the impact of open access to atypical antipsychotics on treatment costs for medi-cal patients with...

Dis Manage Health Outcomes 2006; 14 (5): 287-301ORIGINAL RESEARCH ARTICLE 1173-8790/06/0005-0287/$39.95/0

© 2006 Adis Data Information BV. All rights reserved.

The Impact of Open Access to AtypicalAntipsychotics on Treatment Costs for Medi-CalPatients with Bipolar DisorderSangeeta Narayan,1,2 Kimberly L. Sterling1,3 and Jeffrey S. McCombs1

1 Department of Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California, LosAngeles, California, USA

2 Baxter Bioscience, Westlake Village, California, USA3 Eli Lilly and Company, Indianapolis, Indiana, USA

Background: The California Medicaid Program (Medi-Cal) provided open access to atypical antipsychotics inAbstractOctober 1997. This study investigated the impact of open access to atypical antipsychotics on the costs andduration of therapy for patients with bipolar disorders.

Methods: Paid claims data from Medi-Cal were used to identify episodes of treatment using antipsychotics,antidepressants, mood stabilizers, or selected anticonvulsants initiated by patients with bipolar disorders.Episodes of treatment were assigned to one of three time periods based on the start date: closed access (July 1994to September 1997); a transition period (October 1997 to March 1998); and open access (April 1998 to August1999). Ordinary least squares models for the cost and duration of drug therapy were estimated for episodes oftreatment started after a break in all bipolar-related drug therapy (restarts) and switching/augmentation episodes.

Results: 123 796 restart and 206 157 switching/augmentation episodes were identified. Patients with bipolardisorders cost between $US8000 and $US9000 annually (year of values 1998). Open access increased total costsby $US165–203 per year for restart episodes and $US75–125 per year for switching/augmentation episodes,primarily due to increased drug costs of $US101–103 for restart episodes (p < 0.001) and $US124 for switching/augmentation episodes (p < 0.001). Days of therapy decreased by 3.67 days for restart episodes (p < 0.001) andincreased by 2.59–2.62 days for switching/augmentation episodes (p < 0.001) from the closed access period tothe open access period.

Conclusions: Conventional antipsychotic medications are not used for long-term drug therapy for bipolardisorders, and the long-term effectiveness of atypical antipsychotics was not well established in October 1997. Itis not surprising that open access to atypical antipsychotics had only limited effects on the costs and duration oftherapy for these patients.

Bipolar disorder, or manic-depressive illness, is a cyclic disor- and depression. Mania sometimes presents with psychotic featuresder. Bipolar mania affects approximately 1% of the general popu- and is related to destructive behavior, insomnia, and sexual pro-lation,[1-4] while the 12-month incidence of the full spectrum of miscuity.[7,8] The period of time during which a patient maybipolar disorders is estimated at 2.8%.[5] The initial onset of experience bipolar depression has been reported to be approxi-symptoms occurs before the age of 20 years in 60% of patients.[6] mately 20–30% of the duration of the disease and is closelyThe course of bipolar disorder is episodic in nature but highly associated with significant disability and mortality.[7,8] Judd etvariable in the clinical severity of the associated periods of mania al.[9] found a 3 : 1 ratio of time spent in depression relative to the

288 Narayan et al.

time spent in mania. Moreover, mania accounted for symptoms than conventional antipsychotics.[17] Atypical antipsychotics in-only 10% of the time. Clinicians suspect that as many as 15–20% clude olanzapine, risperidone, quetiapine, clozapine and, moreof untreated patients with depression or bipolar disorder attempt recently, ziprasidone and aripiprazole. At the time of the opensuicide at some point during their life.[10-12] The disease is further access policy change, olanzapine and risperidone were US FDAcomplicated by a substantial co-morbidity of obsessive-compul- approved for acute mania, while quetiapine was shown later to besive disorder, panic disorder, social anxiety disorder, and sub- effective in bipolar depression.[18] Olanzapine received an FDA-stance abuse.[13] Not surprisingly, bipolar disorder causes severe approved indication for maintenance therapy in bipolar disordersemotional and social impairment, which is manifested by distress in January 2004 (which was not captured in the current study data).and disability for the patient and a significant burden on relatives Achieving treatment success (effectiveness) in patients withand other caregivers. bipolar disorders in clinical practice is often difficult. Noncompli-

Bipolar disorder incurs substantial costs to society. The lifetime ance with drug therapy is common due to the cyclical nature ofcost of all people with an onset of bipolar disorder in 1998 was bipolar disorders, denial of illness, drug adverse effects, lack ofestimated at $US45 billion.[14] The average lifetime cost for an control over life, lapsed prescriptions, cost of medications, andindividual patient ranges from $US11 720 for a person with a patients missing the feeling of euphoria during manic or hypoman-single lifetime manic episode to $US624 785 for persons with ic episodes.[19] Li et al.[20] found that only 5.5% of 3349 Medicaidnonresponsive/chronic bipolar disorder characterized by multiple patients in California with bipolar disorder used a relevant medica-treatment episodes.[14] The majority of this lifetime cost was tion continuously for 1 year. Of these patients, 58% were not onattributed to $US28 billion in lost productivity and $US17 billion any medication for more than 1 year; 33% of treated patientsin direct costs for healthcare services and medications, institution- delayed starting therapy for up to 1 year; and 43% of patients withal services, and caregiver services.[15] In a cross-sectional analysis bipolar disorders switched medications within 1 year. Moreover,of approximately 3000 bipolar patients and matched non-bipolar only 18% of the 3349 patients initiated treatment using combina-comparisons (some of whom were receiving CNS medications for tion therapy. These results indicate that a large pool of bipolarother conditions), the healthcare costs per year for bipolar patients patients may not be on active therapy at any point in time.were >4 times those of the matched non-bipolar counterparts The patterns of healthcare costs in the study by Li et al.[20] were($US16 230 840 vs $US4 074 797).[16] consistent with suboptimal drug treatment patterns documented in

Optimal pharmacotherapy for bipolar disorder consists of long- the same study. Total healthcare costs during the first year wereterm maintenance therapy with mood stabilizers, augmented by reduced by $US5044 (p < 0.0001) for patients who used a moodantidepressants and antipsychotics over shorter periods to treat stabilizer relative to patients who used no drug therapy. Patientsacute exacerbations of symptoms of depression and mania, respec- who delayed mood stabilizer therapy had higher total costs relativetively, although some clinicians are concerned about switching to other treated patients ($US5565, p < 0.0001), due primarily topatients into mania if antidepressants are used.[17] Historically, the increased use of hospital services ($US3844, p < 0.01). These datamainstay of acute and maintenance treatment for bipolar disorder support the hypothesis that patients with bipolar disorder whohas been the mood stabilizer lithium; however, its use is limited by restart or switch therapy are responding to an acute exacerbation ofadverse reactions and loss of efficacy over time. Subsequently, the the illness, resulting in higher healthcare costs, particularly in-anticonvulsants carbamazepine, valproate (valproic acid), lamo- creased hospitalizations and outpatient physician visits. Similartrigine, gabapentin, and topiramate have gained acceptance over correlations between increased healthcare costs, delays in therapy,time as effective treatments for bipolar disorder as well.[1] and changes in drug therapy have been documented in California

