LSE Health and Social Care, London School of Economics and Political Science, London
London School of Economics, and Institute of Psychiatry, London, UK
Lundbeck SA, Paris, France
Section of Social and Epidemiological Psychiatry, Department of Psychiatry, University of Leicester, Leicester, UK
Correspondence: Professor Martin Knapp, PSSRU, LSE Health and Social Care, London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK. E-mail: m.knapp{at}lse.ac.uk
Declaration of interest None. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To compare costs, clinical outcomes and quality of life for patients who experienced relapse in schizophrenia with a control group who did not relapse.
Method Patients were randomly selected from current psychiatric case-loads drawn from urban and suburban areas of Leicester. Differences in costs and outcomes by relapse status in the previous 6 months were examined using parametric and non-parametric tests, and multivariate analysis was used to examine factors associated with relapse and costs.
Results Costs for the patients who relapsed were over four times higher than those for the non-relapse group. There were few statistically significant differences in clinical and quality of life measures by relapse status. Multivariate analyses suggested some significant correlates of relapse and costs.
Conclusions The higher costs associated with relapse will be of interest to policy-makers who face difficultchoices concerning new but more expensive treatments for patients with schizophrenia.
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INTRODUCTION |
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METHOD |
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Patients were included as participants if they had received a diagnosis of schizophrenia according to DSMIV criteria (American Psychiatric Association, 1994), had no other psychosis, were aged 1864 years, and gave their informed consent. Patients were excluded from the study if they were roofless, continuously hospitalised for 12 months or more, about to move residence, already participating in a clinical trial, or unable to participate for language reasons. Although such biases were not specifically controlled for, clinicians took every step to avoid biases in the socio-economic and demographic profiles of patients.
Relapse criteria
Many alternative definitions of relapse in schizophrenia have been
published (see Lader, 1995,
for review). These include number of admissions to hospital, detention under a
section of the Mental Health Act, attendance at an acute day care centre,
change of antipsychotic agent, increased staff input and/or more intensive
case staff management, and a significant change in accommodation. Relapse was
identified retrospectively in this study as the re-emergence or aggravation of
psychotic symptoms for at least 7 days during the 6 months prior to the study.
In addition to instances of relapse pointed out by clinical staff, recorded
changes in mental state were regarded as significant and amounting to relapse
if there was a clearly documented assessment of a relapse. A change in
management as appropriate might also have occurred but not necessarily, and
not all relapses led to readmission. Relapse could thus be identified in cases
of patients who had been admitted to hospital in the past 6 months, who had
consulted their psychiatrist and had had their medication changed for
deterioration in their condition, or who had had an increase in intensive
support at home from the community mental health team. A planned hospital
admission was not classed as a relapse. A research team specialist registrar
advised the researcher on any case-note descriptions or accounts from staff
that were unclear.
Instrumentation
Data were collected especially for this study. Data collection was based on
information obtained directly from case notes and from interviews with the
patients in which rating scales were completed (patients gave informed written
consent). The information had not been extracted for any other or prior
reason.
We used the Positive and Negative Syndrome Scale (PANSS; Kay et al, 1987), one question from the Clinical Global Impression scale (CGI; Guy, 1976) covering severity of illness, the Global Assessment of Functioning (GAF; American Psychiatric Association, 1987), the Lehman Quality of Life scale (Lehman, 1996), the visual analogue scale from the EuroQoL EQ5D health-related quality of life measure (Kind, 1996) and the Client Service Receipt Inventory (CSRI; Beecham & Knapp, 1992, 2001). Unit costs attached to services were national average figures for the period over which clinical and service use data were collected, at 19989 prices (Netten et al, 1999).
Statistical analyses
Depending on the distribution of key variables, parametric (independent
t-test) and non-parametric (MannWhitney, KruskalWallis)
tests were carried out to check for significant differences in mean costs,
clinical and QoL outcomes by relapse status. The Pearson chi-squared statistic
was used to test for significant differences between categorical measures and
relapse status, and for other relapse criteria.
