Abstract
Background: Schizophrenia is a serious public health problem that affects ∼1% of the US population.
Aims: To examine treatment patterns and evaluate healthcare resource utilization (HRU) and costs among young adults (18–35 years) with schizophrenia who were early in the disease.
Materials and methods: Patients aged 18–64 years with ≥2 schizophrenia diagnoses in the identification period (January 1, 2012–September 30, 2015) and continuous enrollment for ≥12 months pre- and post-index date were identified from the OptumInsight Clinformatics DataMart. Demographics, clinical characteristics, HRU, costs, and treatment patterns were compared between schizophrenia and non-schizophrenia “controls” cohorts and between young (18–35 years) and older adults (36–64 years) with schizophrenia.
Results: Among 9,889 schizophrenia patients, 23.70% were young adults (aged 18–35), had higher all-cause per-patient-per-year (PPPY) costs ($22,338 vs $7,332; p < .0001), higher inpatient costs ($8,857 vs $1,289; p < .0001), and longer inpatient length-of-stay (LOS) (5.0 vs 0.4 days, p < .0001; adjusted incidence rate ratio [aIRR] = 12.8; 95% confidence interval [CI] = 11.5–14.3) than controls. Among young adults with schizophrenia, there were more mental-health-related and fewer non-mental-health-related diagnoses compared to older adults with schizophrenia; 63.40% were male. Young adults with schizophrenia incurred higher inpatient costs ($15,692 vs $10,274; p < .0001) and longer inpatient LOS (9.6 vs 5.9 days, p < .0001; aIRR = 1.6; 95% CI = 1.4–1.8) compared to older adults with schizophrenia. A substantial proportion of patients were treated with oral antipsychotics vs long-acting injectables in both cohorts (young adults: 98.72% vs 9.71%; older adults: 98.10% vs 13.31%).
Limitations: Claims data are collected for payment and not research. The presence of a prescription claim does not indicate medication was consumed or taken as prescribed.
Conclusions: The economic burden for schizophrenia patients is substantial, especially among young adults. Based on this analysis, further research is warranted to better understand the association between adherent treatment patterns earlier in the disease and long-term health outcomes among patients with schizophrenia.
Introduction
Schizophrenia is a chronic condition characterized by recurrent episodes of acute psychosis, alternating with periods of full or partial remissionCitation1. It is a serious public health problem that affects ∼1% of the US populationCitation2,Citation3. Additionally, it is a pervasive, chronic mental disorder, typically preceded by prodromal symptoms of psychosis leading to a first psychotic episode, with a global prevalence of 0.3–0.7%Citation4,Citation5. Ranked among the top 25 leading causes of disability globally in 2013, it is the most common psychotic disease in the worldCitation6. Schizophrenia is characterized by complex psychopathology, and patients experience a broad range of symptoms leading to a loss of function and autonomy. More than 50% of patients have intermittent but long-term psychiatric problems, and ∼20% have chronic symptoms and disabilityCitation4,Citation7.
Schizophrenia imposes a disproportionately large economic burden relative to other mental disorders which has been linked to early onset of the disease and its chronic nature with persisting symptomsCitation2,Citation3,Citation8. The World Health Organization estimated that direct costs of the disease in Western countries range from 1.6–2.6% of total healthcare expenditures. In the US, the economic burden of schizophrenia is more than $60 billion per yearCitation6. The chronic nature of the disease necessitates hospital admissions, prescription drugs, and indirect costs—including unemployment, productivity loss, premature mortality, and caregiver time, all of which contribute to the substantial cost burdenCitation2. Previous studies have shown that indirect costs contributed to more than half of the total costs associated with schizophreniaCitation6.
