By RAFAEL FONSECA, MD & JOHN A. TUCKER, MBA PhD
A Critical Analysis of a Recent Study by Hadland and colleagues
Association studies that draw correlations between drug company-provided meals and physician prescribing behavior have become a favorite genre among advocates of greater separation between drug manufacturers and physicians. Recent studies have demonstrated correlations between acceptance of drug manufacturer payments and undesirable physician behaviors, such as increased prescription of promoted drugs. The authors of such articles are usually careful to avoid making direct claims of a cause-effect relationship since their observations are based on correlation alone. Nonetheless, such a relationship is often implied by conjecture. Further, the large number of publications in high profile journals on this subject can only be justified by concerns that such a cause-and-effect relationship exists and is widespread and nefarious. In this article, we will examine a recent paper by Hadland et al. which explores correlational data relating opioid prescribing to opioid manufacturer payments and in which the authors imply the existence of a cause-and-effect relationship.1
We propose the relationship between transactions between the private sector (e.g., meals provided, consulting payments) and prescribing habits can fall into one of three categories:
|0||There is no cause-effect relationship between these transactions and prescribing habits. Correlative observations may merely be reflections of practice patterns, and likelihood to use a drug category.||No harm exists.|
|Ia||There is a demonstrable cause-effect for transactions and prescribing patterns. However, this relationship is associated with increased use of drugs that have been proven to be an improvement over the current standard.||The effect is beneficial for patients. “Beneficial marketing.”|
|Ib||An adverse causative effect is documented with establishment of causation. There is a possibility of patient harm.||Patient harm occurs because the wrong medication is administered and contravenes medical standards. A minor damage is done but arguably exists, if a physician prescribes a more expensive medication when a cheaper alternative exists.
Hadland et al.: Opioid Prescriptions and Manufacturer Payments to Physicians
The authors of this paper linked physician-level data from the 2014 CMS Open Payments database to 2015 opioid prescribing behavior described in the Medicare Opioid Prescribing Database. They explored the hypothesis that meals and other payments increase physician opioid prescribing by examining the association between receipt of meals and other financial benefits with the number of opioid prescriptions written. Specifically, they found the following:
- A nearly linear relationship between the number of opioid manufacturer-provided meals accepted by a prescriber and the number of opioid prescriptions written. The relevant data is provided in Figure 1 below. Prescribers who received nine meals from opioid manufacturers in 2014 prescribed opioid analgesics at slightly more than 3x the rate of those who accepted only one meal.
- When broken down by physician specialty, those who accepted any payment from opioid manufacturers wrote between 1.2% more and 11% more opioid prescriptions as those who did not accept any such payments (Table 1).
Figure reproduced from JAMA Internal Medicine 2018, volume 178, 861-3 under the Fair Use provisions of Section 107 of the U.S. Copyright Act.
Table reproduced from JAMA Internal Medicine 2018, volume 178, 861-3 under the Fair Use provisions of Section 107 of the U.S. Act.
Hadland et al. conclude that
Amidst national efforts to curb the overprescribing of opioids, our findings suggest that manufacturers should consider a voluntary decrease or complete cessation of marketing to physicians. Federal and state governments should also consider legal limits on the number and amount of payments.
While no cause-and-effect relationship between payments and prescribing habits has been demonstrated by this correlative study, the implication that one exists is made clear in the authors’ recommendations. In our analysis below, we attempt a deeper dive to determine whether such a cause-and-effect relationship exists.
Our View: It is More Complicated than That….
To better understand the issues presented by the Hadland’s correlative study, we undertook an independent analysis of the same data. We repeated the Hadland data extraction from the CMS sources cited in the paper. We associated payments with prescribing behavior using physician name and geographical information as described by Hadland. Despite the lack of detail provided in the publication, we closely reproduced the number of opioid prescribers, the number of opioid prescribers accepting payments, and the total number of payments described in the Hadland paper. The only discrepancy we found between our data and that reported by Hadland is that we found a more substantial total payment amount of $13.1M vs. the $9.1M reported by Hadland et al. We found no simple explanation for this discrepancy, as the total payment amount was consistently about 50% higher than that described by Hadland when stratified by source or by payment type. While we are not able to firmly assess the source of this difference given the lack of a detailed protocol in the paper, we believe that part of the difference may have arisen by including a more comprehensive range of opiate products in our analysis relative to that used by Hadland.
