Original Research

Changes in Patterns of Utilization and Cost of Health Care Services Associated With Initiation of Asenapine for the Treatment of Schizophrenia in Adults

Abhishek Chitnis, MPharm, PhD
Evidera, Lexington, MA
Shawn X. Sun, PhD
Forest Research Institute, Jersey City, NJ, an affiliate of Actavis, Inc.
Shailja Dixit, MD, MPH
Forest Research Institute
Rosa Wang, MHA
Alie Tawah, BA
Luke Boulanger, MA, MBA


Purpose: To examine changes in patterns of utilization and cost of health care services associated with initiation of asenapine for the treatment of schizophrenia in adults.

Design: Retrospective cohort study using 2 large US health care claims databases.

Methodology: All adults who initiated therapy with asenapine between Aug. 1, 2009, and Dec. 31, 2012, were identified; the date of the earliest claim for asenapine during this period was deemed the index date. Patients without ≥1 claims with a schizophrenia diagnosis within 12 months prior to the index date were excluded. We compared patterns of utilization and cost of health care services between 6-month periods immediately before and after index date (“preindex” and “postindex,” respectively).

Results: 366 patients were identified who initiated asenapine and who met all other selection criteria; mean (SD) age was 40.5 (16.3) years and 57.1% were women. Relative to preindex, patients were less likely during postindex to be hospitalized (41.8% vs 26.2%, P<.001) or to visit the emergency room (24.9% vs 18.9%, P=.03). Mean (SD) total health care costs decreased by $4776 in the postindex period ($16,811 [$26,176] vs $12,035 [$17,037] during preindex), primarily due to a decrease in inpatient costs ($10,616 [$24,977] vs $5286 [$15,846]); mean pharmacy costs increased by $828 ($3656 [$3309] vs $4482 [$3,073]) (all P<.001).

Conclusion: Use of asenapine for the treatment of schizophrenia was associated with reduced levels of health care utilization and cost during the 6-month period immediately following therapy initiation, primarily due to reduced levels of inpatient care.


Schizophrenia is a chronic psychiatric disorder associated with a multitude of debilitating symptoms that limit patients’ ability to live independently, gain employment and/or remain employed, and develop and maintain interpersonal relationships. Between 40 and 60% of patients with schizophrenia suffer lifelong impairments (Crown 2001). Comorbidities are common, including other psychiatric conditions (eg, anxiety, depression, obsessive-compulsory disorder, substance abuse), as well as medical conditions (eg, chronic obstructive pulmonary disease, diabetes) (Boyd 1986, Green 2003). Schizophrenia affects an estimated 2.2 million adults (1.1%) in the United States.

Antipsychotic drugs are the cornerstone of treatment for schizophrenia. While effective in reducing symptoms of schizophrenia, older agents, deemed “first-generation” or “conventional antipsychotics,” are associated with high rates of extrapyramidal symptoms (ie, acute dystonia [sustained abnormal postures and muscle spasms], akathisia [restlessness and pacing], Parkinsonism [tremor, skeletal muscle rigidity, and/or bradykinesia], tardive dyskinesia [involuntary, repetitive facial movements]) (Divac 2014). Newer agents, deemed “second-generation” or “atypical” antipsychotics (AAPs), have similar efficacy to first-generation agents, but substantially lower rates of these side effects (National Institute of Mental Health 2007). Atypical agents are more likely than conventional agents to reduce negative symptoms (eg, lack of emotion, interest, and/or expression), though negative symptoms remain a significant challenge even with the newer atypical agents (Leucht 1999). In addition to pivotal randomized controlled trials, there also is evidence of the effectiveness of these medications for schizophrenia in real-world settings (Lieberman 2005, Mojtabai 2003, Rovner 2005). Consequently, atypical antipsychotics have become the cornerstone of pharmacotherapy for the treatment of schizophrenia.