The survey design also permitted multivariate analysis to examine simultaneously some of the potential correlates of relapse status and costs, although it should be noted that the study did not include a full range of possible associations with relapse (see for example, Robinson et al, 1999). First, a generalised linear model (GLM) with a logit link function was used to predict whether a patient had experienced a relapse or not. The logit GLM is similar to the standard logistic model but also produces a measure of dispersion (the variance of the unexplained part of the model). Odds ratios are presented which show the likelihood of relapse given particular patient characteristics. Second, because costs were skewed to the right (although only 5% were zero values), standard ordinary least squares estimates were inappropriate (cf. Dunn et al, 2003). The results presented are based on a reduced-form GLM model, with a log link function and a Gaussian variance function. Compared with other standard GLM specifications, this produced the best-fitting model in terms of mean predicted cost levels. It also produced the most efficient estimates in terms of lower standard errors and smaller confidence intervals. The statistical analyses were carried out using the Statistical Package for the Social Sciences version 9 for descriptive comparisons and STATA version 6 for the multivariate analyses.
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RESULTS |
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A total of 145 patients completed interviews in the study: 77 relapse cases and 68 non-relapse cases. Another 9 patients who were also interviewed were excluded because of incomplete records or inconsistent data. The limited information available on them suggests that most would have been assigned to the non-relapse group and, if included, their cases would have had little impact on average costs.
Relapse and patient characteristics
Relapse status was defined on the basis of re-emergence or aggravation of
psychotic symptoms. Table 1
lists other patient characteristics previously employed to define relapse
(Lader, 1995). Not
surprisingly, relapse cases were characterised by higher rates of
hospitalisation (63%), reemergence of psychotic symptoms (60%) and aggravation
of positive or negative symptoms (43%), and an increased level of staff input
or more intensive case staff management (33%) (all P<0.05).
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Compared with the non-relapse group, patients who had recently experienced a relapse had been more recently admitted to a psychiatric ward (using actual years: 1997 and 1992, P<0.05), and experienced a higher number of admissions (5.6 and 3.3, P<0.05). Although patients in the non-relapse group appeared to have spent longer in hospital, the difference was not significant (Table 2). There was no difference between the relapse and non-relapse groups with respect to gender, ethnic group, marital status, employment status or highest level of education (Table 3). Relapse patients were more likely to be living alone (P<0.05). Mean ages were 37.9 (s.d.=10.7) years for relapse patients and 41.1 (s.d.=11.1) years for non-relapse patients (not significantly different).
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Clinical health and quality of life
Although higher scores on the PANSS and the CGI suggested worse symptoms
for relapse compared with non-relapse cases, the differences were not
statistically significant. However, GAF scores indicated worse symptoms for
relapse patients (P<0.05; Table
4).
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Using the Lehman delightedterrible (DT) scale and scores, relapse patients appeared to experience lower QoL than non-relapse patients on most dimensions, but the differences were small and not statistically significant, except for the items living arrangements and feelings about current health (P<0.05). There was perhaps some inconsistency in the QoL findings since relapse patients scored slightly better on the EQ5D visual analogue scale compared with non-relapse patients (P<0.05). However, the EQ5D measures own health state today, whereas the Lehman score covers broader dimensions of quality of life.
Resources and costs
Six-month service use rates and costs per patient are summarised in
Table 5. Costs for relapse
cases were four times higher than those for non-relapse cases
£8212 compared with £1899 (P<0.05) with much
of the cost difference accounted for by in-patient days. During the 6 months
prior to the study, patients in the relapse group spent a mean of 58 days in
hospital although this figure was inflated by six patients who were
continuously in hospital for the entire period. By design and selection,
nobody in the non-relapse group experienced any hospitalisation in this
period.
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Psychiatric out-patient visits were also significantly more common in relapse than in non-relapse cases (mean cost £209 v. £135, P<0.05). On the other hand, there was slightly higher use by patients in the non-relapse group of day care centres, group therapy, sheltered workshops, specialist education, general practitioners and community psychiatric nurse (CPN) visits, but apart from day care centres none of the differences was statistically significant at the 5% level. Services are complements, in the sense that patients with greater morbidity are likely to use more of a number of services, but are also substitutes, in that (for example) hospital in-patients will have less need and less opportunity to use day care, primary care and CPN support. These two tendencies may have cancelled out for this sample.