How Large is the Association Between Manufacturer Payments and Prescribing Volume?
Our first criticism of the Hadland analysis is directed at the non-standard presentation of the data in Figure 1. The most widely accepted way to present the relationship between two continuous variables such as payments and the prescription count is a correlation diagram. We present the data in this manner in Figure 2 (Note the logarithmic Y axis). Doctors who accepted no free meals from opioid manufacturers wrote between 0 and 1000 opioid prescriptions in 2015. As did those who accepted 50 or more.
Figure 2. Correlation Diagram Relating Number of Opioid Prescriptions Written to Number of Drug Maker Meals Accepted
This graph gives a very different impression than the presentation of the same data in Figure 1. Why is that? Here we have shown every data point, though some are hard to see because there are so many of them (345K to be exact). In Hadland’s presentation of the data, they grouped the prescribers into categories based on the number of meals that they accepted. They calculated the mean for each group, which hides the tremendous variation in prescribing behavior within each group. The error bars are shown in Hadland’s figure are not standard deviations (a measure of within-group variation) but standard errors (A measure of how precisely the mean has been estimated). The latter value is derived from the former by dividing by the square root of the number of data points, which ranges as high as 8468 for some of the categories in Hadland’s figure. So a clear representation of within-group variation would show error bars as much as 92-fold larger than those shown.
A similar criticism can be directed at the presentation of the data in Table 1. Comparing mean prescribing rates between those who accepted any payment and those who accepted none gives a non-representative picture because the distributions are highly skewed. Imagine a cancer trial in which 5 patients live 2, 3, 3, 4, or 20 months. Reporting that the average survival was 7.5 months and the standard deviation was 8.3 months really doesn’t give a very meaningful picture of what happened in the trial. Similarly, Hadland et al. report that physicians who accepted payments in 2014 wrote 539 +/- 945 prescriptions in 2015, while those who did not wrote 134 +/- 281. Who are the physicians who wrote less than zero prescriptions in 2015, and what does a negative prescription look like? This type of bizarre result arises from applying statistical methods appropriate to a normal distribution of values to a data set that is decidedly non-normal.
The problems become even more apparent when we compare these numbers to the authors’ statement in the text that those who accepted payments in 2014 increased their prescription count in 2015 by 1.6, while those who did not accept payments in 2014 reduced their prescription count by 0.8. How is the difference (2.4 prescriptions) equal to 9.3% of 134 prescriptions (Table 1)? And doe a relative increase of 2.4 prescriptions per year from a base of 539 prescriptions merit publication in JAMA Internal Medicine and a call for legislation?
Are Drug Companies Paying Doctors to Write Prescriptions?
While the correlation between meals and opioid prescriptions is much weaker than implied by the figures presented in Hadland et al., a reasonable person might still object that ANY exchange in which prescriptions result from a conscious or unconscious quid pro quo for free lunches is morally unacceptable (Type Ib). We would certainly take that position. So let’s analyze whether the relationship is causative or merely correlative. Hadland’s implicit hypothesis is that doctors are writing opioid prescriptions in “exchange for pizza.” An alternative explanation might be that attending manufacturer informational sessions at which meals are served and prescribing opioids might both be driven by having a practice that involves treating many pain patients. Let’s look at the data and see if we can distinguish between these possibilities.
- If Doctors are writing prescriptions in exchange for payments, one would expect that the number of prescriptions would rise predictably with the payment amount.
In practice, we find this is not the case.
Regressing the number of opioid prescriptions written on total payments received, we find r2 for the correlation is 0.01. Thus only 1% of the total variation amongst prescribers is associated with variation in the amount of payment received. (The gap in the graph between $0 and $10 arises because CMS does not require reporting of payments below $10).
