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Do cannabis use disorders increase medication non-compliance in schizophrenia?: United States Nationwide inpatient cross-sectional study
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Do cannabis use disorders increase medication non-compliance in schizophrenia?: United States Nationwide inpatient cross-sectional study Rikinkumar S. Patel a,b,⁎, Venkatesh Sreeram c, Ramu Vadukapuram d, Raman Baweja e a
Department of Psychiatry, Griffin Memorial Hospital, Norman, OK, USA Department of Psychiatry and Behavioral Sciences, Oklahoma State University, Tulsa, OK, USA c Department of Psychiatry, Harlem Hospital, New York, NY, USA d Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, USA e Department of Psychiatry and Behavioral Health, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA b
a r t i c l e
i n f o
Article history: Received 27 May 2020 Received in revised form 19 September 2020 Accepted 2 November 2020 Available online xxxx Keywords: Schizophrenia Psychotic disorders Medication noncompliance Nonadherence Relapse Cannabis use Marijuana Substance use
a b s t r a c t Objectives: This study aims to find the prevalence of medication non-compliance among schizophrenia inpatients and to compare the relative risks of medication non-compliance with cannabis use disorders (CUDs) versus without CUDs. In addition, this study also examines the odds of medication non-compliance in schizophrenia inpatients with CUDs. Methods: This is a retrospective cross-sectional analysis of the nationwide inpatient sample. This sample includes 1,030,949 inpatients (age 18 to 65 years) from 2010 to 2014 with primary ICD-9 diagnoses of schizophrenia and other psychotic disorders, that were further sub grouped based on medication non-compliance. CUDs were recognized using the ICD-9 codes. Results: The prevalence of medication non-compliance was 26% among schizophrenia inpatients. Multivariable analysis revealed that CUD comorbidity was a significant risk factor for medication non-compliance among schizophrenia patients when unadjusted (OR 1.49, 95%CI 1.469–1.503), and association remained significant even after adjusting for covariates (adjusted OR 1.38, 95%CI 1.268–1.489). Comorbid CUD was seen in young adults (18–35 years, 62.4%), males (80.5%), African Americans (54.1%) and low-income families below 25th percentile (48.6%) with personality disorders (10.5%). Conclusion: Medication compliance is a challenge among schizophrenia patients, which has a significant adverse impact on the course of illness. CUD Comorbidity increases the risk of medication non-compliance significantly among schizophrenia patients. In addition to case management, an integrated treatment model to address both substance use disorders and psychosis will translate into better long-term outcomes in schizophrenia patients. © 2020 Elsevier B.V. All rights reserved.
1. Introduction Schizophrenia is a devastating chronic psychiatric disorder with a global prevalence of 1% and is one of the top fifteen leading diseases of disability (Disease et al., 2017; Moreno-Kustner et al., 2018). It has a major impact on healthcare systems with a cost burden of $155.7 billion in the United States (US). This includes 24% of direct health service cost, 6% of direct non–health service cost, and 76% of indirect health service cost (Cloutier et al., 2016).
⁎ Corresponding author at: Department of Psychiatry, Griffin Memorial Hospital, 900 E Main St, Norman, OK 73071, USA. E-mail address: [email protected] (R.S. Patel).
Medication non-compliance is highly prevalent in schizophrenia, as per a recent study, about 71% of 1.2 million patients with schizophrenia are non-compliant with medication (Desai and Nayak, 2019). Medication non-compliance has a significant adverse impact on the course of illness and is associated with negative clinical outcomes including relapse, frequent re-hospitalization, longer time to remission, and suicide attempts (Corroon and Kight, 2018). Furthermore, medication noncompliance has also been associated with a higher utilization of emergency services, legal issues, violence, victimizations, poorer life satisfaction, and substance use (Ascher-Svanum et al., 2006). Higher utilization of healthcare resources is seen in schizophrenia patients with noncompliance including more frequent outpatient visits (by two times) and office visits (by 18 times), but has lower utilization of inpatient and emergency room visits compared to medication compliant patients
https://doi.org/10.1016/j.schres.2020.11.002 0920-9964/© 2020 Elsevier B.V. All rights reserved.
Please cite this article as: R.S. Patel, V. Sreeram, R. Vadukapuram, et al., Do cannabis use disorders increase medication non-compliance in schizophrenia?: United States Nation..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2020.11.002
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other psychotic disorders (295.00–298.9, 299.10 or 299.11), and were further sub-grouped based on medication non-compliance (ICD-9 code: V15.81). CUDs were recognized using the ICD-9 codes: 304.30 (cannabis dependence, unspecified), 304.31 (cannabis dependence, continuous), 304.32 (cannabis dependence, episodic), 305.20 (non-dependent cannabis abuse, unspecified), 305.21 (non-dependent cannabis abuse, continuous), and 305.22 (nondependent cannabis abuse, episodic). Demographic characteristics included are age (18–35, 36–50, 51–65 years), gender (male or female), race (Caucasian, African American, Hispanic, and others), median household income in percentiles and primary payer status (Medicare, Medicaid, private, self-pay/ uninsured) (2019a). Comorbid EPS, personality disorders, and SUD (alcohol, tobacco, cocaine, amphetamine, and opioid) were identified using ICD-9 diagnosis codes as mentioned in Appendix (2019a).
