Poor adherence with antipsychotic medication is common among patients with schizophrenia and is associated with increased risk of psychiatric hospitalization. A structured review of studies assessing antipsychotic adherence among patients with schizophrenia in a variety of settings found that approximately 40% of patients were not fully adherent with antipsychotic medications (1). Data from the U.S. Department of Veterans Affairs (VA) indicated that over a 12-month period, approximately 40% of VA patients with schizophrenia filled less than 80% of the medication supplies needed to take antipsychotics in the doses prescribed (2). Furthermore, over a four-year period, 60% of VA patients with schizophrenia had at least one year in which they filled less than 80% of the supplies needed to take their antipsychotic in the doses prescribed (3).
Several large observational studies indicated that patients with poor adherence have 1.4 to 3.9 greater odds of psychiatric hospitalization than patients with good adherence, depending on the time frame used for defining poor adherence (2,4–7). Given that in the VA, fully 18% to 25% of all patients with a diagnosis of schizophrenia are hospitalized each year (8,9), interventions that increase adherence may be important for improving symptoms and for reducing risks of hospitalization.
The impact of a variety of intervention approaches on antipsychotic medication adherence has been assessed (10–12), but only a few approaches have demonstrated improvements in both adherence and outcomes. Interventions that have behavioral components, focus on problem solving, and target specific adherence behaviors may be more likely to be successful (10). Assertive community treatment (ACT), called mental health intensive case management in the VA health system, is a complex set of services designed to reduce inpatient use among individuals with serious mental illness (13). ACT may affect inpatient use, in part, through improving adherence.
ACT emphasizes a team-based approach, a low patient-to-staff ratio, individualized services, and frequent contacts between patients and staff in the community (13). ACT teams accept full responsibility for addressing their clients’ health care, emphasize the importance of medication adherence, and often provide practical assistance for medication management. Some teams may facilitate fills and deliver medications to patients, although this practice likely would not continue without interruption if staff regularly assessed adherence and found nonadherence or partial adherence and extra medication stored.
Most, although not all, studies indicate that ACT decreases use of inpatient services among individuals with serious mental illness, particularly if inpatient use is high before ACT enrollment (14–17). However, the mechanisms underlying ACT’s impact on rehospitalization are less clear, including whether changes in adherence associated with ACT enrollment may be important in reducing hospital use.
To date, the literature regarding ACT’s impact on antipsychotic adherence is mixed, although modestly promising (10). The studies that have examined the relationship between ACT enrollment and medication adherence usually have been small (<100 participants), have examined selected subpopulations (such as patients enrolled in randomized controlled trials that assess another primary outcome or patients with specific comorbidities), have not specified how adherence was measured, or have used subjective adherence measures, such as clinician or patient reports (10,18,19).
This study built upon prior work by using national VA administrative data (including pharmacy fill data) to compare medication adherence for a large, comprehensive sample of VA patients with schizophrenia who enrolled in usual-care ACT programs or were eligible but did not enroll. Pharmacy data were used to construct a well-defined and validated measure of adherence, the medication possession ratio (MPR), and adherence was assessed at multiple points over an extended period (24 months). Among ACT enrollees, the level of program participation and adherence were examined. Finally, exploratory analyses examined the relationship between antipsychotic medication adherence in the first year after the study entry date and the number of inpatient psychiatric admissions in the second year.
The study was approved by the human subjects committees at the Veterans Health Administration medical centers in Ann Arbor, Michigan, and Baltimore.
Study data were obtained from the VA National Psychosis Registry (NPR), which is developed and maintained by the VA Serious Mental Illness Treatment Resource and Evaluation Center in Ann Arbor, Michigan. The NPR includes national VA health system records for all VA patients with diagnoses of schizophrenia, bipolar disorder, and other psychoses.
Using the VA ACT programs’ enrollment registry and data from the VA NPR, we identified all 763 VA patients newly enrolling in ACT between fiscal years 2001 and 2004 (October 1, 2000–September 30, 2004) who had a diagnosis of schizophrenia in the 12 months before enrollment, were alive for 12 months after enrollment, met VA-defined criteria for high hospital use (three or more mental health inpatient admissions or 30 or more mental health inpatient days in the prior 12 months) (20), lived within 60 miles of a VA ACT team (the usual operating area of VA ACT teams), and had 90 or more outpatient days in each of five sequential six-month periods of interest (zero to six months before the date of ACT entry or index date for the control group and zero to six, seven to 12, 13 to 18, and 19 to 24 months after ACT entry date or the index date). To have MPRs calculated during these study periods, patients needed to have had an antipsychotic fill six to 12 months before ACT entry or the index date and also to have had 90 or more outpatient days in each six-month period.
