Time-trends in hospitalizations with cannabis use disorder: A 17-year U.S. national study

The impact of cannabis use disorder on urologic oncologic surgery morbidity, length of stay, and inpatient cost: analysis of the National Inpatient Sample from 2003 to 2014

PURPOSE

This study examined the impact of cannabis use disorder (CUD) on inpatient morbidity, length of stay (LOS), and inpatient cost (IC) of patients undergoing urologic oncologic surgery.

METHODS

The National Inpatient Sample (NIS) from 2003 to 2014 was analyzed for patients undergoing prostatectomy, nephrectomy, or cystectomy (n = 1,612,743). CUD was identified using ICD-9 codes. Complex-survey procedures were used to compare patients with and without CUD. Inpatient major complications, high LOS (4th quartile), and high IC (4th quartile) were examined as endpoints. Univariable and multivariable analysis (MVA) were performed to compare groups.

RESULTS

The incidence of CUD increased from 51 per 100,000 admissions in 2003 to 383 per 100,000 in 2014 (p < 0.001). Overall, 3,503 admissions had CUD. Patients with CUD were more frequently younger (50 vs. 61), male (86% vs. 78.4%), Black (21.7% vs. 9.2%), and had 1st quartile income (36.1% vs. 20.6%); all p < 0.001. CUD had no impact on any complication rates (all p > 0.05). However, CUD patients had higher LOS (3 vs. 2 days; p < 0.001) and IC ($15,609 vs. $12,415; p < 0.001). On MVA, CUD was not an independent predictor of major complications (p = 0.6). Conversely, CUD was associated with high LOS (odds ratio (OR) 1.31; 95% CI 1.08-1.59) and high IC (OR 1.33; 95% CI 1.12-1.59), both p < 0.01.

CONCLUSION

The incidence of CUD at the time of urologic oncologic surgery is increasing. Future research should look into the cause of our observed phenomena and how to decrease LOS and IC in CUD patients.

Trends in Cannabis-positive Urine Toxicology Test Results: US Veterans Health Administration Emergency Department Patients, 2008 to 2019

OBJECTIVES

This study aimed to examine trends in cannabis-positive urine drug screens (UDSs) among emergency department (ED) patients from 2008 to 2019 using data from the Veterans Health Administration (VHA) health care system, and whether these trends differed by age group (18-34, 35-64, and 65-75 years), sex, and race, and ethnicity.

METHOD

VHA electronic health records from 2008 to 2019 were used to identify the percentage of unique VHA patients seen each year at an ED, received a UDS, and screened positive for cannabis. Trends in cannabis-positive UDS were examined by age, race and ethnicity, and sex within age groups.

RESULTS

Of the VHA ED patients with a UDS, the annual prevalence positive for cannabis increased from 16.42% in 2008 to 27.2% in 2019. The largest increases in cannabis-positive UDS were observed in the younger age groups. Male and female ED patients tested positive for cannabis at similar levels. Although the prevalence of cannabis-positive UDS was consistently highest among non-Hispanic Black patients, cannabis-positive UDS increased in all race and ethnicity groups.

DISCUSSION

The increasing prevalence of cannabis-positive UDS supports the validity of previously observed population-level increases in cannabis use and cannabis use disorder from survey and administrative records. Time trends via UDS results provide additional support that previously documented increases in self-reported cannabis use and disorder from surveys and claims data are not spuriously due to changes in patient willingness to report use as it becomes more legalized, or due to greater clinical attention over time.

Psychological Distress, Cannabis Use Frequency, and Cannabis Use Disorder Among US Adults in 2020

Using 2020 National Survey on Drug Use and Health data (N = 27,170, age 18+), we examined associations of psychological distress with: (1) cannabis use frequency among all adults, and (2) cannabis use disorder (CUD) among cannabis users. Of all adults, 18.2% reported past-year cannabis use, 12.9% reported mild-moderate psychological distress, and 12.9% reported serious psychological distress. Greater proportions of cannabis users, especially those under age 35, reported psychological distress. Of cannabis users, 28.1% met DSM-5 CUD criteria. Multinomial logistic regression results showed that serious, compared to no, psychological distress was significantly associated with cannabis use at all frequency levels. Both mild-moderate and serious levels of distress were associated with similar elevated CUD risk (RRR = 1.57, 95% CI = 1.15-2.15 for mild-moderate distress; RRR = 1.58, 95% CI = 1.19-2.09 for serious distress) and 2-4 times higher risks of having moderate or severe, compared to mild, CUD and higher odds of having alcohol use disorder. The prevalence of CUD and other substance use/use disorder among cannabis users is concerning as are the significant associations of psychological distress with greater cannabis use frequency, CUD, and other substance use/use disorder. Younger adults especially may benefit from increased behavioral health services given their high prevalence of psychological distress, cannabis use, and CUD.