(Desai and Nayak, 2019). In contrast, in a three-year prospective study, significantly higher rates of psychiatric hospitalizations and use of emergency psychiatric services were among medication noncompliant as compared to compliant individuals (Haddad et al., 2014). Some risk factors have been associated with medication noncompliance in patients with schizophrenia including substance abuse, illness severity, lack of insight, sociodemographic factors (age, family and marital status, ethnicity and level of education), prior history of noncompliance, comorbid personality disorders/psychopathy, treatmentrelated factors (adverse effects, complex treatment regimen), and environmental factors (physician-patient relationship, financial status) (Higashi et al., 2013; Volavka and Citrome, 2011). African Americans and young adults are more prone to medication non-compliance compared to Caucasians and older adults. Individuals with a lower level of education have a four times higher likelihood of medication noncompliance (Hudson et al., 2004; Valenstein et al., 2004). Medication side effects, like extrapyramidal symptoms (EPS), are one of the main reasons why patients with schizophrenia stopped taking their medications (Dibonaventura et al., 2012). Substance use disorders (SUDs) are a major concern among patients with schizophrenia, which also increase the risk of medication noncompliance. The most common substances abused by patients with schizophrenia are nicotine (60% to 90%) and alcohol (21% to 86%), followed by cannabis (17% to 80.3%) (Kerner, 2015; Volkow, 2009). Furthermore, about half of the patients with schizophrenia have either alcohol or cocaine dependency and between 70% to 90% are nicotinedependent (Brady and Sinha, 2005; Ziedonis et al., 1994). Over the 15year follow-up study, cannabis abuse (significant use on more than 50 occasions) was associated with a six times greater risk of developing schizophrenia (Andreasson et al., 1987). The rate of non-compliance with treatment among patients with schizophrenia is much higher among nicotine and alcohol users (Pristach and Smith, 1990; Uzun et al., 2003). A recent meta-analysis of observational studies (N = 3678) found a higher risk of medication non-compliance in cannabis users in contrast to non-users (Foglia et al., 2017). With the recent change in legal policies, cannabis use disorders (CUDs) have drastically increased. It is unknown at present how this will influence patients with schizophrenia and if comorbid CUDs have any impact on medication compliance (Cerda et al., 2019). There is limited data to determine whether CUD comorbidity is the risk factor associated with medication non-compliance among patients with schizophrenia and comorbid CUDs. In this study, we aim to find the prevalence of medication non-compliance among schizophrenia inpatients and compare the relative risks of medication non-compliance with CUD versus without CUD (non-CUD). Next, we also examine the association between CUD comorbidity among hospitalized patients with schizophrenia and medication non-compliance. Finally, we examine the characteristics of schizophrenia inpatients with CUD and medication non-compliance.
2.3. Statistical analysis The prevalence of medication non-compliance, and CUD and nonCUD cohorts were identified among schizophrenia inpatients by searching the secondary diagnosis fields for CUDs and relative risk was calculated using the binomial logistic regression analysis. We used bivariate analysis to compare demographics, EPS, personality disorders, and comorbid SUDs including CUDs in patients with schizophrenia by medication non-compliance. Multivariable logistic regression analyses, adjusted for demographics, SUDs, personality disorders, and EPS were used to evaluate the adjusted odds ratio (OR) between CUDs and medication non-compliance in schizophrenia inpatients. Another bivariate analysis was conducted in only schizophrenia inpatients with medication non-compliance, sub-grouped by CUDs and Pearson's chi-square test was used. All data analyses were conducted using SPSS version 26 (IBM Corporation, Armonk, NY) with statistical significance set a priori at P < .01 for all analyses. 2.4. Ethical approval Individual patient identifiers are used to protect patient health information (2019a). The use of administrative databases, under the HCUP and publicly available de-identified NIS database, does not require institutional review board approval (2019b). 3. Results 3.1. Prevalence of medication non-compliance Medication non-compliance (N = 265,605) and compliance (N = 765,344) cohorts were identified (age 18–65). The prevalence of medication non-compliance was 25.76% among schizophrenia inpatients.
2. Material and methods 3.2. Risk factors for medication non-compliance 2.1. Data source Both non-compliance and compliance cohorts were compared to identify risk factors for medication non-compliance. Medication noncompliance was more prevalent in young adults (18–35 years) and was two times higher (95% CI 1.915–2.164) odds for non-compliance compared to older adults (51–65 years). Gender was not associated with non-compliance (p = .189). Prevalence of medication noncompliance was higher in African Americans (43.5%) and was at 2.6 times higher risk (95% CI 2.433–2.733) compared to 38.9% Caucasians. Though non-compliance was only seen in 7.3% other races, they were at 1.5 times higher risk (95% CI 1.345–1.621). Patients from lowincome families, below the 25th percentile, had higher odds (adjusted OR 1.11, 95% CI 1.033–1.187) than those from high-income families. Patients covered by Medicaid had 1.4 times higher odds (95% CI 1.308–1.462) than those covered by Medicare.
We conducted a retrospective cross-sectional analysis of the nationwide inpatient sample (NIS) i.e. the largest database in the US for epidemiological estimates involving inpatient care (2019b). The healthcare cost and utilization project (HCUP) NIS acquires administrative data on inpatient discharges from about 4400 non-federal hospitals coming from 44 states in the US, excluding rehabilitation and long-term care hospitals (2019b). Diagnostic information in the NIS is included using the international classification of diseases, ninth edition (ICD-9) codes (2019b). 2.2. Inclusion criteria and variables We included 1,030,949 inpatients (age 18 to 65 years) from the NIS (2010 to 2014) with primary ICD-9 diagnoses of schizophrenia and 2
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CUD cohort in all age groups with a 1.5 times higher risk seen in the age 18–35 years and 36–50 years as shown in Table 2.
EPS was prevalent in all patients in the medication non-compliance cohort as compared to only 1.2% in the medication compliance cohort. There was statistically no significant association between EPS (P = .607) and personality disorders (P = .743) with medication noncompliance in schizophrenia inpatients. Tobacco use disorders were most prevalent (34.7%) in the non-compliance group with 1.32 times higher odds (95% CI 1.257–1.393) followed by alcohol use disorders (18.4%, adjusted OR 1.35, 95% CI 1.254–1.444) compared to without tobacco and alcohol use disorders. There existed no significant association between medication non-compliance with opioid, cocaine, or amphetamine use disorders. Multivariable analysis revealed that CUD comorbidity was a significant risk factor for medication non-compliance among schizophrenia inpatients when unadjusted (OR 1.49, 95% CI 1.469–1.503), and adjusted for demographics and SUD (adjusted OR 1.31, 95% CI 1.291–1.327), and even after adjusting for demographics, SUD, personality disorders, and EPS (adjusted OR 1.38, 95% CI 1.268–1.489) as shown in Table 1. The relative risk of medication non-compliance in schizophrenia inpatients was significantly greater in CUD cohort compared to the non-
