IV analysis relies on the absence of any unmeasured patient and health system confounders (e.g., socioeconomic status, health status, and other lifesaving treatments, such as medications) that may provide an alternative explanation for the relationship between the IV and the patients’ survival. This assumption is the Achilles heel of IV studies. Most administrative data lack important variables correlated with survival (e.g., urban/rural status, or receipt of other lifesaving treatments), or they measure them poorly (e.g., race), representing a violation of the IV assumptions.
Sure there are problems with IV, but are there better alternatives? The authors hold up the Angrist, Chen, and Frandsen (2010) paper as a prime example of high-quality IVs. In this paper, the Vietnam draft lottery was used as a source of real-world randomization.
The authors also claim that IV is a cross-sectional technique and thus is subject to bias due to the potential for pre-existing trends. Instead, the authors recommend using a formal interrupted time series design, as they claim that it is more resistant to bias.
This crowd of helpers, which delighted him, meant that no Nobel prize could be given for wiping out smallpox. If it had been, he might have shared it with William Foege, who first devised surveillance-containment, and Benjamin Rubin, inventor of the bifurcated needle, an easy and ingenious instrument which used a mere 25% of the normal amount of vaccine. But he was the man who kept the whole show on the road, strong-arming governments to provide funds and to make their own vaccines of the necessary purity, potency and stability; conducting his own cold-war diplomacy with the notably helpful Russians; muscling past the tentacular regional bureaucracies of the WHO; sending out continual reports on progress; and answering within three days, before e-mail, every plea that came in from the field.
Problems rose up constantly. In Ethiopia, rebels attacked the vaccinators. Afghanistan brought deep snow and no maps. In Bangladesh trucks could not cross the bamboo bridges; in India mourners had to be stopped from floating smallpox corpses down the Ganges. He experienced most of this himself, frequently decamping from cramped Geneva armed with “Scottish wine” (his favourite medicine) to urge on the troops. Out in the trenches he also faced the full horror of what he was fighting. At a hospital in Dhaka the stench of leaking pus, the pustule-covered hands stretched towards him, the flies clustering on dying eyes, convinced him anew that he had to win this war.
A man who’s life truly had an enormous impact on the health and wellbeing of those alive today.
Dana Goldman–my colleague at PHE and a professor at USC–offers three suggestions on how to prevent generic products from increasing their prices drastically as occurred in the EpiPen saga. In Stat News, he makes three recommendations:
First, Congress should mandate that the Federal Trade Commission report on the availability of all such drugs and devices by identifying all the companies that make them and how they are being supplied to hospitals and pharmacies.
Second, the Food and Drug Administration should examine the FTC report to discover which essential products have competition or supply issues. When supplies are limited — epinephrine has been on a drug shortage list since 2012 — the FDA should be given new authority to allow foreign imports to solve the immediate crisis. In the case of the EpiPen, that would result in prices roughly one-quarter of Mylan’s US listed retail charge.
Finally, the Centers for Disease Control and Prevention, which has experience buying vaccines to prevent supply problems, should be authorized to begin buying essential generic drugs and devices on behalf of federal users, including Veterans Affairs, Medicaid, and Medicare.
Fostering competition is the best approach for driving down the price of generics. When that fails–perhaps due to the prescence of a natural monopoly or limited number of suppliers–then some additional government oversight may be necessary.
Wearables, digital medicine and ‘beyond-the-pill’ are the latest healthcare craze. New technologies–particular those combined with patients mobile phones–offer the promise of improving patient health. One question is will insurance companies, the government and other payers actually reimburse for these technologies. According to a recent FiercePharma article, the answer is yes…if there is evidence.
Payers say they’re willing to reimburse for digital health technologies, the health economics consultancy Xcenda found in a recent survey. But they need proof first. “Payers want to see the clinical effectiveness of these digital health technologies and they want to understand the cost effectiveness,” Xcenda President Tommy Bramley told FiercePharmaMarketing in an interview.
That may be why many payers are evaluating technologies, but few of those surveyed are currently covering them. Digital health purveyors, including pharma, need to better demonstrate the clinical and economic value to payers, Bramley said.
Evidence is key to demonstrating the value of these new technologies.