See discussions, stats, and author profiles fer this publicationat: https://www.researchgate.net/publication/8417 188
`
`Partial Compliance and Risk of Rehospitalization Among California Medicaid
`Patients With Schizophrenia
`
`ResearchGate
`
`Article in Psychiatric Services - September 2004
`DOL 10.1176/appi.ps 5.8.886- Source: PubMed
`
`CITATIONS
`508
`
`4 authors:
`
`Peter Weiden
`University ofIllinois at Chicago
`238 PUBLICATIONS 11,563 CITATIONS
`SEE PROFILE
`
`Amy LGrogg
`AmerisourceBergen
`41 PUBLICATIONS 1,379 CITATIONS
`SEE PROFILE
`
`Someof the authorsof this publication are also working on these related projects:
`
`Pject
`
` treatmentresistance Viewproject
`
`Project
`
`MM Lines View project
`
`READS
`530
`
`Chris Kozma
`
`260 PUBLICATIONS 2,086 CITATIONS
`SEE PROFILE
`
`Julie Lecklear
`EMD Serono
`43 PUBLICATIONS 1,205 CITATIONS
`SEE PROFILE
`
`All contentfollowing this page was upleaded by Amy | Groge on 29 May 2014.
`The user has requested enhancementof the downloadedfile.
`
`LATUDA04357213
`
`Exhibit 2137
`Slayback v. Sumitomo
`IPR2020-01053
`
`1
`
`Exhibit 2137
`Slayback v. Sumitomo
`IPR2020-01053
`
`

`

`
`
`Peter J. Weiden, M.D.
`Chris Kozma, Ph.D.
` Julie Locklear, Pharm.D., MBA.
`
`Objective: The objective of this study was to cvaluate the relationship
`between compliance with an antipsychotic medication regimen andrisk
`of hospitalization in a cohort of California Medicaid patients with schiz-
`ophrenia. Methods: Compliance behavior was estimated by using a rel-
`rospective review of California Medicaid pharmacyrefill and medical
`claims for 4,323 outpatients for whom antipsychotics were prescribed
`for treatmentof schizophrenia from 1999 to 2001. Compliance behav-
`lor was estimated by using four different definilions: gaps in medica-
`tion therapy, medication consistency and persistence, and a medication
`possession ratio. Patients were followed for one year and had an aver-
`age of 19.1 dispensing events. Logistic regression models using each
`compliance eslimale were used lo determine Uhe odds of hospitaliza-
`tion. Resuits: Risk of hospitalization was significantly correlated with
`compliance. With all definitions, lower compliance was associated with
`a greaterrisk of hospitalization over and above any otherrisk factors
`for hospitalization. For example, the presence of any gap in medication
`coverage was associated with increased risk of hospitalization, including
`gaps as small as oneto ten days (odds ratio [OR}]=1.98). A gap of 11 to
`30 days was associated with an ORof 2.81, and a gap of more than 30
`
`days was associated with an ORof 3.96. Conclusions: This study showed
`a direct correlation betweenestimated partial compliance and‘hospital-
`ization risk among patients with schizophrenia across a continuum of
`compliance behavior. (Psychiatric Services 53:886-891, 2004)
`
` ides
`
`sophisticated assessments have found
`that a majorityof patients with schiz-
`
`ophrenia who are considered to be
`compliant wilh their antipsychotic
`medication regimens actually show a
`range of compliance behaviors, prob-
`ably for many diverse reasons. The
`full range of compliance-spectrum
`behavior becomes apparent when pa-
`tient self-report
`is contrasted with
`other, more quantitative, measures,
`such as the Medication Ever Moni-
`toring System (MEMS) (1), or when
`compliance is determined by blood
`ed
`samples taken during unscli
`homevisits (2).
`Thus the term “partial compliance”
`
`seems preterable to “noncomplianc
`
`in that the former explicitly acknowl-
`
`scioes the commonsituation in: which
`
`es some, but not all, of his
`a personta
`or her prescribed medication. Partial
`compliance may take several forms,
`including taking an ammount
`that
`is
`consistently less than recommended,
`
`edication compliance, er—pliance as complete, willful cessation irregular (‘on-and-off) dosing be-
`adherence, among patients
`ofall antipsychotic medications is not
`havior, and having diserete gaps in an-
`tipsychotic therapy—for example, in
`# with schizophrenia has of-
`an accurate representation of actual
`ten been reportedas an all-or-nothing
`medication-taking behavior among
`the case of patients wheare unwilling
`outpatient populations with schizo-
`behavior: the patient either is compli-
`or unable torefill a prescription.