3.3. Medication non-compliance by comorbid cannabis use disorders Schizophrenia inpatients with medication non-compliance were further divided into CUD (N = 37,945) and non-CUD (N = 619,127) cohorts. CUD was seen in young adults (18–35 years, 62.4%), males (80.5%) and African Americans (54.1%) with about half of them from low-income families below the 25th percentile (48.6%). Personality disorders were seen in a significantly higher proportion of the CUD cohort (10.5% vs. 7.4%, P < .001). The prevalence rates of other SUDs were significantly higher in the CUD cohort (P < .001) with the highest seen in tobacco use disorders (46.3% vs. 31.9%) as shown in Table 3. 4. Discussion Among schizophrenia inpatients, approximately 26% presented with medication non-compliance. Furthermore, among the non-compliant group, about 20% had CUD comorbidity. Our study found that schizophrenia inpatients with medication non-compliance and CUD comorbidity were young adults (18–35 years) African American males from low-income families with comorbid personality disorders and higher use of other SUDs. Comorbid CUD had a 49% higher risk for medication non-compliance. Even after adjusting for potential confounders, cannabis use remained a significant independent predictor with an increased risk for medication non-compliance by 38%. Young schizophrenia patients (18–35 years) had about two times higher chance for medication non-compliance. This is comparative to other nationwide study, in which three-fifths of patients were young adults (Vadukapuram et al., 2020). Gender was not a significant predictor for medication non-compliance in this study which is supported by a study by Acosta et al. (2009). In terms of race-wise predictors, African Americans had 2.6 times higher odds for medication non-compliance compared to Caucasians. There are several reasons for non-compliance among different ethnicities including the possibilities of more healthcare providers being white leading to misleading interpretation and treatment, less access to healthcare in other ethnic groups, or usage of alternative therapies, other cultural issues or concerns about the addictive quality of psychotropic medications (Opolka et al., 2003). A substantial portion of schizophrenia inpatients with CUD comorbidity were young (18–35 years) African American male from lowincome families. These findings are consistent with past literature (Hunt et al., 2018; Secades-Villa et al., 2015; Wilson et al., 2019). By age-wise distribution, the odds for medication non-compliance in schizophrenia inpatients were higher in CUD by 1.5 times in adults from 18 to 50 years. In a prospective study, male gender was a significant risk factor for CUD and this association was considered a greater hazard for males to be non-compliant with psychotropic medications (Miller et al., 2009). African American, and those from lower socioeconomic status tend to have lower support systems and a poor therapeutic alliance that makes them vulnerable to cannabis use early in the treatment for psychiatric illness (Miller et al., 2009). Tobacco use disorders were most prevalent (34.7%) in schizophrenia patients with medication non-compliance followed by alcohol use disorders (18.4%). Tobacco use disorders have been considered, by far the
Table 1 Risk factors for medication non-compliance in schizophrenia inpatients. Variables
Compliant Non-compliant OR
95% CI
P-value
–
–
Total inpatients
765,344
265,605
–
Age at admission, % 18–35 years 36–50 years 51–65 years
38.3 32.1 29.6
38.6 32.5 28.8
2.04 1.915–2.165 1.56 1.479–1.648 Reference
<0.001 <0.001
Sex, % Male Female
60.6 39.4
63.3 36.7
0.97 0.923–1.016 Reference
<0.186
Race, % Caucasian African American Hispanic Others
49.7 31.4 12.4 6.4
38.9 43.5 10.3 7.3
Reference 2.58 2.432–2.732 1.52 1.397–1.650 1.48 1.344–1.620
<0.001 <0.001 <0.001
44.2 23.3
1.11 1.034–1.187 0.92 0.858–0.990
0.004 0.025
18.7
1.08 1.004–1.171
0.039
13.8
Reference
37.7 41.3 10.7 10.3
Reference 1.38 1.308–1.462 0.97 0.904–1.045 1.14 1.052–1.243
Side effects from medication, % None – Extrapyramidal 1.2
– 100
Reference 5.97 <0.001–7.795 0.607
Personality disorders No 91.7 Yes 8.3
92.0 8.0
Reference 0.99 0.905–1.074
0.743
Substance use disorder, % None – Alcohol 14.5 Tobacco 28.6 Cannabis 14.1 Opioid 3.5 Amphetamine 4.2 Cocaine 6.8
– 18.4 34.7 19.6 3.7 4.0 10.0
Reference 1.35 1.254–1.444 1.32 1.257–1.393 1.38 1.268–1.489 1.15 1.003–1.327 1.14 0.993–1.314 1.11 1.003–1.238
<0.001 <0.001 <0.001 0.045 0.063 0.044
Median household income, % 0 – 25th percentile 42.0 26th – 50th 25.4 percentile 51st – 75th 19.3 percentile 76th – 100th 13.2 percentile Primary payer, % Medicare Medicaid Private Self-pay or uninsured
36.2 36.9 14.3 12.6
<0.001 0.440 0.002
Table 2 The effect of medication non-compliance on relative risk of schizophrenia hospitalization by age in CUD.
The proportion of non-compliant and compliant patients were obtained using cross tabulation. Odds ratio generated by multinomial logistic regression at 95% confidence interval and significant P values ≤.001. OR: odds ratio; CI: confidence interval.
Age groups
Compliant
Non-compliant
RR
95% CI
P value
18–35 years 36–50 years 51–65 years
68,155 26,425 226,605
32,425 13,445 76,605
1.53 1.53 1.41
1.503–1.551 1.493–1.561 1.366–1.455
<0.001 <0.001 <0.001
Relative risk generated by binomial logistic regression and Significant P values ≤ .001 at 95% confidence interval. RR: relative risk; CI: confidence interval. 3
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between cannabis use and medication non-compliance. Miller and colleagues reported that cannabis use not only affected medication compliance but was also associated with treatment discontinuation. Additionally, cannabis use is associated with a decline in insight, poor judgment, decreased motivation, and exacerbation of psychotic symptoms (Miller et al., 2009). Furthermore, medication non-compliance in current cannabis users increased by 5.8 times compared to non-users and increased by 5.5 times when compared to former cannabis users. A higher number of medication non-compliance in our study, most likely related to sampling coming from more severe cases, which required inpatient hospitalization, while a meta-analysis has included studies from different clinical settings including inpatient and outpatient (Foglia et al., 2017). Also, in our study CUD comorbidity increased odds of medication non-compliance in schizophrenia inpatients by 1.37 times after adjusting for other potential confounders including demographics, EPS, comorbid personality disorders, and other SUD. Several limitations can be taken into account. Firstly, medication noncompliance in study inpatients was only based on ICD-9 codes, which may lead to under-reporting, as many clinicians do not bill the patients by using diagnostic codes for non-compliance, EPS, comorbid personality disorders, or CUD at the time of patient discharge. Secondly, due to Berkson's bias, comorbidities and SUDs in study inpatients tend to be higher than in a community-based general population. It is also possible that schizophrenia inpatients may have more severe and higher rates of certain psychotic symptoms, which required inpatient hospitalization, may have higher rates of CUDs. Given the administrative nature of the NIS database, details regarding symptoms profiles and severity of schizophrenia are not available. Additionally, this is a cross-sectional retrospective study, which lacks data on the causal relationship between cannabis use and medication non-compliance. However, the biggest strength of our study lies in the national representation and uniform collection of inpatient data from 4400 hospitals in the US with higher external validity of the results. This is the first large-sample study to our knowledge including more than one million schizophrenia patients to report the impact of CUDs on medication non-compliance in schizophrenia inpatients after controlling for demographics, SUD, EPS, and comorbid personality disorder. Medication non-compliance is a major concern among patients with schizophrenia and leads to various negative outcomes including relapse and frequent re-hospitalization. As cannabis legalization becomes widespread in the US, it is imperative to continue to monitor cannabis use and medication compliance among patients with schizophrenia and to address CUD comorbidity in addition to the treatment of psychosis.
