The British Journal of Psychiatry (2000) 177: 493-498
© 2000 The Royal College of Psychiatrists
Needs assessment for mentally disordered offenders: measurement of ability to benefit and outcome*
ANDREA COHEN, MA and
NIGEL EASTMAN, FRCPsych
Department of Psychiatry, St George's Hospital Medical School, London,
UK
Correspondence: Andrea Cohen, Shaftesbury Clinic, Springfield Hospital, Glenburnie Road,
London SW17 7DJ, UK. Tel: 020 8682 0033
Declaration of interest None.
* This paper should be read in conjunction with Cohen & Eastman
(1997). Both summarise material
presented in Cohen & Eastman
(2000). 
1 Tansella & Thornicroft
(1998) also describe the
geographical dimension, which refers to different levels within
the health care system: country/region level, local level (i.e. catchment
area) and patient level. 

ABSTRACT
Background The Department of Health defines needs as "the
ability
to benefit from healthcare interventions". Outcome measurement
is an integral component of needs assessment because it underpins
ability to benefit.
Aims To propose a framework for addressing the measurement of
outcome in relation to mentally disordered offenders (MDOs).
Method Based on a literature search, the paper reviews the
definition and measurement of outcome in general mental health care and
specifically in relation to MDOs. It analyses the problems of conducting
outcome research in relation to MDOs.
Results A framework for outcome measurement in relation to MDOs is
presented. Outcome is placed within a broader framework that relates to
service evaluation.
Conclusions Current measurement of outcome in relation to MDOs is
inadequate. A comprehensive framework that acknowledges the multi-dimensional
nature of outcome is essential.
Researchers must be able to justify the dimensions they prioritise.

INTRODUCTION
The ability to benefit from health care interventions
is an
essential component of the Department of Health model
of need
(
National Health Service Management
Executive, 1991).
The model implies that need only exists if there
are interventions
with proven efficacy and effectiveness available to address
that need, and that needs for which there are no such interventions
should not
attract resources. This provides a crude justification
for rationing; only
those individuals who have health problems
that can benefit from interventions
should receive treatment.
This paper evaluates definitions of outcome and
approaches
to measuring outcome both generally in mental health care and
specifically in relation to mentally disordered offenders (MDOs).
It also
examines the relationship between types of outcome
measure and how outcome
fits into a broader framework of service
evaluation. Finally, it draws
together the strands of need,
outcome and service evaluation in an attempt to
create a coherent
framework.

DEFINITION AND MEASUREMENT OF OUTCOME
The concept of ability to benefit is inextricably
linked with
the measurement of outcome, because establishing
the ability to benefit
requires that health care interventions
are clearly defined and linked with
specific benefits or outcomes
for specific patient groups. It can be argued
that knowledge
about outcome is a prerequisite for establishing the ability
to
benefit, because selection of the right patients for the
right interventions
cannot occur without evidence about likely
outcome. Both outcome and ability
to benefit are also highly
politicised, because they relate closely not only
to evidence-based
practice but also to clinical governance. Yet, the
definition
and measurement of ability to benefit and outcome
have long presented theoretical and empirical difficulties in
all health and
related services research, particularly in relation
to mental health.
Ovretveit (1995) defines
health service outcomes as the effect on a person or population that can be
attributed to a health treatment, service or intervention. However,
establishing outcome in relation to mental health interventions, even in
general mental health, is poorly developed. Psychiatric disorders and their
associated social disabilities are complex and multi-factorial in their
aetiology and manifestation (Wing et
al, 1992). Baseline information is limited or non-existent,
and outcomes are multi-dimensional and difficult both to define and measure.
There are also difficulties in defining operationally many of the treatments
and interventions available. Different treatments may be delivered to the same
patient by different professionals, and multi-agency involvement adds further
complexity. Consequently, demonstrating valid and reliable causal
relationships between specific interventions and outcomes is problematic.
Ovretveit (1995) notes that
outcome measurement frequently focuses on end-points rather than health gains
made during the treatment process, and is critical of the tendency for outcome
measurements to fail adequately to include the effects of other services and
environments, or other factors that affect health. He also bemoans the
tendency of outcome studies to overlook patient views and the quality of
service delivery. However, he notes how costly and methodologically difficult
it is routinely to measure outcome effectively, and that commissioners who
require providers to measure outcome will pay in higher prices.