Chronic Pain, Cannabis Legalization and Cannabis Use Disorder in Veterans Health Administration Patients, 2005 to 2019

Background

The risk for cannabis use disorder (CUD) is elevated among U.S. adults with chronic pain, and CUD rates are disproportionately increasing in this group. Little is known about the role of medical cannabis laws (MCL) and recreational cannabis laws (RCL) in these increases. Among U.S. Veterans Health Administration (VHA) patients, we examined whether MCL and RCL effects on CUD prevalence differed between patients with and without chronic pain.

Methods

Patients with ≥1 primary care, emergency, or mental health visit to the VHA and no hospice/palliative care within a given calendar year, 2005-2019 (yearly n=3,234,382 to 4,579,994) were analyzed using VHA electronic health record (EHR) data. To estimate the role of MCL and RCL enactment in the increases in prevalence of diagnosed CUD and whether this differed between patients with and without chronic pain, staggered-adoption difference-in-difference analyses were used, fitting a linear binomial regression model with fixed effects for state, categorical year, time-varying cannabis law status, state-level sociodemographic covariates, a chronic pain indicator, and patient covariates (age group [18-34, 35-64; 65-75], sex, and race and ethnicity). Pain was categorized using an American Pain Society taxonomy of painful medical conditions.

Outcomes

In patients with chronic pain, enacting MCL led to a 0·14% (95% CI=0·12%-0·15%) absolute increase in CUD prevalence, with 8·4% of the total increase in CUD prevalence in MCL-enacting states attributable to MCL. Enacting RCL led to a 0·19% (95%CI: 0·16%, 0·22%) absolute increase in CUD prevalence, with 11·5% of the total increase in CUD prevalence in RCL-enacting states attributable to RCL. In patients without chronic pain, enacting MCL and RCL led to smaller absolute increases in CUD prevalence (MCL: 0·037% [95%CI: 0·03, 0·05]; RCL: 0·042% [95%CI: 0·02, 0·06]), with 5·7% and 6·0% of the increases in CUD prevalence attributable to MCL and RCL. Overall, MCL and RCL effects were significantly greater in patients with than without chronic pain. By age, MCL and RCL effects were negligible in patients age 18-34 with and without pain. In patients age 35-64 with and without pain, MCL and RCL effects were significant (p<0.001) but small. In patients age 65-75 with pain, absolute increases were 0·10% in MCL-only states and 0·22% in MCL/RCL states, with 9·3% of the increase in CUD prevalence in MCL-only states attributable to MCL, and 19.4% of the increase in RCL states attributable to RCL. In patients age 35-64 and 65-75, MCL and RCL effects were significantly greater in patients with pain.

Interpretation

In patients age 35-75, the role of MCL and RCL in the increasing prevalence of CUD was greater in patients with chronic pain than in those without chronic pain, with particularly pronounced effects in patients with chronic pain age 65-75. Although the VHA offers extensive behavioral and non-opioid pharmaceutical treatments for pain, cannabis may seem a more appealing option given media enthusiasm about cannabis, cannabis commercialization activities, and widespread public beliefs about cannabis efficacy. Cannabis does not have the risk/mortality profile of opioids, but CUD is a clinical condition with considerable impairment and comorbidity. Because cannabis legalization in the U.S. is likely to further increase, increasing CUD prevalence among patients with chronic pain following state legalization is a public health concern. The risk of chronic pain increases as individuals age, and the average age of VHA patients and the U.S. general population is increasing. Therefore, clinical monitoring of cannabis use and discussion of the risk of CUD among patients with chronic pain is warranted, especially among older patients.