Relapse correlates
Given the (expected) high costs associated with illness relapse, correlates
of relapse and non-relapse status were examined. The odds ratios in
Table 6 indicate that,
controlling for all other explanatory factors, there was an increased risk of
relapse associated with:
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Cost correlates
The log link method of GLM estimation was used to examine the factors
associated with cost differences (Table
7). Coefficient values represent the percentage change in total
costs (from the average) following a one-unit change in the explanatory
variable (compared with a reference category if the variable is categorical).
Holding constant all other explanatory factors in the model, average costs
were increased by patients who relapsed (147%), and were reduced by patients
who were older (3.6% per year of age), and living with family/others compared
with those in collective accommodation (58%).
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DISCUSSION |
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Clinical and QoL correlates
Surprisingly, perhaps, there were few differences in clinical and QoL
outcomes between patients who had relapsed and those who had not. However,
some of the patients in the former group would have recovered well from their
relapse by the time these clinical and QoL instruments were administered. This
time lapse is probably the reason for the lack of difference.
Associations
Multivariate analyses confirmed some significant correlates of relapse, and
a reduced-form cost equation found, as expected, that relapse status
significantly increased total costs. The cost equation was estimated in
reduced form for two main reasons. First, relapse status as a regressor
captured some of the important partial effects already identified in the
relapse function for example, suicide attempts, previous hospital
admissions and social functioning and reduced the need to include
these variables further as independent effects in the cost analyses. Second,
clinical and QoL variables were excluded from the cost equation because it was
difficult to relate current measures with costs in the previous 6 months. This
is a problem of endogeneity: it is difficult to ascertain the direction of
causation between variables. Although higher levels of service use (and costs)
might have improved health and reduced the likelihood of relapse, relapse
status might have increased service use and costs. However, given that relapse
often resulted in hospitalisation (for about two-thirds of the people in the
relapse group) and in-patient costs accounted for around three-quarters of
total costs, the problem of endogeneity with relapse status was less of an
issue.
Finally, a cautionary note is required on measuring differences in costs and health outcomes between the relapse and non-relapse groups. Although this method is valid, a superior comparison would come from panel or longitudinal data that measure changes in outcomes prospectively for a given population (cf. Robinson et al, 1999). The costs of relapse would then be estimated by examining the differences in costs, before, during and after relapse. Cost-effectiveness comparisons are also required based on experimental evaluations of relapse minimisation strategies.
Policy implications
The significant costs found to be associated with relapse confirm the scale
of the impact in this case measured by service uptake of a
worsening of symptoms for people with schizophrenia. These costs will be of
interest to clinicians and other decision-makers who face difficult choices
about new but more expensive treatments for patients with schizophrenia.
Subject to the above cautionary comment, delaying the time to relapse should
mean delaying the escalation of costs. More importantly, a slower or reduced
rate of relapse means slower or reduced damage to the health and quality of
life of patients, and in some cases also less adverse impact on their
families.
Psychoeducation and related programmes have been shown to reduce medication non-adherence, detect prodromal symptoms of relapse and reduce the rate of hospitalisation (e.g. Birchwood et al, 1989; Kemp et al, 1996; Herz et al, 2000). A relatively inexpensive evidence-based intervention for reducing relapse is family work for patients with schizophrenia living with a relative with high levels of expressed emotion (e.g. Xiong et al, 1994). There is no evidence that these effective interventions have yet come into widespread use.
If new antipsychotic treatments in schizophrenia can improve efficacy and compliance rates compared with conventional neuroleptic therapy, and thereby reduce relapse rates, this might bring about reductions in the service costs of schizophrenia. In turn, as demonstrated in some international studies (Hamilton et al, 1999), and as concluded by the National Institute for Clinical Excellence (2002), the overall costs of the treatment could be reduced.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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REFERENCES |
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American Psychiatric Association (1987) Diagnostic and Statistical Manual of Mental Disorders (3rd edn, revised) (DSMIIIR). Washington, DC: APA.
American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders (4th edn) (DSMIV). Washington, DC: APA.