PRINCIPLES OF OUTCOME MEASUREMENT
Atkisson
et al
(
1992) suggest that outcome
research should
adhere to the following seven principles:
- Outcome measurement should be multi-dimensional and should cover
clinical, rehabilitation, humanitarian and public safety domains. The clinical
domain relates to various aspects of psychopathology and the course of illness
over time, and the rehabilitation domain focuses on adaptation and functional
capacity. The humanitarian domain is concerned with subjective well-being,
consumer satisfaction and quality of life, and the public safety domain is
concerned with setting a balance between liberty and paternalism that will
maximise individual and societal rights to physical safety and well-being. The
clinical, rehabilitation and humanitarian domains are reflected in
well-established research industries in general mental health,
but there is a dearth of empirical evidence regarding each of these domains
specifically in relation to MDOs. Indeed, Robertson
(1997) bemoans the lack of
attention paid to mental health outcome measures in forensic
psychiatric research. The majority of outcome research in relation to MDOs has
focused on the public safety domain. For example, many studies have focused on
recidivism (mainly re-arrest and reconviction rates), especially within the
special hospital population (e.g. Bailey
& MacCulloch, 1992;
Buchanan, 1998), and on the
validity and reliability of risk assessment (cf.
Blumenthal & Lavender,
2000). Although this domain is obviously crucial in relation to
MDOs, future research should endeavour to include other domains.
- Outcome should be measured from multiple perspectives (e.g.
patient, carers, clinicians). Much of the outcome research adopts a clinical
perspective of what constitutes a positive outcome and neglects the views of
other stakeholders.
- Outcome measurement should take into account the fact that different
individuals and groups may perceive the usefulness (or utility) of mental
health outcomes differently. These individual utility
differences are a source of variability that should be measured
and accounted for in outcome studies.
- Cross-sectional and longitudinal studies should be
conducted. Longitudinal studies are especially important in mental health,
given the chronic nature of many mental disorders.
- Standardisation of research design and measurement should be
worked towards, in order to facilitate comparison between studies. However, a
balance must be established between standardisation and specificity.
- Costs should be incorporated into outcome measurement, including
costs to the patient, family and society of the absence (or refusal) of
services.
- Relevance and impact of outcome research should be considered in
relation to clinical practice, policy, legislation and science.
These principles provide a comprehensive framework for outcome measurement.
Although it is self-evident that most researchers will be unable to measure
all of these areas or adhere strictly to all the principles advocated, the
framework is still useful. It forces us to adopt a broad perspective about
outcome measurement and to recognise the limitations on what is achievable. It
also forces us to acknowledge that we may sometimes be prioritising only one
dimension of outcome (and a small one at that), neglecting other domains in
its favour. Public policy, values and resources will partly drive what aspect
of outcome is prioritised and measured, as well as the methods used
to achieve this. Hence, there must be explicit acknowledgement of what is
not being measured and why we should be able to justify, for
example, why it is more important to measure recidivism as an outcome rather
than symptom reduction or quality of life.

