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A national population-based study of cannabis use and correlates among U.S. veterans prescribed opioids in primary care

BMC Psychiatry volume 23, Article number: 177 (2023) Cite this article

Abstract

Background

Cannabis is marketed as a treatment for pain. There is limited data on the prevalence of cannabis use and its correlates among Veterans prescribed opioids.

Objective

To examine the prevalence and correlates of cannabis use among Veterans prescribed opioids.

Design

Cross-sectional study.

Participants

Veterans with a urine drug test (UDT) from Primary Care 2014–2018, in 50 states, Washington, D.C., and Puerto Rico. A total of 1,182,779 patients were identified with an opioid prescription within 90 days prior to UDT.

Main measures

Annual prevalence of cannabis positive UDT by state. We used multivariable logistic regression to assess associations of demographic factors, mental health conditions, substance use disorders, and pain diagnoses with cannabis positive UDT.

Results

Annual prevalence of cannabis positive UDT ranged from 8.5% to 9.7% during the study period, and in 2018 was 18.15% in Washington, D.C. and 10 states with legalized medical and recreational cannabis, 6.1% in Puerto Rico and 25 states with legalized medical cannabis, and 4.5% in non-legal states. Younger age, male sex, being unmarried, and marginal housing were associated with use (p < 0.001). Post-traumatic stress disorder (adjusted odds ratio [AOR] 1.17; 95% confidence interval [CI] 1.13–1.22, p < 0.001), opioid use disorder (AOR 1.14; CI 1.07–1.22, p < 0.001), alcohol use disorder or positive AUDIT-C (AOR 1.34; 95% CI 1.28–1.39, p < 0.001), smoking (AOR 2.58; 95% CI 2.49–2.66, p < 0.001), and other drug use disorders (AOR 1.15; 95% CI 1.03–1.29, p = 0.02) were associated with cannabis use. Positive UDT for amphetamines AOR 1.41; 95% CI 1.26–1.58, p < 0.001), benzodiazepines (AOR 1.41; 95% CI 1.31–1.51, p < 0.001) and cocaine (AOR 2.04; 95% CI 1.75–2.36, p < 0.001) were associated with cannabis positive UDT.

Conclusions

Cannabis use among Veterans prescribed opioids varied by state and by legalization status. Veterans with PTSD and substance use disorders were more likely to have cannabis positive UDT. Opioid-prescribed Veterans using cannabis may benefit from screening for these conditions, referral to treatment, and attention to opioid safety.

Peer Review reports

Background

Cannabis use has increased over the past decade [1], with past-month cannabis use in the United States (U.S.) almost doubling from 5.8% in 2007 to 11.5% in 2019 [2]. The most recent National Survey of Drug Use and Health indicated the highest rates of past-month use among 18–25-year-olds (23%) compared to other age groups, as well as a steady rise among adults 26 years or older, with 7.9%, 8.6%, and 10.2% reporting past month use in 2017, 2018, and 2019, respectively [3, 4]. Cannabis is marketed as a treatment of pain [5] and there is some emerging evidence that it may be beneficial in the management of pain [6]. Therefore, use among patients prescribed opioid analgesic therapy for pain management may be common. Given the current and projected growth of cannabis use in the U.S., understanding the prevalence of cannabis use in those prescribed opioids has important implications for clinical care.

To date, there are no published national data that quantify the prevalence and correlates of cannabis use among U.S. adults prescribed opioids. Previous studies of chronic pain patients have indicated that depression, anxiety, opioid use disorder, tobacco, alcohol, cocaine, and sedative use [7, 8] are associated with cannabis use. Additionally, studies of chronic pain patients include mixed and low-quality evidence on the opioid-sparing properties of cannabis [9, 10]. A recent prospective cohort study suggested that cannabis use does not decrease opioid use among patients prescribed cannabis for non-cancer pain [11]. Cannabis use among adults prescribed opioid therapy is a concern due to potential harms associated with combined use of two psychoactive drugs.

Data from the Veterans’ Health Administration (VHA), the nation’s largest healthcare system, provides a unique opportunity to examine the prevalence of cannabis use and correlates of use among patients prescribed opioids in primary care. In 2014, VHA recommended routine annual urine drug testing (UDT) for all patients prescribed opioids for greater than 90 days in primary care and began tracking compliance with this metric at a national level [12,13,14,15]. This population-based study reports on the annual prevalence of cannabis positive UDT within the VHA during 2014–2018, state-level variation in prevalence according to the legal status of cannabis in 2018, and the association of Veteran demographic factors, mental health diagnoses, substance use disorders and pain diagnoses with cannabis positive UDT.

Methods

Sample: Opioid-prescribed veterans

Using data from the VHA Corporate Data Warehouse (CDW) [16], we identified Veterans aged 18 or older who received a UDT in primary care between 2014 and 2018 using a previously developed algorithm [17, 18]. All UDTs were completed at outpatient laboratories. The sample included Veterans in all 50 states, the District of Columbia, and Puerto Rico.

