REVIEW ARTICLES |
Social Psychiatry, University Department of Psychiatry, Warneford Hospital, Headington, Oxford OX3 7JZ, UK. Email: Tom.burns{at}psych.ox.ac.uk
Declaration of interest T.B. has received payments for lectures and consultancies from Eli Lilly, Janssen and Otsuka in the past 5 years.
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Aims To understand inconsistency of results from studies using hospitalisation as an outcome measure.
Method The advantages and disadvantages of hospitalisation are explored, including the ways in which it is recorded. Regional variation in outcomes and the impact of control services are reviewed.
Results Hospitalisation has face validity as an outcome buttranslates poorly between differing healthcare contexts. These variations can be exploited positively to distinguish potentially effective ingredients in community care (outreach, combined health and social care, team structure) from redundant components.
Conclusions Hospitalisation is a good proxy outcome measure in schizophrenia care in randomised controlled trials, but the dangers of extrapolating to new contexts require care.
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Reporting of hospitalisation
Hospitalisation is generally reported in one of three forms in community
studies.
Number of admissions
This is the simplest approach and consists of recording any psychiatric
admission during the study period. The frequency of admissions is usually
recorded during the follow-up period and outcomes reported in terms of
admitted v. not admitted. This reporting has the advantage that it is
immediately obvious to the reader, who may know little of the local
circumstances or details about admission. If there are many patients with
repeated admissions during the follow-up period then the mean number of
admissions in the study categories may also be presented.
Time to admission
Time to readmission has been more used in relapse prevention studies than
in community care studies. The difference between the timings of relapse in
the experimental and control services are presented either as mean durations
or, more usually, with survival curves (e.g. Kaplan–Meier).
Duration of in-patient care
The most common presentation of hospitalisation as outcome is by days of
in-patient care within the agreed follow-up period. In schizophrenia trials
hospitalisation data are rarely normally distributed and usually have a
pronounced skew. The majority of patients usually have no admissions and a
small number of patients account for most of the in-patient days. Such data
are best presented as medians rather than means, but planners prefer means so
that they can calculate bed needs. It is increasingly common to assess
bed-days with parametric statistics, presenting means, after subjecting the
non-parametric results to bootstrapping techniques
(Efron & Tibshirani,
1993). An advantage of duration of care is that it permits the
pooling of hospitalisation data between studies with differing follow-up
periods, because the durations can be recalculated as, for example, days per
month or days per year.
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Utility
An understanding of changes in bed occupancy has direct utility for service
planning. Indeed, it has been the translation of this outcome into projections
of bed occupancy that has driven much of the research in this area and had an
impact on service developments. There has been concern that the utility of
research in this area has been exaggerated, either through naivety or in the
service of economic imperatives. Well-recognised factors that inflate the
effectiveness of newly established services
(Coid, 1994), such as
charismatic leaders, the recruitment of exceptional staff and the slow accrual
of complex and resistant patients, have been ignored, leading to
overoptimistic bed reductions.
Health economic analyses
Because hospitalisation is such a disproportionately expensive component of
mental health services – still responsible for 80% of costs in many
services (Leff et al,
2000) – careful recording of it is essential to any form of
cost analysis. Mental health economic analyses require careful reading and
careful interpretation. More than in any other branch of medicine the extent
of the costing exercise is open to real debate – how much should housing
and unemployment be included, how is informal care costed, etc.? Small,
apparently unconnected, changes in living conditions can completely reverse
the economic benefits of interventions
(McCrone et al,
1994). Where studies include hospitalisation as an outcome such
complications are unlikely, but conclusions about comparative costs within
services require attention to local conditions. The difference between the
costs of an in-patient day and an outpatient contact with a professional are
not fixed. For example, the difference between the cost of an in-patient day
and a case manager contact was much greater in Stein & Test's study
(Weisbrod et al,
1980) than in the UK700 study
(Byford et al, 2000).
Consequently how many case manager contacts would be paid for by a saved day
in hospital would be very different in the two studies.
Despite these caveats, hospitalisation data are an essential component of health economic analysis and can make a powerful case for expanding or contracting different components in an integrated service. Careful costing of hospitalisation was responsible for dispelling the early myth that deinstitutionalisation was inevitably cheaper than hospital care and helped to identify levels of disability at which hospital care was cheaper overall (Knapp et al, 1990; Hallam et al, 1994).
