Accurate interpretation of drug test results is key to appropriate patient care in numerous settings, including pain management. Despite recommendations that providers should consult laboratory professionals for guidance when necessary, literature demonstrating laboratorian expertise in drug test interpretation is lacking.
To evaluate participating laboratories’ performance on the case-based, interpretive (“dry”) challenge included with each Drug Monitoring for Pain Management proficiency testing program from 2012–2023.
All challenges (n = 23) required participants to identify if drug test results were consistent or inconsistent with prescribed medications in the case history. Relevant medications, presumptive and confirmatory drug test results, and participant responses were extracted from program summary reports and examined for performance and common themes.
Overall, 91.8% (6821 of 7431) of participant responses correctly identified whether drug testing was consistent with medications. There were 8 challenges with participant scores less than 91.8% (range, 59.8% [49 of 82 responses] to 88.9% [193 of 217 responses]). Common knowledge gaps identified in these challenges included false-positive presumptive (screening) results, minor metabolism of opiates, and recognizing that presence of a nonprescribed drug is inconsistent with prescribed medications. Although some participants repeatedly responded incorrectly, there were no associations between laboratory type, personnel responding, or analytical performance and incorrect responses to interpretative challenges.
Program participants performed well overall, but several concerning educational gaps were identified. Laboratorians have a role in providing interpretative guidance for drug testing and should emphasize ongoing education to ensure competence in the setting of constantly changing prescribed and nonprescribed drug use.
Drug testing plays an important role in the management of patients with chronic pain, particularly those prescribed controlled substances such as opioids or benzodiazepines. Clinical guidelines, including those from the Centers for Disease Control and Prevention, Centers for Medicare and Medicaid Services, and the American Academy of Pain Management, recommend drug testing, typically at initiation of high-risk therapy and periodically thereafter, based on individual history and other patient factors.1–3 Studies have demonstrated utility for drug testing as a clinical tool in pain settings, particularly for assessing adherence to prescribed medications and detecting use of nonprescribed substances.4 However, there remains very little consensus between clinical guidelines in terms of how best to perform drug testing, including the preferred methodology (presumptive/screening versus definitive/confirmation), frequency of sampling, or specific drug targets to include.5
Laboratory-focused guidelines provide more detailed recommendations for testing, including Clinical and Laboratory Standards Institute (CLSI) C636 and the 2018 Laboratory Medicine Practice Guideline (LMPG) for drug monitoring in pain management.7 Both documents highlight the limitations of immunoassay (IA)–based presumptive testing, including false positives and false negatives, while acknowledging the relative accessibility of these assays compared to definitive mass spectrometry–based testing. The laboratory guidelines also suggest a range of therapeutic and recreational drug targets to consider for inclusion in testing.
One of the primary goals of drug testing in pain management is to ensure compliance (also termed adherence). CLSI notes that “results expected for a compliant patient point to the use of prescribed medications and the absence of any other drugs.”6 Partial compliance or noncompliance can take the form of altering the frequency, dose, or route of administration. The implications of drug test results can be quite serious: absence of a prescribed medication can be associated with drug diversion, whereas the presence of a nonprescribed compound could indicate risk for substance use disorder.1,2,6 However, accurate interpretation of drug testing must take into account clinical (eg, “as needed” dosing), analytical (eg, variable IA cross-reactivity), and patient (eg, pharmacogenetic variability) factors. Such interpretation can be complex and challenging for even experienced clinicians.8
Clinical and laboratory guidelines note the necessity for, and difficulty of, appropriate drug test interpretation.2,6,9 Unfortunately, limited studies have demonstrated that providers in various clinical specialties have insufficient training, expertise, and confidence in interpreting drug testing results.10–13 The pain management LMPG strongly recommended that “…clinicians should contact laboratory personnel for any test result that is inconsistent with the clinical picture and/or prescribed medications…” and “…clinical laboratories offering pain management testing must also have knowledgeable personnel who can assist clinicians to correctly interpret urine laboratory test results in pain management patients.”9 However, the LMPG also noted the absence of evidence at that time to demonstrate efficacy of consultations with laboratory or pathology staff.9 Subsequently, some literature has emerged supporting the utility of laboratory-generated interpretive reports and on-demand laboratory consultation services.14,15 However, these publications represent the experience of only a few institutions and do not directly address the question of laboratorian expertise in drug test interpretation.