Table 3 Characteristics of schizophrenia inpatients with medication non-compliance by cannabis use disorder. Variablesa
Non- CUD
CUD
P-value
Total patients
213,630
51,975
–
Age at admission, % 18–35 years 36–50 years 51–65 years
32.8 34.2 33.0
62.4 25.9 11.7
<0.001
Sex, % Male Female
59.1 40.9
80.5 19.5
<0.001
41.2 41.0 10.3 7.6
29.8 54.1 10.1 6.1
<0.001
43.1 23.6 19.2 14.0
48.6 22.2 16.6 12.7
< 0.001
40.1 39.6 10.6 9.6 7.4
28.0 48.1 11.2 12.7 10.5
<0.001
Comorbid substance use disorder, % Alcohol abuse 15.0 Tobacco abuse 31.9 Opioid abuse 3.3 Amphetamine abuse 2.8 Cocaine abuse 7.1
32.3 46.3 5.2 8.6 22.0
<0.001 <0.001 <0.001 <0.001 <0.001
Race, % Caucasian African American Hispanic Others Median household income, %, 0 – 25th percentile 26th – 50th percentile 51st – 75th percentile 76th – 100th percentile Primary payer, % Medicare Medicaid Private Self-pay or uninsured Personality disorders
<0.001
The proportion of non-cannabis and cannabis cohorts were obtained using cross tabulation and the Pearson Chi-Square (χ2) test. Significant P values ≤ .001 at 95% confidence interval. CUD: cannabis use disorder. a No statistics are computed because extrapyramidal variable is constant.
most prevalent substance used and thereby affecting medication noncompliance rate in patients with schizophrenia (Fergusson et al., 2006; Vadukapuram et al., 2020). As per our study, other SUDs with opioid, cocaine, and amphetamine were not significantly associated with medication non-compliance in schizophrenia patients. The higher prevalence of other SUDs among cannabis users is not surprising given the findings in the general population where cannabis is considered as a gateway drug for other substance use (Fergusson et al., 2006; SecadesVilla et al., 2015). Among schizophrenia patients with medication non-compliance, potential side effects and poor understanding about the antipsychotics are potential contributors (Spagnoli et al., 1989). EPS is considered a foremost determinant, followed by weight gain and sexual side effects leading to discontinuing antipsychotics medications (Fleischhacker et al., 1994). In our study EPS was seen in all schizophrenia inpatients with medication non-compliance. Comorbid personality disorders also have negative outcomes among patients with schizophrenia including medication non-compliance (Moran and Hodgins, 2004; Volavka and Citrome, 2011). Yet, CUD comorbity was a significant risk factor for medication non-compliance even after controlling for EPS and comorbid personality disorders. Limited studies are available focusing on whether the long-term use of cannabis has a direct correlation to medication non-compliance among the schizophrenic population (Degenhardt and Hall, 2006; Rozin et al., 2019). In a meta-analysis, about 42% of schizophrenia patients had comorbid SUDs and 26% had CUDs (Hunt et al., 2018). The prevalence of cannabis use among the medication-compliance cohort was 14%, while it was 20% among the medication non-compliance cohort in our study. Some prospective studies have reported a correlation
5. Conclusion Schizophrenia is a chronic psychiatric disorder and needs lifelong treatment. Medication compliance is a challenge among patients with schizophrenia, which has a significant adverse impact on the course of illness. CUD comorbidity increases the risk of medication noncompliance significantly among patients with schizophrenia. Young African American males with schizophrenia from low-income families with comorbid personality disorders and use of other SUDs who are also using cannabis or have CUDs are at the highest risk for the medication non-compliance. In addition to case management, an integrated treatment model addressing both SUDs and psychosis will translate into better long-term outcomes for patients with schizophrenia. Role of the funding source This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Declaration of competing interest RS Patel, V Sreeram, R Vadukapuram and R Baweja report no conflicts of interest. 4
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Acknowledgements None.
Appendix A. Appendix
Diagnosis
ICD-9 diagnosis code
Extrapyramidal side effects Personality disorders Alcohol use disorder
333.85, 333.82, 333.99, 781.0, 333.71, 307.3, 307.20, 351.8, 333.81 301.0, 301.10–301.13, 301.20–301.22, 301.3, 301.4, 301.50, 301.51, 301.59, 301.6, 301.7, 301.81–301.84, 301.89, 301.9 291.0–291.3, 291.5, 291.8, 291.81, 281.82, 291.89, 291.9, 303.00–303.93, 305.00–305.03 305.1
Tobacco use disorder Cocaine use 304.20–304.22, 305.60–305.62 disorders Amphetamine use 304.40–304.42, 305.70–305.72 disorders Opioid use disorders 304.00–304.02, 305.51–305.52, 304.70–304.72 ICD-9: international classification of diseases, ninth edition.
References 2019a. NIS Description of Data Elements. Agency for Healthcare Research and Quality, Rockville, MD. 2019b. Overview of the National (Nationwide) Inpatient Sample (NIS). Agency for Healthcare Research and Quality, Rockville, MD. Acosta, F.J., Bosch, E., Sarmiento, G., Juanes, N., Caballero-Hidalgo, A., Mayans, T., 2009. Evaluation of noncompliance in schizophrenia patients using electronic monitoring (MEMS) and its relationship to sociodemographic, clinical and psychopathological variables. Schizophr. Res. 107 (2–3), 213–217. Andreasson, S., Allebeck, P., Engstrom, A., Rydberg, U., 1987. Cannabis and schizophrenia. A longitudinal study of Swedish conscripts. Lancet 2 (8574), 1483–1486. Ascher-Svanum, H., Faries, D.E., Zhu, B., Ernst, F.R., Swartz, M.S., Swanson, J.W., 2006. Medication adherence and long-term functional outcomes in the treatment of schizophrenia in usual care. J Clin Psychiatry 67 (3), 453–460. Brady, K.T., Sinha, R., 2005. Co-occurring mental and substance use disorders: the neurobiological effects of chronic stress. Am. J. Psychiatry 162 (8), 1483–1493. Cerda, M., Mauro, C., Hamilton, A., Levy, N.S., Santaella-Tenorio, J., Hasin, D., Wall, M.M., Keyes, K.M., Martins, S.S., 2019. Association between recreational marijuana legalization in the United States and changes in marijuana use and cannabis use disorder from 2008 to 2016. JAMA Psychiatry 77 (2), 165–171. Cloutier, M., Aigbogun, M.S., Guerin, A., Nitulescu, R., Ramanakumar, A.V., Kamat, S.A., DeLucia, M., Duffy, R., Legacy, S.N., Henderson, C., Francois, C., Wu, E., 2016. The economic burden of schizophrenia in the United States in 2013. J Clin Psychiatry 77 (6), 764–771. Corroon, J., Kight, R., 2018. Regulatory status of cannabidiol in the United States: a perspective. Cannabis Cannabinoid Res 3 (1), 190–194. Degenhardt, L., Hall, W., 2006. Is cannabis use a contributory cause of psychosis? Can. J. Psychiatr. 51 (9), 556–565. Desai, R., Nayak, R., 2019. Effects of medication nonadherence and comorbidity on health resource utilization in schizophrenia. J Manag Care Spec Pharm 25 (1), 37–46. Dibonaventura, M., Gabriel, S., Dupclay, L., Gupta, S., Kim, E., 2012. A patient perspective of the impact of medication side effects on adherence: results of a cross-sectional nationwide survey of patients with schizophrenia. BMC Psychiatry 12, 20. Disease, G.B.D., Injury, I., Prevalence, C., 2017. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 390 (10100), 1211–1259.