PROBLEMS WITH MEASURING OUTCOME IN RELATION TO MDOs
The measurement of outcome for MDOs presents some specific problems.
The
term MDO is itself difficult to define, and MDOs form a
heterogeneous group
that may fall into any diagnostic category
(
Cohen & Eastman, 1997).
They are likely, therefore, to
have many needs for treatment and care that are
similar to
general psychiatric patients. However, they may have additional
needs that relate to their offending behaviour. Consequently,
measuring
ability to benefit and outcome in relation
to MDOs must cover a
wide range of interventions for a wide
variety of problems, including problems
going beyond health
outcome narrowly defined. It is not possible, therefore,
to
provide a single model of what works for MDOs.
The additional
component of offending that is specifically
relevant to MDOs adds at least two
further complicating dimensions
to the measurement of outcome. First,
offending can arise from
factors unrelated, or only partially related, to an
individual's
mental disorder. That is, offending is not necessarily causally
related to mental disorder and a wide range of ordinary criminological
explanations of offending, both individual to the offender and
more broadly
societal, may be relevant to an MDO's offending
behaviour. This introduces not
merely one or two additional
factors to a clinical model but superimposes upon
it a criminological
model that is largely unrelated to mental health services
narrowly
defined. Second, ability to benefit relates, in
the
specific social policy context being considered, not only
to the patient's
ability to benefit but also to the benefits
to society of detaining, and
hopefully successfully treating,
individuals who pose a threat to public
safety. Indeed, the
government's proposals for the preventive detention of
dangerous
individuals with a severe personality
disorder
(
Home Office/Department of
Health, 1999) particularly emphasises
the point. Given the
profound uncertainty about the ability
of mental health professionals reliably
and validly to identify
such a policy-defined group, or to be able to offer
any interventions
that are beneficial to the individual, the distinction
between
ethically valid public health psychiatry and mere
crime
prevention looks fragile (
Eastman,
1999).

OUTCOME, QUALITY AND SERVICE EVALUATION
The measurement of outcome must be placed within a broader framework
that
relates to service quality. According to Glover &
Kamis-Gould
(
1996), outcome is just one
type of performance
indicator that fits into a more general model of service
evaluation.
Jenkins (
1990)
argues that, in order to evaluate any health
care system, it is necessary, in
general terms, first to measure
the baseline health of the population and then
to measure the
impact of health care upon that baseline. She suggests that
this can be achieved in a valid and reproducible manner only
if specific
health indicators are established that apply not
only to general
well-being but also to specific
categories of illness, and if
these categories are then related
to specific strategies of treatment and
prevention. Jenkins
defines an indicator as "a measure that summarises
information
relevant to a particular phenomenon or a reasonable proxy for
such
a measure" (
Jenkins,
1990, p. 501). She accepts that
indicators should be valid and
reliable, but argues that this
is difficult to achieve. Health
indicators are
variables that can be measured directly and that reflect
aspects
of the state of health of a community, and health
care
indicators are variables that reflect aspects of the
state of health
care in a community (World Health Organization,
1981, cited in
Jenkins, 1990). According to
Jenkins, health
care indicators can be categorised into input,
process and outcome (albeit, outcome
indicators
will also be health indicators). Tansella &
Thornicroft
(
1998) refer to this approach
as the temporal
dimension, because it is concerned with the
chronological
steps involved in the delivery of health
care.
1
Input
refers to resources that are put into the mental health
care
system (
Tansella & Thornicroft,
1998). Input variables
include type and size of facilities, human
resources and characteristics
of physical facilities
(
Brugha & Lindsay, 1996).
Process
refers to activities that take place to deliver mental
health
services (
Tansella &
Thornicroft, 1998). Process
variables include the
technical or interpersonal elements that
occur during a health care
intervention, including diagnostic
and therapeutic procedures and features of
the clinicianpatient
relationship
(
Brugha & Lindsay,
1996).
A similar conceptualisation is offered by Donabedian
(1980). He divides research
about the quality of health care into studies that address structures (e.g.
provider systems, organisation of systems, characteristics of treating
facilities), process (specific clinical interventions) and outcome.
Berwick (1989) outlines four
types of health services research that relate to quality of care:
- effectiveness of care (what works for whom);
- appropriateness of care (using what works);
- execution of care (doing well what works);
- examination of the purpose of care (values that underlie action).
According to Atkisson et al
(1992), progress with the
paradigms presented by Donabedian
(1980) and Berwick
(1989) is required in order to
advance research about quality of care.
Glover & Kamis-Gould
(1996) propose a model of
service evaluation that covers two broad aspects of an organisation/system.
The first relates to the capacity of the system. Capacity variables include
human and financial resources, the range and quality of clinical facilities
and the technical capacity to operate, coordinate and monitor all aspects of
organisational functioning. The second relates to the performance of the
system. This is concerned with responsiveness and accessibility (e.g.
congruence with local needs, cultural sensitivity, promptness and sensitivity
of response to clients). Performance is also measured in terms of efficient
use of resources (i.e. levels of productivity, cost containment, occupancy
rates) and effectiveness.
According to Jenkins
(1990), aspects of service
provision that can be most easily measured at present tend to be those that
relate to service input and resources rather than to service outcome. She
notes that input is relatively straightforward to measure, and that process
tends to be measured in terms of performance or
activity indicators (e.g. occupied bed-days). Process indicators
related to delivery of specific interventions or the nature of therapeutic
relationships are more difficult to measure and are unlikely to be available
routinely. Jenkins also points out that process indicators are frequently
selected on the basis of what is collectable (or already available), rather
than being derived from previously specified key aspects of performance.
Indeed, although there may be good ad hoc studies relevant to some
desirable process measures, there is, in fact, a profound lack of ongoing data
that could be of use in the monitoring process and, in particular, in
monitoring the meeting of mental health needs. Jenkins notes that the
measurement of outcomes is more complex than the measurement of input and
process. She points out that input and process indicators are often used as
proxy measures of outcome, which she suggests is based on faulty logic
that is, that service utilisation (process indicator) is equal to
improvement (outcome). So, just as service utilisation is a poor
proxy for need (Cohen & Eastman,
1997), so too is it a poor proxy for outcome.