We chose to evaluate screening in primary care clinics as most opioids are prescribed in this setting. This outpatient setting also allows for examination of data over longer periods of time in comparison to inpatient settings, and in an environment likely reflective of the patient’s usual patterns of use outside of a closely monitored acute care unit. As all Veterans who receive opioids for greater than 90 days are recommended to receive annual urine drug testing, there is less possibility of selection bias in who receives screening. We restricted the sample to the first UDT for each Veteran in primary care (N = 2,447,258) per year. We further restricted the sample to Veterans each year who had filled at least one prescription for an opioid analgesic medication in the 90 days prior to the UDT (N = 1,182,779) (Fig. 1).

Fig. 1
figure 1

Data source and flow diagram to determine prevalence of cannabis use among all US Veterans 18 years and older prescribed opioids 2014–2018

Full size image

Data sources and measurements

The primary dependent variable of interest was the presence of cannabis in the UDT. These tests detect the presence of tetrahydrocannabinol (THC) and can remain positive for up to 30 days after use [19], and we considered a positive result a reasonable proxy for cannabis use. Independent variables included sociodemographic factors, non-substance use mental health diagnoses, substance use disorders, and pain diagnoses. We included these variables as other studies have demonstrated the association of these domains with cannabis use [20, 21]. Pain diagnoses were examined as these were the indications for opioid prescription, and because cannabis is frequently marketed as a treatment for a range of pain syndromes [22].

To identify non-substance use mental health diagnoses, we used the presence of two International Classification of Disease-9 (ICD-9) and ICD-10 outpatient codes in the past two years, or the presence of one inpatient code. We used all data sources available including national VA data, Medicare data and VA community care files to identify ICD codes. We searched for codes for common mental health diagnoses: psychosis, depression, bipolar disorder, PTSD, and anxiety (Table 1). We used a similar approach to identify chronic pain, and searched for codes indicating common pain diagnoses: back pain, neck pain, osteoarthritis, neuropathy, and headache.

Table 1 Baseline characteristics of veterans 18 years and older on prescription opioid therapy who were screened for cannabis via urine toxicology (2018)
Full size table

To identify substance use disorders, we used the presence of a single ICD code in the past two years. We required only a one code for substance use disorders as these conditions tend to be under-coded by providers. We searched for codes indicating common substance use disorders including opioid, benzodiazepine, hallucinogen, stimulant, and alcohol use disorders (Table 1). The category “other drug use disorders” included any drugs not covered by preceding categories (e.g., inhalant use). Notably, as ICD-9 codes contain outdated language such as substance “abuse,” or “dependence,” we reported these diagnoses as “use disorders” in accordance with current standards of addiction-related terminology [23, 24].

In addition to using ICD codes, we included individuals with elevated scores on the Alcohol Use Disorders Identification Test – Concise (AUDIT-C) in the alcohol use category [25]. Screening using the AUDIT-C is required annually by the VHA, and the tool has been well-validated for the detection of risky drinking among Veterans [26]. We defined elevated scores based on the high-risk AUDIT-C scores of ≥ 4 for women and ≥ 5 for men [27]. We used a previously developed algorithm to identify tobacco use [28]. We used UDT data to identify Veterans who had evidence of other substances (cocaine, amphetamines or benzodiazepines) in their urine on the date of the index urine drug screen. As the presence of a substance on UDT alone does not indicate a use disorder, we did not count lab results in the use disorder categories, but rather reported them separately as “Substance Present in Urine Drug Test- day of index” (Table 1 and Fig. 3).

Veterans were classified as “marginally housed” if an ICD code related to housing insecurity or homelessness was present or if they received housing services. We defined self-harm based on ICD code.

Statistical analysis

We assessed the annual prevalence of cannabis use among opioid-prescribed Veterans between 2014 to 2018. To estimate annual prevalence, we first identified all Veterans who received a UDT in a given year and had an opioid prescription within 90 days before the UDT (Fig. 1). For each Veteran with more than one UDT in a given year, the first UDT result was used such that each Veteran appears only once each year. We chose the first UDT of each year as Veterans may complete variable numbers of total UDTs per year, and selection of the first data point allowed us to gather a non-biased, standardized data point for each Veteran. Annual prevalence was estimated by identifying the proportion first UDTs positive for cannabis out of all the tests sampled each year (2014 through 2018).

We described the characteristics of the sample stratified by cannabis present in the urine drug test. Characteristics were summarized using frequencies and proportions and compared as a function of cannabis use using chi-square tests for categorical variables and t-test for continuous variables.

We examined the associations between sociodemographic factors, pain diagnoses, mental health diagnoses, and substance use disorders with cannabis in the UDT in 2018 because this was the most recent year of data in the sample at the time of the analyses. We assessed the association between these factors and cannabis in the UDT using multivariable logistic regression. For the multivariable analysis, we combined the different forms of pain into one category (any pain diagnosis). In a secondary analysis, we examined the association of cannabis in the UDT with the factors outlined above stratified by age (< 55 and > 55). We conducted this analysis because less is known about factors associated with cannabis use among older adults. We used RStudio version 1.4.17 for all analyses.

Institutional approvals

The Institutional Review Board of the University of California, San Francisco approved this study.