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Contents lists available at ScienceDirect
Schizophrenia Research journal homepage: www.elsevier.com/locate/schres
Do cannabis use disorders increase medication non-compliance in schizophrenia?: United States Nationwide inpatient cross-sectional study Rikinkumar S. Patel a,b,⁎, Venkatesh Sreeram c, Ramu Vadukapuram d, Raman Baweja e a
Department of Psychiatry, Griffin Memorial Hospital, Norman, OK, USA Department of Psychiatry and Behavioral Sciences, Oklahoma State University, Tulsa, OK, USA c Department of Psychiatry, Harlem Hospital, New York, NY, USA d Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, USA e Department of Psychiatry and Behavioral Health, Penn State Milton S. Hershey Medical Center, Hershey, PA, USA b
a r t i c l e
i n f o
Article history: Received 27 May 2020 Received in revised form 19 September 2020 Accepted 2 November 2020 Available online xxxx Keywords: Schizophrenia Psychotic disorders Medication noncompliance Nonadherence Relapse Cannabis use Marijuana Substance use
a b s t r a c t Objectives: This study aims to find the prevalence of medication non-compliance among schizophrenia inpatients and to compare the relative risks of medication non-compliance with cannabis use disorders (CUDs) versus without CUDs. In addition, this study also examines the odds of medication non-compliance in schizophrenia inpatients with CUDs. Methods: This is a retrospective cross-sectional analysis of the nationwide inpatient sample. This sample includes 1,030,949 inpatients (age 18 to 65 years) from 2010 to 2014 with primary ICD-9 diagnoses of schizophrenia and other psychotic disorders, that were further sub grouped based on medication non-compliance. CUDs were recognized using the ICD-9 codes. Results: The prevalence of medication non-compliance was 26% among schizophrenia inpatients. Multivariable analysis revealed that CUD comorbidity was a significant risk factor for medication non-compliance among schizophrenia patients when unadjusted (OR 1.49, 95%CI 1.469–1.503), and association remained significant even after adjusting for covariates (adjusted OR 1.38, 95%CI 1.268–1.489). Comorbid CUD was seen in young adults (18–35 years, 62.4%), males (80.5%), African Americans (54.1%) and low-income families below 25th percentile (48.6%) with personality disorders (10.5%). Conclusion: Medication compliance is a challenge among schizophrenia patients, which has a significant adverse impact on the course of illness. CUD Comorbidity increases the risk of medication non-compliance significantly among schizophrenia patients. In addition to case management, an integrated treatment model to address both substance use disorders and psychosis will translate into better long-term outcomes in schizophrenia patients. © 2020 Elsevier B.V. All rights reserved.
1. Introduction Schizophrenia is a devastating chronic psychiatric disorder with a global prevalence of 1% and is one of the top fifteen leading diseases of disability (Disease et al., 2017; Moreno-Kustner et al., 2018). It has a major impact on healthcare systems with a cost burden of $155.7 billion in the United States (US). This includes 24% of direct health service cost, 6% of direct non–health service cost, and 76% of indirect health service cost (Cloutier et al., 2016).
⁎ Corresponding author at: Department of Psychiatry, Griffin Memorial Hospital, 900 E Main St, Norman, OK 73071, USA. E-mail address: [email protected] (R.S. Patel).
Medication non-compliance is highly prevalent in schizophrenia, as per a recent study, about 71% of 1.2 million patients with schizophrenia are non-compliant with medication (Desai and Nayak, 2019). Medication non-compliance has a significant adverse impact on the course of illness and is associated with negative clinical outcomes including relapse, frequent re-hospitalization, longer time to remission, and suicide attempts (Corroon and Kight, 2018). Furthermore, medication noncompliance has also been associated with a higher utilization of emergency services, legal issues, violence, victimizations, poorer life satisfaction, and substance use (Ascher-Svanum et al., 2006). Higher utilization of healthcare resources is seen in schizophrenia patients with noncompliance including more frequent outpatient visits (by two times) and office visits (by 18 times), but has lower utilization of inpatient and emergency room visits compared to medication compliant patients
https://doi.org/10.1016/j.schres.2020.11.002 0920-9964/© 2020 Elsevier B.V. All rights reserved.
Please cite this article as: R.S. Patel, V. Sreeram, R. Vadukapuram, et al., Do cannabis use disorders increase medication non-compliance in schizophrenia?: United States Nation..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2020.11.002
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other psychotic disorders (295.00–298.9, 299.10 or 299.11), and were further sub-grouped based on medication non-compliance (ICD-9 code: V15.81). CUDs were recognized using the ICD-9 codes: 304.30 (cannabis dependence, unspecified), 304.31 (cannabis dependence, continuous), 304.32 (cannabis dependence, episodic), 305.20 (non-dependent cannabis abuse, unspecified), 305.21 (non-dependent cannabis abuse, continuous), and 305.22 (nondependent cannabis abuse, episodic). Demographic characteristics included are age (18–35, 36–50, 51–65 years), gender (male or female), race (Caucasian, African American, Hispanic, and others), median household income in percentiles and primary payer status (Medicare, Medicaid, private, self-pay/ uninsured) (2019a). Comorbid EPS, personality disorders, and SUD (alcohol, tobacco, cocaine, amphetamine, and opioid) were identified using ICD-9 diagnosis codes as mentioned in Appendix (2019a).