Proficiency testing (PT) is a common means of evaluating the capability of laboratory professionals in performing and, when appropriate, interpreting test results. PT offers the advantages of including data from numerous institutions and directly evaluating participant responses against objective standards. The College of American Pathologists (CAP) Drug Monitoring for Pain Management (DMPM) PT program is targeted to laboratories performing testing for opioids, benzodiazepines, and other therapeutic drugs that require compliance monitoring. Each mailing contains 3 analytical (wet) challenges of various drugs spiked into an artificial urine matrix and 1 interpretive (dry) challenge of a realistic case study including relevant drug test results. DMPM dry challenges therefore provide a unique opportunity to directly evaluate laboratory expertise in interpretation of drug testing.
METHODS
The DMPM program is administered twice per year, designated “A” and “B” mailings. Dry challenge results were retrieved for all mailings since the program’s inception (2012–2023-A), for a total of 23 challenges. The dry challenge was initially considered educational (ie, ungraded); grading began in the first mailing of 2021 (2021-A).
The case studies were adapted from true, de-identified patient scenarios, thus a variety of medications and test results were included in the dry challenge scenarios. In early mailings, the test results presented were only those relevant to specific medications. Beginning in 2016, full drug screens (using IA) and relevant confirmation (liquid chromatography–tandem mass spectrometry [LC-MS/MS] or gas chromatography–mass spectrometry [GC-MS]) results were included in all dry challenges. Results were provided for opioids, benzodiazepines, and recreational drugs such as amphetamine-type stimulants, cocaine, and tetrahydrocannabinol metabolite (THC-COOH). Occasionally, other testing such as for the methylphenidate metabolite ritalinic acid was provided to illustrate specific educational points.
Data extracted from each dry challenge included prescribed and nonprescribed drugs in the medication list as well as screening and confirmatory test results. Case details not directly related to drug testing, for example, the reason for requiring chronic pain treatment, were disregarded for this study. Additional themes and educational content were extracted from the expert discussion provided by CAP in each DMPM participant summary of PT event results.
Participating laboratory responses (consistent or inconsistent with prescribed medications) for each mailing were also taken from the participant summary report. Because the summary report does not specify how many laboratories were enrolled, the largest number of responses to any challenge (wet or dry) was assumed to represent the total participation, that is, the number of possible responses in each mailing. Full PT data including unique laboratory identifiers were available for the 2015-A through 2023-A mailings; additionally, supplemental questions addressing laboratory demographics accompanied the 2017-B and 2023-B mailings. These were used to evaluate associations between PT challenge responses and demographics of participating laboratories during this time frame.
RESULTS
The DMPM program grew rapidly from fewer than 100 participants in 2012 to a plateau of approximately 500 laboratories since 2018 (Figure 1). Participation in the dry challenge was excellent, even before grading began in 2021. In 2012–2020, that is, the years the dry challenge was considered educational, 96.6% (5001 of 5176 possible responses across 18 mailings) of laboratories providing DMPM results answered the dry challenge component. A representative set of dry challenge drug test results is shown in Figure 2. Dry challenge scenarios contained up to 3 prescribed drugs (Table 1, left column) for which relevant test results were provided, and up to 10 additional over-the-counter and prescribed medications. Except fentanyl, all medications for which test results were given were in the top 300 most common outpatient prescriptions in the United States in 2020, with most in the top 75.16
Representative example of laboratory results from a dry challenge. Abbreviations: EDDP, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine; LC-MS/MS, liquid chromatography tandem mass spectrometry; THC, tetrahydrocannabinol.
Representative example of laboratory results from a dry challenge. Abbreviations: EDDP, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine; LC-MS/MS, liquid chromatography tandem mass spectrometry; THC, tetrahydrocannabinol.
Relevant Prescribed (Left Column) and Nonprescribed (Right Column) Medications From Dry Challenges
All case studies asked participants to interpret whether the test results provided were “consistent with prescribed medications” or “inconsistent with prescribed medications.” Overall, participating laboratories did very well on the dry challenges. During the study period, 6821 of 7431 total responses (91.8%) correctly identified whether each scenario was consistent or inconsistent with the patient’s medication list. As shown in Figure 3, performance on individual challenges ranged from 59.8% (49 correct responses of 82 total) in the 2013-A mailing to 100% in the 2012-A, 2012-B, and 2017-A mailings (n = 67, 75, and 347, respectively).
Percentage of correct interpretive responses provided to each dry challenge, 2012–2023-A. Triangles denote challenges where the expected response was consistent with prescribed medications; circles denote challenges where the expected response was inconsistent with prescribed medications.