The recommended first-line treatment for patients with schizophrenia is an antipsychotic (AP) agent, which reduces the risk of relapse and enhances long-term functional outcomes. Despite the need for long-term, continuous therapy, patients often have difficulty with adherence to oral medication regimensCitation3,Citation9. Previous research suggests that adequate treatment in the initial stages of psychosis is important in terms of disease course and outcomes and states that correct management might help patients in achieving symptomatic remissionCitation10,Citation11. To reduce the burden of schizophrenia, several countries have introduced comprehensive treatment programs like cognitive behavioral psychotherapy, family education and support, vocational recovery services, and providing low dose APsCitation12. However, the US has been slow to adopt a similar treatment model, for many reasons, including lack of adequate financing. For example, health insurers may not reimburse for psychosocial and rehabilitative services recommended for individuals in the earliest stages of psychosis; moreover, many such individuals in the US may not have health insuranceCitation13. Country-level differences aside, treatment of early-phase schizophrenia, including the first 2–5 years after the first acute episode of psychosis, is critical in determining the long-term prognosisCitation1. Recent randomized controlled trials (RCTs) suggest that long-acting injectables (LAIs) may be used to maintain treatment adherence for chronic schizophrenia patients; however, research suggests, if used in early-phase schizophrenia, LAIs may help to modify the trajectory of the disorder and lead to better long-term outcomesCitation14. Further research is needed to evaluate the treatment patterns and health economic outcomes in early-phase schizophrenia patients.
This study assessed real-world treatment patterns and the health economic burden of schizophrenia among young adults with an aim of conducting: (1) 1-year analysis examining associated costs and healthcare resource utilization (HRU); and (2) 2-year analysis examining treatment patterns (i.e. proportion of days covered [PDC], number of AP treatment changes, number of patients prescribed APs). Since our study lacked clinical data, we assessed patient outcomes of early-phase schizophrenia based on a young adults age range (18–35 years) that captures 2–5 years after the typical onset of schizophrenia diagnosisCitation15.
Methods
Data source
This was a longitudinal, retrospective cohort study utilizing data from the OptumInsight Clinformatics Data Mart from January 1, 2011 through September 30, 2016 (study period). The OptumInsight Clinformatics database is a single-payer health claims database from a large national health insurer that covers ∼32 million livesCitation16. The database also includes claims for commercially-insured and Medicare advantage affiliate members with linked health risk assessment (HRA) and socio-economic status (SES) data. SES data includes information on education level, race, net worth, household income, occupation type, and housing. This dataset provides licensed access to a nexus of information to support analysis requirements including medical claims, pharmacy claims, laboratory analytic results, administrative data, and SES data. This study was exempt from Institutional Review Board approval because individual patient-identifiable data from the OptumInsight Clinformatics Data Mart was not required.
Study population
Patients were included in the study if they were aged 18–64 years. Schizophrenia cases were selected if they had ≥2 diagnoses for schizophrenia (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] code 295.xx, ICD-10-CM: F20.xx) during the identification period from January 1, 2012–September 30, 2015, and controls were selected if they had no diagnosis for schizophrenia during the entire study period of January 1, 2011–September 30, 2016. Cases and controls were also required to have continuous enrollment for at least 12 months pre- (baseline period) and post-index date (follow-up period). The initial schizophrenia diagnosis was designated as the index date. Controls were matched with patients with schizophrenia based on age, sex, race, and region. One control patient was selected for each case patient. If more than one control was available, then one patient was selected randomly. Patients who had missing or unknown values for age, sex, race, and region were excluded.
The control cohort serves to describe the incremental burden of schizophrenia vs non-schizophrenia patients from a payer’s perspective—providing additional context for the burden of the disease. By comparing those with schizophrenia to those without, we were able to observe any significant difference in clinical and economic burden between the groups.
A 1-year analysis examining HRU and costs for all schizophrenia patients was conducted during the identification period (January 1, 2012–September 30, 2015) and a 2-year analysis was conducted only among those patients who were prescribed ≥2 APs within 90 days during the identification period (January 1, 2012–September 30, 2014). The first prescription date was defined as the index date, and patients were required to have continuous health plan enrollment for at least 12 months pre- (baseline period) and 2 years post-index date (follow-up period).