Figure 3. Relationship Between the Number of Opioid Prescriptions Written and Total Payments Received
- If doctors are writing prescriptions as quid pro quo for industry payments, one would expect that non-meal payments would show a correlation with prescribing similar to the correlation with meals shown in Figure 1.
Alternatively, if both attendance at educational sessions at which meals are served and opioid prescribing are driven by having a practice that involves treating many pain patients, one might expect a very modest or no correlation of prescribing with non-meal payments.
In practice, we see the latter (Figure 4).
Figure 4 was drawn using Hadland’s categorical style of presentation to allow direct comparison to Figure 1. While Hadland found that opioid prescribing tripled as the number of industry-sponsored meals increased from one to nine, we find no trend in toward increased prescribing among those who received between $0.01 and $65,536 in non-meal payments from opioid manfacturers. In fact, the geometric mean rate was nearly identical for those receiving less than $1 in non-meal payments (711 prescriptions) and for those receiving $32,000 to $64,000 (718 prescriptions). For the 58 physicians who received more than $65,536, the rate of prescribing was increased by nearly twofold relative to those receiving less than a dollar, but due to large within group differences, this difference was not statistically significant.
The fact that opioid prescribing correlates with the number of meals accepted but not with the total amount of non-meal payments received suggests that attendance at educational events at which meals are served and opioid prescribing are both driven by practice characteristics. In contrast, these data are difficult to accommodate within the theory that the association of prescribing rates with meals accepted is due to quid pro quo, or that companies are bribing doctors to prescribe their products.
Figure 4. Geometric Mean Prescribing Rates by Total Non-Meal Payments Received
- If doctors are writing prescriptions in exchange for free meals, one would not expect meals provided by the manufacturer of non-opioid pain treatment to be associated with increased opioid prescribing. If doctors with large pain practices are more likely to attend informational lunches about pain products, such an association is expected and natural.
In practice, we find that the association of increased opioid prescribing with attendance at informational lunches offered by the manufacturers of pain therapeutics is independent of whether the pain product is an opioid!
St. Jude Medical is a medical device company that sells neuromodulation devices for the treatment of chronic pain. Those who attended St. Jude lunches prescribed opioids at the same rate as doctors who attended an equal number of lunches sponsored by opioid manufacturers. This observation holds up equally well when looking only at those who attended St. Jude lunches but did not attend any opioid lunches. We found similar associations with lunches provided by manufacturers of other non-opioids products (data not shown).
Figure 5. Relationship Between Attendance at Industry-Sponsored Lunches and Opioid Prescribing: St. Jude vs. Opioid Manufacturers
Correlation is not causation. While many advocates of reduced interactions between “commercial” interests and physicians have implied or directly suggested a quid pro quo between industry meals and other financial interactions and prescribing habits, correlation alone does not prove a quid pro quo relationship. In the case of opioid prescribing, we believe that we have presented a strong case that 1) the relationship between industry payments and prescribing is much weaker than has been presented in the literature, and 2) that prescribing and attendance at manufacturer-sponsored informational lunches are both driven by practice characteristics, rather than the meals themselves driving prescriptions (Type 0 relationship).
We believe that much of what has been published regarding the correlation of prescribing with industry payments and sponsored meals suffers from the shortcomings described in this short note. In particular, many of these papers conflate causation with correlation. In cases where fairly simple and obvious analyses would serve to differentiate between the authors’ preconceptions and alternative interpretations of the data, these analyses have not been performed. We urge all with an interest in this area to approach these data with the highest possible level of objectivity, as is our responsibility as scientists. We have done our best to do so here, and commit to doing so in our planned analyses of other papers in this area.
We look forward to a stimulating debate with those who have other data bearing on this issue, or other interpretations of the data presented herein.
Hadland SE, Cerdá M, Li Y, Krieger MS, Marshall BL. Association of pharmaceutical industry marketing of opioid products to physicians with subsequent opioid prescribing. JAMA internal medicine. 2018
. This analysis, as well as alternative analyses performed by the present authors, was limited to the prescribing behavior of those who wrote at least ten opioid prescriptions in 2015 due to redaction of counts between 1 and ten by CMS.