Results

Geographical variation in prevalence of cannabis use

Among Veterans prescribed at least one opioid, the annual prevalence of cannabis positive UDT was 9.7% (95% CI, 9.55% to 9.78%) in 2014, 8.8% (95% CI, 8.68% to 8.90%) in 2015, 8.6% (95% CI 8.50% to 8.71%) in 2016, 8.5% (95%CI 8.41% to 8.64%) in 2017, and 8.7% (95%CI 8.53% to 8.79%) in 2018 (Fig. 1). In 2018, there was heterogeneity in cannabis prevalence among opioid-prescribed Veterans by state (Fig. 2) with the highest prevalence in Oregon (25.2%), Washington (23.6%) and California (18.6%). In 2018, cannabis was legal for recreational and medical purposes in 10 states and the District of Columbia (D.C.), cannabis was legal for medical purposes in 25 states and Puerto Rico, and cannabis was non-legal in 15 states (Fig. 2). The prevalence of cannabis use among opioid-prescribed Veterans was 18.2% in recreationally legal states, 6.1% in medically legal states, and 4.5% in non-legal states (p < 0.001).

Fig. 2
figure 2

Prevalence of Cannabis use in Veterans 18 years and older on prescription opioid therapy across US States and territories in 2018. Original figure created using microsoft word 2021 and microsoft paint 2021

Full size image

Demographic factors and cannabis use

The mean age of the Veterans with an opioid prescription who completed UDT in 2018 was 63.3 years. The majority were male (92.6%) and white (75.7%) (Table 1).

Age below 55 years, male gender (adjusted odds ratio [AOR] 1.52; 95% confidence interval [CI] 1.42–1.63, p < 0.001), being unmarried (AOR 0.71; 95% CI 0.68–0.73, p < 0.001), marginally housed (AOR 1.38; 95% CI 1.3–1.47, p < 0.001), of American Indian or Alaska Native race (AOR 1.28; 95% CI 1.13–1.45, p < 0.001), and of Hispanic or Latino ethnicity (AOR 1.36; 95% CI 1.26–1.46, p < 0.001) were associated with cannabis use (Fig. 3).

Fig. 3
figure 3

Adjusted associations between sociodemographic, pain, mental health, and behavioral factors and presence of cannabis in the urine drug test. All factors listed were included in the model

Full size image

Other substance use disorders and cannabis use

After adjusting for baseline characteristics, patients with opioid use disorder (AOR 1.14; CI 1.07–1.22, p < 0.001), alcohol use disorder or elevated AUDIT C (AOR 1.34; 95% CI 1.28–1.39, p < 0.001), other drug use disorders (AOR 1.15; 95% CI 1.03–1.29, p = 0.02), or who were current smokers (AOR 2.58; 95% CI 2.49–2.66, p < 0.001) had higher odds of cannabis positive UDT. Those with UDT positive for amphetamines (AOR 1.41; 95% CI 1.26–1.58), benzodiazepines (AOR 1.41, 95% CI 1.31–1.51), or cocaine (AOR 2.04, 95% CI 1.75–2.36), were more likely to have cannabis positive UDT (Fig. 3).

Other mental health diagnoses and cannabis use

In adjusted analysis, psychosis, depression, bipolar disorder, anxiety, and self-harm were not associated with increased cannabis positive UDT. Veterans with a post-traumatic stress disorder (PTSD) diagnosis had higher odds of cannabis positive UDT (AOR 1.17; 95% CI 1.13–1.22, p < 0.001) (Fig. 3).

Pain diagnoses, opioid dose, and cannabis use

Among the study population, 84% of Veterans had documented ICD codes for pain diagnoses. In adjusted analysis, presence of any pain diagnosis (back pain, neck pain, osteoarthritis headache or neuropathy) (AOR 0.72; 95% CI 0.69–0.75, p < 0.001) was associated with reduced likelihood of having cannabis in the UDT. (Fig. 3). Veterans who used cannabis were prescribed a higher dose of prescription opioids compared to those without (mean daily morphine equivalent dose 45.9 mg versus 42.5 mg; p < 0.001).

Cannabis use stratified by age

We found that the factors associated with cannabis use were similar among veterans younger than 55 years old and those aged 55 and older with one exception. Veterans 60 to 64 were slightly more likely to have cannabis in the UDT compared to those aged < 55 years (OR 1.12, 95% CI 1.06–1.17 (Fig. 3).

Discussion

This population-based study of biologically verified cannabis use among Veterans prescribed opioids within the VHA demonstrates an overall national prevalence of 8.7% in 2018, similar to non-Veterans with medical conditions (8.8%) [29]. We report higher cannabis use in recreationally legal states compared to non-legal states, with 20–25% of Veterans on opioids using cannabis in California, Oregon, and Washington. Furthermore, our study demonstrated that PTSD, current smoking of tobacco, alcohol, opioid, and other drug use disorders, were associated with cannabis positive UDT.

In contrast to studies of the general adult population [2], we did not find an increase in cannabis use among opioid-prescribed patients over time (between 2014–2018). There are several possible explanations for this finding. The VHA does not mandate the taper of opioids in response to cannabis positive UDT. However, in response to national efforts to improve the safety of patients on opioids [30, 31], some VHA prescribers may taper opioids or counsel against cannabis use if patients use both, contributing to lower prevalence. Additionally, the average age of our study population (63 years) may be older than a non-Veteran general population. However, recent data indicate that cannabis use may be growing more quickly in older persons compared with younger populations [32, 33]. This suggests the added importance of monitoring and addressing the use of cannabis in the aging Veteran population.