Eligible patients with schizophrenia were further stratified as young adults (aged 18–35 years) vs older adults (aged 36–64 years) for 1-year and 2-year analysis. Sensitivity analysis was also conducted among schizophrenia patients after we reclassified the schizophrenia patients by narrowing the age range to 18–25 years vs 26–64 years.
Demographic and baseline clinical characteristics
Patient demographics including age, sex, region, race, and SES (including education level, federal poverty status, household income, and housing) were assessed. Additionally, clinical characteristics, including Charlson Comorbidity Index (CCI) score, other individual diagnoses (including mental-health-related diagnoses consisting of bipolar disorder, any depression disorder, attention deficit hyperactivity disorder, panic disorder, post-traumatic stress disorder, personality disorder, anxiety, suicide attempt and intentional injuries, substance abuse, alcohol, tobacco use), and non-mental-health-related diagnoses (including obesity, diabetes mellitus, metabolic syndrome, hyperlipidemia, hypertension, coronary artery disease, congestive heart failure, HIV, hepatitis C, and chronic obstructive pulmonary disease) were recognized using the ICD-9-CM codes listed in the Appendix, and total baseline healthcare costs were assessed.
Outcome measures
Outcome measures, including HRU and costs during the 12-month follow-up period, were measured. Treatment patterns were measured longitudinally at each data observation period from 1–6 months and at intervals of 6 months for the 2-year follow-up period. Each interval was denoted as first (1–6 months), second (7–12 months), third (13–18 months), and fourth (19–24 months) data observation period. Additionally, the treatment pattern was specifically assessed at month 1.
All-cause, mental-health-related, schizophrenia-related, and non-mental-health-related HRU and costs (including inpatient, outpatient, ER, and pharmacy visits) were assessed among young adults vs older adults. Moreover, treatment patterns among young adults vs older adults were measured as the proportion of patients prescribed APs, antidepressants, anxiolytics, mood stabilizers/anticonvulsants treatment, and three or more drug classes (APs, antidepressants, anxiolytics, and mood stabilizers/anticonvulsants). The number of AP treatment changes was measured as AP treatment gap, where gap was defined as the run-out date (fill date + days of supply) of the last observed APs and prescription fill of new APs. Hence, the sum of all gap days (only gaps comprised of >15 days were considered) was calculated and reported as the mean treatment gap. Furthermore, adherence to medication was also calculated based on the surrogate marker of prescription refills during the follow-up and reported as the proportion of patients who were adherent and non-adherent. Adherence was calculated using PDC, defined as total prescription-covered days (those days that the subject would have had medication according to pharmacy records) divided by total follow-up days within the observation period. Patients with ≥80% were considered as adherent and <80% were considered as non-adherentCitation17.
Statistical analysis
Descriptive statistics on all study variables, including baseline, clinical characteristics, and outcome variables, were provided for young vs older adults with schizophrenia. Statistical tests of significance (Chi-square for categorical and t-test for continuous variables) were conducted to assess differences between cohorts. The level of significance was set at α = 0.05. Treatment patterns (i.e. PDC, number of AP treatment changes, number of patients prescribed an APs) were examined descriptively.
Binary variables in HRU (including occurrence of any pharmacy use, and any medical services utilization) were analyzed using logistic regression. Similarly, count variables in HRU (including the number of pharmacy and medical service visits) were analyzed using negative binomial regression models. Odds ratio (OR), incidence rate ratio (IRR), and 95% CI were reported. To estimate the total costs, generalized linear models (GLMs) with gamma-variance and log-link function were used to compare the all-cause, mental health-related, schizophrenia-related, and non-mental-health-related healthcare costs between cohorts. Logistic regression and GLM procedure were used to adjust for age, sex, US region, CCI score, baseline individual diagnoses, and baseline total healthcare costs. All the analyses were conducted using SAS statistical software (Version 9.3, SAS Institute, Cary, NC, 2012).