Propensity scores for the probability of enrolling in ACT were used to match ACT enrollees 1:1 with patients who met all of the same inclusion criteria but did not enter an ACT program. Propensity scores were calculated on the basis of adherence at baseline, age, sex, race, marital status, homelessness, substance use disorder diagnosis, Charlson comorbidity score, number of inpatient psychiatric stays in the past year, number of inpatient psychiatric days in the past year, service connection, number of domiciliary days in the past year, number of residential rehabilitation days in the past year, number of mental health visits in the past year, number of substance abuse visits in the past year, and the Veterans Integrated Service Network (VISN) in which the patient received care. Propensity score matching is often used to balance between-group differences in the distribution of the key covariates, allowing matching on multiple factors (21).
Measure of antipsychotic medication adherence
As in prior studies, data on the days’ supply of antipsychotic medication dispensed during each six-month study period were used to calculate MPRs. The MPR is defined as the number of days’ supply of antipsychotic received from an outpatient pharmacy divided by the number of days’ supply needed for continuous outpatient antipsychotic use.
For each period, MPRs were calculated by adding the number of days’ supply of antipsychotic medication dispensed by the outpatient pharmacy during the six-month period plus any remaining days’ supply from fills in the prior six months that would have covered days during the period of interest. Medications received at the time of discharge from inpatient settings were included in outpatient pharmacy supplies. Days that patients spent in institutional settings (VA hospitals or nursing homes) were subtracted from the outpatient days’ supply needed.
MPRs calculated from VA pharmacy data have been shown to correlate with important intermediate patient outcomes, including psychiatric admission of patients with schizophrenia to VA facilities and other health care settings (2,22).
Data for all covariates were obtained from administrative data in the VA NPR. Measures included patients’ demographic data (age, sex, race, and marital status). Other covariates were constructed from data from the 12 months before the index date, including an indicator for homelessness (ICD-9 code V60.0 or services utilization in specific clinics or “bed sections”) (23), number of psychiatric inpatient days, number of psychiatric inpatient admissions, number of antipsychotics prescribed, and a substance use disorder diagnosis (ICD-9 codes 291.X, 292.X, 303.0, 303.9–305.0, and 305.2–305.9 without a fifth digit of 3 to signify remission). A modified version of the Charlson Comorbidity Index indicating the presence of 19 medical diagnoses in the year before the index date was included as a measure of medical comorbidity (24).
For an exploratory analysis of the level of ACT participation among enrollees and medication adherence, we constructed a variable for full and partial ACT participation. Level of participation was measured by the frequency of contact between the ACT team and the client. Patients who completed at least 42 ACT visits in a 12-month period were considered to be fully participating in ACT treatment, whereas patients who completed 41 visits or fewer in a 12-month period were considered to be partially participating in ACT care. This represents a relatively conservative estimate for full ACT involvement. VA criteria for ACT programs indicate that ACT usually involves two or three contacts per week, with lower levels of contact only after a year of treatment. VA health system regulations also specify that VA ACT programs must have at least 41 contacts per client per year to qualify for a higher-than-normal budgetary allowance for these patients (25).
Univariate analyses of patient characteristics and good adherence (MPR ≥.8) at various points were described by means and frequencies.
Bivariate analyses assessing the relationship between good adherence and ACT enrollment were completed by using chi square statistics. To assess differences in rates of good antipsychotic adherence among patients who entered or did not enter ACT, we used a generalized linear model with logit link and a generalized estimating equation (GEE) method. These analyses adjusted for patient demographic variables, baseline adherence, homelessness, substance use diagnosis, medical comorbidity score, number of antipsychotics prescribed, and prior inpatient utilization. GEE analyses more appropriately estimate regression coefficients and variance when correlated data are used (26). We used a GEE approach because adherence observations were nested within patients over the two-and-one-half years of the study.
In exploratory analyses, we used chi square statistics to explore whether patients who enrolled in ACT showed significant differences in medication adherence by level of participation in ACT. We used GEEs to assess whether adherence (MPR) in the first year after the index date predicted inpatient admissions in the second year after the index date. A mixed-effects model was used to account for correlation of inpatient days within patient.
Statistical analyses were completed by using SAS software, version 9.2.
Table 1 shows the characteristics of ACT enrollees and ACT-eligible nonenrollees after propensity score matching. After propensity matching, there were no significant group differences across any covariates that might be associated with both adherence and with ACT enrollment.