Research in Context

Evidence before this study: Only three studies have examined the role of state medical cannabis laws (MCL) and/or recreational cannabis laws (RCL) in the increasing prevalence of cannabis use disorder (CUD) in U.S. adults, finding significant MCL and RCL effects but with modest effect sizes. Effects of MCL and RCL may vary across important subgroups of the population, including individuals with chronic pain. PubMed was searched by DH for publications on U.S. time trends in cannabis legalization, cannabis use disorders (CUD) and pain from database inception until March 15, 2023, without language restrictions. The following search terms were used: (medical cannabis laws) AND (pain) AND (cannabis use disorder); (recreational cannabis laws) AND (pain) AND (cannabis use disorder); (cannabis laws) AND (pain) AND (cannabis use disorder). Only one study was found that had CUD as an outcome, and this study used cross-sectional data from a single year, which cannot be used to determine trends over time. Therefore, evidence has been lacking on whether the role of state medical and recreational cannabis legalization in the increasing US adult prevalence of CUD differed by chronic pain status.Added value of this study: To our knowledge, this is the first study to examine whether the effects of state MCL and RCL on the nationally increasing U.S. rates of adult cannabis use disorder differ by whether individuals experience chronic pain or not. Using electronic medical record data from patients in the Veterans Health Administration (VHA) that included extensive information on medical conditions associated with chronic pain, the study showed that the effects of MCL and RCL on the prevalence of CUD were stronger among individuals with chronic pain age 35-64 and 65-75, an effect that was particularly pronounced in older patients ages 65-75.Implications of all the available evidence: MCL and RCL are likely to influence the prevalence of CUD through commercialization that increases availability and portrays cannabis use as 'normal' and safe, thereby decreasing perception of cannabis risk. In patients with pain, the overall U.S. decline in prescribed opioids may also have contributed to MCL and RCL effects, leading to substitution of cannabis use that expanded the pool of individuals vulnerable to CUD. The VHA offers extensive non-opioid pain programs. However, positive media reports on cannabis, positive online "information" that can sometimes be misleading, and increasing popular beliefs that cannabis is a useful prevention and treatment agent may make cannabis seem preferable to the evidence-based treatments that the VHA offers, and also as an easily accessible option among those not connected to a healthcare system, who may face more barriers than VHA patients in accessing non-opioid pain management. When developing cannabis legislation, unintended consequences should be considered, including increased risk of CUD in large vulnerable subgroups of the population.

Dimensionality and differential functioning of DSM-5 cannabis use disorder criteria in an online sample of adults with frequent cannabis use

The DSM-5 criteria for cannabis use disorder (CUD) combine DSM-IV dependence and abuse criteria (without legal problems) and new withdrawal and craving criteria. Information on dimensionality, internal reliability, and differential functioning of the DSM-5 CUD criteria is lacking. Additionally, dimensionality of the DSM-5 withdrawal items is unknown. This study examined the psychometric properties of the DSM-5 CUD criteria among adults who used cannabis in the past 7 days (N = 5,119). Adults with frequent cannabis use were recruited from the US general population through social media and filled in a web-based survey about demographics and cannabis use behaviors. Factor analysis was used to assess dimensionality, and item response theory analysis models were used to explore relationships between the criteria and the underlying latent trait (CUD), and whether each criterion and the criteria set functioned differently by demographic and clinical characteristics: sex, age, state-level cannabis laws, reasons for cannabis use, and frequency of use. The DSM-5 CUD criteria showed unidimensionality and provided information about the CUD latent trait across the severity spectrum. The cannabis withdrawal items indicated one underlying latent factor. While some CUD criteria functioned differently in specific subgroups, the criteria set as a whole functioned similarly across subgroups. In this online sample of adults with frequent cannabis use, evidence supports the reliability, validity, and utility of the DSM-5 CUD diagnostic criteria set, which can be used for determining a major risk of cannabis use, i.e., CUD, to inform cannabis policies and public health messaging, and for developing intervention strategies.

Trends in substance use disorder diagnoses among Veterans, 2009-2019

BACKGROUND AND OBJECTIVES

Substance use disorder (SUD) represents a substantial health burden to US Veterans. We aimed to quantify recent time trends in Veterans' substance-specific disorders using Veterans Health Administration (VA) data.

METHODS

We identified Veteran VA patients for fiscal years (FY) 2010-2019 (October 1, 2009-September 9, 2019) and extracted patient demographics and diagnoses from electronic health records (~6 million annually). We defined alcohol, cannabis, cocaine, opioid, sedative, and stimulant use disorders with ICD-9 (FY10-FY15) or ICD-10 (FY16-FY19) codes and variables for polysubstance use disorder, drug use disorder (DUD), and SUD.

RESULTS

Diagnoses for substance-specific disorders (excluding cocaine), polysubstance use disorder, DUD, and SUD increased 2%-13% annually for FY10-FY15. Alcohol, cannabis, and stimulant use disorders increased 4%-18% annually for FY16-FY19, while cocaine, opioid, and sedative use disorders changed by ≤1%. Stimulant and cannabis use disorder diagnoses increased most rapidly, and older Veterans had the largest increases across substances.

DISCUSSION AND CONCLUSIONS

Rapid increases in cannabis and stimulant use disorder present a treatment challenge and key subgroups (e.g., older adults) may require tailored screening and treatment options. Diagnoses for SUD are increasing among Veterans overall, but there is important heterogeneity by substance and subgroup. Efforts to ensure access to evidence-based treatment for SUD may require greater focus on cannabis and stimulants, particularly for older adults.