Results
Based on the inclusion criteria for 1-year analysis, of the identified 9,889 schizophrenia patients, 2,344 (23.70%) were young adults (aged 18–35 years) and 7,545 (76.30%) were older adults (aged 36–64 years). Based on the inclusion criteria for 2-year analysis, of the identified 5,194 schizophrenia patients, 1,092 (21.02%) were young adults, and 4,102 (78.97%) were older adults ().
Figure 1. Study population and cohorts. Patients were 1:1 matched based on the following variables: age, sex, race, and geographic region.
Baseline characteristics
Schizophrenia vs control patients
The average age of schizophrenia patients was 46 years. A higher proportion of schizophrenia patients reported a high school diploma as their highest education level (36.82% vs 25.58%; p < .0001) compared to controls; however, a lesser proportion of schizophrenia patients obtained a bachelor’s degree and/or higher (11.54% vs 19.77%; p < .0001), and a higher proportion of schizophrenia patients earned a household income of < $40K (25.79% vs 11.35%; p < .0001) as compared to controls. Additionally, schizophrenia patients had a higher mean CCI score (1.01 vs 0.37; p < .0001), higher mental-health-related diagnoses (including any depression disorder [53.02% vs 8.19%; p < .0001] and anxiety [32.09% vs 8.05%; p < .0001]), and higher baseline annual healthcare costs ($26,911 vs $7,258; p < .0001) as compared to controls (data not shown).
Young vs older adults with schizophrenia
Of the identified young adults (aged 18–35) with schizophrenia (n = 2,344), a higher proportion was comprised of men (63.40% vs 50.11%, p < .0001). Young adults were more likely to earn a household income of $100K+ (31.31% vs 12.78%; p < .0001) and had a lower mean CCI score (0.32 vs 1.82; p < .0001). Despite a lower mean CCI score, young adults had a higher burden of mental-health-related diagnoses, including any depressive disorder (59.85% vs 50.89%; p < .0001), anxiety (39.68% vs 29.86%; p < .0001), bipolar disorder (33.87% vs 29.68%; p = .0001), ADHD (14.97% vs 2.20%; p < .0001), and personality disorder (7.89% vs 5.46%; p < .0001), as compared to older adults with schizophrenia (). However, young adults with schizophrenia had fewer non-mental-health-related diagnoses, including hypertension (11.01% vs 49.28%; p < .0001), hyperlipidemia (11.13% vs 47.42%; p < .0001), diabetes mellitus (6.14% vs 29.21%; p < .0001), COPD (4.01% vs 16.82%; p < .0001), obesity (9.60% vs 15.57%; p < .0001), and significantly lower baseline total healthcare costs ($22,578 vs $28,857; p < .0001) as compared to their counterparts (). A similar trend was observed in the sensitivity analysis among schizophrenia patients aged 18–25 years (n = 1,377) vs 26–64 years (n = 8,512).
Table 1. Baseline demographics and clinical characteristics of young vs older adults with schizophrenia.
Adjusted 1-year follow-up economic outcomes
Schizophrenia vs control patients
As compared to controls, schizophrenia patients were more likely to have higher all-cause HRU, including any inpatient (adjusted odds ratio [aOR] = 7.1, 95% CI = 6.4–8.0), outpatient office (aOR = 1.9, 95% CI = 1.6–2.1), ER (aOR = 2.3, 95% CI = 2.1–2.5), and pharmacy visits (aOR = 3.2, 95% CI = 2.9–3.6), and had higher total all-cause healthcare costs ($22,338 vs $7,332; p < .0001). Inpatient and pharmacy costs were the major drivers of total all-cause healthcare costs. A similar trend was observed for mental-health-related and non-mental-health-related HRU and costs, including inpatient, ER, and pharmacy visits and related costs (data not shown).