Rafael Fonseca is a hematologist at the Mayo Clinic in Arizona.
John Tucker is a medicinal chemist residing in Northern California.
(Disclosures: Fonseca is a consultant to AMGEN, BMS, Celgene, Takeda, Bayer, Jansen, AbbVie,Pharmacyclics, Merck, Sanofi, Kite, and Juno, and is on the Scientific Advisory Board of Adaptive Biotechnologies)
Well written. Digital technology is advancing exponentially. Today healthcare is moving toward a completely new age of patient treatment, health monitoring, and management. Solutions like patient referral management, chronic care management, and care management will be of help for quality patient care and better patient outcome and also for improved operational efficiency.
So if docs go to meetings with meals about pacemakers, they use more pacemakers. If they go to meetings with meals about opioids, they prescribe more opioids. The conclusion then is that since meals increase both pacemakers and opioids we should continue having meetings with meals to increase the sales of opioids.
Well Steve, that would be a devastating rebuttal if the article had said anything at all about pacemakers or pacemaker prescriptions.
What we showed is that the correlation of increased prescribing of opioids with sponsored meals is independent of whether the sponsor sells opioids or not. The meal only needs to be associated with products for the treatment of pain.
The “bribery” model doesn’t provide a good explanation for why doctors who attend lunches about anti-pain neuromodulation devices would prescribe more opioids than those who don’t. The observation is, however, explained very nicely by the “Practice characteristics determine both meal attendance and opioid prescribing” model.
I hope you’ll read the article again, doing so with an open mind to the data this time.
I suspect that the practice patterns of a physician’s community peers also plays a role.
St Jude doesn’t make pacemakers anymore? Pretty sure they do. Where are the cardiologists when I need one? Anyway, I am all for better studies, so lets hope we see them. That said, I am pretty sure that the best data on whether meals and rep visits increase sales already exists and is owned by the drug companies. The fact that drug companies want to make money, and they are very successful at it, suggests that they think the meals increase sales.
They do sell pacemakers Steve, but if you had read the paper before criticizing it you would have seen that the specific meals were related to neuromodulation devices for pain treatment and the increased prescriptions shown in the chart were for opioids, not pacemakers.
If you would care to critique the analysis in the paper, we would be happy to discuss any concerns or objections. Of course in order to do that you’ll have to actually read it. There doesn’t seem to be much value in continuing to respond to criticisms of things that aren’t actually in the paper.
Thank you for this hard work and excellent presentation….and a happy conclusion (for us docs.)
Unfortunately, there is still many sources of bad smells coming from the pharmaceutical barnyard:
1. Why should there ever be any money or value going from drug sellers to doctors? How is the prescribing of a drug for a patient any different from the use of another physician in a referral? To have that referral physician pay the referring doc any dough is an illegal kickback. To have the drug firm pay the doc for getting the prescribing order is also a kickback.
2. Why do we let PBMs set up formularies? We are the ones that use the drugs and know best their attributes and problems. The PBMs are business people who are there for one reason only: to facilitate oligosonic purchasing (large dominant purchasing.)
3. Why is money going from the manufactures to the PBMs? Answer: to pay them for getting drugs on the formularies. Do you like this practice?
4. Why is money going from the PBMs to the hospitals? Not only PBMs, but GPOs—group purchasing organizations—send kickbacks to the hospitals? This whole industry is highly secretive and is costing patients a lot of extra money. Why do our professional organizations not dig into these kickbacks thoroughly and get us informed? Are there kickbacks to our own associations?
Ask your hospital about money coming from GPOs: Vizient, Premier Inc.,HealthTrust and Intalere. And the same question about PBMs: Express Scripts, CVS and OptumRX.
Well, first I don’t think pharmaceutical companies particularly like paying PBMs. Why do you pay money to someone who holds a gun to your head? Isn’t that supporting and encouraging crime? One does it because the person holding the gun has the power to wreak tremendous harm if one does not accede to their demands.