(Desai and Nayak, 2019). In contrast, in a three-year prospective study, significantly higher rates of psychiatric hospitalizations and use of emergency psychiatric services were among medication noncompliant as compared to compliant individuals (Haddad et al., 2014). Some risk factors have been associated with medication noncompliance in patients with schizophrenia including substance abuse, illness severity, lack of insight, sociodemographic factors (age, family and marital status, ethnicity and level of education), prior history of noncompliance, comorbid personality disorders/psychopathy, treatmentrelated factors (adverse effects, complex treatment regimen), and environmental factors (physician-patient relationship, financial status) (Higashi et al., 2013; Volavka and Citrome, 2011). African Americans and young adults are more prone to medication non-compliance compared to Caucasians and older adults. Individuals with a lower level of education have a four times higher likelihood of medication noncompliance (Hudson et al., 2004; Valenstein et al., 2004). Medication side effects, like extrapyramidal symptoms (EPS), are one of the main reasons why patients with schizophrenia stopped taking their medications (Dibonaventura et al., 2012). Substance use disorders (SUDs) are a major concern among patients with schizophrenia, which also increase the risk of medication noncompliance. The most common substances abused by patients with schizophrenia are nicotine (60% to 90%) and alcohol (21% to 86%), followed by cannabis (17% to 80.3%) (Kerner, 2015; Volkow, 2009). Furthermore, about half of the patients with schizophrenia have either alcohol or cocaine dependency and between 70% to 90% are nicotinedependent (Brady and Sinha, 2005; Ziedonis et al., 1994). Over the 15year follow-up study, cannabis abuse (significant use on more than 50 occasions) was associated with a six times greater risk of developing schizophrenia (Andreasson et al., 1987). The rate of non-compliance with treatment among patients with schizophrenia is much higher among nicotine and alcohol users (Pristach and Smith, 1990; Uzun et al., 2003). A recent meta-analysis of observational studies (N = 3678) found a higher risk of medication non-compliance in cannabis users in contrast to non-users (Foglia et al., 2017). With the recent change in legal policies, cannabis use disorders (CUDs) have drastically increased. It is unknown at present how this will influence patients with schizophrenia and if comorbid CUDs have any impact on medication compliance (Cerda et al., 2019). There is limited data to determine whether CUD comorbidity is the risk factor associated with medication non-compliance among patients with schizophrenia and comorbid CUDs. In this study, we aim to find the prevalence of medication non-compliance among schizophrenia inpatients and compare the relative risks of medication non-compliance with CUD versus without CUD (non-CUD). Next, we also examine the association between CUD comorbidity among hospitalized patients with schizophrenia and medication non-compliance. Finally, we examine the characteristics of schizophrenia inpatients with CUD and medication non-compliance.
2.3. Statistical analysis The prevalence of medication non-compliance, and CUD and nonCUD cohorts were identified among schizophrenia inpatients by searching the secondary diagnosis fields for CUDs and relative risk was calculated using the binomial logistic regression analysis. We used bivariate analysis to compare demographics, EPS, personality disorders, and comorbid SUDs including CUDs in patients with schizophrenia by medication non-compliance. Multivariable logistic regression analyses, adjusted for demographics, SUDs, personality disorders, and EPS were used to evaluate the adjusted odds ratio (OR) between CUDs and medication non-compliance in schizophrenia inpatients. Another bivariate analysis was conducted in only schizophrenia inpatients with medication non-compliance, sub-grouped by CUDs and Pearson's chi-square test was used. All data analyses were conducted using SPSS version 26 (IBM Corporation, Armonk, NY) with statistical significance set a priori at P < .01 for all analyses. 2.4. Ethical approval Individual patient identifiers are used to protect patient health information (2019a). The use of administrative databases, under the HCUP and publicly available de-identified NIS database, does not require institutional review board approval (2019b). 3. Results 3.1. Prevalence of medication non-compliance Medication non-compliance (N = 265,605) and compliance (N = 765,344) cohorts were identified (age 18–65). The prevalence of medication non-compliance was 25.76% among schizophrenia inpatients.
2. Material and methods 3.2. Risk factors for medication non-compliance 2.1. Data source Both non-compliance and compliance cohorts were compared to identify risk factors for medication non-compliance. Medication noncompliance was more prevalent in young adults (18–35 years) and was two times higher (95% CI 1.915–2.164) odds for non-compliance compared to older adults (51–65 years). Gender was not associated with non-compliance (p = .189). Prevalence of medication noncompliance was higher in African Americans (43.5%) and was at 2.6 times higher risk (95% CI 2.433–2.733) compared to 38.9% Caucasians. Though non-compliance was only seen in 7.3% other races, they were at 1.5 times higher risk (95% CI 1.345–1.621). Patients from lowincome families, below the 25th percentile, had higher odds (adjusted OR 1.11, 95% CI 1.033–1.187) than those from high-income families. Patients covered by Medicaid had 1.4 times higher odds (95% CI 1.308–1.462) than those covered by Medicare.
We conducted a retrospective cross-sectional analysis of the nationwide inpatient sample (NIS) i.e. the largest database in the US for epidemiological estimates involving inpatient care (2019b). The healthcare cost and utilization project (HCUP) NIS acquires administrative data on inpatient discharges from about 4400 non-federal hospitals coming from 44 states in the US, excluding rehabilitation and long-term care hospitals (2019b). Diagnostic information in the NIS is included using the international classification of diseases, ninth edition (ICD-9) codes (2019b). 2.2. Inclusion criteria and variables We included 1,030,949 inpatients (age 18 to 65 years) from the NIS (2010 to 2014) with primary ICD-9 diagnoses of schizophrenia and 2
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CUD cohort in all age groups with a 1.5 times higher risk seen in the age 18–35 years and 36–50 years as shown in Table 2.