Percentage of correct interpretive responses provided to each dry challenge, 2012–2023-A. Triangles denote challenges where the expected response was consistent with prescribed medications; circles denote challenges where the expected response was inconsistent with prescribed medications.
Of the 23 dry challenges evaluated, 8 described patient scenarios where test results were consistent with prescribed medications. Interestingly, 5 of the 8 “consistent” challenges had scores less than the 91.8% overall performance observed for the full study period (74.9%, 83.2%, 86.8%, 88.8%, and 80.1%; Table 2). These 5 challenges included 4 cases with false-positive results, that is, positive IA screens with negative confirmation testing, and 2 cases demonstrating minor opiate metabolism (conversion of codeine to hydrocodone or of morphine to hydromorphone; 1 case included both false positives and minor metabolism). In contrast, none of the 3 consistent challenges with scores greater than 91.8% described false-positive screens, and only 1 included minor opiate metabolism.
All 15 challenges describing results inconsistent with prescribed medications included detection of 1 or more nonprescribed drug (Table 1, right column). In 8 of these, the presence of a nonprescribed drug was the only inconsistent finding; 6 other scenarios also described absence of at least 1 prescribed medication despite targeted testing. The final “inconsistent” challenge included nonprescribed drugs as well as a high concentration of the prescribed medication in the absence of metabolites, suggesting simulated compliance (ie, surreptitiously adding drug directly into the urine specimen). Only 3 of these 15 challenges had scores less than the 91.8% overall performance threshold (59.8%, 79.3%, and 88.9%; Table 2); all 3 described scenarios where the prescribed medication and appropriate metabolites were present, and thus the interpretation of “inconsistent” was based solely on detection of nonprescribed medications.
Participating Laboratories
The DMPM program does not routinely gather demographic data for the individuals answering the dry challenges. Supplemental questions were sent out with 2017 and 2023 mailings to query respondents’ job roles and whether they had specific training in toxicology or therapeutic drug monitoring. In 2017, the majority answered that their job roles were best described as “supervisor or administrative lead” (123 of 405 responses, 30.4%), “quality or technical lead” (103 of 405, 25.4%), “PhD lab scientist” (95 of 405, 23.5%), or “bench technologist” (67 of 405, 16.5%). Most respondents (276 of 387, 71.3%) stated they had specific training in toxicology or therapeutic drug monitoring, ranging from on-the-job training to board certification in forensic or clinical toxicology. Implementation of formal grading did not substantially influence the demographics of staff answering dry challenges: in 2023, 178 (36.6%), 122 (25.1%), 83 (17.1%), and 82 (16.9%) of 486 respondents identified as supervisor or administrative lead, quality or technical lead, PhD lab scientist, or bench technologist, respectively. However, more pathologists answered dry challenges in 2023 (n = 18) than in 2017 (n = 2), and more respondents (81.8%, 374 of 457; P < .001) stated they had specific training in toxicology or therapeutic drug monitoring. The 2023 supplementary questions also found that the vast majority of respondents (454 of 482, 94.2%) reviewed the educational summaries provided with each mailing (this question was not asked in 2017).
A variety of laboratories participated in the DMPM program. Responses to the 2017 supplemental questions indicated that most (51.5%, 207 of 402) were regional independent laboratories, 28.9% (116 of 402) were reference laboratories, 30.6% (123 of 402) were clinic or provider offices, 11.2% (45 of 402) were hospital laboratories, and 6.5% (26 of 402) were national corporate laboratories (note that participants could choose multiple responses; this question was not asked in 2023). Participants included general chemistry and toxicology laboratories as well as those supporting clinical practices such as pain management and substance use disorder treatment.
Participating laboratories used several methodologies for DMPM analytical “wet” challenges. Although the numbers and proportions of analytical techniques used differed between target drugs and program mailings, DMPM participants reported both qualitative and quantitative methods throughout the study period. The former comprised mostly IA and LC-MS/MS; the latter were predominated by LC-MS/MS with some GC-MS and liquid chromatography with single-stage mass spectrometry (LC-MS). Evolution in test methodologies was apparent across the duration of this study. Qualitative testing was almost exclusively performed with IAs in the early years of the program, but over time the use of qualitative LC-MS/MS increased substantially. For example, in 2023-A, 90 participants reported qualitative LC-MS/MS results for fentanyl, compared to 82 laboratories using IA. In contrast, in 2012-A only 6 laboratories reported fentanyl by qualitative LC-MS/MS, compared to 13 using IA. Shifts in quantitative methodologies occurred as well; for example, in 2012-A, at least 24% (12 of 50) of participants reported hydromorphone by GC-MS, whereas in 2023-A, at least 97% (380 of 390) of participants used LC-MS(/MS) to quantify that same drug. Laboratories reporting IA results were consistently a minority of the total number of participants, indicating that most participants used some form of mass spectrometry throughout the study period.
