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Restrictive Drug Distribution Program Improves Rate of Transmucosal Fentanyl Prescriptions

June 11, 2019

By Julie Gould

will fleischmanWilliam Fleischman, MD, MHS, director of Quality and Implementation Science at the Hackensack Meridian Health System, explains how a restrictive drug distribution program reduced the rate of TIRF prescribing and he identifies the critical role pharmacists play in patient safety.

Please tell us a little about yourself.

My name is William Fleischman. I'm an emergency physician. My official title is Director of Quality and Implementation Science at the Hackensack Meridian Health System. I'm in the Department of Patient Safety and Quality.

My research interests which I have been working on since I was a resident and a fellow at Yale were primarily around things that influence physician decision‑making.

The specific domain of which most of my research has been has been around influences on physician decision‑making related to prescribing, and specifically, influences from pharmaceutical manufacturers.

Can you briefly discuss the rate of TIRF prescriptions prior to the REMS program implementation?

My colleagues and I have published studies that have shown associations between how pharmaceutical manufacturers market their drugs and how physicians prescribe them, essentially showing that there are strong associations between payment ‑‑ meaning lunches, dinners, and so on ‑‑ and the subsequent prescription of this medication that was being marketed.

This study came not directly out of a desire to study the tie between payments and prescribing but related to how the FDA was trying to influence physician prescribing by way of this REMS program and others.

REMS programs specifically related to opioids have not been studied rigorously to see whether the REMS program had an impact on prescribing and this is what we wanted to look at, this is why we wanted to look at this.

People are constantly proposing new, different types of programs to try to improve prescribing for opioids. We are building programs based on previous programs, but nobody has ever looked at whether the previous program was effective, which seemed a bit odd to us, and that's why we took this under to study.

Of note, as I mention in the paper, when we did this study, I, myself, and one of the other authors were employees of CMS, and one of the other authors is also an employee of FDA. There's obviously conflicts of interest and biases that need to be acknowledged.

In terms of the rate of TIRF prescriptions before the REMS program implementation, there were decreases. If you look at the graph, there is a decreasing rate of prescription in the years prior that is statistically significant. The trend is statistically significant.

Although if you break it down a little further, the analysis looks at before/after because that's how we designed it. In the year before the REMS was implemented, the trend is relatively flat.

Following the start of the TIRF-REMS program, how has TIRF prescribing changed?

What happened after implementation is that there was an immediate 27% decrease in the rate of prescribing to Medicare patients. This lasted for approximately a year, after which the rate started creeping up, and eventually went close to and occasionally surpassed the initial levels before the REMS was implemented.

Like we talk about, why this happens is something of course we can't prove one way or another. Just for the rate of prescribing, there are some suggestions and hints that a certain drug ‑‑ Subsys, one of the TIRF drugs ‑‑ may have been responsible for that increase.

There have been lots and lots of news articles talking about the illegal marketing that Subsys undertook, the bribery, the just incredibly shady practices that they employed to try to increase sales of their product.

This is one of the possible explanations, in the time frame we looked at, for why the REMS didn't persistently decrease prescribing of TIRF drugs for the Medicare population.

To make a couple points of what we found in terms of the impact of REMS ‑‑ I don't want to say effect because this is not a randomized, control trial. We're looking at association, so this is correlations and impact, but it's not absolute proof.

We looked at whether the REMS changed the percentage of prescriptions to patients without cancer because of the REMS educational materials.

One of the key points of the TIRF‑REMS educational program is that TIRFs are only approved by FDA for patients with cancer. Reports before our study and our study both show that most prescriptions and most patients who get TIRF medications do not have cancer.

From what we saw, there either was no change or there might have been a very small, modest change, a seven‑percent change. It all depends on how you define cancer.

If you define cancer as happening in the year that that prescription was prescribed ‑‑ meaning that there was a documented claim related to cancer in the year the prescription was prescribed ‑‑ then there looks like there were no changes related to the percentage of prescriptions prescribed for non‑cancer patients, meaning the TIRF‑REMS program did not appear to impact off‑label prescribing.

However, If you make the definition much broader, if we're going to say that anyone whose had cancer during the entire study ‑‑ the entire five years that we studied ‑‑ that that's the time period that we're going to define cancer by, then the TIRF‑REMS program may have DEcreased the off‑label prescribing by about seven‑percent. This is a relative number, not seven‑percent whole. It's a pretty modest reduction if it had an effect on it.

Lastly, the other main outcome we looked at was the percentage of prescriptions that were written for patients who were not opioid‑tolerant.