Table 1Characteristics of patients enrolled or not enrolled in assertive community treatment (ACT)
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| Never married||719||47||362||47||357||47|
|Homeless in past year||340||22||179||24||161||21||.268|
|Inpatient psychiatric admissions in past year (mean±SD)||2.8±2||2.8±2||2.8||2||.355|
|Inpatient psychiatric days in past year (mean±SD)||51.8±39.3||53.1±42.3||50.6±36.0||.102|
|MPR at baseline (mean±SD)b||.81±.29||.83±.28||.80±.30||.111|
The study sample (N=1,526) was predominantly male (89%) and older, with a mean±SD age of 50±10 years. Most patients were white (57%), but black patients constituted a substantial minority (35%). Approximately 22% of patients had an indicator for homelessness in the year before the index date, and 43% had a concurrent substance use diagnosis.
Medication adherence by ACT enrollment
In the six months before the study index date, there were no differences in adherence (MPR ≥.8) among patients who enrolled (72%) or did not enroll (70%) in ACT. However, in all six-month periods that followed the index date, the percentage of patients with MPRs ≥.8 was higher among ACT enrollees than among nonenrollees, both in unadjusted (Table 2) and adjusted analyses (Table 3). In multivariate logistic regression analyses, the odds of good adherence among ACT enrollees were greatest in the six-month period immediately following enrollment. However, the odds of good adherence were twice as high or higher among ACT enrollees versus nonenrollees across all periods following enrollment.
Table 2Patients enrolled or not enrolled in assertive community treatment (ACT) with good adherence to antipsychotic medication, by study perioda
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|6 months before ACT entry or index date||1,082||71||549||72||533||70||.367|
|After ACT entry|
| 0–6 months||1,072||70||617||81||455||60||<.001|
| 7–12 months||1,019||67||580||76||439||58||<.001|
| 13–18 months||993||65||559||73||434||57||<.001|
| 19–24 months||965||63||553||73||412||54||<.001|
Table 3Association of good adherence with medication and enrollment in assertive community treatment (ACT), by patient characteristic and study perioda
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|0–6 months||7–12 months||13–18 months||19–24 months|
|Characteristic||OR||95% CI||OR||95% CI||OR||95% CI||OR||95% CI|
|ACT (reference: no)||2.97||2.25–3.92||2.27||1.77–2.92||2.00||1.55–2.59||2.11||1.63–2.74|
|Baseline MPR ≥.8 (reference: <.8)||4.69||3.58–6.15||3.94||3.01–5.15||2.98||2.28–3.90||2.23||1.70–2.92|
|Male (reference: female)||.90||.57–1.42||1.11||.72–1.70||.74||.49–1.10||.81||.53–1.24|
|Race-ethnicity (reference: white)|
|Marital status (reference: married)|
| Never married||.96||.62–1.48||1.11||.74–1.67||1.56||1.03–2.35||1.30||.89–1.90|
|Homeless (reference: no)||1.07||.78–1.48||.84||.62–1.15||.70||.51–.97||.78||.57–1.08|
|Substance abuse (reference: no)||.77||.57–1.02||.90||.68–1.18||.80||.61–1.07||.91||.69–1.21|
|CCI score (reference: 0)b|
|Inpatient psychiatric admissions||.84||.77–.90||.88||.82–.95||.91||.84–.99||.89||.81–.98|
|Inpatient psychiatric days||1.00||1.00–1.01||1.01||1.00–1.01||1.00||1.00–1.01||1.01||1.00–1.01|
|Number of antipsychotics||2.85||2.30–3.54||3.40||2.63–4.40||4.54||3.44–5.99||5.67||4.36–7.38|
After adjustment for demographic and clinical variables, GEE analyses that examined the impact of ACT enrollment over time indicated that ACT enrollees were 2.3 times more likely than nonenrollees to have good antipsychotic adherence (Table 4).
Table 4Association of good adherence with medication and enrollment in ACT over time, by patient characteristica
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|ACT (reference: no)||2.26||1.90–2.69|
|Baseline MPR ≥.8 (reference: <.8)||3.28||2.72–3.95|
|Male (reference: female)||.88||.66–1.17|
|Race-ethnicity (reference: white)|
|Marital status (reference: married)|
| Never married||1.20||.91–1.60|
|Homeless (reference: no)||.84||.68–1.03|
|Substance abuse (reference: no)||.85||.70–1.03|
|CCI score (reference: 0)|
|Inpatient psychiatric admissions||.88||.83–.93|
|Inpatient psychiatric days||1.00||1.00–1.01|
|Number of antipsychotics||3.95||3.39–4.60|
ACT participation and adherence
As outlined in Table 5, ACT enrollees who received higher levels of ACT services were more likely to have MPRs ≥.8. Between seven and 24 months postenrollment, approximately 80% of patients who averaged 42 or more ACT visits in a year had MPRs ≥.8, compared with 55% to 70% of patients with fewer ACT visits. Only 31% to 42% of patients who discontinued ACT involvement entirely in the second year had good antipsychotic adherence in that year.