Responses to the 2015-A through 2023-A mailings revealed 1068 different laboratories participated in the DMPM program during that window. Of these, 407 unique laboratories (38.1%) provided a total of 541 incorrect responses to dry challenges: 283 (69.5%), 90 (22.1%), 28 (6.9%), and 6 (1.5%) participants responded incorrectly 1, 2, 3, and 4 times, respectively. Laboratories with any incorrect responses were enrolled in a similar number of mailings between 2015 and 2023 (median, 7 mailings; range, 1–17 mailings) compared to the full group of participating laboratories (median, 6 mailings; range, 1–17 mailings). The profiles of institution type and responding personnel were also similar for laboratories with any incorrect responses and for those with repeated (>2) incorrect responses, compared to those described above for the full participant group. No association was found between repeated incorrect responses to dry challenges and poor performance on analytical (wet) challenges.
DISCUSSION
PT is often primarily targeted at the analytical phase of laboratory testing, with less emphasis on postanalytical aspects. However, laboratorians have an essential role in proper interpretation of drug testing, particularly as a resource for providers facing unexpected results.2,9 This study demonstrated that DMPM-participating laboratories generally performed well on the dry challenges but revealed some concerning findings with the potential to impact patient care. Although the overall performance of 91.8% is excellent at first glance, this translates to nearly 1 in 10 incorrect interpretations of clinical scenarios. During 2015–2023, 38.1% of participants provided at least 1 incorrect dry challenge interpretation, with several laboratories answering incorrectly up to 4 times in this window. Given that all dry challenges were real-world case scenarios, this could indicate that laboratories are at risk of providing misinformation to clinicians seeking assistance in test interpretation.
DMPM participants ranged from laboratories focused on pain management or substance use disorder support to national reference laboratories and large hospitals. Personnel answering the dry challenges were also quite diverse, ranging from bench technologists to pathologists and PhDs. The lack of association between the type of participating laboratory, the personnel responding, and performance on DMPM dry challenges suggests that no categories of laboratories or staff are “immune” from misinterpreting clinical scenarios. Given the constantly evolving nature of drug use and testing, all laboratory staff who might be asked for interpretative guidance not only must receive initial training, but also should be vigilant about maintaining ongoing education.
Although most respondents stated they reviewed educational commentaries provided with DMPM result summaries, participant performance on dry challenges did not improve over time. This could indicate that the educational material was unclear or was not reviewed by the personnel answering subsequent dry challenges. There was substantial turnover in participating laboratories, as evidenced by more than 1000 unique laboratories responding to a median of 6 mailings between 2015 and 2023; typical enrollment per mailing in that window was approximately 400 participants. Enrollment of new participants and turnover of staff within participating laboratories are additional factors that could limit the impact of DMPM educational commentaries on subsequent performance. High turnover could also indicate that some laboratories found the DMPM program to be a poor fit for the type of testing they performed.
Examination of case scenarios with scores less than the 91.8% overall performance identified 3 specific knowledge gaps that laboratorians providing drug test interpretation in support of pain management should evaluate: false-positive screens, minor opiate metabolism, and noncompliance indicated by presence of both nonprescribed and prescribed drugs. These represent potential analytical (false positives) and clinical (metabolism and compliance) areas where additional education could be of benefit.
False positives are a common limitation of IAs. A subset of DMPM laboratories provided IA-only results on wet challenges, indicating that some participants do not perform mass spectrometry–based testing. Although no association was found between dry challenge misinterpretation and analytical performance, it is possible that participants using presumptive methods might not recognize the role of confirmatory testing in identifying false-positive screens. Available cross-reactivity data for IA screens vary widely between manufacturers and often fail to address common sources of false positives.17 Laboratory staff should recognize that false positives can occur despite the absence of a clear explanation for the result (ie, a known cross-reacting compound). Similarly, laboratorians should be aware of compounds that are commonly—but incorrectly—perceived to cross-react on screens, such as methylphenidate (amphetamine IAs) and zolpidem (benzodiazepine IAs).