This is incredibly important because patients who are not opioid‑tolerant are the most at risk for being harmed by these drugs. If you're not opioid‑tolerant then one whiff of these incredibly powerful opioids can kill you.

From our data, it looks like the REMS program was associated with a pretty meaningful decrease in the percentage of prescriptions written for those type of patients who are not opioid‑tolerant.

We found approximately 22‑1/2‑percent relative decline in those patients and that the trend continued to decline. If you look at Figure 4 of the paper that shows that change, so it looks like the program did have a beneficial impact for that outcome.

What role does a pharmacist play to help ensure patient safety?

I think they're critical. I'm not a pharmacist, but what I understand a pharmacist to be is really the last line in defense of the patient's safety and the patient's well‑being.

If a clinician prescribes a medication that is inappropriate either by mistake or intentionally, the pharmacist is the last line of defense for the patient's well‑being.

They have a right, and they should take this seriously, where they should not dispense any medication they think can be harmful for the patient. Which is why the TIRF‑REMS program was designed where the pharmacists are just as important a cog in the program.

The clinician, the patient, the pharmacist, and the distributors all have to sign up and be involved in this program. At each of those steps, you can have a stop, and the pharmacist is supposed to be and act as important a stop as the physician.

If a pharmacist doesn't think that a patient is opioid‑tolerant then they should absolutely not dispense their medication no matter what the clinician writes a prescription for.

What are the major takeaways from your study? How do these findings improve patient outcomes? 

Major takeaways from the study. The REMS program for TIRF seems to have had an immediate impact, and depending on the outcome you're looking at, may have had a lasting impact on prescribing.

It is clear that these programs can impact prescribing, but it's also clear that these things can be subverted. If a company, if clinicians have ulterior motives, they can subvert the program.

It is vital, it is incredibly important when you implement a program like this to have really close monitoring of the operation of the program and of the data that's coming out of the program to identify very quickly whether there are people and companies and so on that are subverting the program and patch it right away.

We studied this several years after the program was implemented. The FDA also had internal data according to a study that was published about month ago in "JAMA," showing that the program may have had some gaps, but modification to the program only is happening now seven years after the program was implemented.

One important lesson is that these programs, after they're implemented, they need to be more agile in responding to the world around them and to how bad players and bad actors may be adjusting to the program, and then go on and modify the program to address those gaps. So that's one major lesson I would take away from the study.

The findings show that it's possible to impact meaningful outcomes with such a program. For example, the fact that it appears that the percentage of prescriptions written for patients who are not opioid‑tolerant decreased and persistently so is a very encouraging sign.

What knowledge gaps still exist among TIRF prescribing?

In terms of knowledge gaps that still exist for TIRF prescribing, that is a good question. I would say our study is limited to Medicare patients only. It's actually a subset of Medicare patients because it's only patients who have Part D prescription.

We know that most prescriptions written for these drugs are not for Medicare patients. You've got a company like Subsys that made hundreds of millions of dollars in profit.

From Medicare patients alone, they would not survive, so obviously, most prescriptions are not written for Medicare patients, for Part D patients.

If public health researchers had access to data on these types of prescriptions beyond Part D, it would be helpful to do this kind of research on those patient populations to see who is getting these medications and where interventions can be implemented to prevent harm.

Some of the other things that stand out, a few other points that stand out from the study is the one I mentioned already that most patients did not have cancer.

The fact that patients who don't have terminal diseases are being prescribed these potent opioids is something that can be used almost as an identifier for a population that's at incredibly high risk for addiction, to highlight them to insurance companies, to health systems as folks that could potentially benefit from help with opioid addiction.

The other thing is, in a similar vein, nearly 80‑percent of prescriptions for TIRFs in Part D were for patients who were younger than 65, which is a very surprising number I have to say. Medicare is generally for people who are above 65.

The groups that are under 65 would be the end‑stage renal disease patients and the disabled patient. Those patients are already at high risk for health issues to begin with.

It points to another very specific population that should be the focus of closer scrutiny by both FDA as well as health systems and other public health organizations.

Is there anything else you would like to add? 

Lastly, I would say this is not the focus of this study, but this is just one more example of an area where a pharmaceutical manufacturer was able to influence physicians and not in a very beneficial way for patients.

Some of my co‑authors and I are publishing a paper in the next few days. This is fine to mention because it's already going to press. We are showing that patients who saw physicians who received payments from opioid manufacturers tended to get higher average opioid doses compared to patients who saw physicians who did not get payments from opioid manufacturers.

We are not alone. There have been other studies showing very similar associations between payments and opioid prescribing. Our study, while not looking at this question directly is also highlighting this intersection between payments and prescribing and how it can affect public health and patient well‑being.

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