`
`ant or is not. This notion of noncom-
`phrenia. Recen
`7 studies using more
`that partial
`It is important
`to note
`compliance relers only to compliance
`behavior and does not reflect either the
`efficacy of the treatment or the per-
`son's attitude toward taking mecica-
`tion. Fer example, partial compliance
`can be due to efficaey problems (such
`as cognitive dystimetion that loads to
`forgetting to pick upa refill), systems
`barriers (for example, a prescriptionis
`not rotlled because insurance caver-
`
`
`
`agicdisorder service ofthe State University of
` Dr. Weidenis affiliated withthe neurabi
`
`jated
`
` fil New York in Brooklyn. Dr. Rosmais «
`awith the College of Pharmary of the Uni-
`Dr. Grogs and Dr. Locklearare wi
` he outcomes
`
`
`rsity ofSouth Carolina in Columbia.
`fer
`
`
`
`espon-
`research division of Janssen Medical Affairs in Titusville. New
`sey, Send cor
`dence to Dr. Locklearat Janssen Medical Affeirs, L
`C., 1125 Prenton Harbourton Road,
`
`y GB560 (e-mail,flockle1G}janus.jnj.com}: At
`
`Titusville, New Je
`orsion ofthis paper wes
`
`ind Neurologic Pharma-
`
`
`presented at the annual meeting of the Coll of Psychtatr
`cists, held May 1 to 4, 2008, in Charleston, South Carolina.
`B86
`PSYCHIATRIC SERVICES
`
`http://ps.psychiatryonline.org
`
`August 2004 Vol. $5 No. 8
`
`LATUDA04357214
`
`2
`
`

`

`
`after each patient’s index date (the ob-
`servation period), Because compliance
`patterns might be affected wien pa-
`Honts arc about to lose eligibility.
`pa-
`
`
`ts ine:
`tle
`a
`ed in the study were
`those
`who remained eligible tor California
`Medicaid for an additional
`three
`months after the obscrvation period.
`Patients were exchided if they were
`younger than 1S years al the start of
`the study period,
`if they had long-
`
`term-care visits (because of the possi-
`bility ofincomplete records), or iftheir
`
`calculated medication use (rm
`units dispensed divided by days’ sup-
`ply was ten or more. The reason for
`the uni ts-perdlay restriction was that a
`use of ten or more times per day sug-
`gests data entry errors.
`Patients who had a claim coded
`with an [CD-9-CM code for bipolar
`disorder (296.0x, 296.1x, or 296.4—
`296.8) al any poinl within the avail-
`able data set were dropped from the
`analysis on the grounds that these pa-
`
`tients might use
`drugs other than an-
`lipsycholics Yor example, lithium) as
`a primarytherapy(thusviolating nec-
`essary
`assumptions lor caleulation of
`
`compliance variables). Patients who
`were receiving long-acting enlipsy-
`choties (haloperidol decancate or
`fliphenazine decanoate) were ex-
`cluded because of inconsistencies in
`the number ofdays’ supplyrecorded.
`
`\
`
`Measures of partial compliance
`
`Four measures of compliance were
`evalnated: gaps in medication Lhera-
`py, medication consistency, medica-
`
`tion persistence, and a m
`tion
`possession ratio (MPR). Because the
`results from all measures were simi-
`
`lar, the primaryfoensin this
`3 is
`on gaps in medication, a measure that
`is conceptually straightiorward and
`
`easiest to use in clinical practice. For
`this study, medication gap was de-
`f
`as “the longest period during
`
`
`scl ta be
`
`no medication appeare
`available. Ce
`mili guons periods
`in
`which no medication appeared to be
`available were based on dispensing
`date and record.
`i days’ supply for
`each antipsychotic prescription. Four
`categories based on each putiert’s
`
`maximum gap in therapy were de-
`
`fined:
`zero days, one to tendavs, 11 to
`30 days, and more than 30 days. The
`mean numberofgaps per patient and
`887
`
`LATUDA04357215
`
`age has run out}, or an intentional deci-
`sion to stop taking medication.