Little is known about the association of the recently approved AAPs with respect to health care resource utilization (HRU) and economic cost burden. Asenapine is one of the recently approved AAPs; it was approved in 2009 to treat schizophrenia in adults. The efficacy and safety profile of this AAP has been confirmed by a number of clinical studies (Citrome 2009, Kane 2010, Schoemaker 2012). However, there is a lack of evidence about HRU and cost outcomes associated with use of asenapine in schizophrenia patients. The objective of this study was to assess the impact of asenapine use on HRU and cost among schizophrenia patients before and after the initiation of asenapine.


Data source

All data were extracted from the Truven MarketScan Commercial Claims and Encounters Database and the Truven Medicare Supplemental Coordination of Benefits Database. The former database contains administrative claims and eligibility records for approximately 30 million commercially insured individuals (ie, working age adults and their dependents) across the US; the latter database contains comparable information for about 3 million Medicare enrollees who purchase supplemental commercial insurance.

Both databases contain information on age, gender, geographical region of residence, health insurance payer type, monthly enrollment status, and an annual indicator of whether the patient’s health plan contained a mental health carve-out. Both databases also contain inpatient and outpatient medical claims with diagnoses (in International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] format) and procedures (in ICD-9-CM, Current Procedural Terminology 4th edition [CPT-4], and Healthcare Common Procedure Coding System [HCPCS] format), date and duration of service (eg, length of stay [LOS] for hospital admissions), provider type and place of service, and total reimbursed amount (ie, plan payment plus patient liability [eg, copayment, deductible]). Pharmacy claims include medication dispensed (in National Drug Codes [NDC] format), therapeutic class, dispense date, quantity and days supplied, and total reimbursed amount.

Rigorous validation methods are utilized to ensure that claims and enrollment data are complete, accurate, and reliable. Patient identifiers in both databases have been encrypted, and each database is fully de-identified and compliant with the Health Insurance Portability and Accountability Act of 1996 (HIPAA). Both databases spanned the period Jan. 1, 2009, to Dec. 31, 2012.

Sample selection

The study population included adults (aged ≥18 years) with schizophrenia who initiated treatment with asenapine. All patients with ≥1 prescriptions for asenapine between Aug. 1, 2009, and Dec. 31, 2012, were identified. The date of the earliest claim for asenapine during this period was deemed the index date, and all patients were required to be continuously enrolled in the database for the 6-month periods immediately before and after this date (“preindex” and “postindex,” respectively). Patients without ≥1 inpatient or outpatient medical claims with a diagnosis of schizophrenia (ICD-9-CM 295.xx) during the 12-month period prior to index date were excluded, as were those with evidence of use of asenapine during the preindex period, those with evidence of use of a depot formulation of asenapine during pre- or postindex, and those with evidence of a mental health insurance carve-out during pre- or postindex.

Study Measures
Demographics and clinical characteristics

Demographic characteristics like age, gender, insurance type, and region were identified as of the index date. We examined the prevalence of selected comorbidities, including both medical conditions (eg, diabetes) and psychiatric disorders (eg, depression, anxiety), based on diagnoses listed on all medical claims during the 6-month preindex period; we also estimated the Charlson Comorbidity Index (CCI) (D’Hoore 1996, Schneeweiss 2000) for each patient based on information noted during the preindex period.

Health resource utilization and costs

Levels of health care utilization and cost were examined during the 6-month pre- and postindex periods, respectively. Measures included the proportions of patients with, and corresponding numbers of, the following: (1) hospitalizations, (2) hospital outpatient visits, (3) physician office visits (including psychiatrist visits), and (4) emergency department (ED) visits. Length of stay in hospital also was assessed. We assessed utilization and cost of health care services alternatively on an “all-cause” and “schizophrenia-related” basis. The latter was defined by the presence of schizophrenia diagnosis code (primary or secondary) on the claim. In all instances, measures were calculated using all patients in the study sample as the denominator. For example, in a hypothetical cohort of 10 patients, one of whom had one ED visit and the remaining nine had none, the mean number of ED visits would be 0.1 (ie, 1/10). Costs were adjusted to 2012 dollars using the annual medical care component of the US Consumer Price Index (CPI) to reflect inflation between 2009 and 2012.