Medicaid (Medi-Cal) patients with schizophrenia[21,22] and in pa-Antipsychotic therapy is usually initiated to treat acute maniatients with schizophrenia in Medicaid programs in four otherwith the intent to withdraw therapy after the resolution of manicstates.[23]symptoms in order to avoid the adverse effects of these medica-

tions. Short-term use is especially important for conventional The Medi-Cal program granted open access to the newer atypi-(first-generation) antipsychotics, such as haloperidol and chlor- cal antipsychotics in October 1997, primarily based on data docu-promazine, as these medications are associated with significant menting the efficacy of these medications in treating schizophre-adverse effects, including tardive dyskinesia and extrapyramidal nia. Prior to this time, patients were generally subjected to a ‘twosymptoms.[1] Atypical, or second-generation, antipsychotics are failure’ criterion before atypical antipsychotics could be pre-generally associated with a more favorable adverse effect profile scribed, although other clinical justifications were allowed. Given

© 2006 Adis Data Information BV. All rights reserved. Dis Manage Health Outcomes 2006; 14 (5)

Open Access to Atypical Antipsychotics 289

the level of noncompliance and intermittent drug use patterns in true – i.e. that open access has no significant effects on the treat-both schizophrenia and bipolar disorders,[20-24] it is not surprising ment of patients with bipolar disorders – would also be an impor-that olanzapine and risperidone quickly became the two most tant contribution. Unlike patients with schizophrenia, patients withcostly drugs on the Medi-Cal formulary in terms of total expendi- bipolar disorders are more likely to be covered by private insur-tures regardless of disease state.[25] Given the high costs of these ance or to be members of managed care organizations. Confirma-drugs, many administrators have questioned whether patients are tion of the null hypothesis would suggest that these payers needbetter controlled (i.e. have better compliance and lower numbers not be concerned with controlling access to atypical antipsychoticsof acute events) and whether resource utilization (i.e. hospitaliza- in treating bipolar disorders due to their limited role in managingtions, ambulatory care) have been reduced after open access was this disease.granted in October 1997.

MethodsThis analysis investigates the impact of Medi-Cal’s open accesspolicy for atypical antipsychotics on drug use patterns and treat-ment costs for Medi-Cal patients diagnosed with bipolar disorder. DataMcCombs et al.[26] analyzed Medi-Cal data for all patients initiat-ing antipsychotic drug therapy before and after the formulary This analysis used paid claims data from the Medi-Cal programchange, regardless of diagnosis. However, <10% of their study for patients diagnosed with a bipolar disorder. The data for thissample were patients with bipolar disorders. Their results clearly study were derived from the historical paid claims files from thedocumented that open access to atypical antipsychotics caused an fee-for-service Medi-Cal program, which finances a wide range ofimmediately but temporary increase in the total number of patients healthcare services for the poor and disabled. Paid claims forinitiating treatment, but it was unclear whether these results ap- services delivered between January 1994 and August 1999 wereplied to patients with bipolar disorders. Not surprisingly, the used to identify patients with at least one paid claim with atemporary access effect was associated with significant changes in recorded bipolar disorder diagnosis (International Classifica-the characteristics of the patient population, especially the cost of tion of Diseases [9th revision] = 296.00–296.19, 286.40–296.89).nursing home use in the 6 months prior to starting antipsychotic Unique, encrypted personal identifiers enabled the claims fortherapy.[26] A similar but permanent ‘access effect’ was also patients with bipolar disorder to be retrieved and linked longitudi-observed when Medi-Cal added selective serotonin reuptake in- nally. Patient data included the date of birth, sex, race, eligibilityhibitor (SSRI) antidepressants to its formulary in May 1996. Open status (e.g. Aid to Families with Dependent Children [AFDC],access to antidepressant therapy resulted in a significant change in disabled), county of residence, and disease co-morbidities such asthe characteristics of the treated population and a reduction in both schizophrenia, depression, other affective disorders, anxiety, sub-the duration of drug therapy and switching to a second antidepres- stance abuse, personality disorder, dementia, and other mentalsant.[27,28] health diagnoses.

The impact of open access to atypical antipsychotics on the The data collected included the type of service, provider type,treatment of patients with bipolar disorders may be quite limited. physician specialty, date of service, amount paid, and units ofFirst, while a large pool of untreated Medi-Cal bipolar disorder service. For institutional services provided by hospitals and nurs-patients is likely to exist,[19] open access to atypical antipsychotics ing homes, the unit of service is a patient day. Many Medi-Calmay not generate an access effect. Most patients with bipolar dis- patients with severe mental disorders are dually eligible for bothorders initiate treatment in the depressed phase of the illness,[7-9] Medicare and Medicaid coverage, with Medicare assuming fiscalwhereas the recommended role of antipsychotic medications is in responsibility as the first payer. A method of adjustment wastreating bipolar mania or hypomania.[17,29-31] Second, dramatic devised to estimate missing Medicare ambulatory service (Part B)changes in drug use patterns may not appear since antipsychotic payment data, based on the amount paid by Medicaid and thetherapy for bipolar patients may be limited to short-term use Medicare Part B deductible and coinsurance rate. First, the totalduring the acute manic phase of the illness. If the ‘access effect’ is amount paid by Medicaid for services covered by Part B waslimited and the use of atypical antipsychotics is intended as short- totalled over the 1-year post-treatment period and the Part B-term use during acute mania, then dramatic changes in the cost of deductible amount was subtracted to approximate the amount oftreating bipolar patients under open access are also unlikely to the Medicaid payments that corresponded to the Medicare coinsur-appear. However, confirmation that our null hypothesis is ance liability. If the estimated coinsurance liability was greater


290 Narayan et al.

and Medicaid Services data for California).[33] To avoid potentialproblems of differential costing methods being applied to duallyeligible and Medi-Cal-only populations, the per diem pricingmethod was applied to all patients.