`A tumber of studies have shown
`that most paticnts withschizophrenia
` 90
`are partially compliant
`(3,4
`L
`ty anc colleagues (3) found that
`percent of patients wilh schizophre-
`nia had some degree ofpartial com-
`
`plance. In this overall sample of 675
`patients, medications were not avail-
`
`able for 36 percentof patient-days of
`medication exposure. McCombs and
`collcaguos (4) found that G2 perecnt
`of a sample of 2,010 patients with
`schizophrenia had at least one disrup-
`tion in antipsychotic medication cov-
`
`erage during the course of a year and
`that the mean duration of therapy was
`ouly 142 days per year (4). Another
`study reported that among patients
`with early-episede schizophrenia, 63
`
`percent ofa sample of 182 hadat least
`
`y OVET & One-year
`one gap in ther
`period, with mosi of these gaps ex-
`tending over a month (5). However,
`comparison of partial compliance
`rates between studies is difficult, be-
`COUSO the techniques used to mneasure
`
`compliance, as well
`as thedefinitions
`of compliance.
`vary from study to
`study.
`tt
`is well known that medication
`noncompliance is one of the most im-
`portant modifiable risk factors forre-
`lapse among patients with schizo-
`pbrenia (6.7). Estimates suggest that
`noncompliance causes about 40 per-
`
`cent of relapse (8). A reviewof seven
`studies demonstrated that noncom-
`pliant patients had a six-month to
`two-year relapse risk that was about
`3.7 times that of compliant patients
`(9). First-episode patients, who po-
`tontially have the most to lose from
`repeated relapse, are similarly likely
`to experience relapse when their
`
`treatment is itderrupted (10). How-
`
`ever, these studies usedthe tracition-
`
`that
`al definition of noncompliance
`ontinuation of an-
`is, complete di
`
` sycholic medication. Thus the rela-
`Lip
`
`tionship between partial compliance
`and relapse risk is not known. An un-
`derstandingofthe role of partial com-
`pliancein relapse will help define the
`threshold between the extent of par-
`tial complianceandrisk ofrelapse.
`One approach for examining theef-
`fect of partial compliance on outcome
`is ta uso pharmacy clairns data as a
`PSYCHIATRIC SERVICES
`
`conservative proxy measure for com-
`pliance behavior. Analysis of pharma-
`ey claims has been used successsfally
`
`for cxam-
`for other chronic disc ases
`
`
`
`ple, hyperte:
`ion and epilepsy-
`
`showrelatior
`ships between partial
`compliance
`and
`hospitalization
`(11-14). Claims records in adminis-
`trative databases can be usedto assess
`whether patients discontinue their
`medication therapy (stop taking their
`medication) or refill medications in-
`consistently (skip doses} (15-20).
`The primary objectives ofthe analy-
`sis reported here were to determine
`the association between estiinates of
`partial compliance and outcome, with
`the hypothesis that the lower the com-
`pliance, the vreater the risk of hospi-
`talization, andto ovaluate the quantita-
`tive characteristics that define any po-
`tential relationship between partial
`compliance and hospilalizalion.
`
`Methods
`
`Stidy design and population
`A 20 percent
`random sample of
`1999-2001 California Medicaid data
`was used to evaluatethe association be-
`
`tween partial compliance and hospital-
`izalion. To be inchuded, patients wilh
`
`schizophrenia—that
`is, patients with
`an ICD-9.CM code of 295 xx-—-had to
`
`haveat least two disp
`sing events for
`
`antipsychotic medications chaning2a six
`month enrollment period Guly 1
`ts
`December 31, 1999). Qualifying pre-
`scription claims included claims forall
`approved oral antipsychotic medica-
`
`
`tions, including newer antipsychotics
`available before January 1, 2000.
`Each patient was assigned an index
`date, defined as the date of the pa-
`tiont’s first prescription chiring the on-
`rollment period. Because it is possible
`that patients with new diagnoses
`would lave significantly different
`compliance issues while heing stabi-
`lized with medicationtherapy, the goal
`was to studypatients who were
`&
`’
`Therefore,
`
`
`receiving antipsychotics
`patients were also required to have at
`least one prescription in the six
`months before their index date. The
`study was not examined byan institu-
`tional review board, because all per-
`sonal
`identifiers were removed and
`the investigators were not aware ofthe
`patients’ identities at any time.