Statistical Analysis

Means (standard deviations [SDs]) were reported for continuous variables; numbers (percentages [%]) were reported for categorical variables. The statistical significance of differences in levels of healthcare utilization and cost between the pre- and postindex periods were assessed using paired t tests for continuous variables and McNemar tests for categorical variables. For each assessment, differences associated with a P value <.05 were considered statistically significant. All analyses were performed using SAS software version 9.2 (SAS Institute, Cary, N.C.).


Sample selection

We identified 9876 adults who received asenapine between Aug. 1, 2009, and Dec. 31, 2012, of whom 1240 had ≥1 inpatient or outpatient claim for schizophrenia and were aged ≥18 years as of index date. 447 patients were found to have continuous enrollment for medical and pharmacy enrollment in the pre- and postindex period. After applying the exclusion criteria, 366 adult patients (3.7% of all asenapine users during this period) were deemed to have initiated asenapine for the treatment of schizophrenia.

Baseline demographic and clinical characteristics

Baseline characteristics of asenapine patients are presented in Table 1. Mean (SD) age was 40.5 (16.3) years; 57.1% were women. One half of the patients were enrolled in preferred provider organization health plans, and about one third lived in the Midwest. There was high prevalence of psychiatric comorbidities, including bipolar disorder (46.5%), depression (41.0%), alcohol/substance abuse (19.4%), and anxiety (12.6%); 12.3% had diabetes. The mean (SD) Charlson Comorbidity Index score was 0.52 (1.09).

Table 1 Demographic and clinical characteristics of asenapine patients
Characteristics Asenapine
Number of patients 366
Age: mean years (SD) 40.5 (16.3)
Age group: n (%)
18–24 years 96 (26.2%)
25–34 years 53 (14.5%)
35–44 years 61 (16.7%)
45–54 years 74 (20.2%)
55–64 years 57 (15.6%)
65+ years 25 (6.8%)
Female 209 (57.1%)
Plan Types: n (%)
Health maintenance organization (HMO) 66 (18.0%)
Point-of-service plan (POS) 41 (11.2%)
Preferred provider organization (PPO) 183 (50.0%)
Other 74 (20.2%)
Missing/unknown 2 (0.6%)
Region: n (%)
Northeast 48 (13.1%)
Midwest 123 (33.6%)
South 117 (32.0%)
West 77 (21.0%)
Unknown 1 (0.3%)
Charlson Comorbidity Index Score: Mean (SD) 0.52 (1.09)
Comorbid conditions: n (%)
Bipolar 170 (46.5%)
Anxiety 46 (12.6%)
Depression 150 (41.0%)
Alcohol/substance abuse 71 (19.4%)
Diabetes 45 (12.3%)
SD=standard deviation.
Utilization of Health Care Services

The proportion of patients with ≥1 hospitalization decreased from 41.8% during preindex to 26.2% in the 6-month period following initiation of asenapine (P<.001); corresponding reductions were observed in the mean [SD] number of admissions (from 0.71 [1.09] to 0.40 [0.87]) and mean [SD] LOS (6.75 [13.67] days to. 3.33 [8.98] days) (both P<.001) (Table 2). The proportion of patients with ≥1 ED visits also decreased, from 24.9% during preindex to 18.9% (P=.03) during postindex, as did the corresponding mean numbers of such visits (from 0.41 [0.88] to 0.33 [0.88], P=.04). The number of patients visiting physicians’ office visits was unchanged (from 96.2% during preindex to 97.0% during postindex [P=.32]), as was the corresponding mean number of such visits (from 12.96 [10.85] to 13.31 [11.60], P=.70).

