Improvement of pain physicians' practices of opioid management: population-based urinary excretion data.

2017 
Background: Physicians treating patients for chronic pain have limited means of determining whether a person is taking their medications as prescribed and are not taking extra medication. Complicating patient treatment regimens is the fact that pain physicians’ prescribing practices may come under scrutiny by the Drug Enforcement Agency and other licensing agencies. If questioned, doctors can be hard-pressed to substantiate that their particular practices meet the established standard of care. It would be helpful to establish that their patients adhere to medications when compared with other practices. Previous studies show that urinary excretion data transformed by mathematical models can produce a reliable range of expected values for pain medications and may be useful to help resolve the aforementioned issues. Purpose of the study: To provide comparative urinary excretion information data on three commonly prescribed opioid medications (morphine, hydrocodone, and oxycodone). Methods: This retrospective study involved quantitative analysis of 300,000 urine specimens for three test drugs using previously described methods. The results were analyzed as percent frequency distributions and logarithmic functions. Results: The authors established a creatinine-normalized range of urinary concentration values for each drug. Results for two practices were compared with the meta-findings, providing quantitative evidence of overall standard of care prescription practice by that physician. Conclusions: Expected urinary drug excretion values for morphine, hydrocodone, and oxycodone can potentially benefit pain physicians by showing that they are within the expected standard of care, helping to establish patient compliance, and identifying patients whose metabolism of these drugs may put them at risk.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    2
    Citations
    NaN
    KQI
    []