Chapter 1: Identification of HARMS Program Patients

Now that we’ve covered why a system for UDT might be important, let’s look at the first step in applying it – identification of eligible patients…

One of the challenges when we first started designing a program to apply UDT in CNCP was in deciding who should be enrolled. Unfortunately, the literature supports that our behavioural observations are not enough to identify who is at risk for being harmed by these medications.1,2 As a result, it was decided to apply “universal precautions” to everyone. This is consistent with more recent “expert recommendations”.3 Everyone at our clinic prescribed opioids long-term for CNCP is part of HARMS and is randomized to provide UDT, with a few exceptions.

There is a spectrum between those who use opioids one week per year for a pain flare, and those who take multiple doses every day. Should these patients be monitored in the same manner? While a cutoff using average morphine equivalent dose per day would be a reasonable way to separate who is enrolled in HARMS and who isn’t, it was felt that having physicians calculate this could present unnecessary impediments to physician buy-in. As a result, it was decided to use as a general cut-off “average daily use”. Meaning if the person gets, for example, an average of 30 tablets of Tylenol #3 per month he would be enrolled. The second point of clarification is around what qualifies as “chronic pain”. We stuck with the definition used by CDC and others that it is pain lasting >90 days or past the time of normal healing.4 To summarize:

Averaging daily use of opioid (i.e. averaging ≥1 dose/day, or fentanyl patch, etc.)
Chronic pain lasting >90 days or past the time of normal healing

Palliative and/or cancer pain
Significant mobility issues (i.e. cannot leave house)
Dispensed in a nursing home/supervised setting

When starting the HARMS Program, practically speaking, how might one go about finding all the patients that meet these criteria? What we did, and what we would recommend to others depending on your EMR capacity, is to have clinical administration run a query that generates a patient list. The Association of Family Health Teams of Ontario (AFHTO) has created resources to help guide this, including a pdf EMR Query for HARMS Patient Identification from AFHTO and a website.

The list generated from the query has all patients prescribed opioids, but does not differentiate acute from chronic pain, nor does it identify palliative/cancer pain. At our clinic, we gave each physician this list of his/her patients prescribed an opioid in the last 12 months. The physician then reviews his/her list and removes patients that don’t qualify (in our case, the majority of patients excluded were because they were prescribed opioids for acute pain). If desired, the physician may even assign risk categories at the same time on this same list (see Chapter 2: Initial Risk Stratification), and hand back to clinical administration who will formulate the master list (see Chapter 3: Patient Master Lists – Creation and Maintenance). Patients are then randomized from this master list (see Chapter 4: UDT Selection). We recommend this approach of applying risk categories at the time of enrollment – using the clinical Gestalt to dictate risk category – as it consumes significantly less time than the alternative of applying formal risk stratification tools and/or baseline UDT prior to assigning a risk category. However, if time and energy allow, you may consider using these. While not in clinical use at the time of this 1st edition of the HARMS Manual, a future version of START-IT may also allow automated application of validated risk stratification tool(s).

For patients identified using the query who are “unattached” (i.e. do not have a family physician or Most Responsible Physician – MRP), it is still important to review their eligibility for HARMS. A non-physician staff member may feel comfortable checking this list to see if opioids are prescribed long-term, averaging daily use, and patient has a non-palliative/non-cancer diagnosis. Most patients will once again be excluded because opioids were for acute pain. For patients not immediately excludable, physician consultation may be required. At our clinic, once the list of unattached patients prescribed an opioid was reviewed, we didn’t have any patients prescribed opioids for chronic pain without an MRP.

Additional Resources:
1) AFHTO EMR Query Online Link

2) AFHTO EMR Query pdf for HARMS Patient Identification


Case 1

Mr. Smith is on your opioid list generated by the EMR query. You know that for his chronic shoulder pain he is prescribed oxycodone/acetaminophen (Percocet) at 30 tabs/month for the about three years. He is mobile and working. Should he be a part of the HARMS Program?

He should be part of the HARMS Program. Consider assigning a risk category immediately based on your clinical Gestalt (see Ch. 2 for important markers of risk), however if time and energy allow you may consider applying a validated risk stratification tool and/ or baseline UDT for guidance.

Case 2

Mr. Thompson is on your opioid list generated by the EMR query. You prescribe hydromorphone 2mg TID prn for the last 2 months for back pain. He has lumbar spine decompression surgery booked next month. Should he be enrolled in HARMS?

In this case, Mr. Thompson would not be a candidate currently for HARMS because he has been prescribed opioids less than 3 months. When considering HARMS enrollment, you may also consider pending interventions and their likelihood for reducing pain (in this case his surgery).

Case 3

Mrs. White is prescribed short-acting morphine 5mg for intermittent back pain flares. You review her file and she received 60 tabs on two occasions over the past year. Should she be enrolled in HARMS?

No, she is averaging less than daily use. Your clinic may consider an alternative cutoff for quantity/frequency, such as using average morphine equivalents/day, however we prioritized simplicity. A recurrent theme with HARMS is that clinical judgement always prevails. If there is a high level of concern about misuse in this patient then you may still consider including in the program.

Chapter Pearls

  • Universal precautions are necessary - physicians are unable to identify patients being harmed by opioids based on patient self-reports, or clinical/behavioural observations1,2,5, therefore objective and universally applied monitoring is needed. No patient is zero risk and therefore UDT should be applied to everyone prescribed opioids for CNCP (with rare exclusions as above).
  • Use the EMR query to quickly screen who should be part of the HARMS Program and then physicians can do the final check of inclusion/exclusion criteria.
  • Standardization of HARMS was prioritized in its design. As much as possible, HARMS is meant to be easily consistent between different clinics, and different physicians within the same clinic. There are always grey areas and these will be discussed throughout this manual.


  1. McCarberg BH. A critical assessment of opioid treatment adherence using urine drug testing in chronic pain management. Postgrad Med. 2011;123(6):124-131. doi:10.3810/pgm.2011.11.2502
  2. Katz NP, Sherburne S, Beach M, et al. Behavioral monitoring and urine toxicology testing in patients receiving long-term opioid therapy. Anesth Analg. 2003;97(4):1097-1102, table of contents.
  3. Argoff CE, Alford DP, Fudin J, et al. Rational Urine Drug Monitoring in Patients Receiving Opioids for Chronic Pain: Consensus Recommendations. Pain Med. 2018;19(1):97-117. doi:10.1093/pm/pnx285
  4. Classification of chronic pain. Descriptions of chronic pain syndromes and definitions of pain terms. Prepared by the International Association for the Study of Pain, Subcommittee on Taxonomy. Pain Suppl. 1986;3:S1-226.
  5. Chen WJ, Fang C-C, Shyu R-S, Lin K-C. Underreporting of illicit drug use by patients at emergency departments as revealed by two-tiered urinalysis. Addict Behav. 2006;31(12):2304-2308. doi:10.1016/j.addbeh.2006.02.015

Now that patients prescribed opioids for CNCP have been identified, the next step is to determine individual risk levels that guide how tightly we monitor and prescribe for that person…