“Why is any value at all going from pharmaceutical companies to doctors?” Lots of reasons. In the case of lunches, to get them to come and hear a pitch. In the case of consulting contracts, because their input is valued and because they won’t work for free.
I think we did a pretty convincing job here of showing that in the case of opioid prescribing, there is little or no harm associated with current practice. At least not in the form of increased opioid prescribing.
John, your article is superb. But $ $ from pharmaceutical firms==>doctors…..???
We should not be educated by entities that are highly biased. Why don’t medical schools bring pharma in to give lectures? Docs should PAY the firms for the luncheons and talks if we want knowledge and expertise from their manufacturing point of view. This practice would have less conflict of interest.
And BTW, Why don’t the patients get any benefits from money coming from the PBMs and GPOs back to the hospitals?
There is such a complex stink going on that it is like trying to find out who stepped in the dog poo as a big family gets into a car going out to dinner.
The easiest algorithm to use to find the answer to these ethical questions is to ask yourself “What would the patient want us to do?”
I like formularies conceptually because overly expensive drugs can be excluded at least in theory. I also like tiers because differential copays can help to steer both doctors and patients toward less expensive drugs within a therapeutic class usually without sacrificing efficacy.
PBM’s pass the bulk of the rebates they receive on to their insurance company and self-funded employer customers who, in turn, use that money to reduce member premiums from what they would otherwise be. The biggest weakness in the rebate system is that it exposes uninsured patients and patients with high deductible insurance plans to the full list price of drugs within the deductible. United is addressing that issue starting next year for patients with high deductible plans by passing the rebate on to the insured member. Under the current system, the sick subsidize the healthy which is not the way insurance is supposed to work.
Medicaid insures some 70 million people and presumably has no formulary or tier structure. Yet politicians force Medicaid to cover every drug approved by the FDA even if it’s far more expensive and no more effective than another drug to treat the same disease or condition. That’s what can happen when politicians instead of markets make the rules.
That’s precisely why pharmaceuticals are nearly the only product that consumers cannot buy without the intermediacy of a trained professional. If Medicaid were restricting access to a drug that you wanted to prescribe or your doctor wanted to prescribe for you, the complaints would be loud and full of outrage. The responsibility for these decisions should not lie with Medicare, but with doctors.
Don’t you think payers should be able to push back against drug companies that grossly overprice their drugs? Unfavorable formulary placement and refusal to cover a drug deemed too expensive are the only tools payers have to combat price gouging. Patients can self-pay if they can afford to or can try find a charity to pay on their behalf. Doctors, for their part, historically didn’t consider knowing or caring about costs as part of their job unless the patient brought it up as an issue.
Well, I think they do. Private insurers definitely have formularies. The government gets the full advantage of this without restricting access because pharmaceutical companies are required to give the government the “best price” negotiated with any private payer or a fixed discount (I think its 23%), whichever produces the lower price.
“I would very much want my doctor to get all the information they can from every available source.”
No you don’t. You want your doc to get all the info they can get from reliable, non-biased sources. For example, you don’t want to get your information about vaccines from Wakefield or that actress, whatever her name is. You don’t want to get your information on treating breast cancer from Suzanne Summers. Drug companies clearly have a vested interest in presenting data that tells a story sympathetic to their product, not necessarily the entire story. Since many physicians seem to think that they are immune to being influenced by stuff like free meals, they should know that is not necessarily true. At the very least, they should know that the drug companies think it works.
PS-If I am wrong we can expect drug companies to give up this practice.
Unless of course there is a new drug that could substantially improve the treatment of your pulmonary hypertension, and your doctor hasn’t heard of it because she works 60 hours a week, has a family, and doesn’t always find time to read the literature. I interviewed non-academic neurologists 2 months before dimethyl fumarate was approved for multiple sclerosis. The Phase 3 trials had been published in the NEJM, but none of them were prepared to discuss it because they had not heard of it.
Allow me to offer a thought experiment.