`Data were obtained for 12 months
`
`hitp://ps.psychiatryonline org
`
`August 2004 Vol. 35 No. 8
`
`3
`
`

`

`claim) were summed. The MPR was
`calculated bydividingthis sumbythe
`number of ambulatory days in the
`stney period. By evaluating the per-
`
`fixed period,
`
`ments of
`
`
`wle«composite measure.
`
`Measure of bospitatization
`A tnarker was created to indicate
`whether a patient had at
`least one
`“mental health hospitalization” dur-
`ing the one-vear, postindex observa-
`tion period. Mental health hospitul-
`izations were identified by using
`“mental health” [CD-9-CMdiagnosis
`codes in the first (primary) diagnosis
`field. The following diagnosis codes
`were used:
`schiz yphrenia |(295xx),
`3
`296. Ox,
`296.3x,
`
`depression
`300.45, 309.0x,
`or SLixx),
`
`306.9X,
`300.2x,
`300.3x,
`(306.0%,
`308.xx, 309.9%, 309.4x, or GO9.9x).
`other psychoses
`(297.xx,
`298.xx,
`299.xx, 300. Lx, 302.8x, or 307.9x), and
`dementia (290.5x, 291.2, 310.9x, or
`331.0). Use of a broad delinition of
`psychiatric hospitalization ensured
`that no relevant psychiatric hespital-
`izations related to the index diagnosis
`of schizophrenia were missed.
`
`Statistical analysis
`The primary analysis evaluated the
`relationship between compliance and
`the presence of at least one mental
`health hospitalization duringthe one-
`year lollow-up period. Logistic re-
`
`gression models predicting presence
`of at least one hospitalization in the
`postindex year were developed for
`cach
`of the complianee measures.
`Medication gap models predicted
`hospitalization by using four gap cate-
`ro days, one to teu days, 11
`
`to 30 days, and more than 30 days.
`Logistic models for consistency, per
`
`and the MPRpredicteed hos-
`pitalization by using continuous
`measures. Interactions were included
`onlyif they addedsignificantly to the
`explanatory power ofthe model, vari-
`ab
` es were dropped [rom the models
`if they were insignificant and had a
`negative inypact en model fit. Cam-
`pliance was also categorized and eval-
`uated by using chi square tests.
`For descriptive analyses, consisten-
`PSYCHIATRIC SERVICES
`
`cy, persistence, and MPR meanscores
`as well as categorical frequencies are
`presented. For consistency and the
`MPR, the compliance categories de-
`
`Hance
`fined less than 70 percent corm
`
`
`as noncompliant and
`at least 70 per-
`cenl compliance as compliant. Ab
`though no standard is available for
`identitying compliance categories,
`the
`literature suggests that a 70 percent
`cutoff is reasonable (3,22,23). The
`MPR was caleulated in a mannor such
`
`that no values cxeceded 100 percent.
`The categories for persistence were
`less than 90 percent conpliance andat
`
`least 90 percent compHance.
`
`Results
`Patient disposition and
`demographic characteristics
`A total of 4,325 patients met the se-
`lectioncriteria. Patient characteristics
`are SUI marized inh
`‘Table 1. The pa-
`tients’ mean age was 44.2 vears; 58.5
`percent were men, and 55.6 percent
`
`were white. Approximately half were
`also Medicare eligible (48.9 percent).
`
`A total of 654 patients (15.1 percent
`had at least one psychiatric hospital-
`ization. Analysis ofthe crude dataalso
`showed thal age, ellnicity, and insur-
`ance status were associated with like-
`
`lihood ofhospital
`on. Hospitaliza-
`tion wasless likely with increasingage
`but more likely
`amongpatients“who
`
`were African American and among
`patients who were
`eligible
`for
`
`Medicare (Table 2).
`
`Partial compliance
`and bospitalization
`The patients in the study were on the
`more compliant end of the conapli-
`anee continimam,
`as indicated bythe
`mean compliance variables, shownin
`Table 3. Only 267
`patients (6.2 per-
`cent) had a persistence level of less
`than 90 percent, vieiding an average
`
`persistence of 97 percent. Duringthe
`
`s-year observation period patients
`had a mean=SD wumber of dispens-
`x events of 19.1415.9 for 1.65+.87
`
`
`
`rent drug entities.