Young vs older adults with schizophrenia
As compared to older adults, young adults with schizophrenia were more likely to have higher all-cause HRU, including any inpatient (aOR = 2.0, 95% CI = 1.8–2.3), outpatient office (aOR = 2.7, 95% CI = 2.0–3.5) and ER (aOR = 1.5, 95% CI = 1.3–1.7) visits (), and a longer average all-cause inpatient LOS (9.6 vs 5.9 days; p < .0001; aIRR = 1.6, 95% CI = 1.4–1.8). Young adults with schizophrenia also incurred significantly higher costs related to inpatient stay ($15,692 vs $10,274, p < .0001), ER visits ($3,238 vs $2,783; p < .0001), and outpatient office visits ($5,791 vs $5,037; p = .0052). Total all-cause healthcare costs trended higher among young adults as compared to older adults with schizophrenia ($32,452 vs $27,242; p = .8664) but did not reach statistical significance (). However, the results of sensitivity analysis among schizophrenia patients aged 18–25 years vs schizophrenia patients aged 26–64 years revealed that the total all-cause healthcare costs were significantly higher among schizophrenia patients aged 18–25 years ($36,728 vs $27,163; p < .0001), including inpatient and ER costs.
Figure 2. Adjusted odds ratio (95% CI) for all-cause HRU among young vs older adults with schizophrenia.
Figure 3. One-year adjusted follow-up all-cause healthcare costs among young vs older adults with schizophrenia.
Two-year follow-up treatment patterns
Young vs older adults with schizophrenia
In the 2-year follow-up period, ∼ 97.80% and 4.67% of young adults and 96.22% and 8.56% of older adults with schizophrenia were prescribed an oral antipsychotic treatment (OAT) and LAI, respectively, at 1-month post-index date. OAT consumption decreased over time from the second data observation period of 7–12 months among both young and older adults with schizophrenia. Moreover, the utilization of LAIs was highest (6.78% and 10.26%) at the first data observation period of 1–6 months among both young and older adults with schizophrenia, respectively. Our study results revealed that most patients were prescribed APs; however, in those taking other types of medications as well, the second and third most commonly prescribed medication classes were mental-health-related, including antidepressants and mood stabilizers ().
Table 2. Two-year follow-up treatment outcomes among young vs older adults with schizophrenia.
Among older adults with schizophrenia, adherence declined drastically at the first data observation period of 1–6 months (68.70%) and continuing at the second data observation period of 7–12 months (54.64%) but, thereafter, remained constant overtime in each subsequent data observation period (). A similar trend was seen among young adults with schizophrenia, where adherence declined drastically at the second data observation period of 1–6 months (53.57%) and the third data observation period of 7–12 months (42.25%) but, thereafter, remained constant over time in each subsequent data observation period (). The mean AP treatment gap in both young and older adults with schizophrenia increased dramatically at the first data observation period of 1–6 months, followed by a more gradual increase over time, as depicted in . Additionally, the mean AP treatment gap at the fourth data observation period of 19–24 months was found to be highest among young adults (aged 18–35; 62.19 days) compared to older adults with schizophrenia (aged 36–64; 35.29 days). Based on the sensitivity analysis, the gap in treatment was found to be even higher among patients aged 18–25 (74.58 days) as compared to patients aged 26–64 (36.35 days) ().
Figure 4. Longitudinal analysis: proportion of patients prescribed APs with PDC ≥80%: young vs older adults with schizophrenia. Some patients had prescription fills with a lower number of days of supply, i.e. < 1 month, which resulted in adherence levels below 100% at month 1 after the index date. PDC, proportion of days covered.
Figure 5. Longitudinal analysis: mean antipsychotic treatment gap: young vs older adults with schizophrenia. Some patients had prescription fills with a lower number of days of supply, i.e. < 1 month, which resulted in adherence levels below 100% at month 1 after the index date.
Discussion
This retrospective claims-based study comprehensively assessed the treatment patterns and economic burden of schizophrenia among young adults and older adults. Prior research has shown that the first episode of psychosis typically occurs in adolescence or early adulthood, and that adequate treatment given during the first psychotic episode helps in reducing relapse of the diseaseCitation10. Although AP treatment has been shown to reduce relapse rates, adherence to therapy can be a major challengeCitation1.