Our study indicates an association between PTSD and cannabis use among Veterans prescribed opioids, similar to the association seen in the broader veteran population [34]. This finding suggests the importance of screening and connecting opioid-prescribed Veterans to evidence-based treatments for PTSD, as they may be using cannabis to cope with symptoms [35].

The finding that opioid and alcohol use disorders were associated with cannabis positive UDT suggests that cannabis use may be a marker of elevated risk in this population. Veterans on opioid therapy who use cannabis may benefit from evaluation for opioid use disorder and connection to evidence-based treatments within the VHA [36]. The association with alcohol also raises safety concerns, as both alcohol and cannabis have psychoactive affects and are associated with impaired driving [37]. In combination with alcohol, cannabis has a significantly enhanced impact on cognition, attention and concentration, and can potentiate the effects of impairment [38, 39]. These risks are also compounded by opioids, and patients should be educated regarding risks of combined use. While our finding of other substances on UDT are not of themselves indicative of use disorders, Veterans may benefit from further inquiry into patterns of use and counseling regarding the medical risks of using multiple substances [40].

Cannabis use alone is not indicative of cannabis use disorder (CUD). However, given the high prevalence of use and the association of other drug use with cannabis positive UDT, this population may benefit from screening for CUD. This would be congruent with current VHA guidance which recommend discussion of the health impacts of cannabis and documentation of use within veterans’ electronic health records [41]. However, these guidelines do not include specific recommendations on the screening for cannabis use disorder (CUD). Potential screening methods may include clinical interview regarding ongoing use despite consequences [42], standardized tools such as the Cannabis Use Disorder Identification Test (CUDIT) [43], or use of criteria from the Diagnostic and Statistical Manual of Psychiatry (DSM) 5 [44]. If identified, CUD may be managed via referral to cognitive behavioral therapy and motivational enhancement therapy [45]. Patients seeking cannabis cessation may be educated that off-label medications have shown some benefit in treatment of CUD and cannabis withdrawal, though none are currently approved by the Food and Drug Administration [46, 47].

If screening all opioid prescribed patients is not feasible, consideration may be given to initiation of screening in areas with high prevalence such as in the states that have recreationally legalized cannabis use, or in vulnerable populations such as patients with histories of other addiction, psychotic disorders, and PTSD [48, 49]. As a cross-sectional study, ours did not examine the change in prevalence of cannabis positive UDT in each state before and after legalization, though such future analysis may better elucidate the impact of legalization on prevalence.

Our study indicates that current tobacco use was common and had a strong association with cannabis positive UDT. This indicates the need for screening and treatment for nicotine (tobacco) use disorder, particularly given the potential harmful effects of combined inhaled use of cannabis and tobacco [50, 51], although we were unable to distinguish between routes of cannabis use in this study.

Cannabis is being marketed to consumers as a remedy for opioid use, and some states have legalized the dispensing of cannabis for the treatment for opioid use disorder [52]. Our analyses are cross-sectional, and we cannot infer how cannabis use may impact opioid use. However, it is noteworthy that the average opioid doses were higher among those with cannabis positive UDT, and that patients with opioid use disorder were more likely to have cannabis positive UDT. While we did not measure pain severity in this study, previous studies indicate that this alone is an unlikely explanation for combined cannabis and opioid use [11]. Our findings align with other recent studies questioning the utility of cannabis as an alternative to opioids, or as a treatment for opioid use disorder [53, 54]. For patients who report using cannabis use for pain, given emerging research into the efficacy of certain cannabinoids for pain syndromes, prescribers should discuss the relative risks and benefits of using cannabis in a patient-centered manner [6, 55].

Some limitations of this study deserve comment. This a cross-sectional study with all the limitations thereof. While this is a population-based study, some Veterans on opioids may not have received urine drug screens. However, urine drug testing is now an established feature of practice in the VHA for care of Veterans receiving opioids and > 90% of Veterans receiving long-term opioids are screened [18, 56, 57]. In addition, while routine annual urine drug testing is primarily recommended and monitored for Veterans receiving chronic opioid analgesic therapy in primary care, it is possible that some patients received a urine drug screen for other reasons (e.g., mental status and behavioral changes).” Veterans who use cannabis infrequently may not be captured, and our estimates may be an undercount of actual prevalence. We used a UDT to assess for cannabis use, the current gold standard test for assessing cannabis use. However, these tests do not provide information on routes, frequency or forms of use, and may detect positive tests more reliably for those who use frequently [58]. Additionally, given the potential ramifications of a positive result, particularly in states where cannabis remains illegal, some patients may avoid completing a UDT, although an annual UDT is recommended for opioid continuation and compliance is monitored [59]. Though some patients may have prescriptions for benzodiazepines or stimulants, close monitoring remains important given the risks of drug-drug interactions with opioids and the potential misuse of controlled substance prescriptions [60,61,62]. We used ICD codes, AUDIT-C scores, and urine drug screens to capture substance use disorders. However, primary care physicians may not routinely code for these conditions, leading to a likely underestimate of substance use in this population. While high AUDIT-C scores indicate risk for alcohol use disorder, they are not diagnostic, supporting the need for additional evaluation.