`Figure ] shows the percentage of
`patients hospitalized as categorized
`by medication gup within a one-year
`
`period. All pairwise comparisons with
`the reference group were significant
`(p<.005), As the maximum gap in-
`ercased,
`the pereentage of patients
`
`http://ps.psychiatryonline.org
`
`August 2004 Vol. $5 No. 8
`
`LATUDA04357216
`
`Table F
`
`Characteristics of a saruple of 4,325
`outpaticnts for whom antipsychotics
`wer
`é prescribed for
`treatment of
`
`schizophrenia
`Variable
`
`N
`
`% M
`
`ale
`
`
`African American
`Asian
`
`Hispanic
`Other
`Unknown or mis
`
`Medicareeligibility
`Yes
`No
`Tlospitalized
`Yes
`No
`
`
`
`2114
`2911
`
`654
`3.671
`
`48.9
`511
`
`15.1
`84.9
`
`the mean gap duration (across all
`
`therapy gaps) were also calculated.
`Medication consisloneyis a measure
`of whether patients skipped doses
`when medication should have been
`
`available—that is, between the dates
`
`ofthe first andlast prescriptions a pa-
`tient had filled. Consisteneywas calcu-
`lated, using a modified definition from
`the literature (21), as the percentage
`of time a patient appears to have
`medication available divided by the
`period during which the patient
`should have theoretically used all the
`available medication. A weighted ay-
`crage was taken across antipsychotic
`therapies. Medication persistence
`captures whethera patient discontin-
`wed all
`therapies. This calculation
`represents the number of days be-
`tween the first and last prescription,
`
`divided by the fixed number of days
`in the study period.
`The MPRwas calculated in a man-
`ner similar to that used lor therapy
`hoe
`ag
`.
`*
`”
`gaps and is a modification of the liter-
`ature-based formula (15,16). The
`uumuber of days a patient was not hos-
`pitalized and showedevidence ofuse
`
`of
`any antipsychotic medication
`
`(based on. dispensing date and days’
`supply recorded on the preseription
`a8
`
`4
`
`

`

`fable Z
`
`Odds of hospitalization for a sanuple of 4,325 outpatients for whom antipsychotics
`
`
`
`Variable
`
`
`
`
`
`
`
`
`hospitalized increased. For consisten-
`ey and the MPR, significant differ-
`enees (p<.001) in the percentages of
`pationts with at least one hospitaliza-
`tion were found. Partially compliant
`patients hac. significantly higher rates
`of hospitalization. Patients whe were
`Duration of maximumgap (days)*
`Lito 10
`less than 70 percent compliant by the
`Ll to 30
`MPRhad higher rates of hospitaliza-
`Morethan 30
`tion than those who were at least TO
`
`Ten-year increase in age
`percent compliant (22.3 percent and
`Race?
`13.8 percent.
`respectively, p<.001).
`
`026
`4.94
`131
`African Arocrican
`
`Similar results wore observed for con-
`723
`12
`26
`Or
`
`sistency(24.5 percent compared with
`804
`02
`LO
`Missing
`Medicareeligihle®
`1.58
`25.7
`< O01
`
`12.8 percent, p<.001).
`In addition,
`patients who were identified as being
`2 Zero is the
`
`
`b Whiteisthe re rent.
`less than 90 percent compliant by the
`° Not Medicare c
`Ic is the referent.
`persistence measure had higher rates
`
`
`Fated
`
`of hospitalization than those who
`wore identified as being at least 90
`percent persistent (25.1 percent and
`145 percent,
`respectively, p<.001)
`(Table 3).
`
`
`
`O04
`< 001
`< OO
`OO
`
`LBS
`2.81
`3.96
`52
`
`1.27-3.25
`1.84.64
`2.54-6.5
`76-88
`
`
`
`Discussion
`
`The major finding of this study was
`the direct relationship between meas-
`ures of partial compliance and risk of
`of
`hospitalization: the lower the les
`the greater the risk of
`compliance,
`hospitalization. We emphasize that
`
`this finding is not as intuitive as iL
`might appear. Most published studies
`showing the link between nencompli-
`ance and relapse define noncompli-
`ance as persistent and complete dis-
`continuation ofantipsvchotic medica-
`tion, From that perspective,
`the co-
`
`hort in our analysis was mostly com-
`pliant, and even then a relationship
`was observed between partial compli-
`ance and hospitalization risk. This as-
`sociation behaves more like a contin-
`uous function than. a categorical func-
`
`tion—that is, once any degree of par-
`
`tial compliance was in
`ed by the
`data, there did not seem to be any
`low-end cutott below which hospital-
`ization risk reverted to that of the ref-
`erence cohort (noindication ofpartial
`compliance), This observation held
`for all
`four compliance measures.
