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To estimate the national annual cost of rehospitalization for multiple-episode schizophrenia outpatients, and to determine the relative cost burden from loss of medication efficacy and from medication noncompliance, the yearly number of neuroleptic-responsive multiple-episode schizophrenia inpatients in the United States who are discharged back to outpatient treatment was estimated. The cohort at risk for future relapse and rehospitalization was determined. The research literature on the expected rates of relapse for schizophrenia patients on maintenance antipsychotic medication was reviewed; in particular, monthly relapse rates under the optimal medication conditions of compliant patients taking optimal doses of a depot neuroleptic (optimal neuroleptic dose) and under the less optimal conditions of patients stopping medication (medication noncompliant) was estimated. Using established noncompliance rates from the literature, it became possible to estimate a "real world" rehospitalization rate for this cohort, as well as the relative burden accruing from loss of medication efficacy and from medication non-compliance. Finally, cost estimates for index hospitalizations and rehospitalizations were derived from data on national expenditures for inpatient mental health care. The monthly relapse rates are estimated to be 3.5 percent per month for patients on maintenance neuroleptics and 11.0 percent per month for patients who have discontinued their medication. Postdischarge noncompliance rates in community settings are estimated to be 7.6 percent per month. These estimates were entered into a survival analysis model to determine the real world relapse rate of this cohort. An estimated 257,446 multiple-episode (>= two hospitalizations) schizophrenia patients were discharged from short-stay (=< 90 Schizophrenia Bulletin, 21(3): 419-429, 1995. Schizophrenia inflicts incalculable suffering on patients and their families, and imposes a substantial economic burden on society (Wyatt and Clark 1987; McGuire 1991). Although cost estimates fail to capture the devastating human dimensions of the illness, they can help guide the allocation of treatment resources. Economists traditionally distinguish between direct and indirect costs. Direct costs are the actual dollar expenditures related to the treatment of an illness and typically include institutional care, professional services, and medications. Indirect costs include lost productivity and losses due to premature death. This article focuses on direct costs. Not surprisingly, the direct cost of schizophrenia is very large (Gunderson and Mosher 1975; Rice et al. 1990); a recent estimate of the total annual direct cost of schizophrenia is $19 billion (Wyatt et al., in press). Many cost studies divide direct costs into component costs (e.g., inpatient treatment, outpatient treatment, jail, medication, etc.). A limitation of this approach, however, is that it is static and provides little information about specific costs that come from particular aspects of the disease, patient behavior, or treatment. For example, an obvious issue in the maintenance (outpatient) treatment of schizophrenia is the risk of relapse and its associated costs. Two major contributors to relapse during maintenance treatment are loss of medication efficacy and medication noncompliance. Clearly, it would be very useful to better understand the relationship between specific problems such as these and the ultimate cost of schizophrenia. MethodOverview of Design. This analysis focuses on the neuroleptic-responsive, multiple-episode schizophrenia outpatient. First, we estimated the annual number of neuroleptic-responsive acute schizophrenia inpatients in the United States who are discharged back to outpatient treatment. This gave us a cohort at risk for future relapse and rehospitalization. Cost estimates for index hospitalizations and rehospitalizations were derived from data on national expenditures for inpatient mental health care during 1986, adjusted to 1993 dollars. Next, we reviewed the research on the expected rates of relapse for schizophrenia outpatients. In particular, we estimated the monthly relapse rates both under the best conditions, in which compliant patients are taking optimal neuroleptic doses, and under the higher risk condition of recent medication noncompliance. Finally, we used estimates of noncompliance rates to derive the "real world" rehospitalization rate as well as the relative cost burden from loss of medication efficacy and from medication noncompliance. Population at Risk. To estimate the annual number and hospital distribution of chronic neuroleptic-responsive schizophrenia patients discharged to outpatient treatment in the community, we used the National Institute of Mental Health (NIMH) 1986 Client/Patient Sample Survey (C/PSS; Manderscheid and Sonnenschein 1990) and set a priori criteria to include those inpatients who - (1) had at least one prior psychiatric hospitalization;
- (2) had a primary discharge diagnosis of schizophrenic, schizoaffective, or schizophreniform disorder;
- (3) had an index hospital stay of no more than 90 days; and
- (4) were neither admitted from nor discharged to another inpatient or residential care facility.
Thus, the number we arrived at represents a conservative estimate of the total U.S. cohort of chronic, multiple-episode schizophrenia patients who are discharged annually to the community. Defining Relapse Risk Categories. We reviewed prospective maintenance studies with at least 6 months of followup. Our goal was to determine relapse rates for patient groups under more narrowly defined treatment conditions than provided in other meta-analyses of maintenance neuroleptic studies (Davis 1976). We refer to these maintenance treatment conditions as "optimal neuroleptic dose," "medication noncompliant," and "medication withdrawal." For the optimal neuroleptic dose relapse risk group, we wanted to identify patients who were on an optimal dose of maintenance antipsychotic (but who were not otherwise "protected" by intensive psychosocial therapies) under circumstances in which medication compliance was known. To develop the optimal neuroleptic dose analysis, we identified studies or study subgroups with subjects who (1) had recently relapsed and were restabilized (most often, the patients had been recently discharged) and (2) were receiving long-acting depot neuroleptic (e.g., fluphenazine or haloperidol decanoate) as their maintenance therapy. Excluded from the optimal neuroleptic dose group were study patients who (1) were initially recruited from a stable outpatient population, (2) dropped out of a study or showed signs of noncompliance before relapse, (3) were assigned to a less efficacious depot dose (e.g., a low-dose medication assignment), and (4) received high-intensity psychosocial therapy in addition to a depot neuroleptic and standard outpatient care. In effect, many of the patients in this category were identified subgroups from larger studies in which some, but not all, of the subjects met these four criteria. The medication noncompliant relapse risk group was made up of stabilized patients who then became noncompliant to maintenance treatment. To be included in this group, subjects had to have been stabilized outpatients who, in the judgment of the investigator, stopped taking their medications while clinically stable. To see whether relapse rates in these patients differ from those in patients whose medications were discontinued by their physicians, we also analyzed monthly relapse rates of discharged patients whose antipsychotic medications were withdrawn by their clinicians. These patients made up the medication withdrawal risk group. Inclusion criteria for this group were that the patient had to have been recently stabilized from a relapse or recently discharged, and that the patient's medication withdrawal had to have occurred during outpatient treatment. Owing to the variability of the study methods and the data presentation, we had to make several simplifying assumptions. First, because there is no consensus definition of relapse (Falloon et al. 1983), we stayed with each author's definition as long as it was a categorical outcome. Later on, however, during the cost analysis, we equated relapse with rehospitalization. At first glance, this would appear to exaggerate the subsequent rehospitalization cost estimates. However, there is a countervailing selection bias that underestimates the number of patients at risk for rehospitalization. Specifically, the index hospital cohort actually comes from a larger patient pool of relapsed schizophrenia outpatients, some of whom relapsed but were not rehospitalized during the 1986 calendar year.
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