Data for prescription drug claims included National DrugCodes for the specific medication used, quantity dispensed, andnumber of days’ supply. It should be noted that prescription drugpayment claims were not filed for medications used by Medicareand/or Medi-Cal-only patients while hospitalized. Therefore, thisanalysis does not document the extent to which open access in theambulatory Medi-Cal program affected the use of atypical antip-sychotics in hospitals. However, this analysis did capture theextent to which hospitalized patients used these medications ondischarge.

Policy Variable Specification

Open access to atypical antipsychotic medications was grant-

Table I. Psychotropic drugs used in this study

Drug class Specific drugs

Antipsychotics Chlorpromazine, amitriptyline/perphenazine,clozapine, fluphenazine decanoate,fluphenazine hydrochloride, haloperidol,haloperidol decanoate, loxapine,mesoridazine, molindone, olanzapine,quetiapine, risperidone, thioridazine,thiothixene, trifluoperazine, ziprasidone,promazine

Antidepressants Amitriptyline, amitriptyline/perphenazine,bupropion, citalopram, desipramine, doxepin,fluoxetine, fluvoxamine, imipramine,maprotiline, mirtazapine, nefazodone,nortriptyline, paroxetine, protriptyline,sertraline, trazodone, trimipramine,venlafaxine, amoxapine, clomipramine

Mood stabilizers and Carbamazepine, lithium, valproic acid,selected anticonvulsants lamotrigine, topiramate, levetiracetam,

gabapentin

ed as of October 1, 1997. A closed access period was definedas episodes initiated before the formulary expansion (Julythan zero, it was then multiplied by a factor of five to reinflate the1994–September 30, 1997). A 6-month transition period wasestimated 20% Medicaid coinsurance liability to an estimate of thedefined as the 6 months following the formulary expansion datetotal payments allowed by Medicare. The deductible was then re-(October 1997–March 31, 1998) to account for all possible tempo-added to the estimated costs. If the estimated coinsurance liabilityrary access effects. The open access period was defined as span-was zero or negative, the actual amount paid by Medicaid wasning April 1, 1998, through August 1999.used as the estimate of total Part B payments.

The total cost for institutional care was estimated using perEpisodes of Drug Therapy

diem cost estimates and reported days of service. Hospital dayswere assigned a cost of $US1032 per patient per day (derived from Two approaches have been proposed in the literature for evalu-Medi-Cal data),[32] while nursing home costs were valued at ating drug policy changes: (i) the policy model; and (ii) the clinical$US270 per patient per day (derived from Centers for Medicine model.[34] The policy model approach compares trends in patient

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Fig. 1. Effect of open access on the number of restart and switching/augmentation episodes initiated per month using monotherapy. Open access wasintroduced in October 1997.



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Fig. 2. Effect of open access on the number of restart and switching/augmentation episodes initiated per month using combination therapy. Open accesswas introduced in October 1997.

outcomes and costs over time for the cohort of patients affected by of symptom remission or hypomania. Third, the policy and clinicalmodels assume that the policy being evaluated does not affect thethe policy change and then projects what these patients would haveclinical criteria used by patients and physicians to decide if theexperienced in the absence of the policy change, preferably basedpatient will receive treatment. This may not be the case here, ason an external cohort not affected by the policy change. Theatypical antipsychotics have been shown to be better tolerated thanclinical model compares time trends for patients who comply withconventional antipsychotics.[17] This reduction in risk may result inthe policy change (i.e. those who switch medications) and patientsthe treatment of patients who have less severe episodes of symp-who are not affected by the policy change (i.e. those with notom exacerbation.change in therapy). In the clinical model, the index date of the

comparison can be set at the effective date of the new policy or the The policy and clinical models also do not match well with thedate on which the individual patient complies with the new policy, clinical nature of bipolar disorders. Bipolar disorder symptoms arewith pseudo-compliance dates being generated for noncompliant cyclical in nature, with alternating periods of mania and depres-patients (i.e. non-switchers). sion. This cycling between moods and high rates of noncompli-

ance leads to periodic episodes of drug therapy initiated primarilyBoth the policy and clinical models implicitly assume that theduring a depressed state. For example, Li et al.[20] found that onlypatient population affected by the policy can be identified prior to5.5% of Medi-Cal patients with bipolar disorder used a moodthe policy’s implementation. For the purposes of this study, thisstabilizer consistently for 1 year, and these patients often exper-approach would require the identification of all patients using theienced significant periods of time without any active drug therapy.medications affected directly or indirectly by open access. Howev-This episodic use of drug therapy also creates the potential forer, this could not be accomplished in this study for several reasons.open access to a previously restricted class of medications to resultFirst, open access is likely to cause patients to restart drug therapyin both significant access effects and high rates of substitution ofafter a long period with no drug treatment. These patients could benew medications for older drug therapies under a wide range ofidentified in the pre-policy period if diagnostic data are accurateclinical conditions.and complete or if the average period of no drug use is relatively

short. Medi-Cal does not require diagnostic data for payment of An alternative approach was used in this analysis to measureclaims, and not surprisingly, diagnostic data are often missing the impact of formulary expansion on patient outcomes. Specifi-from individual paid claims. Second, both the policy and clinical cally, episodes of drug therapy were defined as being each time amodels assume that the affected population is reasonably constant patient started, restarted, or changed a drug therapy used to treatover time. Unfortunately, eligibility for Medi-Cal coverage often bipolar disorders, i.e. antipsychotics, mood stabilizers, selecteddepends on unemployment, which may be intermittent for patients anticonvulsants, and antidepressants. An individual patient mightwith bipolar disorders who are able to return to work during period have multiple episodes of therapy over time. The index date for


292 Narayan et al.

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Fig. 3. Effect of open access on the use of different drug classes used to treat restart episodes. Open access was introduced in October 1997. AD =antidepressant; AP = antipsychotic; MS = mood stabilizer.

each episode was determined by the date of each change in drug patient who was truly treatment naive. Therefore, ‘first use’ treat-ment episodes were excluded from further analysis.therapy. Patient episodes were then compared based on whether

the episode was initiated before or after the open access policy A restart episode was defined as being each time a patienttook affect. restarted drug therapy after being off all related drugs for a

minimum of 15 days. A person defined as initiating a restartPatient episodes of drug therapy were initially stratified intoepisode might be on the same medication used in their most recentfour categories based on the patient’s medication history: first use,treatment attempt or might start an alternative medication notrestarts, switches, and augmentation. First-use treatment episodesincluded in their most recent treatment regimen.were those episodes of mood stabilizer, anticonvulsant, antip-

sychotic, or antidepressant drug use with no prior history of a Switching and augmentation episodes of drug therapy wereprescription for any of these therapeutic classes (table I). By defined as being when patients started an alternative medicationdefinition, all patients included in the study had a ‘first use’ (either monotherapy or combination therapy, respectively) withoutepisode of drug therapy. However, it is impossible to know defini- a 15-day break in therapy; these episodes were combined into atively if a ‘first use’ episode of drug therapy was prescribed for a single category for the purpose of this analysis.