Table 2 Health resource utilization during pre- and post-initiation of asenapine
Health resource utilization Preindex Postindex P value*
Psychiatric use 78.1% 76.2% .34
Any hospital admissions 41.8% 26.2% <.001
Length of stay, mean (SD) 6.75 (13.67) 3.33 (8.98) <.001
Inpatient visits, mean (SD) 0.71 (1.09) 0.40 (0.87) <.001
Any outpatient hospital visits 60.9% 57.1% .18
Outpatient visits, mean (SD) 2.75 (4.96) 2.79 (5.81) .33
Any physician office visits 96.2% 97.0% .32
Physician office visits, mean (SD) 12.96 (10.85) 13.31 (11.60) .70
Any emergency room visits 24.9% 18.9% .03
Emergency room visits, mean (SD) 0.41 (0.88) 0.33 (0.88) .04
Psychiatric use 48.6% 45.1% .11
Any hospital admissions 28.4% 15.6% <.001
Length of stay, mean (SD) 4.15 (10.55) 2.07 (7.60) <.001
Inpatient visits, mean (SD) 0.39 (0.78) 0.22 (0.60) <.001
Any outpatient hospital visits 15.3% 15.3% 0.99
Outpatient visits, mean (SD) 0.53 (2.07) 0.80 (3.22) .22
Any physician office visits 61.2% 54.9% .006
Physician office visits, mean (SD) 3.68 (5.91) 4.17 (7.70) .86
Any emergency room visits 5.2% 1.9% .007
Emergency room visits, mean (SD) 0.06 (0.29) 0.04 (0.41) .06
SD=standard deviation.
*P values were computed using McNemar test for categorical variables and paired t test for continuous variables.

Similar trends in utilization of schizophrenia-related health care services were observed, including the proportion of patients with ≥1 schizophrenia-related hospitalizations (from 28.4% in preindex to 15.6% in postindex, P<.001), the mean (SD) number of such admissions (from 0.39 [0.78] to 0.22 [0.60], P<.001), the mean (SD) LOS for such admissions (4.15 [10.55] days to 2.07 [7.60], P<.001 days), and the proportion of patients with ≥1 schizophrenia-related ED visits (from 5.2% to 1.9%, P=.007). Patients also were slightly less likely to have schizophrenia-related physician office visits following initiation of asenapine (61.2% had ≥1 such visits during preindex vs 54.9% during postindex, P=.006).

Health Care Costs

Total mean (SD) health care costs decreased by $4776 during the 6-month period of interest (from $16,811 during preindex to $12,035 during postindex), primarily due to a decrease in the cost of inpatient care (from $10,616 to $5286, both P<.001); costs of ED visits also decreased (from $147 to $76, P=.02) (Table 3). However, pharmacy costs increased by $826 during postindex (from $3656 to $4482, P<.001).

Table 3 Costs during pre- and post-intiation of asenapine
Costs Preindex Postindex P value*
All-cause: mean (SD)
Total $16,811 (26,176) $12,035 (17,037) <.001
Outpatient services $2392 (3365) $2192 (2991) .27
Inpatient services $10,616 (24,977) $5286 (15,846) <.001
Emergency room services $147 (589) $76 (326) .02
Pharmacy costs $3,656 (3309) $4,482 (3073) <.001
Schizophrenia-related: mean (SD)
Total $8,080 (16151) $5,960 (8675) .006
Outpatient services $594 (1663) $678 (1662) .40
Inpatient services $5,412 (15682) $2,334 (7737) <.001
Emergency room services $46 (363) $10 (92) .06
Pharmacy costs $2,028 (2321) $2,939 (2316) <.001
SD=standard deviation.
*P values were computed using McNemar test for categorical variables and paired t test for continuous variables.

As found with all-cause costs, schizophrenia-related costs also decreased, from $8080 during preindex to $5960 during postindex, again primarily due to a decrease in the cost of inpatient care (from $5412 to $2334) (P=.006 and P<.001, respectively); schizophrenia-related pharmacy costs also increased (from $2028 during preindex to $2939 during postindex, P<.001).


Schizophrenia poses a substantial financial burden on the health care system as well as patient burden among sufferers (Nicholl 2010). Several studies have reported an association between schizophrenia (including its associated comorbidities) and increased levels of utilization and cost of health care resources, including hospitalizations, ED visits, and other outpatient visits (Nicholl 2010, Wu 2005). In 2002, the estimated direct costs due to schizophrenia in the US were $22.7 billion (Wu 2005).