SCIENTIFIC SIGNIFICANCE

These findings represent the first assessment of time trends in substance-specific disorders among Veterans, overall and by age and sex. Notable findings include large increases in diagnoses for cannabis and stimulant use disorder and among older adults.

State Cannabis Legalization and Cannabis Use Disorder in the US Veterans Health Administration, 2005 to 2019

Importance

Cannabis use disorder (CUD) is increasing among US adults. Few national studies have addressed the role of medical cannabis laws (MCLs) and recreational cannabis laws (RCLs) in these increases, particularly in patient populations with high rates of CUD risk factors.

Objective

To quantify the role of MCL and RCL enactment in the increases in diagnosed CUD prevalence among Veterans Health Administration (VHA) patients from 2005 to 2019.

Design, Setting, and Participants

Staggered-adoption difference-in-difference analyses were used to estimate the role of MCL and RCL in the increases in prevalence of CUD diagnoses, fitting a linear binomial regression model with fixed effects for state, categorical year, time-varying cannabis law status, state-level sociodemographic covariates, and patient age group, sex, and race and ethnicity. Patients aged 18 to 75 years with 1 or more VHA primary care, emergency department, or mental health visit and no hospice/palliative care within a given calendar year were included. Time-varying yearly state control covariates were state/year rates from American Community Survey data: percentage male, Black, Hispanic, White, 18 years or older, unemployed, income below poverty threshold, and yearly median household income. Analysis took place between February to December 2022.

Main Outcomes and Measures

As preplanned, International Classification of Diseases, Clinical Modification, ninth and tenth revisions, CUD diagnoses from electronic health records were analyzed.

Results

The number of individuals analyzed ranged from 3 234 382 in 2005 to 4 579 994 in 2019. Patients were largely male (94.1% in 2005 and 89.0% in 2019) and White (75.0% in 2005 and 66.6% in 2019), with a mean (SD) age of 57.0 [14.4] years. From 2005 to 2019, adjusted CUD prevalences increased from 1.38% to 2.25% in states with no cannabis laws (no CLs), 1.38% to 2.54% in MCL-only enacting states, and 1.39% to 2.56% in RCL-enacting states. Difference-in-difference results indicated that MCL-only enactment was associated with a 0.05% (0.05-0.06) absolute increase in CUD prevalence, ie, that 4.7% of the total increase in CUD prevalence in MCL-only enacting states could be attributed to MCLs, while RCL enactment was associated with a 1.12% (95% CI, 0.10-0.13) absolute increase in CUD prevalence, ie, that 9.8% of the total increase in CUD prevalence in RCL-enacting states could be attributed to RCLs. The role of RCL in the increases in CUD prevalence was greatest in patients aged 65 to 75 years, with an absolute increase of 0.15% (95% CI, 0.13-0.17) in CUD prevalence associated with RCLs, ie, 18.6% of the total increase in CUD prevalence in that age group.

Conclusions and Relevance

In this study of VHA patients, MCL and RCL enactment played a significant role in the overall increases in CUD prevalence, particularly in older patients. However, consistent with general population studies, effect sizes were relatively small, suggesting that cumulatively, laws affected cannabis attitudes diffusely across the country or that other factors played a larger role in the overall increases in adult CUD. Results underscore the need to screen for cannabis use and CUD and to treat CUD when it is present.

Risk of readmission among individuals with cannabis use disorder during a 15-year cohort study: the impact of socio-economic factors and psychiatric comorbidity

BACKGROUND AND AIM

Cannabis use disorder (CUD) is one of the main reasons for seeking substance treatment in the Nordic countries, but there are few studies on readmission to care. We aimed to characterize CUD readmission and estimate the magnitude of how socio-economic factors and psychiatric comorbidity influence the risk of CUD readmission.

DESIGN, SETTING AND PARTICIPANTS

This was a nation-wide cohort study carried out between 2001 and 2016 in Sweden. The participants were individuals with CUD, aged 17 years and above (n = 12 143).

MEASUREMENTS

Information on predictors was obtained from registers and included education, income and psychiatric comorbidity assessed by six disease groups. The outcome measure was readmission, defined as a CUD visit to health-care at least 6 months after initial CUD diagnosis. Hazard ratios (HR) were estimated using Cox survival analyses and flexible parametric survival analyses to assess risk of readmission and how the risk varied with age.