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Fig. 4. Effect of open access on the use of different drug classes used to treat switching/augmentation episodes. Open access was introduced in October1997. AD = antidepressant; AP = antipsychotic; MS = mood stabilizer.



Table II. Demographic and descriptive characteristics for patients receiving treatment for restart episodes

Characteristic Closed access Transition period Open access Statistical p-Value(n = 69 400) (n = 13 656) (n = 40 740) test valuea

Mean age [years (SD)] 43.3 (14.2) 43.9 (13.8) 42.9 (13.7) 4.52 <0.0001

Age category (%)

<25 years 9.1 8.9 10.0 68.42 <0.0001

25–34 years 22.4 20.2 22.1 72.30 <0.0001

35–44 years 30.1 29.9 30.5 5.13 0.0711

45–54 years 20.4 22.1 21.1 55.81 <0.0001

55–64 years 10.1 10.7 9.4 48.60 <0.0001

65+ years 8.0 8.2 6.9 120.79 <0.0001

Male (%) 38.0 38.2 37.8 1.10 0.5781

Race (%)

White 60.7 60.9 60.3 2.20 0.3336

Asian 1.4 1.2 1.6 15.77 0.0004

African American 12.0 12.3 12.7 10.63 0.0049

Hispanic 4.3 4.3 4.7 10.70 0.0047

other 21.6 21.4 20.7 11.51 0.0032

Category for eligibility for Medicaid(% of patients)

blind 0.6 0.5 0.4 6.49 0.0390

old age assistance 3.6 3.0 3.2 22.84 <0.0001

disabled 71.8 73.8 71.0 40.93 <0.0001

AFDC 18.5 17.2 19.4 34.97 <0.0001

Prior co-morbidities (%)

schizophrenia 22.4 24.3 22.9 25.38 <0.0001

depression 8.4 7.8 8.4 4.15 0.1259

personality disorder 2.3 2.4 2.2 3.44 0.1791

obsessive-compulsive 0.4 0.4 0.4 3.10 0.2124

alcohol abuse 0.6 0.5 0.6 3.27 0.1949

drug abuse 3.3 3.2 3.3 0.3135 0.8549

Episode of therapy [days (SD)]

time off drug 77 (107) 133 (210) 100 (161) 29.90 <0.0001

duration of therapy 115 (117) 129 (123) 116 (115) 2.48 0.0131

Type of drug used prior (%)

mood stabilizer 31.9 33.0 38.9 555.56 <0.0001

antidepressant 43.0 46.2 50.7 619.18 <0.0001

conventional antipsychotic 39.2 28.1 14.4 7 593 <0.0001

atypical antipsychotic 6.2 20.9 30.5 11 601 <0.0001

combination therapy 20.7 27.6 31.8 272.22 <0.0001

a Statistical test: ANOVA for continuous variables; χ2 for categorical variables.

AFDC = Aid to Families with Dependent Children.

Monotherapy was defined as a patient treatment episode utiliz- was defined as a patient treatment episode in which two or moreing a mood stabilizer, anticonvulsant, antipsychotic, or antidepres- bipolar-related medications were used as of the index date. Bysant alone at the start of a treatment episode. Combination therapy definition, episodes of augmentation therapy involved combina-


294 Narayan et al.

Table III. Unadjusted healthcare costs for patients receiving treatment for restart episodes

Healthcare cost Closed access Transition period Open access F-test p-Value(n = 69 400) n = 13 656) (n = 40 740)

Cost per month 6 months pre-treatment ($US)

Prescription drugs 159 188 168 45.68 <0.0001

Hospital 87 74 94 5.99 0.0025

Long-term care 333 345 302 7.00 0.0009

Ambulatory care 93 92 97 7.14 0.0008

Other services 13 16 14 9.74 <0.0001

Net (total minus drug) cost 526 528 507 1.89 0.1505

Total cost 684 715 674 3.00 0.0497

Cost per month 12 months post-treatment ($US)

Prescription costs 197 242 215 92.58 <0.0001

Hospital 77 87 88 6.18 0.0021

Long-term care 364 384 334 7.36 0.0006

Ambulatory care 100 99 102 2.38 0.0929

Other services 15 18 15 4.74 0.0087


Total cost 752 830 755 10.45 <0.0001

Difference between pre-treatment and post-treatment (%)

Net (total minus drug) cost +5.5 +11.3 +6.5 NA

Total cost +9.9 +16.1 +12.0 NA

NA = not applicable.

tion therapy as the augmented prescription was continued for at ysis was conducted to analyze the effects of open access on thesetwo subsamples of treatment episodes.least one additional refill.

The final data set of 123 796 restart episodes consisted only ofThe healthcare utilization data collected for each patient epi-episodes of drug therapy that included an antipsychotic medication

sode of treatment were separated into three time periods: (i) the(69 400 initiated during closed access, 13 656 initiated during the

index month in which the episode of treatment was initiated; (ii) 66-month transition period from closed access to open access, and

months prior to the index month (pre-treatment period); and40 740 initiated during open access). The corresponding count for

(iii) 12 months after the index month (post-treatment period). The switching/augmentation episodes was 206 157 total episodespost-treatment period was not terminated if patients terminated or (117 791 initiated during closed access, 22 319 initiated in theswitched therapies; therefore, episodes might span different peri- transition period, and 66 047 initiated during open access).ods of data. Episodes of drug treatment were excluded from the

analysis if the patient’s reported age was <18 years at the time of Statistical Methods

treatment or if the episode of treatment included <6 months of pre-Descriptive statistics were used to document changes in patienttreatment data and <12 months of post-treatment data.

characteristics that might have resulted from the implementationEpisodes of treatment were categorized into institutionalized

of open access in October 1997. Ordinary least squares (OLS)(long-term care) or ambulatory episodes, depending on the status

regression models were used to estimate the cost impact of openof the patient on or before the index date. Institutionalized patients access, adjusting for patient characteristics. Separate analyseswere defined as those with a history of nursing home utilization were conducted for restart episodes and switching/augmentationwithin the 6 months prior to treatment initiation. Since institution- episodes. Dummy variables were used to identify treatment epi-alized patients are more likely to be more severely disabled and sodes initiated during the transition and open access periods, usingconsume significantly more healthcare services, a sensitivity anal- treatment episodes under closed access as the reference group.