EPS was prevalent in all patients in the medication non-compliance cohort as compared to only 1.2% in the medication compliance cohort. There was statistically no significant association between EPS (P = .607) and personality disorders (P = .743) with medication noncompliance in schizophrenia inpatients. Tobacco use disorders were most prevalent (34.7%) in the non-compliance group with 1.32 times higher odds (95% CI 1.257–1.393) followed by alcohol use disorders (18.4%, adjusted OR 1.35, 95% CI 1.254–1.444) compared to without tobacco and alcohol use disorders. There existed no significant association between medication non-compliance with opioid, cocaine, or amphetamine use disorders. Multivariable analysis revealed that CUD comorbidity was a significant risk factor for medication non-compliance among schizophrenia inpatients when unadjusted (OR 1.49, 95% CI 1.469–1.503), and adjusted for demographics and SUD (adjusted OR 1.31, 95% CI 1.291–1.327), and even after adjusting for demographics, SUD, personality disorders, and EPS (adjusted OR 1.38, 95% CI 1.268–1.489) as shown in Table 1. The relative risk of medication non-compliance in schizophrenia inpatients was significantly greater in CUD cohort compared to the non-
3.3. Medication non-compliance by comorbid cannabis use disorders Schizophrenia inpatients with medication non-compliance were further divided into CUD (N = 37,945) and non-CUD (N = 619,127) cohorts. CUD was seen in young adults (18–35 years, 62.4%), males (80.5%) and African Americans (54.1%) with about half of them from low-income families below the 25th percentile (48.6%). Personality disorders were seen in a significantly higher proportion of the CUD cohort (10.5% vs. 7.4%, P < .001). The prevalence rates of other SUDs were significantly higher in the CUD cohort (P < .001) with the highest seen in tobacco use disorders (46.3% vs. 31.9%) as shown in Table 3. 4. Discussion Among schizophrenia inpatients, approximately 26% presented with medication non-compliance. Furthermore, among the non-compliant group, about 20% had CUD comorbidity. Our study found that schizophrenia inpatients with medication non-compliance and CUD comorbidity were young adults (18–35 years) African American males from low-income families with comorbid personality disorders and higher use of other SUDs. Comorbid CUD had a 49% higher risk for medication non-compliance. Even after adjusting for potential confounders, cannabis use remained a significant independent predictor with an increased risk for medication non-compliance by 38%. Young schizophrenia patients (18–35 years) had about two times higher chance for medication non-compliance. This is comparative to other nationwide study, in which three-fifths of patients were young adults (Vadukapuram et al., 2020). Gender was not a significant predictor for medication non-compliance in this study which is supported by a study by Acosta et al. (2009). In terms of race-wise predictors, African Americans had 2.6 times higher odds for medication non-compliance compared to Caucasians. There are several reasons for non-compliance among different ethnicities including the possibilities of more healthcare providers being white leading to misleading interpretation and treatment, less access to healthcare in other ethnic groups, or usage of alternative therapies, other cultural issues or concerns about the addictive quality of psychotropic medications (Opolka et al., 2003). A substantial portion of schizophrenia inpatients with CUD comorbidity were young (18–35 years) African American male from lowincome families. These findings are consistent with past literature (Hunt et al., 2018; Secades-Villa et al., 2015; Wilson et al., 2019). By age-wise distribution, the odds for medication non-compliance in schizophrenia inpatients were higher in CUD by 1.5 times in adults from 18 to 50 years. In a prospective study, male gender was a significant risk factor for CUD and this association was considered a greater hazard for males to be non-compliant with psychotropic medications (Miller et al., 2009). African American, and those from lower socioeconomic status tend to have lower support systems and a poor therapeutic alliance that makes them vulnerable to cannabis use early in the treatment for psychiatric illness (Miller et al., 2009). Tobacco use disorders were most prevalent (34.7%) in schizophrenia patients with medication non-compliance followed by alcohol use disorders (18.4%). Tobacco use disorders have been considered, by far the
Table 1 Risk factors for medication non-compliance in schizophrenia inpatients. Variables
Compliant Non-compliant OR
95% CI
P-value
–
–
Total inpatients
765,344
265,605
–
Age at admission, % 18–35 years 36–50 years 51–65 years
38.3 32.1 29.6
38.6 32.5 28.8
2.04 1.915–2.165 1.56 1.479–1.648 Reference
<0.001 <0.001
Sex, % Male Female
60.6 39.4
63.3 36.7
0.97 0.923–1.016 Reference
<0.186
Race, % Caucasian African American Hispanic Others
49.7 31.4 12.4 6.4
38.9 43.5 10.3 7.3
Reference 2.58 2.432–2.732 1.52 1.397–1.650 1.48 1.344–1.620
<0.001 <0.001 <0.001
44.2 23.3
1.11 1.034–1.187 0.92 0.858–0.990
0.004 0.025
18.7
1.08 1.004–1.171
0.039
13.8
Reference
37.7 41.3 10.7 10.3
Reference 1.38 1.308–1.462 0.97 0.904–1.045 1.14 1.052–1.243
Side effects from medication, % None – Extrapyramidal 1.2
– 100
Reference 5.97 <0.001–7.795 0.607
Personality disorders No 91.7 Yes 8.3
92.0 8.0
Reference 0.99 0.905–1.074
0.743
Substance use disorder, % None – Alcohol 14.5 Tobacco 28.6 Cannabis 14.1 Opioid 3.5 Amphetamine 4.2 Cocaine 6.8
– 18.4 34.7 19.6 3.7 4.0 10.0
Reference 1.35 1.254–1.444 1.32 1.257–1.393 1.38 1.268–1.489 1.15 1.003–1.327 1.14 0.993–1.314 1.11 1.003–1.238
<0.001 <0.001 <0.001 0.045 0.063 0.044
Median household income, % 0 – 25th percentile 42.0 26th – 50th 25.4 percentile 51st – 75th 19.3 percentile 76th – 100th 13.2 percentile Primary payer, % Medicare Medicaid Private Self-pay or uninsured
36.2 36.9 14.3 12.6
<0.001 0.440 0.002
Table 2 The effect of medication non-compliance on relative risk of schizophrenia hospitalization by age in CUD.
The proportion of non-compliant and compliant patients were obtained using cross tabulation. Odds ratio generated by multinomial logistic regression at 95% confidence interval and significant P values ≤.001. OR: odds ratio; CI: confidence interval.
