Definition 4/4: Maximum Daily Dose
The "CDC Method" ignores dates and days supply for max single-day exposure, used in the CDC Opioid Guideline mobile app.
For reals, does any of this really matter?
Stay tuned: Subtle choices make huge differences.
A Controlled Experiment that mimics an observational policy/intervention evaluation.
Compare 2 places to see which has more "high dose" patients.
Same dataset, same conversion factors.
The ONLY source of variation comes from the4 definitions ofdaily MME.
Methods. PDMP data for 3Q2018.
9,436,640 opioid analgesic prescriptions
California n=5,677,277
Florida n=3,759,363
3,916,461 unique adult residents
California n=2,430,870 (7.9 per 100 residents)
Florida n=1,485,591 (8.7 per 100 residents)
3-fold difference in which patients are considered high dose between D1 and D4. Both are described in published papers as the "CDC Method": 5.9% vs. 14.2% (FL)
Arbitrary definition choice impacts hundreds of thousands of patients with painful conditions.
4 policy/intervention evaluations on the SAME DATA with the SAME CONVERSION TABLES wouldn't agree how many more "high dose" patients were in FL: 64%, 59%, 84%, or 39% more
Any of these means or medians could have been justified scientifically. SAME DATA but 8 different results. See? Subtle choices have huge consequences.
Would we say that doses are similar (1 mg difference) but lots more "high dose" patients in FL?
or
FL has a bit more "high dose" patients, but they are getting A LOT more (13 mg)?
Imma a say it again: Subtle choices have huge consequences in what we infer.
Why is this happening? Overlapping prescription days supply has a lot to do with it.
Epi/stats folks, beware. Changes in US prescribing patterns mean that certain definitions (D1) will attenuate intervention effects over time!
If you shift the “high dose” threshold from 90.9 to 90.0, you increase the number of “high dose” patients by 15.4% (CI: 15.2%, 15.7%).
If an insurance company and physician use 90.0 vs. 90.9, they would disagree on "high dose" status in 1 out of every 30 patients with D4.
Which definition to use? I like D2 in general, but D3 is good for long-term use because it is more robust to misclassification. Do not use D1. If toxicity is short-term in opioid naive patients, D4 could possibly maybe be sorta acceptable.
We are building a tool for research decisions. We need beta testers! DM or email me if you're interested.
"And while everyone debates whether the MME limit was the right thing to do, we are forced to live by it, because medical personnel treat guidelines as mandates. So we wait. And we suffer. And we hope it will all get sorted so we can get the care we need.” Liz Joniak-Grant
Or, as one patient put it to me when I showed them the results: "It's f--king arithmetic. Get it right."
Limitations of our study are here. We don't recommend using these conversion factors naively for clinical decisions, either.
If a study doesn't sufficiently define how they calculated MME per day, I don't read the results.
These results will be published in @ClinJrnlPain (Clinical Journal of Pain) in a couple of weeks. Paper has been accepted and proofs are being typeset one last round. And yes, it'll be free open access. In the meantime, check out OpioidData.org for details.
Thanks to our talented illustrator-in-residence @brittainpeck for breathing visual life into technical medical concepts. Feel free to use any images or slides.
In closing, if you are a researcher, please please please state your definition. Feel free to reuse our equations or slides. In this way, we can be allied with patients to reduce the most harm, with the best information.
Would love @VetFinals to provide clinical insight too
@JessTilley7@mary_figgatt@WeezieBeale@nc_usu@VetFinals 2. At issue is this flyer where we say "Naloxone works on opioids. It may work on xylazine, but the evidence is unclear. Always use naloxone in the event of an overdose."
@JessTilley7@mary_figgatt@WeezieBeale@nc_usu@VetFinals 3. Xylazine is called a "sedative" but is in a different pharmacological family from benzodiazepines. It is not an opioid. It's legit to think naloxone might work on xylazine alone. So let's unpack that from the perspectives of pharmacology, veterinary med, and street drugs.
I'm seeing epidemiologists make a logical fallacy about the COVID vax + blood clots. Saying the risk (or rate) is "1 in a million" = misleading
Here’s a quick breakdown on how to do better by #pharmacovigilance (PV) stats
Audience: #epitwitter#datascience#RxEpi
2/ Comparing to birth control risks isn't proper. The *type* of clot is different. But also, quantified risk of clots from The Pill are from studies where each patient was assessed for the outcome (side effect). That's not so with COVID vaccine data now
3/ In some of the COVID vax clinical trials, only 1-out-5 had systematic detailed assessment of side effects. For the other 80%, the trials relied on "spontaneous reporting"
During a global emergency, making clever use of existing resources is a fundamental human impulse. But, the cavalier repurposing of hydroxychloroquine, chloroquine, and azithromycin during the COVID-19 pandemic has consequences.
"Is silence better than getting it wrong?" when it comes to emerging medication safety issues for patients - Priya Bahri asks of #drugsafety at #ICPE20