Cannabis use is common among Veterans who receive prescription opioids and is highly prevalent among Veterans who reside in recreationally legal states. Opioid and alcohol use disorders, as well as tobacco and other drug disorders use are more common among patients who use cannabis. Cannabis use may be a marker of high-risk behavior in this population, which may benefit for screening for other substance use disorders and referral to appropriate treatment.

Availability of data and materials

A de-identified dataset can be made available according to the Veterans Health Administration policies and procedures.

References

  1. Hasin DS. US epidemiology of cannabis use and associated problems. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. 2018;43(1):195–212.

    Article  PubMed  Google Scholar 

  2. Center for behavioral health statistics and quality, substance abuse and mental health services administration. 2019 national survey on drug use and health: detailed tables. https://www.samhsa.gov/data/sites/default/files/reports/rpt29394/NSDUHDetailedTabs2019/NSDUHDetTabs1-25to1-27pe2019.pd.

  3. Substance abuse and mental health services administration. (2020). key substance use and mental health indicators in the United States: results from the 2019 national survey on drug use and health (HHS Publication No. PEP20–07–01–001, NSDUH Series H-55). Rockville, MD: center for behavioral health statistics and quality, substance abuse and mental health services administration. Retrieved from https://www.samhsa.gov/data/

  4. Woolcott JC, Richardson KJ, Wiens MO, Patel B, Marin J, Khan KM, Marra CA. Meta-analysis of the impact of 9 medication classes on falls in elderly persons. Arch Intern Med. 2009;169(21):1952–60. https://doi.org/10.1001/archinternmed.2009.357.Erratum.In:ArchInternMed.2010Mar8;170(5):477. (PMID: 19933955).

    Article  PubMed  Google Scholar 

  5. Lau N, Gerson M, Korenstein D, Keyhani S. Internet claims on the health benefits of cannabis use. J Gen Intern Med. 2021;36(11):3611–4.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Busse JW, Vankrunkelsven P, Zeng L, Heen AF, Merglen A, Campbell F, et al. Medical cannabis or cannabinoids for chronic pain: a clinical practice guideline. BMJ. 2021;374:n2040.

    Article  PubMed  Google Scholar 

  7. Olfson M, Wall MM, Liu SM, Blanco C. Cannabis use and risk of prescription opioid use disorder in the United States. Am J Psychiatry. 2018;175(1):47–53.

    Article  PubMed  Google Scholar 

  8. Rogers AH, Bakhshaie J, Buckner JD, Orr MF, Paulus DJ, Ditre JW, Zvolensky MJ. Opioid and cannabis co-use among adults with chronic pain: relations to substance misuse, mental health, and pain experience. J Addict Med. 2019;13(4):287–94.

    Article  PubMed  Google Scholar 

  9. Noori A, Miroshnychenko A, Shergill Y, et al. Opioid-sparing effects of medical cannabis or cannabinoids for chronic pain: a systematic review and meta-analysis of randomised and observational studies. BMJ Open. 2021;11:047717.

  10. Ishida JH, Wong PO, Cohen BE, Vali M, Steigerwald S, Keyhani S. Substitution of marijuana for opioids in a national survey of US adults. PLoS ONE. 2019;14(10):0222577.

  11. Campbell G, Hall WD, Peacock A, Lintzeris N, Bruno R, Larance B, Nielsen S, Cohen M, Chan G, Mattick RP, Blyth F, Shanahan M, Dobbins T, Farrell M, Degenhardt L. Effect of cannabis use in people with chronic non-cancer pain prescribed opioids: findings from a 4-year prospective cohort study. Lancet Public Health. 2018;3(7):e341–50. https://doi.org/10.1016/S2468-2667(18)30110-5.PMID:29976328;PMCID:PMC6684473.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Veterans Health Administration Opioids Safety Initiative. Available at: https://www.va.gov/PAINMANAGEMENT/docs/OSI_1_Toolkit_Pain_Educational_Guide.pdf. Accessed 25 Dec 2021.

  13. U.S. Department of Veterans Affairs Pain Management and Opioid Safety Educational Guide 2014. Available at: https://www.va.gov/PAINMANAGEMENT/docs/OSI_1_Toolkit_Pain_Educational_Guide.pdf. Accessed 25 Dec 2021.

  14. Edlund MJ, Austen MA, Sullivan MD, Martin BC, Williams JS, Fortney JC, Hudson TJ. Patterns of opioid use for chronic noncancer pain in the Veterans Health Administration from 2009 to 2011. Pain. 2014;155(11):2337–43. https://doi.org/10.1016/j.pain.2014.08.033.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Sandbrink F, Oliva EM, McMullen TL, Aylor AR, Harvey MA, Christopher ML, Cunningham F, Minegishi T, Emmendorfer T, Perry JM. Opioid prescribing and opioid risk mitigation strategies in the veterans health administration. J Gen Intern Med. 2020;35(Suppl 3):927–34. https://doi.org/10.1007/s11606-020-06258-3.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Veterns Health Administration Corporate Data Warehouse. https://www.hsrd.research.va.gov/for_researchers/vinci/cdw.cfm

  17. Morasco BJ, Shull SE, Adams MH, Dobscha SK, Lovejoy TI. Development of an algorithm to identify cannabis urine drug test results within a multi-site electronic health record system. J Med Syst. 2018;42(9):163. https://doi.org/10.1007/s10916-018-1021-7. (PMID: 30043122).