Table 5Engagement in ACT services among patients with good medication adherence, by study perioda
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|Total||No ACT visitsb||Partial engagementc||Full engagementd|
Adherence and psychiatric inpatient days
An exploratory analysis of the study sample indicated that adherence in the first year was not significantly related to the number of inpatient admissions in the second year after enrollment. Only the number of inpatient stays, substance use, patient age, and the number of antipsychotics prescribed in the first year were significantly associated with the number of inpatient stays in the second year after enrollment. [A table presenting the results of this mixed model is available online as a data supplement to this article.]
This study of propensity-matched patients who enrolled or did not enroll in ACT is the largest effort, to date, to assess the relationship between ACT enrollment and subsequent antipsychotic adherence among patients with schizophrenia. Study results indicated that ACT enrollment is strongly associated with the likelihood of good antipsychotic adherence (MPR ≥.8). Furthermore, the association between ACT enrollment and adherence persisted over a 24-month period. Last, among patients who were enrolled in ACT, higher use of ACT services was associated with higher levels of adherence. The latter association may be due to a participation-related salutary impact of ACT on adherence or to a third factor that influenced both receipt of ACT services and adherence.
However, taken together, the findings suggested that ACT and other similar intensive case management models may improve medication adherence. The results of this study were congruent with most, although not all, prior studies examining adherence after ACT enrollment (10,18,19) and add to the growing literature that suggests that ACT may have a strong and lasting impact on antipsychotic medication adherence.
Although the primary study analyses indicated that ACT enrollment was associated with increased likelihood of MPRs ≥.8, the exploratory analysis examining the relationship between antipsychotic adherence in the first year after enrollment and inpatient admissions in the second year after enrollment did not show the expected association between increased adherence and decreased admissions.
Interventions that improve antipsychotic adherence have not always been associated with reduced hospitalization (11,12). A prior study found that after entering ACT, homeless patients had improved adherence and improved symptoms but no changes in inpatient readmission (18). In this study, patients who enrolled in ACT had approximately 20% more days with adequate medications on hand. This increment may not have been sufficient to have a differential impact on the number of inpatient days. ACT staff may also have facilitated hospitalization of enrolled patients at earlier stages of decompensation, appropriately reducing risks of harm to self or others during unstable periods or diverting patients from judicial or other nonmedical institutional settings.
In a related study, ACT enrollment has been found to be associated with reduced medical costs but to have a complex relationship with hospitalization, including no change in the number of hospital stays but fewer number of hospital days and increased use of partial hospitalization. Cost benefits were strongly influenced by the level of patient hospital use before ACT enrollment (27).
Several caveats should be considered when interpreting the study findings. First, although we matched ACT-enrolled patients with ACT-eligible but nonenrolled patients by using propensity scores, these scores use only measured variables. Unobserved variables may remain unbalanced between the two groups and contribute to the differences observed in adherence. Our sample was constituted from ACT patients and a matched control group who had to have at least 90 outpatient days in five consecutive six-month periods. As a result, study patients may have been somewhat healthier than other ACT patients.
Improvements in adherence and associations between adherence and hospital stays may have been more robust among patients with very high levels of hospital use. MPRs are also imperfect measures of adherence. Patients might fill their antipsychotic medications outside the VA system, and their low MPRs might inaccurately suggest poor adherence. Conversely, patients might refill their prescriptions, have high MPRs, but fail to ingest their medications. Potentially, these measurement issues may have differed for patients who were enrolled or not enrolled in ACT. For example, ACT patients may have been more likely than individuals in the matched control group to receive refills but not use the medications if ACT staff were more successful in their efforts to facilitate refills than to facilitate regular ingestion.
This is the largest study, to date, to examine the relationship between ACT enrollment and subsequent antipsychotic adherence among patients with schizophrenia treated in clinical settings. Patients’ adherence was assessed by using an objective, validated, but unobtrusive measure—the MPR. We found that ACT enrollment was strongly associated with adherence to antipsychotic medication as measured by the MPR. This association persisted for at least 24 months. Furthermore, ACT patients with higher levels of participation had higher levels of adherence.
These findings add to the growing literature suggesting that ACT has a strong and long-lasting impact on antipsychotic medication adherence. However, additional studies are needed to assess the degree to which improvements in adherence that are due to ACT services affect subsequent rehospitalization or inpatient lengths of stay.
This study was funded by a grant (IIR-06-115) to Dr. Slade from the Health Services Research and Development Service, U.S. Department of Veterans Affairs.
The authors report no competing interests.