You’re walking through the subway station and you see someone giving away pizza. You’re hungry and you walk over to see what’s up. It turns out that they’re recruiters for Greenpeace. You chat with them to be polite while you’re eating the free pizza that they have you, and in the course of the conversation, become convinced that global warming is an pressing and important threat that will destroy the quality of life for our grandchildren and hundreds of generations thereafter.
You join the organization and spend hundreds of hours working to raise awareness of the issue among the public and to help elect pro-environmental candidates. You stop voting for candidates who you previously voted for because of your agreement with their position on economic issues, because you’ve decided that the environmental issue is more important in the long run.
Did Greeanpeace just buy hundreds of hours of your time with a slice of pizza?
Are you a “shill” because you’re campaigning for an organization from which you’ve received a slice of pizza?
Are you guilty of selling your vote for financial considerations, a violation of federal law?
Of course not. No one is going to sell hundreds of hours of their time, as well as their vote, for a single slice of pizza. Its not credible. However they will more likely come over and hear what you have to say because pizza was being given away. And the fact that the relationship started with eating pizza while hearing a pitch doesn’t turn everything downstream from that interaction into shilling and vote-selling.
The paper shows that there is no correlation between prescribing and non-meal payments. It would be odd indeed if doctors were willing to sell their prescription pads for $15 worth of pizza but not change their prescribing habits over a $5K consulting contract. As an economist might point out, they could always take the $5K and buy a LOT of slices of pizza.
The most logical explanation is that pizza is an inducement to listen to a pitch, not a bribe to write prescriptions.
I hope you’ll read the paper. We put a lot of work into it and I think we showed some interesting findings. We all make better choices when we use data to form our opinions rather than using our opinions to decide what data to pay attention to.
Or suppose you accept that slice of pizza from a group advocating high dose vitamin therapy for breast cancer. You follow their advice and die. So, I actually did read your paper, just not that impressed (nor by the original for that matter). Where I will agree is that what is being bought (mostly) is access. What I think is clear, is that access works. While physicians are often guilty of believing that they are not influenced by these kinds of events, or small gifts, I think we are probably influenced just about as much as most other people. I would point towards the literature on provider induced demand as evidence that we are influenced by financial considerations.
Finally, pharmaceutical companies have been very profitable for a very long time. They believe that offering meals helps them to sell their products. I am inclined to believe them as it makes sense and comports with what I observe in my fellow human beings and physicians. So when we put this paper in context, it is drawn from data in 2014 and 2015 if I am reading it correctly, This was at a time when we were realizing that we have an opioid crisis on our hands. Looking at our priors, I really would not have expected to see any influence. The fact that buying access mean that there was even a small increase is surprising to me, but it turns out the drug companies knew better. Buying access worked. One wonders what these numbers would have looked like back 10-15 years ago when these drugs were being sold as having little risk of addiction? So, as I always tell the medical students, we should rarely base much of what do just upon one study. I will await other, more convincing evidence.
“While physicians are often guilty of believing that they are not influenced by these kinds of events, or small gifts, I think we are probably influenced just about as much as most other people”
Thats a nice hypothesis, but its incompatible with the data, at least in the context of what we studied here. We showed that 1) there is zero correlation of Rxing with non-meal payments, and 2) that the correlation of opioid Rxing with meals is identical whether the meals are provided by an opioid manufacturer or a manufacturer of a non-opioid pain therapeutic. Can you explain how your hypothesis incorporates this data?
“One wonders what these numbers would have looked like back 10-15 years ago when these drugs were being sold as having little risk of addiction? …..So, as I always tell the medical students, we should rarely base much of what do just upon one study. I will await other, more convincing evidence”
The selective skepticism here is interesting. You dismiss the data analysis we’ve conducted as “unconvincing” though in six posts you’ve offered no specific criticism of the methodology. On the other hand, you are perfectly happy to cite speculation about what might have happened 15 years ago as evidence in support of your position. But this is not surprising given that you posted a snarky comment criticizing the study before you had even read it. I’d urge you to think about this behavior and what it says about your approach to data. It seems clear to me that the definition of a “convincing” study in this case is one that supports what you already believe.