INPUT, PROCESS AND OUTCOME INDICATORS IN FORENSIC MENTAL HEALTH
Jenkins (
1990) provides a
system of input, process and outcome
indicators related specifically to
forensic psychiatry. Her
approach requires that reference be made to
ordinary
mental health outcome measures in relation to MDOs with
mental
illness and learning disabilities. She presents special
indicators only in relation to personality disorder, although
her rationale
for this is unclear.
As a policy starting point, Jenkins offers a series of health objectives
specific to MDOs. These are essentially policy objectives and are clearly
influenced by Health of the Nation
(Department of Health, 1992) targets. Examples include:
- reducing the incidence of MDOs;
- reducing the incidence of personality disorder;
- reducing suicide rates;
- preventing entry and re-entry into the criminal justice system;
- reducing homelessness.
She goes on to suggest a range of input, process and outcome indicators
that relate to her proposed objectives. Input indicators include:
- systems to provide psychiatric services for assessment and advice to
agencies of the criminal justice system (e.g. courts) and to provide early
diversion from the criminal justice system;
- systems to provide psychiatric services to prisons and to aid the transfer
of MDOs from prison to hospital;
- access to housing.
She then argues that process indicators should be established that reflect
activity on all the above input indicators.
Finally, Jenkins identifies a number of outcome indicators:
- numbers of patients detained under Part III of the Mental Health Act 1983,
and their admission and readmission rates;
- prevalence of treatable MDOs in the prison population;
- numbers of patients diverted from the criminal justice system;
- suicide rates in prison;
- standardised mortality ratios.
Jenkins' lists of objectives and indicators may no longer accurately
reflect policy priorities of the current government, and it is important to
note their historical limitations. They were formulated when diversion from
the criminal justice system was particularly high on the political agenda and
before the publication of the Reed Committee Report
(Department of Health/Home Office,
1992). Although the Reed Report itself then reinforced the need
for diversion from the criminal justice system, it also suggested an
additional range of objectives and indicators, such as systems to identify and
treat patients who no longer require particular levels of security. Similarly,
the recent Ashworth Inquiry (Fallon et
al, 1999), and the wealth of national and local inquiries
following homicide by people with mental illness, have subsequently suggested
a wide range of other potential objectives and indicators (e.g.
Sheppard, 1996;
National Confidential Inquiry into Suicide
and Homicide by People with Mental Illness, 1999). Hence, a
current set of input, process and outcome indicators might now be drawn
significantly differently. It is important to recognise, therefore, that
appropriate objectives and indicators will change over time, according to
altered policy considerations, as well as in response to changes in service
structure and advances in the ability to measure need and outcome.
There are, in any event, a number of criticisms that can be levelled at
Jenkins' earlier choice of objectives and indicators. One of their
disadvantages is that they reflect a public health stance that tends to
neglect outcome at the individual level. Jenkins' system also includes some
objectives that are difficult to conceptualise as being legitimate objectives
of psychiatric services and are dependent upon many factors that are arguably
beyond the remit of MDO health or even social service interventions (e.g. to
reduce homelessness). Further, the majority of indicators suggested have no
adequate baselines specific to MDOs and are not routinely measured at a local,
regional or national level, and it is difficult to envisage how many of them
could be measured reliably and validly in the future, particularly at a level
that would be useful to commissioners and service providers. It is also
noteworthy that many of Jenkins' suggested outcome indicators fall well short
of being direct measures of outcome. For example, both the number of patients
detained under Part III of the Mental Health Act and readmission rates
represent indirect or proxy measures of outcome, with an assumption that, in
relation to the achievement of goals relating to each, good will
follow (e.g. that service utilisation equates with a positive outcome).
Indeed, of Jenkins' outcome indicators, only the suicide rate in prison and
standardised mortality ratios can be seen as direct outcome variables,
although these indicators are not currently statistically available
specifically in relation to MDOs, and the extent to which they directly
reflect mental health outcome is also debatable.
The criticisms levelled at Jenkins' system, which at face value appear
entirely reasonable, illustrate just how much of a challenge it is to attempt
to formulate any system. It is very difficult to select objectives and
indicators that are both reasonable and realistic (e.g. measurable in relation
to baselines, input, process and outcome) and that take into account broader
policy objectives, as well as clinical and system realities.