Perhaps not surprisingly, schizophrenia patients incurred higher all-cause healthcare costs for outpatient and pharmacy visits when compared to control patients. Additionally, schizophrenia patients incurred significantly higher total all-cause healthcare costs ($22,338 vs $7,332 PPPY), mostly driven by inpatient costs, followed by outpatient and pharmacy costs, as compared to controls. The findings of our study were in accordance with the study conducted by Fitch et al.Citation18, which revealed that the costs among a commercially-insured schizophrenia population were majorly driven by inpatient ($762 PPPM) followed by outpatient ($592 PPPM) and pharmacy visits ($452 PPPM).
Similar results were found among young adults; they had a significantly higher proportion of outpatient (99.00% vs 97.35%), followed by pharmacy (96.70% vs 95.96%), ER (60.76% vs 50.94%), and inpatient visits (52.06% vs 34.96%) as compared to older adults with schizophrenia. Our study also found that, when compared to older adults, young adults with schizophrenia incurred significantly higher all-cause costs related to inpatient ($15,692 vs $10,274 PPPY) and outpatient ($7,568 vs $7,083 PPPY) visits, but statistically insignificant total all-cause healthcare costs. However, results of sensitivity analysis suggested that total healthcare cost was significantly different among patients aged 18–25 years and 26–64 years ($36,728 vs $27,163; p < .0001). This significant increase in costs among the 18–25-years cohort is particularly relevant for payers due to the Affordable Care Act (ACA) policy which allows plan members between the ages of 19–25 years to remain as dependents under their parents’ planCitation19. As a result, this policy change also increased mental health treatment by 5.3% among people of 18–25 years, which may contribute to the significant cost difference in commercially insured schizophrenia patients aged 18–25 years vs those aged 26–64 yearsCitation19. Furthermore, these findings on HRU and costs suggest that the economic burden of schizophrenia is higher among young patients (18–35 years and 18–25 years); hence, payers should consider coverage decisions that are designed to enhance the health outcomes of young adult patients diagnosed with schizophrenia. Previous studies have also concluded that, as the adherence to APs decreases, the risk of hospitalization increases, as patients will eventually relapse at some point, thereby increasing overall healthcare costs as wellCitation20,Citation21. A study comparing short-term vs long-term LAI use in the Medicaid population found that patients with long-term LAI use had significantly lower HRU, including mean number of hospitalization and LOS. Also, this same study revealed that hospital payments were lower by 26% among patients with long-term LAI useCitation22.
The AP treatment gap and low adherence rates are inversely proportional to each other. Similar to our findings of a higher average AP treatment gap (194.88 days in older adults and 223.27 days in young adults) and low adherence rates (60.43% in older adults and 37.91% in young adults), previous work by Offord et al.Citation23 showed that only 40% of schizophrenia patients were adherent to their medication. Results from another study support our findings of further reductions in adherence over time, as these investigators observed that adherence rates decreased with every 60-day increment from 63% to 46%Citation24. Substance abuse is one common reason to observe poor adherence, as well as poor treatment control, loss of function, and increased suicidality and hospitalization, thereby also leading to increased risk of psychosis and symptom exacerbationCitation25. Poor adherence is often considered the primary clinical indicator to use LAIs, yet many previous studies reported <20% use of LAIs among patients with evidence of poor adherenceCitation22. Recent US studies on LAIs revealed that only 19–30% of patients who were non-adherent were prescribed LAIs, which is comparable to our study findingsCitation20.