`These results suggest that relatively
`small changes in overall compliance
`are meaningfully associated with
`changes in therisk of hospitalization.
`Partial compliance seems to be as-
`sociated with increasing risk of re-
`lapse in the long-term treatment of
`schizophrenia. We found that med-
`ication gaps as small as one to ten
`
`continuous days in a one-year period
`were associated with a twofold in-
`
`crease
`
`in. hospitalization risk. Th
`
`Figure i
`Percentage of patients with schizophrenia who were rehospitalized, by maximum
`gap in therapy*
`
`Compliance as a
`predictor of hospitalization
`Having a maximum gap in use of
`ruedication that was as sraail as one
`to ten days in a one-year period was
`associated with a significantly in-
`creased risk of hospitalization (odds
`
`ratio [OR]=1.98)
`(Table 2}. Com-
`pared with patients who did not have
`
`lication therapy, patients
`gaps ir
`who had a one- to ten-day maximum
`gap had almost
`twice the odds of
`hospitalization. As the gap increased
`to 11 to 30 days and more than 30
`
`2.81 and
`days, ORs increased to
`3.96, respectively.
`Logistic regression results for the
`other three compliance measures
`were similar to the results for med-
`ication gaps. With a 10 pereent im-
`provement
`in consistency, persist-
`ence, or the MPR, the odds of hos-
`pitalization were lowered by factors
`of 16 percent, 9 percent, and 23 per-
`cent,
`respectively (p<.01). These
`models are consistent with the re-
`sulls observed for
`the maximura
`medication gap models. Odds of
`hospitalization were also significant-
`ly affected by Medicare eligibility,
`depending on the compliance vari-
`able (Table 4). Medicare eligibility
`and an inercase in age of ton years
`were significant factors in the mod-
`els for the MPR. consistence, and
`persistence.
`PSYCHIATRIC SERVICES
`
`
`
` 235
`
`2-4
`
`
`
`ge
`
`eg
`Ra
`BT oe
`an b+
`Fae5
`oo
`i&
`~
`S
`5 5oy
`64
`
`11-30
`>30
`Total
`
`num gap (days within one year}
`se comparisons were siginificant al p<.005,
`
`
`hitp://ps.psychiatryonline org
`
`August 2004 Vol. 35 No. 8
`
`LATUDA04357217
`
`5
`
`

`

`Table 3
` tions in a surple of 4,325 outpatients
`Couiplianee and use ofpsescription mec
`for shorn antipsyct
`© prescribed for treatment ofschize
`ohronia
`
`
`Not ho
`Variable
`
`
`
`
`Gap in medication th
`"y
`
`Maximum gap( days}
`@ days?
`1 to 10 days*
`1] to 30 days!
`Morethan 30 days
`Consistency*
`73
`<70 percent compliant
`2700 percent compliant
`444
`ef
`O72 14
`
`
`<90 perce
`87
`290 percent compliant
`“7
`Medication possession ratiot
`862.18
`|
`150
`504
`
`24
`203
`188
`242
`
`54
`11.9
`16.1
`21.6
`
`882.2
`
`306
`1,507
`978
`880
`
`93.6
`88.1
`83.9
`78.4
`
`with their antipsychotic medication
`
`
`5), These data suggest
`regimens
`
`that patients whe do not achieve
`sat-
`i sfactory responses to treatincnt may
`be experiencing partial compliance
`
`problems rather than medicationeffi-
`cacy problems. Steps tuken to im-
`prove compliance offcr an important
`treatment option that should be con-
`sidered along with other options,
`
`aii-
`such as combining or switching
`tipsychotic medications.
