As a non-clinician patient advocate and health care writer, I am frequently reminded of a quotation attributed to Samuel Clemens (Mark Twain): “Figures don’t lie. But liars figure.” I am also aware of a second quotation from economist Ronald H Coase: “If you torture the data for long enough, it will confess to anything.”

I find that both quotations apply directly to the U.S. Centers for Disease Control and Prevention (CDC) with respect to prevailing public health policy on the treatment of acute and chronic pain. Abundant published data demonstrate a fundamental lack of relationship between clinical prescribing of opioid pain relievers, hospitalizations for opioid toxicity, and deaths in which a prescription opioid is believed to have contributed. Much of this data is published by the CDC itself. But the CDC has consistently ignored its own data in favor of unsupported assertions that the U.S. “opioid crisis” was created by doctors prescribing to their patients.

It is time to correct such misinformation.

Two public sources assist us in this project. The first is the National Center for Health Statistics, Multiple Cause of Death database, accessed through the CDC-Wonder interface. The second is also from the National Center for Health Statistics: “United States Opioid Dispensing Rate Maps.”

Cause of death statistics are compiled every month from death certificates filed by County Coroners and Medical Examiners across the U.S. Prescribing rate maps are constructed separately by the IQVIA Institute for Human Data Science™ and likewise reported by the CDC. What is fascinating is that the CDC has for years avoided bringing these sources together. When we do so, we discover relationships very similar to the following chart.

Note 1: Mortality reports for categories T40.2 and T40.4, CDC-Wonder interface. Prescribing rates from CDC Prescribing Rate Maps, accessed December 8, 2023.

In this chart, the independent variable (horizontal axis) is the rate of opioid prescribing reported by each state in prescriptions per 100 population. The dependent variable (vertical axis) is the number of accidental mortality reports per 100,000 population in the 50 states in two categories closely related to prescription opioid drugs:

Mortality is coded from the International Classification of Diseases, 10th edition:

X42 is “accidental poisoning by and exposure to narcotics and psychodysleptics [hallucinogens], not elsewhere classified.”

Sub-category T40.2 is “other opioids,” including over 50 prescription opioids.

Sub-category T40.4 is “other synthetic narcotics,” including 30+ prescription opioids like Tramadol, Fentanyl, and chemical analogs of Fentanyl.

If one asserts that prescription opioid drugs are a significant factor in the widely discussed “U.S. prescription opioid crisis,” then the sort of chart we would expect to see above should show closely clumped data points along a trend line that rises from left to right. But this is clearly not what we observe. We instead see a “splatter pattern” like the blast of a shotgun against a barn door. We all understand the dictum “correlation is not cause.” But we often forget the corollary: “Without correlation, there can be no cause and effect.”

It is also informative to ask whether states with the highest prescribing rates also show the highest incidence of mortality reports where a prescription opioid is believed to contribute. Again, this is not what we see in the data:

In 2020, the top five states ranked by highest prescription-opioid-related overdose reports and those ranked by highest prescribing rates are highlighted in gray. The bottom five states are highlighted in green.

In 2020, none of the top five states ranked by mortality were also among the top five ranked by prescribing. Indeed, prescribing rates in the top five fell below the national average, with New Jersey among the bottom five.

Conversely, none of the top five states ranked by prescribing rates was also in the top five ranked by mortality. Again, the incidence of mortality where prescription opioids contributed is below the national average in states where prescribing rates are highest.

Also of interest is the ratio of mortality reports to prescriptions dispensed, which varies widely, from one mortality report in 1,114 prescriptions (DC) to one in 32,157 (Kansas).

Scatter charts for years from 2006 to 2020 are highly similar to the chart above. The conclusion to which we are inevitably led by this data is that clinicians prescribing to their patients and the prescriptions that they write were never responsible for causing the U.S. opioid crisis – and the current criminalization of medicine by the U.S. Department of Justice is founded on mythology, not fact.

In mid-December 2023, the CDC released a new “Dashboard” for their State Unintentional Drug Overdose Reporting System (SUDORS). The new dashboard narrows the definition of “Prescription Drugs” from 80 identified historically to 23, including Methadone, while also clarifying differences between “legal” and “illegal” drugs. The following is an example “scatter diagram” for “prescription drug deaths in 2020 among 34 states that reported to SUDORS.

Note 1: Dashboard accessed December 20, 2023.

As we might expect, the range of prescription-related death rates per 100,000 population reported by the SUDORS Dashboard for 2020 is somewhat narrower than reported by CDC-Wonder for a larger category of drugs. States with the highest prescription-related mortality rates are also different in the two sources. However, the overall character of the scatter diagrams is quite similar. Trend lines are flat and correlation coefficients are miniscule. Both sources indicate no consistent relationship between prescribing rates and prescription-related mortality.

Thus, we are compelled to understand that prescribing by clinicians is not — and likely has never been — a major driving factor causing the U.S. opioid crisis. The figures don’t lie, even if the CDC does.

Acknowledgements:

This paper has been validated against the clinical experience and research of Stephen E. Nadeau, MD and Jay Joshi, MD, with whom the author collaborated on a one-hour podcast in December 2023. The original concept for comparing prescribing rates to opioid mortality was developed by business analyst John Alan Tucker in 2016 and posted to Twitter that year. However, the author remains fully responsible for the current content.

Richard A. Lawhern is a nationally recognized health care educator and patient advocate who has spent nearly three decades researching pain management and addiction policy. His extensive body of work, including over 300 published papers and interviews, reflects a deep critique of U.S. health care agencies and their approaches to chronic pain treatment. Now retired from formal academic and hospital affiliations, Richard continues to engage with professional and public audiences through platforms such as LinkedIn, Facebook, and his contributions to KevinMD. His advocacy extends to online communities like Protect People in Pain, where he works to elevate the voices of patients navigating restrictive opioid policies. Among his many publications is a guideline on opioid use for chronic non-cancer pain, reflecting his commitment to evidence-based reform in pain medicine.