Separate analyses were conducted for all treatment episodes and Resultsfor treatment episodes initiated by ambulatory patients only.

The presence of multiple episodes of treatment observations for Time Trends in Treatment Episode Frequency

some patients violated the assumption of independence acrossFigure 1 and figure 2 document the number of treatment

observations. Under these conditions, the OLS estimators contin-episodes initiated per month by episode type for monotherapy and

ued to be unbiased; however, the estimated standard errors were combination therapy, respectively. Three important results can beinflated. Statistical estimation techniques were used that adjusted derived from these two time series plots. First, there was very littleestimated standard errors for serial correlation and heteroscedas- evidence of a significant access effect, with the exception ofticity.[35] augmentation episodes using combination therapy (figure 2). This

modest access effect was temporary. Second, in monotherapyMultiple regression models were used to estimate the impact oftreatment, restart episodes were more common than switching/open access on 12-month post-treatment costs by type of serviceaugmentation episodes, while in combination therapy, switching/(e.g. ambulatory care, prescription drugs, psychiatric hospital,augmentation episodes were more common than restart episodes.

acute hospital, nursing home, psychologist, hospice care, homeThird, combination therapy was approximately as common as

health, and other services). Approximately 60 other independentmonotherapy, which is consistent with treatment guidelines.[17]

factors were included to control for changes in patient characteris-The time trends of the use of different classes of medications taken

tics over time. These factors included age, race, sex, urban or rural as restart episodes or switching/augmentation episodes are shownresidence, disability status, the variety of medical diagnoses re- in figure 3 and figure 4, respectively. Both figures show ancorded in the prior 6 months, the mental health diagnosis preced- immediate and persistent increase in the use of atypical antip-ing the episode, prior use of healthcare by type of service in the sychotic drugs in October 1997, which was offset over time by aprior 6 months, and medication use. reduction in the use of conventional antipsychotic drugs (substitu-

Table IV. Adjusted impact of open access on healthcare costs 12 months post-treatment for patients receiving treatment for restart episodes

Component of cost All episodes (n = 123 795) Ambulatory episodes (n = 116 813)

estimate t-test p-value estimate t-test p-value

Transition period

Ambulatory care ($US) –12 0.47 0.638 –5 0.22 0.822

Prescription drugs ($US) 169 5.22 <0.001 158 5.46 <0.001

Psychiatric hospital ($US) 83 1.92 0.052 92 2.51 0.012

Acute hospital ($US) 24 0.59 0.554 9 0.25 0.804

Nursing home care ($US) 49 0.57 0.567 –38 0.75 0.452

Other services ($US) –1 0.09 0.930 –2 0.17 0.869

Net (total minus drug) cost ($US) 90 1.29 0.196 57 0.70 0.481

Total costs ($US) 311 2.66 0.008 215 2.46 0.014

Duration of drug therapy (days) 6.74 6.23 <0.001 6.34 5.70 <0.0001

Open access period

Ambulatory care ($US) 3 0.13 0.893 7 0.49 0.624



Acute hospital ($US) 9 0.24 0.807 13 0.51 0.607

Nursing home care ($US) 23 0.32 0.747 50 1.41 0.158

Other services ($US) –4 0.44 0.659 –5 0.76 0.446


Total costs ($US) 165 1.72 0.085 203 3.29 0.001

Duration of drug therapy (days) –3.67 4.80 <0.0001 –3.67 4.68 <0.0001


296 Narayan et al.

Table V. Demographic and descriptive characteristics for patients receiving treatment for switching/augmentation episodes

Characteristic Closed access Transition period Open access Statistical p-Value(n = 117 791) (n = 22 319) (n = 66 047) test valuea

Mean age [years (SD)] 43.2 (14.1) 43.8 (13.9) 42.7 (13.8) 7.16 <0.0001

Age category (%)

<25 years 7.2 6.3 7.5 35.12 <0.0001

25–34 years 20.8 19.8 21.4 24.80 <0.0001

35–44 years 31.1 31.0 30.9 0.59 0.7452

45–54 years 22.2 23.4 23.3 36.42 <0.0001

55–64 years 10.6 11.5 10.1 34.90 <0.0001

65+ years 8.2 8.1 6.9 99.33 <0.0001

Male (%) 39.1 39.2 38.2 14.07 0.0009

Race (%)

White 60.8 60.6 60.2 6.09 0.476

African American 12.8 12.2 12.6 5.95 0.501

Hispanic 4.3 4.1 4.8 33.35 <0.0001

Asian 1.3 1.3 1.4 3.92 0.1406

other 20.8 21.8 20.9 12.30 0.0021

Category for eligibility for Medicaid(% of patients)

blind 0.5 0.4 0.3 37.22 <0.0001

old age assistance 3.6 3.0 3.1 52.36 <0.0001

disabled 72.6 73.8 71.9 31.92 <0.0001

AFDC 17.6 16.7 18.5 42.56 <0.0001

Prior co-morbidities (%)

schizophrenia 22.2 24.6 22.7 64.59 <0.0001

depression 8.4 8.0 8.3 3.44 0.1794

personality disorder 2.3 2.1 2.2 4.67 0.0969

obsessive-compulsive 0.5 0.4 0.5 4.85 0.0885

alcohol abuse 0.6 0.6 0.6 4.11 0.1281

drug abuse 3.2 3.4 3.1 5.19 0.0746

other mental disorder 17.6 16.7 18.0 18.62 <0.0001

Duration of drug therapy (days) 104 112 106 5.27 <0.0001

Type of drugs switched/augmented (%)

mood stabilizers 25.1 22.0 27.3 269 <0.0001

antidepressants 33.7 35.1 38.3 481 <0.0001

conventional antipsychotics 31.0 21.2 11.6 8913 <0.0001

atypical antipsychotics 9.3 20.7 20.8 5386 <0.0001

2 or more drugs 13.4 16.7 20.1 1441 <0.0001

a Statistical test: ANOVA for continuous variables; χ2 for categorical variables.