Recognition of morphine conversion to hydromorphone, and codeine to hydrocodone, is relatively recent considering the long history of these drugs.18,19 Detection of hydromorphone in the urine of patients using high-dose morphine was published only a few years before the first DMPM program to challenge this minor metabolic pathway. However, hydrocodone as a metabolite of codeine was described approximately 20 years before its inclusion in a DMPM challenge. The finding that many participants misinterpreted these results further indicates the need for ongoing education of laboratory staff who might provide result interpretation. It is important to note that the challenges describing minor metabolism (2013-B and 2020-B) reflected hydromorphone and hydrocodone at low concentrations relative to the parent drugs. In contrast, other challenges describing co-ingestion of additional drugs (eg, 2015-B, where morphine, hydrocodone, and hydromorphone were detected) incorporated comparatively high concentrations to clearly demonstrate use of multiple medications. The shift toward highly sensitive LC-MS/MS for both qualitative and quantitative testing observed in this study likely will increase recognition of low-concentration metabolites and impurities. Laboratorians should recognize that quantitative mass spectrometry is key to accurately comparing relative amounts of drugs and recognize the implications of highly sensitive methodologies when assessing alternative explanations such as co-ingestion versus metabolism or impurities.20,21
The final theme identified as an educational gap, that is, determining compliance from drug test results, is somewhat complex. Ideally, compliance includes taking medication(s) as prescribed, including dose, timing, and route8 ; unfortunately, drug testing cannot adequately address all of these factors given variability in pharmacokinetics of medications.6,9 In the 3 “inconsistent” challenges with scores below the overall study performance, the prescribed medications and appropriate metabolites were detected successfully. However, 1 or more nonprescribed, potentially high-risk compounds were also detected (amphetamine, hydrocodone, lorazepam). Abstinence from nonprescribed drugs is a key component of compliance, particularly in settings such as pain management that might require patient contracts agreeing to drug avoidance as a condition of therapy.
Presence of THC-COOH or unconfirmed screening results were never the only indications of inconsistent results. Given the evolving legality of cannabinoid usage within North America, the implications of THC-COOH positivity would differ by location, time, and clinical practice. Although increasing legality raises the question of whether testing for THC exposure is necessary, it remains relevant for many clinical areas, including pain management.1 Similarly, some providers may decline to confirm presumptive results, for example, if results are consistent with prescribed medications, or if they are unconcerned with drugs such as marijuana; insurance coverage or payer-specific limitations can also influence the use of mass spectrometry–based testing. Laboratories performing testing in support of pain management and related practices should work with the appropriate clinical team(s) to tailor drug test menus and confirmation testing strategies for their specific patient populations.
Limitations of this study included reliance upon 2 queries of self-reported laboratory and staff demographics in 2017 and 2023 to characterize participating laboratories. Although response rates to the supplemental questions were excellent, enrollment in the DMPM program was fluid throughout the study period. Therefore these participant responses represented snapshots in time and might not capture other laboratories not enrolled or responding at those times. An additional limitation is that respondents to the DMPM dry challenge might not be the individuals who would receive clinical inquiries during normal laboratory workflow.
This study addresses laboratorians’ role in the postanalytical process of interpreting results relative to clinical context. The DMPM program is somewhat unusual in offering participants ongoing opportunities to evaluate their own education and interpretative abilities in the setting of constantly changing prescribed and nonprescribed drug use. Although most responses correctly aligned drug test results with the clinical scenario provided, potential concerns identified in this study include a nearly 1-in-10 incorrect response rate, with several participants repeatedly misinterpreting the dry challenge. This has the potential to translate into incorrect guidance to clinicians, which in turn could lead to patient harm, inappropriate dismissal from care, or other consequences. Despite recommendations for clinical staff to seek assistance from the testing laboratory when faced with unexpected results, there are few studies directly assessing laboratorian competence in this arena. The findings of this study suggest that future investigations should attempt to identify additional knowledge gaps in pain management and other areas of drug testing and to assess the impact of interventions such as targeted education to laboratory and clinical staff who interpret drug test results.
CONCLUSIONS
Participating laboratories performed well on the DMPM program overall, including challenging scenarios such as simulated compliance. Potential educational needs were identified, specifically the role of presumptive versus definitive testing, recognition of minor metabolic pathways, and understanding that medication compliance in pain management and related settings includes avoidance of nonprescribed drugs.