Medication choice is one factor that can have a significant impact on long-term treatment outcomes and costs. In this study, nearly every patient in both the cohorts was prescribed OATs; however, only 9.71% of young adults and 13.31% of older adults with schizophrenia were prescribed LAIs. Despite having higher overall inpatient and ER visits, LAI utilization and adherence to OATs was found to be lower among young patients. Consistent with our findings, Offord et al.Citation20 reported that consumption of LAIs among the commercially-insured and Medicare-insured populations was 13.1% and 22%, respectively. Moreover, when compared to treatment continuation, discontinuation of treatment increases the risk of relapse, despite being stable on APs for up to 5 years after an acute episodeCitation5. Therefore, Canadian guidelines suggest the use of LAIs in all phases of the disease, including the first 2–5 yearsCitation1. Based on the study by Correll et al.Citation22, the most effective treatment in psychiatry for schizophrenia is LAIs. Study results indicated that LAIs help to maintain treatment adherence among chronic schizophrenia patients; however, they are under-utilized in clinical practice.
High rates of hospitalization and less use of LAIs in both cohorts analyzed here suggest that it would be of great interest in the future to examine LAI usage and its association with number of hospitalizations and to examine the predictors of LAI use in young and older adult patients. Specific investigations with young patients may further reveal how early long-term therapeutic interventions, such as LAIs, can affect HRU and associated costs over time. Comparisons of LAI use and OAT use have been discussed without consideration for antipsychotic polypharmacy, which is also very common in real-world settings, with prevalence rates ranging from 4–70%. This study did not specifically examine this practice; therefore, it may also be of great interest to explore polypharmacy among young and older schizophrenia patientsCitation26.
While claims data are extremely valuable for the efficient and effective examination of healthcare outcomes, treatment patterns, and HRU and costs, claims data are collected for the purpose of payment and not research. Therefore, certain limitations are associated with claims data use. The presence of a claim for a filled prescription does not indicate that the medication was consumed or that it was taken as prescribed. Hence, the calculated adherence in the study may not represent the true adherence. Additionally, medications filled over-the-counter or provided as samples by the physician will not be observed in the claims data. The presence of a diagnosis code on a medical claim does not necessarily indicate a positive presence of disease, as the diagnosis code may be incorrectly coded or included as rule-out criteria rather than actual disease. Since age was used as a proxy to assess patients 2–5 years after the typical onset of schizophrenia diagnosis, the cohort definition does not factor patients with adolescent or late onset schizophrenia. Certain information is not readily available in claims data that could influence study outcomes, such as clinical and disease-specific parameters. Finally, other conditions, such as persistent substance induced psychotic disorder, have the potential for misdiagnosis as schizophrenia, and the specific clinical diagnostic criteria met by individual patients is not available in claims data. However, our requirement of two separate schizophrenia diagnoses for study inclusion aimed to mitigate this limitation.
Conclusions
The burden of the schizophrenia is significant. Young adults with schizophrenia incurred higher mental-health-related and schizophrenia-related HRU and costs and were less adherent to treatment compared with older adults. Despite higher HRU and costs among young adults, utilization of LAIs, which are designed to mitigate the consequences of medication gaps, was actually lower as compared to older adults. Additional research is needed to assess the impact of LAI use in acute and maintenance treatment of schizophrenia, with the intent to bridge the gap from early treatment to lifelong care. Based on this analysis, further research is warranted to better understand prescribing patterns and clinical interventions related to managing schizophrenia (especially among young adults) and optimal ways to enhance patient outcomes.
Transparency
Declaration of funding
This study was funded by Janssen Scientific Affairs, LLC.
Declaration of financial/other interests
AH and LW are employees of STATinMED Research, which is a paid consultant to Janssen Scientific Affairs, LLC. TA and KJ are paid employees of Janssen Scientific Affairs, LLC. AN is a paid employee of Janssen Global Services, LLC. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Previous presentations
Results from this study were previously presented at the US Psych Congress 2017 held in New Orleans, Louisiana, September 16–19, 2017.
Supplemental Material
Download MS Word (14.5 KB)Acknowledgments
Editorial support was provided by Michael Moriarty of STATinMED Research. The study utilized the OptumInsight Clinformatics Data Mart. Data are available through Optum.
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Appendix
Table A1. List of ICD-9-CM codes.
Table A2. HCPCS codes for substance abuse description.