`Several
`limitations of this study
`should be nated. One of the most im-
`portant limitations is that pharmacy
`claimus data do not provide insights
`into the reasons for partial compli-
`ance. Partial compliance is a behav-
`ioral finding with no attributable un-
`derlying cause. For example, there is
`no wayto know whether partial com-
`plance in ourstudy sample reflected
`
`an intentional decision to slop taking
`medication or was unintentional, per-
`haps due to service barriers such as
`discontinuity of care (26),
`Furthermore, Ube causalily of the
`association between partial compli-
`anee and hospitalization has not been
`established. For examiple, it is possible
`that patients who do not fully respond
`to their medication would be more
`likely to have medication gaps and
`that the commonsharedris] isincom-
`>
` acy (27),
`plete medication«
`Wedic
`not attempt a test of temporal conti-
`guity between noncompliance and
`hospitalization, but such a test could
`
`
`be consideredfor a fultrre analysis
`The database we used had techni-
`cal limitations. The use of Medicaid
`
`claims data as a proxyfor partial com-
`plance relies on ininimal coding er-
`
`245
`12.8
`25.1
`145
`92.3
`13.8
`
`538
`3,018
`200
`3,471
`522
`3,149
`
`75.5
`87.2.
`
`74.9
`85.5
`V7
`
`$6.2
`xys versus | to 1Gcays, gos
`30 days
`
`
`
`Lai, dfet
`od unless the patient had at least Loree dispensing
`
`results are consistent with those of
`other studies that have demonstrated
`the negative consequences of partial
`compliance. Valenstein and col-
`leagues (23) foundthat patients who
`had poor compliance were 9.4 times
`as
`
`likely to have inpatient admissions
`compared with patients who had
`good cormpliance.
`In addition, pa-
`tients who had peor compliance had a
`greater total number of psychiatric
`inpatient days (a mean of 33 days per
`
`year) compared with patients who
`had good compliance (a mean of 24
`days peryear).
`
`Anotherstudy found that partially
`compliant patients were 49 percent as
`likely as compliant patients to have an
`inpatient hospitalization (24). Most
`recently, Gilmer and coworkers (25),
`in an analysis ofa California Medicaid
`database, also foundthat rates of psy-
`chiatric hospitalization were lowest
`along patients who were compliant
`
`
`
`
`
`
`
`
`
` 325 outpatients for whom antipsychotics were prescribed for treatmont of schizo-
`Odds of hospitalization for a sample of
`
`phrenia, based on compliance models*
`
`Consistency
`Persistence
`Medication possession ratio
`OR
`OR.
`OR
`
`Endpoint
`estimate
`7?
`df
`estimate
`ea
`df
`estimate
`e
`df
`
`9.07
`1
`87
`AS.7
`i
`gl*
`10 percent improved compliance
`3a
`86.42
`i
`28.04
`i
`82"
`27.78
`i
`Si
`Ten-year increase in age
`Bo
`22.18
`i
`
`8.19 : o
`LE4
`African American versus whiteans a
`
`Modicarccligible
`1.55"
`21.65
`1
`5a"
`23.81
`1
`23.84
`I
`*
`4 Gnlyvariables that were significant in the model are shown.
`p<.01
`fe
`p< O01
`
`
`
`
`
`BOD PSYCHIATRIC SERVICES=-http://ps.psychiatryonline.org August 2004 Vol. $4 No. 8
`
`LATUDA04357218
`
`6
`
`

`

`der
`
`
`associated hosp
`2711591166, 1959
`
`
`
`
`
`cd scription
`
`14825,
`
`
`15. Selar DA, Skacr TL,
`
`
`ransderraal deliv
`
`sive therapy:
`
`Gifsuppl LA)
`16. Selar DA, Skaer TL.
`Cl
`
`
`transdermaldeliverysyst
`
`
`or antihyperte =
`
`sive therapy: E, Aau
`1 Journal of Medi-
`
`
`5, 181
`e eel1A}378
`, Monane M, et al:
`17. Garwily
`
`;
`L lor
`. Ara
`
`TES, £993
`
`foot of val
`
`
`refill con
`2:endent diabete
`
`
`Pharmacyand Thoepenté is
`
`299, 1993
`ig. >
`
`
`
`20.)
`
`di
`
`tial compliance on other aspects of
`schizophrenia, such as the duration
`and severity of ilness. Ultimately, en-
`hanced compliance, through improved
`pharmacolog!
`drug delivery interven-
`
`tions or behavioral interventions, could
`reduce the loll ef relapse and rehospi-
`talization associated with the long-term
`treatment afschizophrenia.
`
`Acknowledgment
`This study was supported by Janssen
`Pharmaceutica Products, L.P.
`
`References
`
`1. Gli
`
`NF Matsui D,_Hermann C,
`
`
`
`ag of antipsychotics and antidepres-
`latric Medicine 8163-197, L891
`
`
`B Grogs AL, Kozma a.