As scientists I think its important to form our opinions from objectively looking at the data, rather than using our opinions to decide which data is worthy of consideration.
So I sat down with a couple of my pain docs and asked them why they would order more opioids after going to a St Jude meeting. If these were implantable pumps, then they would have expected more narcotic prescriptions because they would order them to treat the pain caused by pump placement. Given the time period, I would guess this was St Jude selling DRG stimulators, so what we are probably talking about is surgery. The goal may have been to teach people to use stimulators, or sell them, but like many other surgical procedures, it also results in the use of more narcotics.
Which is interesting, but still not sure how relevant it is. You have documented an increase in narc prescribing that increases along with the number of meals attended, at a time when we should expect there to bed little or no effect. If you read the medical and health policy literature widely, there are many instances of financial interests influencing physician behavior. I would suggest you start with Provider induced demand.
I would very much want my doctor to get all the information they can from every available source.
As a biotech stock analyst, its my job to predict whether drugs in Phase 2 or Phase 3 will give good results and eventually get approved. What is the first place I go to when I start learning about a new drug? The company that is developing it.
Hearing what the company has to say is a fantastic place for me to start. I hear the “bull” case for the drug, and all that means. Its the “best possible case” story, and its full of spin. Having that as a starting point, I go to the literature and attempt to objectively evaluate what the company is claiming.
I’d honestly feel lost if I didn’t have access to company websites. It gives me an organized picture of what the company’s claims are. I don’t take those claims at face value, but taking their story and deciding for myself how much of it is realistic is the fastest way for me to get the big picture of what is going on.
As for “pharmaceutical $$ => doctors”….
1. Doctors are an important part of developing new drugs. How would you propose to do that without input from the best and brightest? For the most part the very best don’t want to be employees, and they won’t work for free either. Your fire wall will hurt drug development.
2. As for meals, well, in the present case we’ve found no evidence for harm. What I would ask you is this: If a $10 Subway sandwich is going to influence a doctor’s prescribing habits, what should we do about doctors recommending and then being paid hundreds to thousands of dollars to perform procedures? I find it strange that so many people think the definition of COI requires the use of the word “pharmaceutical”. If $10 lunches change medical practice, I shudder to think how many of the cataract surgeries, prostatectomies, and hysterectomies done in this country are unnecessary. At hundreds to thousands of dollars a pop, I’d have to conclude the vast majority of them.
Personally, I use the ProPublica Dollars for Docs database to find physicians when I’m looking for a specialist. When it comes to research funding at least, pharma doesn’t fool around with amateurs. The docs I worked with when I was in industry were among the finest I’ve known. I see the database as a list of physicians that pharma has vetted on my behalf, as these are the people they want to work with, and they have vast resources for finding the best people. So far, I’ve never been disappointed.
The shenanigans of Big Pharma can be best understood by an understanding of its basic business model: 40% of cash revenue equals profit margin plus promotion expense. Its total promotional expense is second only to the beer industry. As Chairman of a hospital Formulary Committee (initially one hospital and ending with >10 hospitals) for 20 years, nothing would surprise me.
Since it probably requires @$1 Billion to bring a new medication to market, this Paradigm is unlikely to be changed if we really want the newest and the best medications, entrepreneurship at it fullest magnificence. Similarly, the business model for physicians varies from physician to physician AND from state to state.
Actually most industries that have a high dependence on new product development for financial viability spend a lot of money on marketing and also have high profit margins. Microsoft, for example, spends 22% on SGA and earns 20% net profit. Adobe spends 43% on marketing and earns a net profit of 17%. Adidas spends 40% on marketing and takes home a net of 10%.
I agree with you that costs are too high throughout our healthcare system. As it sounds like you are in a fairly senior role at the institution you work at, I’d urge you to do your best to address costs there as well. A quick perusal of the hospital form 990s shows that at a typical 200 bed community hospital, the cost of paying the executive management comes to several hundred dollars per bed night. Clearly the costs are unsustainable throughout the entire system.
Wow! Magisterial! Well-done!