AFDC = Aid to Families with Dependent Children.

tion effect). It should also be noted that the use of antidepressants Patients Restarting Treatment

increased significantly and permanently in May 1996 when Medi-Patient demographics for restart treatment episodes are summa-Cal added two SSRI antidepressants to its formulary.[27,28]

rized in table II. Patients with restart episodes in the open-accessperiod were, on average, slightly younger than patients with restart



episodes under closed access (42.9 vs 43.3 years, p < 0.0001). This atypical antipsychotic (30.5% vs 6.2% during closed access). Insmall change in the mean age was due to an increase in the contrast, the percentage of restart episodes in which a conventionalproportion of patients younger than 25 years (from 9.1% to 10.0%, antipsychotic was used decreased from 39.2% in the closed accessp < 0.0001) and a decrease in the proportion of those aged 65+ period to 14.4% in the open access period. Furthermore, a greateryears (from 8.0% to 6.9%, p < 0.0001) following the introduction percentage of restart episodes were treated with combination treat-of open access. There was a slight increase in the proportion of ment under open access (from 20.7% to 31.8%) compared withrestart episodes occurring in racial minority groups (i.e. Asian, closed access; this increase is probably due to the augmentationAfrican American, Hispanic) in the open access period (increases role of atypical antipsychotics.ranged between 0.2% and 1% for different groups) relative to the

Comparisons of unadjusted monthly costs for restart episodesclosed access period. There were no significant differences over

during pre-treatment (6 months prior to the index month) and post-time in the reported co-morbidities recorded in the patient’s paidtreatment (12 months after the index month) periods are presentedclaims file prior to initiating therapy. However, for restart epi-in table III. The total healthcare costs during the pre-treatmentsodes, the time a patient spent without any therapy before re-period increased from $US684 per month in the closed accessentering the system increased from 77 days in the closed accessperiod to $US715 per month in the transition period, then de-period to 133 days in the transition period and 100 days under opencreased to $US674 per month in the open access period. Althoughaccess. Although patients were without therapy for longer beforepost-treatment costs revealed an increase in monthly costs duringseeking treatment under open access, there was virtually nothe transition period (from $US752 to $US830), the net change inchange in the duration of therapy in the open access period versustotal post-treatment costs was minimal in the open access periodthe closed access period (115 days vs 116 days). During open(from $US752 to $US755). The spike in costs during the transitionaccess, there were greater proportions of restart episodes treatedperiod was mostly due to an increase in prescription costs (fromwith a mood stabilizer (38.9% vs 31.9% during closed access), an$US197 to $US242 per month), hospital costs (from $US77 toantidepressant (50.7% vs 43.0% during closed access), or an

Table VI. Unadjusted healthcare costs for patients receiving treatment for switching/augmentation episodes

Healthcare cost Closed access Transition period Open access F-test p-Value(n = 117 791) (n = 22 319) (n = 66 047)

Cost per month 6 months pre-treatment ($US)

Prescription drugs 154 187 159 105 <0.0001

Hospital 87 80 92 4.00 0.0183

Long-term care 304 334 285 10.29 <0.0001

Ambulatory care 93 95 97 7.99 <0.0003

Other services 13 18 13 29.61 <0.0001


Total cost 651 714 645 15.94 <0.0001

Cost per month 12 months post-treatment ($US)

Prescription drugs 193 248 209 240 <0.0001

Hospital 74 83 79 5.04 0.0065

Long-term care 342 371 317 12.41 <0.0001

Ambulatory care 100 103 101 2.12 0.1200

Other services 16 20 15 22.17 <0.0001

Net (total minus drug) cost 532 577 513 16.29 <0.0001

Total cost 725 825 722 38.99 <0.0001

Difference between pre-treatment and post-treatment (%)

Net (total minus drug) cost +7.0 +9.5 +5.5 NA

Total cost +11.4 +15.5 +11.9 NA

NA = not applicable.


298 Narayan et al.

Table VII. Adjusted impact of open access on healthcare costs for patients receiving treatment for switching/augmentation episodes

Component of cost All episodes (n = 206 156) Ambulatory episodes (n = 195 000)

estimate t-test p-value estimate t-test p-value

Transition period

Ambulatory care ($US) 16 1.07 0.283 3 0.11 0.910


Psychiatric hospital ($US) 100 4.52 <0.001 103 2.93 0.003

Acute hospital ($US) –15 –0.57 0.569 –29 0.69 0.489

Nursing home care ($US) 6 0.11 0.915 18 0.30 0.762

Other services ($US) 14 2.01 0.045 6 0.51 0.608


Total cost ($US) 421 5.68 <0.001 390 3.69 <0.001


Open access period

Ambulatory care ($US) –16 1.65 0.010 –16 0.87 0.384



Acute hospital ($US) –1 0.06 0.953 7 0.20 0.839

Nursing home care ($US) –42 1.16 0.247 <1 0.01 0.993

Other services ($US) –2 0.44 0.662 2 0.21 0.837

Net (total minus drug) cost ($US) –50 1.06 0.288 1 0.01 0.992

Total costs ($US) 75 1.51 0.131 125 1.64 0.100


$US87 per month), and long-term care costs (from $US364 to from $US165 (p < 0.05) for all restart episodes to $US203(p < 0.001) for restart treatment episodes initiated by ambulatory$US384 per month).patients (i.e. patients with no history of long-term care use in theSimple comparisons were used to adjust post-treatment costsprior 6 months). In relative terms, this translated into an increasefor changes in prior use over time. The percentage differences inof $US13.75 per month for all patients and $US16.91 per monththe average monthly costs between the 6-month pre-treatmentfor ambulatory episodes on an average baseline of $US755 perperiod and the 12-month post-treatment period are shown in tablemonth in total costs. Most of the increase in costs was due to aIII. There was little evidence of decreasing costs associated withsignificant increase in prescription costs (approximately

open access. The average total costs per month under closed+$US100) with nonsignificant increases in other component costs.

access increased by 9.9% in the post-treatment period relative to

the pre-treatment period. The average total costs increased by upPatients Switching or Augmenting Treatmentto 16.1% in the transition period and 12.0% under open access.

Similar, albeit slightly smaller, increases were seen for net (totalPatient demographics for those defined as having switching or

minus drug) costs, with a 6.5% increase in costs in the open accessaugmentation episodes of current therapy are presented in table V.