`Att
`hhreria:
`
`
`
`
`cal Care 32
`
`
`
`
`einer JP, Prochaz|
`refill complia:
`rmacy records:
`
`ions. Journal of
`Cb
`firsl-acdmiss
`
`05-116, L907
`1 4Q
`
`JSG Lo 1996. Psyclsi
`
`
`
`6. Ayiso-Gati
`
`influencing
`
`
`
`
`
`
`
`rors (28 29). Patients’ discontinuation
`of use of Medicaid services may not
`be reflected in a timely fashion (28):
`Medicaid pationts may not be repre-
`sentative of the population as a whole;
`and claims data may not include po-
`lenlial confounders, such as medical
`
`history andlifestyle factors (28).
`Cal-
`culations for compliancevariables are
`dependent on accurate claims infor-
`
`mation pertaining to dates, days’ sup-
`ply of medication, the patient's being
`discharged onthe same medication as
`
`at admission, and the assumption that
`there are no other sources of medica-
`tion supply—for example, medication
`samples. Theselatter problems could
`lead to an overestimation of the asso-
`iation between medication gaps and
`hospitalization Althongh the use of
`pharmacy claims methodology has
`the potential advantage of assessment
`of large colioris of palients over
`longer periods, potential sources of
`errorlie in the assumption that claims
`data are a proxy for partial compli-
`anee. Although these factors may
`have iutrodueed bius into our analy-
`
`2
`mized
`sis.
`the
`analysis
`plan
`sources of differential error between
`ihe reference group and the partial
`compliance group.
`it
`Given these factors, however,
`should be noted that medical claims
`data almost certainly overestimate
`compliance, because claims data can
`report only whether the prescription
`
`was filled, not whether the medica-
`tion. was taken correctly orat all (28).
`Furthermore,
`the reference group
`likely inchided some patients who
`
`
`could be more accurately described
`as partially compliant. Thus the actu-
`al relationship between partial com-
`pliance and hospitalizationis likely to
`be stronger than could be identified
`frou our data. Factors other than
`partial compliance, many of which
`would not be captured in a claims
`database, inchiding social support—
`or
`lack Ubereol—and
`substance
`abuse, can affect hospitalizationrates.
`
`souree u
`
`ea
`
`
`
`ation. Journal of Clinical
`try 5O(suppi $):21-25, 1805
`
`:
`Jo
`havioral Healtth Marchi:LO6—110, 1997
`9. Fenton WS, Blyler CR, Heinssen. RR: Deter-
`
`
`10, Robinson 1D, Woorn
`Predictors ofFolapsei
`
`Bulletin 23:63
`
`AB, 1997
`
`
`
`
`
`bost$
`
`al: The ef
`addy M, Mauch RB, et
`Wa
`
`psychotic partial con yplianc
`ationin a schizophrenic and bipo-
`
`
`wut. Poster presented at the annual
`tar populul
`ical Drag t'valuation
`iny ofthe New¢
`
`
`
`
`, Boca Raton, #
`, fone 12, 2008
`
`PCR, Lacro [P et
`
`
`ant withanti psychotic
`ical
`
`. American
`
`89, 2004
`
`26. Weid
`
`
`
`
`voncompltanes and nent health policy,
`ir
`
`1
`mad the Treatment Alliance.
`
`
`
`wood, 1996
`1: P Oltsou M: Cost of relay
`
`ophrenia. Schizophrenia Bu
`498, 1995
`
`
`25. Bright BA, Avorn I Everii
`
`data as a resource for epic
`
`
`Sens an
`ations, Jou
`pidemiclogy 42:037-945, 1989
`29. lezzoni Lh Assessing quality using adminis-
`trative data, A
`Internal Medi
`
`
`Laks pt 2): S674, 1997
`
`Conclusions
`The results of this study suggest that
`enhancing courpliance across‘the range
`ofpartial compliance behaviors can re-
`duce the risk of hospitalization among
`patients with schizophrenia. Future
`
`
`studies will oxplore the impact of par-
`
`
`August 2004 Vol. 35 No. 8
`chiatryonline.<
`PSYCHIATRIC SERVICES—uttp://ps.p
`
`iL. Choo BY,Rand CS, Haul TS. et al: Validation
`edCey
`
` rn
`thods for measuring and
`
`13, Maronde RE Chan LS, Larsen FY, et al: Un-
`
`LATUDA04357219
`
`7
`
`