This study found that patients with schizophrenia treated with asenapine had substantial reduction in HRU and cost burden after the initiation of asenapine. The cost reduction was mainly due to reduction in the all-cause as well as schizophrenia-related inpatient cost. The inpatient costs reduction after asenapine initiation may be due to a smaller proportion of patients admitted to hospital, shorter LOS, and lower number of hospital visits as compared with preinitiation. All-cause hospitalizations showed a substantial drop in claims for other mental health-related condition from pre- to postindex periods. Therefore, the all-cause inpatient cost reduction may be due to beneficial effects of asenapine on other mental health-related costs beyond attributing it to regression to the mean. Similarly, the decrease in ED costs may be due to a smaller proportion of patients with ED visits and a lower number of ED visits.

It is also important to note that pharmacy costs increased after initiation of asenapine, but these costs were more than offset by cost savings due to inpatient admissions. The increase in pharmacy costs may be due to improved medication management (including start of new schizophrenia-related medications and augmentation of therapy) and use of brand-name medications that cost more than generics. However, the claims database does not allow the causes behind the change in costs to be determined. Despite the increase in pharmacy costs, the decrease in aggregate costs suggests overall improvement in symptom control among patients with schizophrenia, who often interface with the health care system in emergency and other high-intensity settings. This information on the outcomes and costs of pharmacotherapy is important to health care decision-makers who focus on identifying an appropriate balance between patient benefit and cost of treatment.

To our knowledge, ours is the first study to examine the real-world impact of initiation of asenapine for the treatment of schizophrenia on levels of utilization and cost of health care services. Findings from our study are similar to previous studies that have assessed the impact of initiation of other atypical antipsychotics for the treatment of schizophrenia on levels of utilization and cost of health care services (Fuller 2009). In one such study conducted among US military veterans suffering from schizophrenia or schizoaffective disorder that also employed a “pre-post” design, significant decreases were observed in the percentage of patients with ≥1 psychiatric-related hospitalizations (from 75% vs 42%), mean number of such hospitalizations (mean [SD] change = 0.8 [2.0]), and LOS (mean [SD] change = 25 [63.6] days); following therapy initiation, the mean (SD) number of outpatient visits/month increased by 1.0 (2.8) (all values P<.001) (Fuller 2009). In another study (Peng 2011), the percentage of patients with ≥1 all-cause hospitalizations decreased from 53.9% to 22.4% in the 6-month periods immediately before and after initiation of a new antipsychotic agent, and the percentage of patients with ≥1 schizophrenia-related hospitalizations decreased from 42.9% to 20.4%; mean total health care costs decreased by $3227 (from $11,111 to $7884), primarily due to decreases in the costs of inpatient care (from $6696 to $3593) (costs of schizophrenia-related admissions decreased from $4143 to $2377) (Peng 2011).


Our study has a number of limitations. First, we controlled for potential confounding by means of a “pre-post” design in which each patient served as his or her own control. Observed changes in utilization and cost of health care services may, therefore, have been attributable to reasons other than the initiation of asenapine. For example, patients may have suffered a relapse of symptoms of schizophrenia during the preindex period that may have resulted in an ED visit and/or hospital admission and that ultimately triggered initiation of asenapine; postindex costs would therefore have been lower as a result of control of symptoms, regardless of the AAP selected (ie, our findings may reflect regression to the mean). However, we note that in other analyses we undertook that compared a subset of these patients with a propensity-matched sample of other patients with schizophrenia who initiated treatment with other branded AAPs, initiation of asenapine was associated with nominally larger reductions of all-cause HRU and costs. Findings from the current study, coupled with those from the other analyses, suggest that initiation of asenapine is associated with subsequent decreases in levels of HRU and cost above and beyond what might be expected with regression to the mean. Further study is needed to better understand the degree to which asenapine affects downstream HRU and costs.

Second, our study was a retrospective observational study using a claims database; thus, and, as with any claims database, there may be errors in recording on claims. No causal inference could be drawn due to the observational nature of the database. As noted above, lower observed costs in the postindex period may be due to unmeasured factors, such as onset of a schizophrenia-related episode that necessitated an admission—with its attendant cost—in the preindex period followed by change of therapy not specific to asenapine (ie, regression to the mean). Following patients for a longer period of time (eg, over a year) may help to better understand the association between asenapine and HRU and costs, and the degree to which the former impacts the latter. Inclusion of a comparison group similar to the work undertaken by Nguyen and colleagues also would help increase knowledge of how initiation of asenapine changes subsequent levels of HRU and cost (Nguyen 2015).