period compared with a 5.5% increase in the closed access period. Changes in the population characteristics were generally similar toThe estimated impacts of open access on healthcare costs for those observed for restart episodes. Open access slightly increased

restart episodes during the 12-month post-treatment period are the proportion of switching or augmentation episodes initiated bysummarized in table IV. Separate estimates were generated for the younger patients and decreased the proportion of such episodes fortransition and open access periods relative to the closed access older patients. Treatment patterns for switching and augmentationperiod in an effort to account for the transitory access effect on episodes also displayed trends consistent with restart episodes.costs. Open access was associated with a significant increase in The average continuous days on therapy stayed relatively constant,total healthcare costs over the first post-treatment year, ranging increasing by only 2 days (from 104 to 106) in the open access



period compared with the closed access period. Additionally, the components of medical costs were statistically significant. Patientsproportion of episodes increased slightly for mood stabilizers restarting treatment in the open access period increased initiation(from 25.1% to 27.3%) and antidepressants (from 33.7% to of atypical antipsychotics by approximately 24% and mood stabi-38.3%) but increased dramatically for atypical antipsychotics lizers by 8%. The limited influx of patients restarting treatment(from 9.3% to 20.8%) under open access. In contrast, the percent- because of open access significantly increased the average time offage of switching or augmentation episodes in which conventional therapy from 77 days to 133 days in the transition period. Similarantipsychotics were utilized decreased from 31.0% in the closed trends were seen for switching/augmentation episodes, whereaccess period to only 11.6% in the open access period. there was a 10% increase in the number of episodes in which

patients largely added/switched to an atypical agent. MedicationSimilar to trends seen with restarting episodes, the unadjustedutilization demonstrated that in both cases, patients initiated orcost trends (table VI) for switching/augmentation episodes re-changed their therapy with a conventional antipsychotic less oftenvealed that the increase in average monthly costs from pre- to post-in the open access period.treatment periods was greater for episodes initiated in the transi-

tion period (15.5%) compared with episodes initiated in the closed Based on the monthly cost data presented in table III and tableaccess period (11.4%). Total post-treatment costs per month in- IV, this study reported that the 12-month post-treatment costs forcreased by 11.9% in the open access period. The increase in total an episode of bipolar disorder averaged between $US8000 andpost-treatment costs per month during the transition period was $US10 000. The real-world significance of the reported increasesmostly due to increases in prescription costs (from $US193 to in yearly total costs remains questionable, given the somewhat$US248) and long-term care costs (from $US342 to $US371) minimal increases in costs during the open access period. Itduring the transition period. follows that caution should be used when interpreting these results

in the overall context of this costly disorder.The estimated impacts of open access on healthcare costs forswitching/augmentation treatment episodes are summarized in Patients switching or augmenting their existing antipsychotictable VII. The estimated impacts were generally consistent with drug therapy were much less sensitive to the open access period incorresponding estimates for patients restarting therapy. As with terms of their demographics and pre-treatment costs. It is possiblerestart episodes, open access was associated with a small and that physicians and patients altered their selection of an alternativestatistically insignificant increase in costs in the first post-treat- therapy for switching or augmentation, as this research found thatment year for all patients who switched or augmented their drug the rate of initiation of switching/augmentation did not changetherapy in the open access period (+$US75, p = 0.131). A similar significantly in the open access period compared with the closedresult was found for switching/augmentation episodes initiated by access period. Again, open access was not associated with aambulatory patients with no prior long-term care use (+$US125, significant increase in the overall cost of treating a patient withp = 0.10). Open access was associated with an increase of $US124 bipolar disorder. There was little evidence that the increase inin prescription drugs over the first post-treatment year in both the prescription costs was offset by reductions in the other compo-restart and switching/augmentation subsamples of treatment epi- nents of healthcare costs.sodes. Conversion of these nonsignificant findings to monthly Estimation of the impact of a policy change over time may becosts corresponded to an average increase in total costs of between confounded by many factors. Although this analysis focused on$US6 and $US10 per month relative to a baseline average total episodes of drug therapy rather than patients, the results may havecost of $US722 per month. been biased by time-dependent changes in the healthcare environ-

ment that affected the population under study. These may haveincluded, but were not limited to, differences in enrollment eligi-Discussion and Conclusionsbility, a change in the collection of data, a shift in the criteria forchoosing an atypical agent, and key time periods when publica-California Medicaid’s decision to provide open access to atypi-tions were released.cal antipsychotics to patients with bipolar disorder was weakly

correlated with a small increase in total costs that ranged between Although we included numerous independent variables within$US165 and $US203 per year for restart episodes and $US75 and the multivariate cost models to control for patient differences,$US125 per year for switching/augmentation episodes. In both changes in patient characteristics may not have been fully account-cases, increased prescription drug costs proved to be the primary ed for in this analysis. It would be beneficial for future researcherseffect of open access, and few of the estimated effects on the other to revisit this analysis by focusing on treatment selection bias as a


300 Narayan et al.

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6. Hirschfeld RM, Lewis L, Vornik LA. Perceptions and impact of bipolar disorder:find significant differences between different risk groups of pa-how far have we really come? Results of the National Depressive and Manic-

tients. depressive Association 2000 survey of individuals with bipolar disorder. J ClinPsychiatry 2003; 64 (2): 161-74It is important to keep in mind that the costs reported in this

7. Jamison KR. Suicide and bipolar disorder. J Clin Psychiatry 2000; 61 Suppl. 9:analysis were reported per treatment episode. Since there may47-51

have been many episodes within a single patient, the interpretabili- 8. Baldessarini RJ, Tondo L. Suicide risk and treatments for patients with bipolardisorder [editorial]. JAMA 2003; 290 (11): 1517-9ty of these cost estimates is uncertain. However, multiple episode

9. Judd LL, Akiskal HS, Schettler PJ, et al. The long-term natural history of theobservations per patient would not result in biased estimated weekly symptomatic status of bipolar I disorder. Arch Gen Psychiatry 2002; 59:

530–537effects, and the estimated standard errors were adjusted for multi-10. Tondo L, Baldessarini RJ. Reduced suicide risk during lithium maintenanceple observation bias.[35]

treatment. J Clin Psychiatry 2000; 61 Suppl. 9: 97-105Identification of patients for this analysis was based on a single 11. Angst J, Angst F, Stassen HH. Suicide risk in patients with major depressive

disorder. J Clin Psychiatry 1999; 60 Suppl. 2: 57-62paid claim with a bipolar diagnosis. Given recent research results12. Angst F, Stassen HH, Clayton PJ. Mortality of patients with mood disorders:

documenting the extent of misdiagnosis and delays in recognizing follow-up over 34–38 years. J Affect Disord 2002; 68: 167-81bipolar disorders,[36-38] it is likely that this analysis did not capture 13. Perugi G, Akiskal HS, Ramacciotti S. Depressive comorbidity of panic, social

phobic, and obsessive-compulsive disorders re-examined: is there a bipolar IIall Medi-Cal patients with bipolar disorders.connection? J Psychiatr Res 1999; 33: 53-61

The treatment of bipolar disorder involves many agents at 14. Begley CE, Annegers JF, Swann AC. The lifetime cost of bipolar disorder in theUS: an estimate for new cases in 1998. Pharmacoeconomics 2001; 19 (5):different stages of disease, and it becomes difficult to assess the483-96

impact of this policy change on a particular drug class or drug in a 15. Wyatt RJ, Henter I. An economic evaluation of manic-depressive illness – 1991.Soc Psychiatry Psychiatr Epidemiol 1995; 30: 213-9retrospective study. Naturalistic settings make it difficult to con-