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There are also disadvantages from a service development and delivery perspective of an exclusive focus on reduced hospitalisation. Sustaining mental health services relies on recruiting and retaining committed, high-quality staff, and for this the day-to-day business of care must be centred on the individual well-being of the patient directly in front of the staff member. Maintaining focus and motivation for the staff member and engaging the patient require a clear therapeutic goal that can be shared and realised in that interaction (e.g. reducing distress, improving understanding of the illness or treatment, ensuring adherence to medication). Reducing bed occupancy is not one such shared goal. Reframing this as `promoting stability' or `improving community tenure' goes some way to presenting it as a desirable positive goal, but statistical probabilities are weak motivators in human behaviour. Clinical experience emphasises the need to identify the clinical practices and the interpersonal and patient-centred outcomes that lead to a goal of reduced hospitalisation (Wright et al, 2004) and enshrine these in operational policies (Burns & Firn, 2002).
Research distraction
Another criticism of hospitalisation as an outcome measure is that it can
distract from efforts to explore the mechanisms of schizophrenia care. This
criticism certainly does have salience in service development research
(Burns et al, 1999),
where preoccupation with organisation has led to a relative neglect of the
operative components (Wright et
al, 2004), but it is probably unwarranted in the area of
schizophrenia outcomes. Current research in schizophrenia care demonstrates
attention to a wide range of specified interventions, both pharmacological and
psychosocial, and a wide range of outcome measures.
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The Lambeth Early Onset study of early intervention in psychosis has reported a reliable method for estimating relapse from regular systematised assessments of case notes (Bebbington et al, 2006). The assessed relapses were strongly correlated with independently assessed PANSS scores. Whether such an approach will erode the status of hospitalisation as an outcome measure is as yet unclear. A series of studies using such instruments might provide a guide to the relationship between relapse rates and hospitalisation rates in schizophrenia that can then be used to scale up the inevitably conservative hospitalisation rates.
Crisis resolution/home treatment studies
Unlike research into case management or assertive outreach, studies of
crisis resolution/home treatment teams also use hospitalisation as a primary
outcome measure but without the assumption that a change reflects a change in
relapse rate. The clinical rationale of assertive outreach is that improved
continuity of care leads to better clinical management and reduced relapse
(Stein & Test, 1980) and
that reduced hospitalisation is a reflection of this
(Marshall & Lockwood,
1998). In studies of crisis resolution/home treatment teams,
however, the intervention comprises a different style of managing
relapses, not preventing them (Johnson
et al, 2005; Glover
et al, 2006; Killaspy
et al, 2006). Thus a reduction in hospitalisation is a
marker for more effective management of relapse (i.e. successful care in the
home) not a marker for reduced relapse. The relationship between
hospitalisation and relapse in these two different types of studies needs to
be recognised for their interpretation.
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Can hospitalisation rates be used in meta-analyses?
Meta-analyses of medical trials consolidate the outcomes from several small
trials into a single result for that outcome, treating all the data as if from
a single trial. The benefits of this approach, and the world-wide Cochrane
Collaboration that supports it, is that conclusions can be established earlier
(thereby introducing life-saving treatments and also avoiding unnecessary
subsequent trials) and with greater confidence. The delay in introducing
clot-busting drugs after myocardial infarction is often cited as the most
convincing case for meta-analysis (Antman
et al, 1992). The importance of meta-analyses has been
emphasised for mental health research because of the preponderance of small,
underpowered studies (Coid,
1994). Within the Cochrane Collaboration, difference in
hospitalisation rates has been the most influential outcome in meta-analyses
of community mental health services
(Marshall & Lockwood,
1998; Marshall et al,
2001) although others are reported (e.g. loss to follow-up care,
satisfaction with care, cost of care). Clinical and social functioning are
often too inconsistently collected for influential findings to be
presented.
The meta-analyses of hospitalisation for ACT teams (Marshall & Lockwood, 1998) and case management (Marshall et al, 2001) have been consistently cited to confirm that ACT reduces the need for hospitalisation compared with standard care. As a consequence, ACT has been mandated in many US and Australian states, Canadian provinces and increasingly across Europe. In the UK ACT teams are the basis for the reorganisation of mental health services required by the NHS Plan (Department of Health, 2000), with the establishment of over 170 teams. Close examination of the forest plots indicates that there is quite a lot of heterogeneity in the results. Some caution should therefore be exercised in applying meta-analytical techniques to hospitalisation outcomes and efforts should be made to understand the source of the heterogeneity.