    Article  PubMed  Google Scholar 

  18. Wong P, Leonard S, Maas R, Keyhani S. A validated algorithm to identify opioid and cannabis users using urine toxicology results. J Gen Intern Med. 2020;35(Suppl 1):S1–779.

    Google Scholar 

  19. Schuster RM, Potter K, Vandrey R, Hareli M, Gilman J, Schoenfeld D, Evins AE. Urinary 11-nor-9-carboxy-tetrahydrocannabinol elimination in adolescent and young adult cannabis users during one month of sustained and biochemically-verified abstinence. J Psychopharmacol. 2020;34(2):197–210.

    Article  CAS  PubMed  Google Scholar 

  20. Jeffers AM, Glantz S, Byers A, Keyhani S. Sociodemographic characteristics associated with and prevalence and frequency of cannabis use among adults in the US. JAMA Netw Open. 2021;4(11):2136571.

  21. Enkema MC, Hasin DS, Browne KC, Stohl M, Shmulewitz D, Fink DS, Olfson M, Martins SS, Bohnert KM, Sherman SE, Cerda M, Wall M, Aharonovich E, Keyhani S, Saxon AJ. Pain, cannabis use, and physical and mental health indicators among veterans and nonveterans: results from the national epidemiologic survey on alcohol and related conditions-III. Pain. 2022;163(2):267–73. https://doi.org/10.1097/j.pain.0000000000002345.PMID:34108436;PMCID:PMC8985055.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Caputi TL. The medical marijuana industry and the use of “Research as Marketing.” Am J Public Health. 2020;110(2):174–5. https://doi.org/10.2105/AJPH.2019.305477.PMID:31913671;PMCID:PMC6951364.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kelly JF, Saitz R, Wakeman S. Language, substance use disorders, and policy: The need to reach consensus on an “addiction-ary.” Alcohol Treatment Quarterly. 2016;34(1):116–23.

    Article  Google Scholar 

  24. Marchand K, Beaumont S, Westfall J, MacDonald S, Harrison S, Marsh DC, Schechter MT, Oviedo-Joekes E. Patient-centred care for addiction treatment: a scoping review protocol. BMJ open. 2018;8(12):024588.

  25. Higgins-Biddle JC, Babor TF. A review of the Alcohol Use Disorders Identification Test (AUDIT), AUDIT-C, and USAUDIT for screening in the United States: Past issues and future directions. Am J Drug Alcohol Abuse. 2018;44(6):578–86. https://doi.org/10.1080/00952990.2018.1456545.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Bradley KA, Rubinsky AD, Lapham GT, Berger D, Bryson C, Achtmeyer C, Hawkins EJ, Chavez LJ, Williams EC, Kivlahan DR. Predictive validity of clinical AUDIT-C alcohol screening scores and changes in scores for three objective alcohol-related outcomes in a Veterans Affairs population. Addiction. 2016;111(11):1975–84. https://doi.org/10.1111/add.13505. (Epub 2016 Aug 2 PMID: 27349855).

    Article  PubMed  Google Scholar 

  27. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. ambulatory care quality improvement project (ACQUIP). alcohol use disorders identification test. Arch Intern Med. 1998;158(16):1789–95.

    Article  CAS  PubMed  Google Scholar 

  28. Barnett PG, Chow A, Flores NE. Using tobacco health factors data for VA health services research. technical report 28. Menlo Park, CA. VA Palo Alto, health economics resource center; 2014

  29. Dai H, Richter KP. A national survey of marijuana use among US adults with medical conditions, 2016–2017. JAMA Netw Open. 2019;2(9):1911936.

  30. Lin LA, Bohnert ASB, Kerns RD, Clay MA, Ganoczy D, Ilgen MA. Impact of the opioid Safety Initiative on opioid-related prescribing in veterans. Pain. 2017;158(5):833–9. https://doi.org/10.1097/j.pain.0000000000000837. (PMID: 28240996).

    Article  PubMed  Google Scholar 

  31. Becker WC, Krebs EE, Edmond SN, Lin LA, Sullivan MD, Weiss RD, Gordon AJ. A research agenda for advancing strategies to improve opioid safety: findings from a VHA State of the art conference. J Gen Intern Med. 2020;35(Suppl 3):978–82.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Han BH, Palamar JJ. Marijuana use by middle-aged and older adults in the United States, 2015–2016  [published correction appears in drug alcohol depend 2018 Sep 25;192:171]. Drug Alcohol Depend. 2018;191(374):381.

    Google Scholar 

  33. Salas-Wright CP, Hai AH, Oh S, Alsolami A, Vaughn MG. Trends in cannabis views and use among American adults: intersections with alcohol consumption, 2002–2018. Addict Behav. 2021;116:106818.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Betthauser K, Pilz J, Vollmer LE. Use and effects of cannabinoids in military veterans with posttraumatic stress disorder. Am J Health Syst Pharm. 2015;72(15):1279–84. https://doi.org/10.2146/ajhp140523. (PMID: 26195653).

