This year, Washington State has a new law focused on trying to reduce risks associated with prescription of opioids for chronic noncancer pain. The requisite starter links:
- House Bill 2876
- Interagency Opioid Dosing Guidelines
- Medical Quality Assurance Comission’s Rules (MQAC)
Currently the evidence on most of the recommendations in the Interagency Guidelines and the MQAC Rules are based on expert consensus opinion. Most specific guidelines have little/no high quality studies associated. The best summary of the evidence through 2009 (and lack thereof, too):
- American Pain Association Guideline for the Use of Chronic Opioid Therapy in Chronic Noncancer Pain Evidence Review.. (Although it’s ~200 pages, it’s easy to scan.)
- Opioid Risk Tool by Webster can be found on PainKnowledge.com with the scoring template. Much better than the low-quality version used in the interagency guidelines.
- PHQ-9 Depression Screening Tool (or Anxiety) is available for download.
- The ‘CAGE’ screening tool has been modified to include drug use.
- For Specifics of Limitations to Urine Toxicology, the Mayo Clinic Preceedings summary is useful.
- Google: “Employee Drug Testing Ace 12 panel” for an example of a $9 Point of Care Urine Drug Screening Cup.
In 2005, I made a simplified version of Stephen Passik’s PADT (a documentation tool for follow up of chronic pain management:
- The 5 A’s (Documentation Tool)PADT
Opioid Treatment Agreement
MS3 Opioid Lecture (not focused on Washington Pain management Law.)
A while back I gave a lecture to local MS3s. It had a different but related focus. These are DO students and there was one interesting tidbit. I asked, “How many of you have seen a patient where you thought the doctor had prescribed too much pain medicine?” All raised their hands. Then I asked the reverse, too little pain medication. No one responded. Clearly the threshold for opiates in office practice has dropped in the past few decades. But still, it seems like there would be some example of under-treatment. There’s a cognitive bias here, I suspect. Errors of prescription are more obvious than errors of omission.