Beecham, J. K. & Knapp, M. R. J. (1992) Costing psychiatric interventions. In Measuring Mental Health Needs (eds G. Thornicroft, C. Brewin & J. K. Wing), pp. 163 183. London: Gaskell.
Beecham J. K. & Knapp, M. R. J. (2001) Costing psychiatric interventions. In Measuring Mental Health Needs (ed. G. Thornicroft) (2nd edn), pp. 200 224. London: Gaskell.
Birchwood, M., Smith, J., Macmillan, F., et al (1989) Predicting relapse in schizophrenia: the development and implementation of an early signs monitoring system using patients and families as observers: a preliminary investigation. Psychological Medicine, 19, 649 656.[Medline]
Davies, L. M. & Drummond, M. F. (1993) Assessment of costs and benefits of drug therapy for treatment-resistant schizophrenia in the United Kingdom. British Journal of Psychiatry, 162, 38 42.[Abstract]
Dunn, G., Mirandola, M., Amaddeo, F., et al
(2003) Describing, explaining or predicting mental health
care costs: a guide to regression models: methodological review.
British Journal of Psychiatry,
183, 398
404.
Guy, W. (1976) Clinical global impressions. In ECDEU Assessment Manual for Psychopharmacology, revised. Rockville, MD: National Institute of Mental Health.
Hamilton, S. H., Revicki, D. A., Edgell, E. T., et al (1999) Clinical and economic outcomes of olanzapine compared with haloperidol for schizophrenia: results from a randomised trial. Pharmacoeconomics, 15, 469 480.[Medline]
Herz, M. I., Lamberti, S., Mintx, J., et al
(2000) A programme for relapse prevention in schizophrenia: a
controlled study. Archives of General Psychiatry,
57, 277
283.
Kay, S. R., Fiszbein, A. & Opler, L. A. (1987) The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia Bulletin, 13, 261 276.[Medline]
Kemp, R., Hayward, P., Applewhaite, G., et al
(1996) Compliance therapy in psychotic patients: randomised
controlled trial. BMJ,
312, 345
349.
Kind, P. (1996) The EuroQoL instrument: an index of health-related quality of life. In Quality of Life and Pharmacoeconomics in Clinical Trials (ed. B. Spilker). Philadelphia: LippincottRaven.
Knapp, M. R. J., Simon, J., Almond, S., et al (2003) Costs of schizophrenia. In WPA Series in Evidence and Experience in Psychiatry: Schizophrenia (eds M. Maj & N. Sartorius), pp. 413460. New York: Wiley.
Knapp, M. R. J., Mangalore, R. & Simon, J. (2004) The global costs of schizophrenia. Schizophrenia Bulletin, in press.
Lader, M. (1995) What is relapse in schizophrenia? International Clinical Psychopharmacology, 9 (suppl. 5), 5 9.[Medline]
Lehman, A. F. (1996) Quality of life among persons with severe and persistent mental disorders. In Mental Health Outcome Measures (eds G. Thornicroft & M. Tansella), pp. 7592. London: Springer.
National Institute for Clinical Excellence (2002) Guidance on the Use of Newer (Atypical) Antipsychotic Drugs for the Treatment of Schizophrenia.Technical Appraisal Guidance No. 43. London: NICE.
Netten, A., Dennett, J. & Knight, J. (1999) Unit Costs of Health and Social Care 1999. Canterbury: PSSRU, University of Kent.
Robinson, D., Woerner, M. G., Ma, J., et al
(1999) Predictors of relapse following response from a first
episode of schizophrenia or schizoaffective disorder. Archives of
General Psychiatry, 56, 241
247.
Weiden, P J. & Olfson, M. (1995) Cost of relapse in schizophrenia. Schizophrenia Bulletin, 21, 419 429.[Medline]
Xiong, W., Phillips, M.R., Hu, X., et al (1994) Family-based intervention for schizophrenic patients in China: a randomised controlled trial. British Journal of Psychiatry, 165, 239 247.[Abstract]
Received for publication February 28, 2003. Revision received November 5, 2003. Accepted for publication December 2, 2003.
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