    Article  PubMed  Google Scholar 

  35. Boden MT, Babson KA, Vujanovic AA, Short NA, Bonn-Miller MO. Posttraumatic stress disorder and cannabis use characteristics among military veterans with cannabis dependence. Am J Addict. 2013;22(3):277–84.

    Article  PubMed  Google Scholar 

  36. Wyse JJ, Gordon AJ, Dobscha SK, Morasco BJ, Tiffany E, Drexler K, Sandbrink F, Lovejoy TI. Medications for opioid use disorder in the Department of Veterans Affairs (VA) health care system: Historical perspective, lessons learned, and next steps. Subst Abus. 2018;39(2):139–44. https://doi.org/10.1080/08897077.2018.1452327.PMID:29595375;PMCID:PMC8054831.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Asbridge M, Hayden JA, Cartwright JL. Acute cannabis consumption and motor vehicle collision risk: systematic review of observational studies and meta-analysis. BMJ. 2012;344: e536.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Dubois S, et al. The combined effects of alcohol and cannabis on driving: impact on crash risk. Forensic Sci Int. 2015;248:94–100.

    Article  CAS  PubMed  Google Scholar 

  39. Yurasek AM, Aston ER, Metrik J. Co-use of alcohol and cannabis: a review. Curr Addict Rep. 2017;4(2):184–93.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Schulte MT, Hser YI. Substance use and associated health conditions throughout the lifespan. Public Health Rev. 2014;35(2). https://web-beta.archive.org/web/20150206061220/http://www.publichealthreviews.eu/upload/pdf_files/14/00_Schulte_Hser.pdf. https://doi.org/10.1007/BF03391702.

  41. U.S. Department of Veterans Affairs Directive 1315. Available at: https://www.va.gov/vhapublications/ViewPublication.asp?pub_ID=5711. Accessed 25 Dec 2021.

  42. NIDA. 2020, July 13. Drug Misuse and Addiction. Retrieved from https://nida.nih.gov/publications/drugs-brains-behavior-science-addiction/drug-misuse-addiction on 25 May 2022.

  43. Bonn-Miller MO, Heinz AJ, Smith EV, Bruno R, Adamson S. Preliminary development of a brief cannabis use disorder screening tool: the cannabis use disorder identification test short-form. Cannabis and cannabinoid research. 2016;1(1):252–61. https://doi.org/10.1089/can.2016.0022.

    Article  PubMed  PubMed Central  Google Scholar 

  44. American Psychiatric Association. (2013). Cannabis Use Disorder. In Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA.

  45. Sherman BJ, McRae-Clark AL. Treatment of cannabis use disorder: current science and future outlook. Pharmacotherapy. 2016;36(5):511–35. https://doi.org/10.1002/phar.1747.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Gorelick DA. Pharmacological treatment of cannabis-related disorders: a narrative review. Curr Pharm Des. 2016;22(42):6409–19.

    Article  CAS  PubMed  Google Scholar 

  47. Mason BJ, et al. A proof-of-concept randomized controlled study of gabapentin: effects on cannabis use, withdrawal and executive function deficits in cannabis-dependent adults. Neuropsychopharmacology. 2012;37(7):1689–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Hill KP, Gold MS, Nemeroff CB, McDonald W, Grzenda A, Widge AS, Rodriguez C, Kraguljac NV, Krystal JH, Carpenter LL. Risks and benefits of cannabis and cannabinoids in psychiatry. Am J Psychiatry. 2022;179(2):98–109. https://doi.org/10.1176/appi.ajp.2021.21030320. (Epub 2021 Dec 8 PMID: 34875873).

    Article  PubMed  Google Scholar 

  49. Volkow ND, Baler RD, Compton WM, Weiss SR. Adverse health effects of marijuana use. N Engl J Med. 2014;370(23):2219–27. https://doi.org/10.1056/NEJMra1402309.PMID:24897085;PMCID:PMC4827335.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Martinasek MP, McGrogan JB, Maysonet A. A systematic review of the respiratory effects of inhalational marijuana. Respir Care. 2016;61(11):1543–51. https://doi.org/10.4187/respcare.04846. (Epub 2016 Aug 9 PMID: 27507173).

    Article  PubMed  Google Scholar 

  51. Henry JA, Oldfield WL, Kon OM. Comparing cannabis with tobacco BMJ (Clinical research ed). 2003;326(7396):942–3. https://doi.org/10.1136/bmj.326.7396.942.

    Article  PubMed  Google Scholar 

  52. Shover CL, Vest NA, Chen D, Stueber A, Falasinnu TO, Hah JM, Kim J, Mackey I, Weber KA 2nd, Ziadni M, Humphreys K. Association of State policies allowing medical cannabis for opioid use disorder with dispensary marketing for this Indication. JAMA Netw Open. 2020;3(7):2010001.