Age groups
Compliant
Non-compliant
RR
95% CI
P value
18–35 years 36–50 years 51–65 years
68,155 26,425 226,605
32,425 13,445 76,605
1.53 1.53 1.41
1.503–1.551 1.493–1.561 1.366–1.455
<0.001 <0.001 <0.001
Relative risk generated by binomial logistic regression and Significant P values ≤ .001 at 95% confidence interval. RR: relative risk; CI: confidence interval. 3
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between cannabis use and medication non-compliance. Miller and colleagues reported that cannabis use not only affected medication compliance but was also associated with treatment discontinuation. Additionally, cannabis use is associated with a decline in insight, poor judgment, decreased motivation, and exacerbation of psychotic symptoms (Miller et al., 2009). Furthermore, medication non-compliance in current cannabis users increased by 5.8 times compared to non-users and increased by 5.5 times when compared to former cannabis users. A higher number of medication non-compliance in our study, most likely related to sampling coming from more severe cases, which required inpatient hospitalization, while a meta-analysis has included studies from different clinical settings including inpatient and outpatient (Foglia et al., 2017). Also, in our study CUD comorbidity increased odds of medication non-compliance in schizophrenia inpatients by 1.37 times after adjusting for other potential confounders including demographics, EPS, comorbid personality disorders, and other SUD. Several limitations can be taken into account. Firstly, medication noncompliance in study inpatients was only based on ICD-9 codes, which may lead to under-reporting, as many clinicians do not bill the patients by using diagnostic codes for non-compliance, EPS, comorbid personality disorders, or CUD at the time of patient discharge. Secondly, due to Berkson's bias, comorbidities and SUDs in study inpatients tend to be higher than in a community-based general population. It is also possible that schizophrenia inpatients may have more severe and higher rates of certain psychotic symptoms, which required inpatient hospitalization, may have higher rates of CUDs. Given the administrative nature of the NIS database, details regarding symptoms profiles and severity of schizophrenia are not available. Additionally, this is a cross-sectional retrospective study, which lacks data on the causal relationship between cannabis use and medication non-compliance. However, the biggest strength of our study lies in the national representation and uniform collection of inpatient data from 4400 hospitals in the US with higher external validity of the results. This is the first large-sample study to our knowledge including more than one million schizophrenia patients to report the impact of CUDs on medication non-compliance in schizophrenia inpatients after controlling for demographics, SUD, EPS, and comorbid personality disorder. Medication non-compliance is a major concern among patients with schizophrenia and leads to various negative outcomes including relapse and frequent re-hospitalization. As cannabis legalization becomes widespread in the US, it is imperative to continue to monitor cannabis use and medication compliance among patients with schizophrenia and to address CUD comorbidity in addition to the treatment of psychosis.
Table 3 Characteristics of schizophrenia inpatients with medication non-compliance by cannabis use disorder. Variablesa
Non- CUD
CUD
P-value
Total patients
213,630
51,975
–
Age at admission, % 18–35 years 36–50 years 51–65 years
32.8 34.2 33.0
62.4 25.9 11.7
<0.001
Sex, % Male Female
59.1 40.9
80.5 19.5
<0.001
41.2 41.0 10.3 7.6
29.8 54.1 10.1 6.1
<0.001
43.1 23.6 19.2 14.0
48.6 22.2 16.6 12.7
< 0.001
40.1 39.6 10.6 9.6 7.4
28.0 48.1 11.2 12.7 10.5
<0.001
Comorbid substance use disorder, % Alcohol abuse 15.0 Tobacco abuse 31.9 Opioid abuse 3.3 Amphetamine abuse 2.8 Cocaine abuse 7.1
32.3 46.3 5.2 8.6 22.0
<0.001 <0.001 <0.001 <0.001 <0.001
Race, % Caucasian African American Hispanic Others Median household income, %, 0 – 25th percentile 26th – 50th percentile 51st – 75th percentile 76th – 100th percentile Primary payer, % Medicare Medicaid Private Self-pay or uninsured Personality disorders
<0.001
The proportion of non-cannabis and cannabis cohorts were obtained using cross tabulation and the Pearson Chi-Square (χ2) test. Significant P values ≤ .001 at 95% confidence interval. CUD: cannabis use disorder. a No statistics are computed because extrapyramidal variable is constant.
most prevalent substance used and thereby affecting medication noncompliance rate in patients with schizophrenia (Fergusson et al., 2006; Vadukapuram et al., 2020). As per our study, other SUDs with opioid, cocaine, and amphetamine were not significantly associated with medication non-compliance in schizophrenia patients. The higher prevalence of other SUDs among cannabis users is not surprising given the findings in the general population where cannabis is considered as a gateway drug for other substance use (Fergusson et al., 2006; SecadesVilla et al., 2015). Among schizophrenia patients with medication non-compliance, potential side effects and poor understanding about the antipsychotics are potential contributors (Spagnoli et al., 1989). EPS is considered a foremost determinant, followed by weight gain and sexual side effects leading to discontinuing antipsychotics medications (Fleischhacker et al., 1994). In our study EPS was seen in all schizophrenia inpatients with medication non-compliance. Comorbid personality disorders also have negative outcomes among patients with schizophrenia including medication non-compliance (Moran and Hodgins, 2004; Volavka and Citrome, 2011). Yet, CUD comorbity was a significant risk factor for medication non-compliance even after controlling for EPS and comorbid personality disorders. Limited studies are available focusing on whether the long-term use of cannabis has a direct correlation to medication non-compliance among the schizophrenic population (Degenhardt and Hall, 2006; Rozin et al., 2019). In a meta-analysis, about 42% of schizophrenia patients had comorbid SUDs and 26% had CUDs (Hunt et al., 2018). The prevalence of cannabis use among the medication-compliance cohort was 14%, while it was 20% among the medication non-compliance cohort in our study. Some prospective studies have reported a correlation
5. Conclusion Schizophrenia is a chronic psychiatric disorder and needs lifelong treatment. Medication compliance is a challenge among patients with schizophrenia, which has a significant adverse impact on the course of illness. CUD comorbidity increases the risk of medication noncompliance significantly among patients with schizophrenia. Young African American males with schizophrenia from low-income families with comorbid personality disorders and use of other SUDs who are also using cannabis or have CUDs are at the highest risk for the medication non-compliance. In addition to case management, an integrated treatment model addressing both SUDs and psychosis will translate into better long-term outcomes for patients with schizophrenia. Role of the funding source This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Declaration of competing interest RS Patel, V Sreeram, R Vadukapuram and R Baweja report no conflicts of interest. 4
R.S. Patel, V. Sreeram, R. Vadukapuram et al.
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Acknowledgements None.
Appendix A. Appendix
Diagnosis
ICD-9 diagnosis code
Extrapyramidal side effects Personality disorders Alcohol use disorder
333.85, 333.82, 333.99, 781.0, 333.71, 307.3, 307.20, 351.8, 333.81 301.0, 301.10–301.13, 301.20–301.22, 301.3, 301.4, 301.50, 301.51, 301.59, 301.6, 301.7, 301.81–301.84, 301.89, 301.9 291.0–291.3, 291.5, 291.8, 291.81, 281.82, 291.89, 291.9, 303.00–303.93, 305.00–305.03 305.1
Tobacco use disorder Cocaine use 304.20–304.22, 305.60–305.62 disorders Amphetamine use 304.40–304.42, 305.70–305.72 disorders Opioid use disorders 304.00–304.02, 305.51–305.52, 304.70–304.72 ICD-9: international classification of diseases, ninth edition.
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