The American Journal of Managed Care April 2007
Employee Costs Before and After Treatment Initiation for Bipolar Disorder
Objective: To examine pretreatment and posttreatment total medical costs and overall mental healthcare costs for patients with bipolar disorder (BPD) treated with different medication regimens (alone and in combination) vs an untreated (UnTx) cohort.
Study Design: Retrospective employer-based administrative database analysis of costs before and after the start of therapy for BPD from 2001 through 2004.
Methods: Patients were grouped into 3 cohorts based on type of therapy vs the UnTx cohort. Total medical and mental health-specific healthcare costs were compared between the 6-month preindex period and the 6-month postindex period. A mean index date of the treated cohorts was assigned to the UnTx cohort. Regression models were used to calculate cost differences.
Results: Reductions in direct medical costs among 1284 patients were largest for the cohort receiving atypical antipsychotics (ATYP) only (-$2886 [n = 55]), followed by the UnTx cohort (-$365 [n = 306]) and the cohort receiving ATYP plus other BPD medications (BOTH) (-$78 [n = 369]). In the cohort receiving other BPD medications (OTHR), costs increased by $168 (n = 554). Differences between the ATYP cohort and the OTHR cohort were significant (P = .04). For specific direct mental health-related costs, the cost changes were -$1523 for the ATYP cohort, -$441 for the OTHR cohort, -$38 for the BOTH cohort, and -$704 for the UnTx cohort. Differences between the ATYP cohort and the OTHR and BOTH cohorts were significant (P = .02 and P = .002, respectively).
Conclusions: Patients using ATYP for BPD seem to have the largest cost reductions. Additional investigation is needed to identify whether the UnTx cohort had the least severe BPD, had nonadherent prescription fill behavior, or both.
(Am J Manag Care. 2007;13:179-186)
Employees with bipolar disorder (BPD) have been found to have annual total direct and indirect medical costs approximately 3 times as high as those for employees without BPD. Employers should be aware that:
- The prevalence of BPD among 1284 employees in this study was 0.3%.
- The range of total medical costs for patients with BPD during a 6-month posttreatment period was $2385 to $4187 (or $4770-$8374 per year).
- Patients using atypical antipsychotics for BPD had the largest direct medical cost reductions during the 6-month posttreatment period.
Bipolar disorder (BPD) extracts a heavy economic burden in the United States, with a 1991 cost estimate for direct inpatient and outpatient care placed at $7.6 billion and at $38 billion for indirect costs.1 In previous investigations exploring costs in managed care settings, employees with BPD have been found to have annual total direct and indirect medical costs that were approximately 3 times as high as those for employees without BPD, and these costs were greater for every component of healthcare studied, including medical, prescription, and absence costs.2 Total medical costs have been found to be higher for mental health-related and nonmental health-related care in managed care settings,3 with the greatest proportion of mental healthcare costs being related to inpatient admissions.4
There is little research available to examine the effect of treatment initiation on costs in managed care settings and in particular on total medical costs. Most research has compared persons with BPD with those without BPD,5 some research has compared persons with BPD with persons with other diseases,6 and other research is based on trials conducted in populations treated at Veterans Affairs hospitals7 and at mental health clinics.8 In addition, there has been little research to investigate the effect of the increasing introduction of new psychotropic drug classes to treat BPD on these cost variables. The primary aim of this study was to examine the demographic differences among employees treated with different classes of psychotropic drugs. We then assessed changes before and after treatment initiation in the following: (1) total medical costs (excluding prescription costs), (2) costs in the subcategories of nonmental health-related and mental health-related medical care, and (3) total prescription costs. In addition, the study aimed to determine differences in the likelihood of mental health-related emergency department (ED) visits and inpatient admissions before and after treatment initiation among patients taking different classes of psychotropic drugs.
Data for this retrospective analysis were taken from the Human Capital Management Services Research Reference Database. The database contained health insurance claims information, including those for demographics, payroll, healthcare (with prescription drug data), disability, absence, and workers' compensation, for a population of more than 300 000 employees and their covered dependents. These data were compiled from several large national US employers and represented retail, service, manufacturing, and financial industries. Employees and spouses with a diagnosis of BPD (type I or type II) were identified from the overall database if they were noted to have a primary, secondary, or tertiary International Classification of Diseases, Ninth Edition (ICD-9-CM) diagnostic code for BPD (code 296.0x, 296.1x, 296.4x, 296.5x, 296.6x, 296.7x, or 296.8x) from 2001 through 2003.
Four cohorts of patients with BPD were identified based on their treatment patterns. The first cohort was defined as employees and spouses with BPD who received only atypical antipsychotics (ATYP). The second cohort was defined as employees and spouses with BPD who received at least 1 medication from a category labeled as OTHR (taking other BPD medications) that comprised conventional antipsychotics, primary mood stabilizers (including carbamazepine, valproic acid, divalproex sodium, and lithium carbonate), potential mood stabilizers (including additional anticonvulsants used in the treatment of BPD), zonisamide, and tiagabine hydrochloride. Individuals in the ATYP and OTHR cohorts could receive more than 1 drug from their designated drug category sequentially or simultaneously. The third treatment cohort took an atypical antipsychotic and an OTHR sequentially or simultaneously (BOTH). Assignment to the ATYP, OTHR, or BOTH cohorts was based on 1 or more dispensed prescriptions. The fourth untreated (UnTx) cohort had a BPD diagnosis but no BPD medication claims. The cohort classification is given in Table 1.