Third, asenapine is also indicated for bipolar I disorder, and the database used does not record the purpose of medication. It is possible that asenapine could have been prescribed for bipolar disease, which was prevalent in 45% of the study population. On a related matter, our sample selection criteria were relatively less stringent as compared to previous studies, which may have led to misclassification of schizophrenia patients. For example, we required patients to have at least 1 outpatient visit or 1 inpatient admission in the preindex period, whereas Offord and Peng et al required at least 2 outpatient claims or 1 inpatient visit (Offord 2013, Peng 2011). However, the trends in costs and HRU in our study were similar to previous studies.

Only direct health care costs based on plan and patient out-of-pocket payment for each service were assessed. Indirect costs, such as lost productivity and opportunity costs associated with time lost seeking treatment, and medical services, prescriptions paid completely out of pocket, and caregiver burden, were not captured, which could have the effect of underestimating the impact of asenapine on potential indirect savings. The correspondence between pharmacy submission of claims and patients’ receipt and consumption of the medication is assumed and not directly measured. However, prior work suggests that medication exposure measures can be accurately derived from pharmacy claims (Crown 2001).

The results presented are most generalizable to patients with Medicare supplemental insurance and Medicaid patients, and they may not be generalizable to other populations.


Use of asenapine for the treatment of schizophrenia in adults was associated with reduced levels of health care utilization and cost during the 6-month period immediately following therapy initiation, primarily due to reduced levels of inpatient care. Further research is needed to confirm the findings of this study and to better understand the degree to which these reductions are sustained with continued use of asenapine.


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Key points

  • Second-generation, or “atypical,” antipsychotics demonstrate comparable effectiveness as first-generation agents as a treatment for schizophrenia and have substantially lower rates of extrapyramidal symptoms (eg, acute dystonia, akathisia, tardive dyskinesia).
  • Little is known, though, about how recently approved atypical antipsychotic agents affect health care resource use and associated costs.
  • Asenapine (sold as Saphris in the United States), approved in 2009, is one of those recently approved atypical antipsychotic agents.
  • Using US claims data, the authors identified 366 patients with schizophrenia who started treatment with asenapine. The authors compared the health care utilization (eg, inpatient hospitalizations, emergency department visits) of these patients during the 6 months before and after they started asenapine.
  • Relative to the pre-period, health care costs decreased by $4776 in the post-period, mainly because of a decrease in hospitalizations. That savings offset the $828 increase in pharmacy costs.
  • Observed decreases in levels of utilization and cost of health care services may have been the result of factors other than asenapine (eg, regression to the mean following onset of a schizophrenic episode immediately before initiation of such therapy).
  • Asenapine is also approved as a treatment for bipolar I disorder, and the databases used to conduct this study do not record the reason for prescribing. Asenapine may have been prescribed for bipolar disease, not schizophrenia, in some cases.

Corresponding author
Abhishek S. Chitnis, MPharm, PhD
430 Bedford Street, Suite 300
Lexington, MA 02420
Email: abhishek.chitnis@evidera.com

A synopsis of the current research was presented in poster format at the American Psychiatric Association (APA) meeting (Toronto, May 16–20, 2015), and at the 20th Annual International Meeting of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) (May 16–20, 2015, Philadelphia).

Acknowledgments: This research was sponsored by Forest Research Institute Inc., an affiliate of Actavis Inc.

Disclosures: Abhishek Chitnis, Rosa Wang, and Alie Tawah are employees of Evidera; at the time this research was conducted, Luke Boulanger also was employed by Evidera. Evidera received consultancy fees from Forest Research Institute Inc., an affiliate of Actavis Inc. Shawn Sun and Shailja Dixit are employees of Forest Research Institute Inc., an affiliate of Actavis Inc.


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