Two potential sources of heterogeneity are immediately clear from a cursory examination of the forest plots. First, in the ACT meta-analysis the studies demonstrating major reductions are all from the USA, and the only non-American study included (Muijen et al, 1992) demonstrates minimal reduction. In the case management analysis three of the studies are from the UK. This difference might indicate an impact of differing healthcare systems on the results of these two meta-analyses. There is also a suggestion that later studies indicate less benefit for ACT, although the difference is not as pronounced as that for the geographical differences. The importance of these observations becomes clear with the failure of any recent, high-quality European studies of ACT to replicate the reduction in hospitalisation. Indeed several recent European studies have been sufficiently powered that their failure to demonstrate reduction in hospitalisation can be interpreted as confirmation that there is no reduction. Hospitalisation is therefore not a reliable outcome in meta-analyses. Variation in hospitalisation as an outcome, on the other hand, has proved to be most useful by leading analyses that produce better understanding in service evaluations.
Control services are not placebos
Examination of the differences between US and European (predominantly UK)
community care studies confirmed that the impression that US studies were more
successful in reducing hospitalisation is indeed the case
(Burns et al, 2002).
This holds despite evidence that the interventions were substantially similar
(Fiander et al,
2003). Home-based care in the US (the definition was widened to
ensure consistency and to avoid post hoc rationalisation in
labelling) did reduce in-patient care by a statistically significant mean of
about 10 days a year compared with standard care, whereas in European studies
it increased in-patient care by a non-significant average of 3 days a
year. However, the conclusion that US experimental services kept patients out
of hospital more is not supported. Mean days in hospital were essentially the
same for experimental service patients in the US and Europe (19 and 21 days
respectively); the differences stem from the differences in hospitalisation
for the control services (means of 28 and 17 days respectively).
This exploration of variation in hospitalisation data confirms our earlier call for community psychiatry studies to pay much greater attention to service characterisation and, in particular, characterisation of the control services (Burns & Priebe, 1996). Hospitalisation as an outcome measure certainly has some generalisability, but its limitations need to be considered when it is used as a basis for service planning.
Distinguishing effective ingredients
An important consequence of the heterogeneity of hospitalisation as an
outcome is that it has stimulated a search for the sources of that
heterogeneity and this has helped distinguish effective from more redundant
components in complex interventions. In the systematic review of home-based
care by Catty et al
(2002) we obtained data from
the 60 of the 90 researchers to characterise their experimental services at
the time of the investigations. The information was collected using 20
operationalised `components of care', which were subjected both to cluster
analysis to identify common characteristics of practice and to regression
against reduction in hospitalisation to identify whether any were more
strongly associated. Figure 1
shows the six regularly occurring components reported. The two found in a
regression analysis to be significantly associated with reduction in
hospitalisation are home visiting and joint health and social care. This is
only a post hoc analysis and the sample was quite restricted.
However, what it does do is indicate how hospitalisation as an outcome can be
used to explore community mental health services in greater depth.
![]() View larger version (15K): [in a new window] [as a PowerPoint slide] |
Fig. 1 Consistent care components of home-based care. From Wright et al
(2004). Reprinted with
permission.
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Reducing unnecessary hospitalisation has also, arguably, increased the overall efficiency of mental healthcare. The disproportionate cost of in-patient care per patient contact (which is, after all, where the treatment occurs) reflects the capital costs, hotel costs and 24-hour staffing. In-patient care has declined for most physical disorders as the population increasingly has clean, well-heated accommodation affording adequate privacy. These extra costs of hospital care are justified when they add to safety or ensure adherence. However, for many patients it is not necessary and there is no clear evidence that treatments are any more effective for being delivered in hospitals than in clinics or patients' homes. Indeed, the difficulty of `transfer of learning' from hospital to home is one of the underlying reasons for Stein & Test's emphasis on what they call `in vivo' care in assertive outreach (Stein & Test, 1980).
Reducing hospitalisation is also in line with most current thinking in bioethics, where the emphasis has been on the provision of mental healthcare in the `least restrictive' environment (Lin, 2003). Much of this ethical debate has centred around the care of legally detained patients. However, there is accumulating evidence of informal coercion in mental healthcare (Monahan et al, 2005), suggesting that the distinction between voluntary and involuntary may be better conceptualised as a gradient rather than a dichotomy (Bonnie & Monahan, 2005). Patient and ethical views about legally enforced admission may, in some measure, also apply to most admissions.
The utility and apparent simplicity of hospitalisation as an outcome measure should not, however, blind us to its limitations. It is a good proxy for relapse in schizophrenia in well-functioning and coordinated services. However, it is a social sciences outcome that is not independent of context and it needs to be interpreted that way. Its reputation has been somewhat tarnished by overextrapolation; there is a need for greater caution in its interpretation to ensure its reputation is rehabilitated.
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