  53. Shover CL, Davis CS, Gordon SC, Humphreys K. Association between medical cannabis laws and opioid overdose mortality has reversed over time. Proc Natl Acad Sci U S A. 2019;116(26):12624–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Suzuki J, Weiss RD. Cannabinoids for the treatment of opioid use disorder: where is the evidence? J Addict Med. 2021;15(2):91–2. https://doi.org/10.1097/ADM.0000000000000711.PMID:32909980;PMCID:PMC7986228.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Hill KP, Palastro MD, Johnson B, Ditre JW. Cannabis and pain: a clinical review. Cannabis and cannabinoid research. 2017;2(1):96–104. https://doi.org/10.1089/can.2017.0017.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Veterans administration/department of defense practice guideline for the use of opioid therapy for chronic pain. department of veterans affairs, 2017.

  57. Personal communication from Friedhelm Sandbrink, acting director, national pain management, opioid safety and prescription drug monitoring program, veterans health administration, Washington DC.

  58. Raouf M, Bettinger JJ, Fudin J. A practical guide to urine drug monitoring. Federal practitioner : for the health care professionals of the VA, DoD, and PHS. 2018;35(4):38–44.

    PubMed  Google Scholar 

  59. Kulig K. Interpretation of workplace tests for cannabinoids. Journal of medical toxicology : official journal of the American College of Medical Toxicology. 2017;13(1):106–10. https://doi.org/10.1007/s13181-016-0587-z.

    Article  CAS  PubMed  Google Scholar 

  60. Park TW, Saitz R, Ganoczy D, Ilgen MA, Bohnert AS. Benzodiazepine prescribing patterns and deaths from drug overdose among US veterans receiving opioid analgesics: case-cohort study. BMJ. 2015;350:2698.

  61. Bukstein O. Substance abuse in patients with attention-deficit/hyperactivity disorder. Medscape J Med. 2008;10(1):24.

    PubMed  PubMed Central  Google Scholar 

  62. Morasco BJ, Dobscha SK. Prescription medication misuse and substance use disorder in VA primary care patients with chronic pain. Gen Hosp Psychiatry. 2008;30(2):93–9.

    Article  PubMed  Google Scholar 

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Acknowledgements

Not applicable.

Author disclosures

None of the authors have conflicts of interest to report. The funding source (VA HSR&D) had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Grant support

This project was supported by VA HSR&D 1 I01 HX002737-01A1. The VA/CMS Data for Research Project is funded by the VA Health Services Research and Development (HSR&D) Service, VA Information Resource Center (Project Numbers SDR 02-237 and 98-004)

Prior presentations

None.

Funding

Authors were supported by salaries from the Veterans Health Administration (VHA) and the University of California, San Francisco.

Author information

Authors and Affiliations

  1. Addiction Recovery and Treatments Services, San Francisco VA Health Care System, San Francisco, CA, USA

    Tauheed Zaman

  2. Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA

    Tauheed Zaman & Amy L. Byers

  3. Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA

    Dawn M. Bravata

  4. Departments of Medicine and Neurology, Indiana University School of Medicine, Indianapolis, IN, USA

    Dawn M. Bravata

  5. Department of Medicine, University of California, San Francisco, CA, USA

    Amy L. Byers & Salomeh Keyhani

  6. San Francisco VA Medical Center, San Francisco, CA, USA

    Amy L. Byers & Salomeh Keyhani

  7. Center for Care Delivery and Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA

    Erin E. Krebs

  8. Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA

    Erin E. Krebs

  9. Northern California Institute for Research and Education, San Francisco, CA, USA

    Samuel J. Leonard & Wylie Barker

  10. National Pain Management, Opioid Safety and Prescription Drug Monitoring Program, Veterans Health Administration, Washington, DC, USA

    Friedhelm Sandbrink

  11. Department of Neurology, George Washington University, Washington, DC, USA

    Friedhelm Sandbrink

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  1. Tauheed Zaman
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  2. Dawn M. Bravata
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  3. Amy L. Byers
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  4. Erin E. Krebs
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  5. Samuel J. Leonard
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  6. Friedhelm Sandbrink
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  7. Wylie Barker
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  8. Salomeh Keyhani
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Contributions

Dr. Keyhani had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Zaman, Bravata, Byers, Krebs, Keyhani. Acquisition, analysis, or interpretation of data: Zaman, Bravata, Byers, Krebs, Leonard, Sandbrink, Barker, Keyhani. Drafting of the manuscript: Zaman, Leonard, Barker, Keyhani. Critical revision of the manuscript for important intellectual content: Zaman, Bravata, Byers, Krebs, Sandbrink, Keyhani. Statistical analysis: Leonard. Obtained funding: Keyhani. Administrative, technical, or material support: Zaman, Barker, Leonard, Sandbrink. Study supervision: Keyhani. DB, AM, EK, and SK participated in study design. SL and WB gathered data and carried out statistical analysis. DB, AM, EK, SK, FS, and TZ contributed to data interpretation and manuscript writing. The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Tauheed Zaman.

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The Institutional Review Board of the University of California, San Francisco, approved this study. There were no additional requirements for ethics approval and consent.

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Not applicable.

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None of the authors had any financial or non-financial competing interests regarding this study.

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Zaman, T., Bravata, D.M., Byers, A.L. et al. A national population-based study of cannabis use and correlates among U.S. veterans prescribed opioids in primary care. BMC Psychiatry 23, 177 (2023). https://doi.org/10.1186/s12888-023-04648-5

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Keywords

BMC Psychiatry

ISSN: 1471-244X

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