16. Stender M, Bryant-Comstock L, Phillips S. Medical resource use among patientsfirm causal relationships between specific medications and out-treated for bipolar disorder: a retrospective, cross-sectional, descriptive analy-

comes since it is quite common for these patients to be utilizing sis. Clinical Therapeutics 2002; 24 (10): 1668-7617. American Psychiatric Association. Practice guideline for the treatment of patientsmore than one agent or drug class; moreover, our data set limited

with bipolar disorder. J Clin Psychiatry 1994; 151 Suppl. 12: 1-36us from collecting information related to the severity of illness or

18. Calabrese JR, Keck Jr PE, Macfadden W, et al. A randomized, double-blind,the phase of the disorder. placebo-controlled trial of quetiapine in the treatment of bipolar I and II

depression. Am J Psychiatry 2005; 162 (7): 1351-60Finally, the Medi-Cal program does not have a population that19. Keck Jr PE, McElroy SL, Strakowski SM, et al. Compliance with maintenance

is representative of the general population of the US, nor of all treatment in bipolar disorder. Psychopharmacol Bull 1997; 33: 87-9120. Li J, McCombs JS, Stimmel GL. Cost of treating bipolar disorder in the Californiapatients with bipolar disorder. The implications of this policy

Medicaid (Medi-Cal) program. J Affect Disord 2002; 71: 131-9decision cannot be extrapolated to other state Medicaid popula-

21. McCombs JS, Luo M, Johnstone BM. The use of conventional antipsychoticstions or the insured general population. medications for patients with schizophrenia in a Medicaid population: therapeu-

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Acknowledgments nia. Psychiatr Serv 2000; 51: 525-723. Lyu RR, McCombs JS, Johnstone BM. Use of conventional antipsychotics and the

This research was funded by Eli Lilly and Company, makers of olanzapine, cost of treating schizophrenia. Health Care Financ Rev 2001; 23 (2): 83-9924. McCombs JS, Nichol MB, Stimmel GL. Use patterns for antipsychotic medicationsin the form of Fellowships for Dr Narayan and Dr Sterling. The University of

in Medicaid patients with schizophrenia. J Clin Psychiatry 1999; 60 Suppl. 19:Southern California retains publication rights to all study results subject to5-13time-limited review and comment by Eli Lilly and Company. The authors

25. California’s Medical Assistance Program. Medi-Cal top 100 drug use report: 1999have no other conflicts of interest relevant to this manuscript.

year-to-date through June 1999. Sacramento (CA): Medical Care StatisticsSection, Department of Health Services, 1999

26. McCombs JS, Mulani P, Gibson PJ. Open access to innovative drugs: treatmentReferences substitutions or treatment expansion? Health Care Financ Rev 2004; 25 (3):

1. Nemeroff CB. An ever-increasing pharmacopoeia for the management of patients 35-53with bipolar disorder. J Clin Psychiatry 2000; 61 Suppl. 13: 19-25 27. McCombs JS, Shi L, Croghan TW. Access to drug therapy and substitution

2. Woods SW. The economic burden of bipolar disease. J Clin Psychiatry 2000; 61 between alternative antidepressants following an expansion of the CaliforniaSuppl. 13: 38-41 Medicaid formulary. Health Policy 2003; 65: 301-11

3. Weissman MM, Bland RC, Canino GJ, et al. Cross-national epidemiology of major 28. McCombs JS, Shi L, Stimmel GL. A retrospective analysis of the revocation ofdepression and bipolar disorder. JAMA 1996; 276: 293-9 prior authorization restrictions and the use of antidepressant medications for

treating major depressive disorder. Clin Ther 2002; 24 (11): 1939-594. Kessler RC, McGonagle KA, Zhao S, et al. Lifetime and 12-month prevalence ofDSM-III-R psychiatric disorders in the United States. Arch Gen Psychiatry 29. Kahn D, Frances A, Docherty J. Expert consensus guideline series: treatment of1994; 51: 8-19 bipolar disorder. J Clin Psychiatry 1996; 57 Suppl. 12A: 1-89



30. Goldberg JF. Treatment guidelines: current and future management of bipolar 37. Shi L, Thiebaud P, McCombs JS. The impact of unrecognized bipolar disorders fordisorder. J Clin Psychiatry 2000; 61 Suppl. 13: 12-8 patients treated for depression with antidepressants in the fee-for-service Cali-

fornia Medicaid (Medi-Cal) program. J Affect Disord 2004; 82: 373-8331. Keck PE, McElroy SL, Strackowski SM. 12-month outcome of patients with38. McCombs JS, Ahn J, Tencer T, et al. The impact of unrecognized bipolar disordersbipolar disorder following hospitalization for a major or mixed episode. Am J

among patients treated for depression with antidepressants in the fee-for-servicePsychiatry 1998; 155: 646-52California Medicaid (Medi-Cal) program: a 6-year retrospective analysis. J

32. California’s Medical Assistance Program. Annual statistical report: calendar yearAffect Disord. In press

1997. Sacramento (CA): Medical Care Statistics Section, Department of HealthServices, 1998

33. US Department of Health and Human Services, Health Care Financing Administra- About the Author: Sangeeta Narayan is medical outcomes researcher work-tion. Medicare and Medicaid statistical supplement, 1996. Health Care Financ ing with Baxter Bioscience. Previously, she served as a consultant to phar-Rev Stat Suppl 1996; 1-472 maceutical companies on conducting retrospective database studies and

34. Schneeweiss S, Maclure M, Soumerai SB, et al. Quasi-experimental longitudinal cost-effectiveness analyses. Her research interests include bipolar disorder,designs to evaluate drug benefit policy changes with low policy compliance. J

major depressive disorder, and biosurgery.Clin Epidemiol 2002; 55: 833-41Correspondence and offprints: Dr. Jeffrey S. McCombs, Department of Phar-

35. White H. A heteroscedasticity-consistent covariance matrix estimator and a directmaceutical Economics and Policy, School of Pharmacy, University oftest for heteroscedasticity. Econometrica 1980; 48: 817-38Southern California, 1540 East Alcazar Street, Room CHP-140, Los Angeles,36. Birnbaum HG, Shi L, Dial E. Economic consequences of not recognizing bipolarCA 90089-9004, USA.disorder patients: a cross-sectional descriptive analysis. J Clin Psychiatry 2003;

64 (10): 1201-9 E-mail: [email protected]


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