The analysis plan established index dates for each cohort based on the start of therapy. An index prescription date was defined for patients in the ATYP, OTHR, and BOTH cohorts as the date of the patient's first BPD-related prescription following his or her BPD diagnosis. Patients in these 3 cohorts were required to have health insurance enrollment for 6 months before and after the index prescription date. To reduce confounding of results, there could be no record of any BPD-related medication prescription in the 6-month period before this index date. The pretreatment period was defined as the 6-month period before the index prescription date, and the posttreatment period was defined as the 6-month period that followed. Individuals in the ATYP cohort received no prescriptions from the OTHR classification during the posttreatment period, and individuals in the OTHR cohort received no ATYP during the posttreatment period.
On average, the index prescription date was found to be 121 days after the index diagnosis date (defined as the date of the first diagnosis) for the 3 cohorts that were prescribed medications. Therefore, the index prescription dates for the UnTx cohort were defined to be 121 days after their index diagnosis dates. Patients were excluded from this cohort if they did not have health insurance enrollment for at least 6 months before and after the newly created index prescription date or if they received a BPD-related prescription during this period.
The mean values for the demographic data of the 4 cohorts were calculated and compared using t tests for continuous variables and ?2 tests for discrete variables. Results were considered significant at P < .05. Unadjusted semiannual cost differences before and after the index prescription date were calculated for all 4 cohorts. Total pretreatment medical costs (excluding prescription costs) were defined as all medical claims insurance payments related to any ICD-9-CM code during the pretreatment period, with the total posttreatment medical costs defined similarly. Prescription costs were defined as all pharmacy and mail-order prescription drug claim insurance payments during similar pretreatment and posttreatment periods. Mental health-related medical costs (again excluding prescription drug costs) were calculated from claims related to any ICD-9-CM code from the Agency for Healthcare Research Quality major diagnostic category of mental disorder,9 while medical costs related to all other ICD-9-CM codes not included in the mental disorder classification were classified as nonmental health-related medical costs. The likelihood of a mental health-related ED visit was calculated during a 6-month period by including all ED visits related to an ICD-9-CM code from the Agency for Healthcare Research Quality mental disorder major diagnostic category, with a similar method used to calculate the likelihood of a mental health-related inpatient admission.
Comparisons were made for the following: (1) total medical costs, excluding prescription costs; (2) total prescription costs; (3) mental health-related medical costs; (4) nonmental health-related medical costs; (5) the likelihood of a mental health-related ED visit; and (6) the likelihood of a mental health-related inpatient admission.
To calculate adjusted values of semiannual cost and likelihood changes, linear regression models were used to measure the effect of drug treatment class on the following dependent variables: change in medical costs, change in prescription drug costs, change in mental health-related medical costs, change in nonmental health-related medical costs, change in the likelihood of a mental health-related ED visit, and change in the likelihood of a mental health-related inpatient admission. The models were designed to control for the effects of other confounding factors (where applicable and after examining collinearity). These factors included age, sex, pretreatment BPD-specific healthcare costs, other pretreatment healthcare costs, pretreatment Charlson Comorbidity Index scores,10 region (as designated by the first digit in the subject's ZIP code), and an employee versus spouse indicator. Variables representing the interaction between the employee versus spouse indicator and marital status, race/ethnicity, full-time or part-time status, and annual salary were also included in the models. The interaction variables were included because some information was only available for employees and not for spouses. Version 9.1 of SAS System for Windows (SAS Institute, Inc, Cary, NC) was used to generate all statistical analyses.
Overall, 1542 patients (employees and spouses) were identified with BPD. The prevalence of the condition among employees was found to be 0.3%.11 The mean age of the overall patient population with BPD was 41.60 years (95% confidence interval, 41.15-42.05 years), and the mean percentage of employees (vs spouses) in the patient population with BPD was 60.8% (95% confidence interval, 58.4%-63.3%).
Table 2 gives the overall descriptive demographic characteristics of the 4 cohorts by cohort. Patients in the BOTH cohort were more likely to be female than patients in the UnTx cohort (P < .05). Table 2 reflects that certain elements, such as tenure, annual salary, marital status, race/ethnicity, exempt status, and full-time status, were only available for employees and not for spouses. The UnTx cohort had a significantly higher percentage of employees (vs spouses) than the ATYP and BOTH cohorts (P < .05). Patients in the OTHR cohort were also more likely to be employees than patients in the BOTH cohort (P < .05). In addition, the employees in the OTHR and UnTx cohorts were more likely to be married than the employees in the BOTH cohort (P < .05). In the UnTx cohort, employees also had higher annual salaries than employees in the BOTH and OTHR cohorts ($56 089 compared with $45 725 and $50 075, respectively; P < .05). On the whole, employees in the OTHR and UnTx cohorts had higher annual salaries than employees in the ATYP and BOTH cohorts. In addition, employees in the OTHR cohort were more likely to be in salaried positions (exempt) than patients in the BOTH cohort (P < .05), and employees in the UnTx cohort were more likely to work full-time than employees in the ATYP and BOTH cohorts (P < .05).