FINDINGS

The vast majority of CUD visits took place in outpatient care (~80%). Approximately 23% of the included individuals were readmitted to care during follow-up. The fully adjusted model showed an increased risk of readmission among those with schizophrenia and other psychotic disorders [HR = 1.54, 95% confidence interval (CI) = 1.29-1.84], low education (HR = 1.40, 95% CI = 1.24-1.57), personality disorders (HR = 1.27, 95% CI = 1.05-1.54) or mood disorders (HR = 1.27, 95% CI = 1.12-1.45). Flexible parametric modeling revealed increased risk of readmission mainly in individuals aged 18-35 years.

CONCLUSIONS

The risk of readmission was highest among those with low education, schizophrenia and other psychotic disorders, mood-related disorders or personality disorders. Individuals aged 18-35 years showed the highest risk of readmission. Our findings highlight individuals with complex health-care needs.

Prevalence of Substance use disorder among young adults hospitalized in the US hospital: A decade of change

INTRODUCTION

Mental health disorders (MHD) and substance use disorders (SUD) lead to outstanding socioeconomic costs and increased hospital visits. However, very few studies have quantified this trend over time and across specific conditions. ​​Our study aims to investigate and compare the prevalence of MHDs and SUDs in hospitalizations between 2007 and 2017.

METHODS

We used hospital records for 2007 and 2017 from the National Inpatient Sample (NIS) datasets to identify young adults (18-44 years) hospitalized with MHD and SUD. The prevalence of MHD in hospitalized patients in 2017 vs. 2007 was measured and compared. We generated a multivariable logistic regression analysis controlled for confounders, including age, sex, race, and payer status. We evaluated these outcomes using Odds Ratio (OR) and 95% Confidence Interval (CI).

RESULTS

A total 10,353,890 patients were included in 2007, and 8,569,789 patients were included in 2017. The prevalence of drug abuse among hospitalized patients was 8.4% in 2017 vs. 6.2% in 2007. Prevalence increased in both genders (15.7% vs. 13.0% among male, 5.7% vs. 3.9% among females) in 2017 vs. 2007. All psychiatric disorders showed a higher prevalence in 2017 compared to 2007. When stratified by race, the prevalence of substance use disorder increased among all races except Black race between 2017 vs. 2007. On multivariable analysis, widespread drug abuse was significantly associated with hospital admissions in 2017 vs. 2007 (OR: 1.27, 95% CI: 1.20-1.34, p<0.001). These associations held across many substance abuse cases and mental health disorders except cocaine abuse (OR: 0.84, 95%CI: 0.76-0.93, p<0.001).

CONCLUSION

There was a significant rise in substance use disorder and psychiatric disorder a decade later, from 2007, in hospitalized patients in the age group 18-44 years. The most increase was observed in amphetamine use disorder and anxiety disorder. Suicide and intentional self-inflicted injury increased in all races, with a maximum increase observed in Native Americans. Further studies evaluating the factors responsible for this upward trend would be beneficial.

Trends in Cannabis Use Disorder Diagnoses in the U.S. Veterans Health Administration, 2005-2019

OBJECTIVE

In the United States, adult cannabis use has increased over time, but less information is available on time trends in cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine change over time in cannabis use disorder diagnoses among veterans, an important population subgroup, and whether such trends differ by age group (<35 years, 35-64 years, ≥65 years), sex, or race/ethnicity.

METHODS

VHA electronic health records from 2005 to 2019 (range of Ns per year, 4,403,027-5,797,240) were used to identify the percentage of VHA patients seen each year with a cannabis use disorder diagnosis (ICD-9-CM, January 1, 2005-September 30, 2015; ICD-10-CM, October 1, 2015-December 31, 2019). Trends in cannabis use disorder diagnoses were examined by age and by race/ethnicity and sex within age groups. Given the transition in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM).

RESULTS

In 2005, the percentages of VHA patients diagnosed with cannabis use disorder in the <35, 35-64, and ≥65 year age groups were 1.70%, 1.59%, and 0.03%, respectively; by 2019, the percentages had increased to 4.84%, 2.86%, and 0.74%, respectively. Although the prevalence of cannabis use disorder was consistently higher among males than females, between 2016 and 2019, the prevalence increased more among females than males in the <35 year group. Black patients had a consistently higher prevalence of cannabis use disorder than other racial/ethnic groups, and increases were greater among Black than White patients in the <35 year group in both periods.

CONCLUSIONS

Since 2005, diagnoses of cannabis use disorder have increased substantially among VHA patients, as they have in the general population and other patient populations. Possible explanations warranting investigation include decreasing perception of risk, changing laws, increasing cannabis potency, stressors related to growing socioeconomic inequality, and use of cannabis to self-treat pain. Clinicians and the public should be educated about the increases in cannabis use disorder in general in the United States, including among patients treated at the VHA.