CONCEPTUAL FRAMEWORK FOR EVALUATING FORENSIC MENTAL HEALTH
SERVICES
Table 1 provides a
conceptual framework for the measurement
of input, process and outcome for
MDOs that integrates the
different models presented thus far. This framework
uses Tansella
& Thornicroft's
(
1998) temporal
dimension
of input, process and outcome as the foundation of the model.
It integrates the conceptualisations of Atkisson
et al
(
1992),
Donabedian
(
1980), Berwick
(
1989) and Glover &
Kamis-Gould
(
1996) into the
relevant temporal dimensions, while providing
examples of the types of
variables that may be measured within
each dimension. It then superimposes
factors that can be measured
at each of the temporal dimensions (e.g. values,
costs). The
model acknowledges that variables within each temporal dimension
can be measured at different geographical levels
(
Tansella & Thornicroft,
1998)
and at different levels of the mental
health care system
(
Beecham & Chisholm, 1995).
The essential
value of this framework is that it forces us to acknowledge
the
inherent complexity of what we are attempting to measure.
It also helps us to
recognise the interrelatedness of the concepts
that we are measuring and makes
us acknowledge, and justify,
what we are unable, or choose not, to measure.
Within the framework,
prioritisation will be determined by both national and
local
policy, by locally assessed need and by what is practically
achievable.
Of course, it should be possible to justify why
a particular element has been
prioritised.
View this table:
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Table 1 A comprehensive conceptual framework for the measurement of outcome,
quality and service evaluation for mentally disordered
offenders1
|
The conceptual model of outcome measurement and service evaluation
presented in Table 1 poses
considerable challenges in both methodological and practical terms. It is
therefore unlikely that we shall see anything that approaches the degree of
comprehensiveness suggested by the model in the near future, although this
should be the gold standard towards which to strive. The existing mechanisms
and measures available both for estimating outcome and for evaluating services
in relation to MDOs verge on being hopelessly inadequate. At the root of this
problem is a lack of knowledge about how particular clinical interventions and
services influence outcome. Indeed, there are not even any generally agreed
upon service designs and protocols that might be measured in their effects.
This inhibits not only the determination of appropriate outcome measures but
also the definition of need itself. How can we define
need if there is little agreement over the details of effective
service response to need? Until we are able adequately to answer questions
about input, process and outcome, we shall not be able properly to answer
questions about ability to benefit and, hence, about need.

Clinical Implications and Limitations
CLINICAL IMPLICATIONS
- Estimating mental health need requires reliable and valid information
about the efficacy, effectiveness and efficiency of mental health care
interventions.
- The question of what works for mentally disordered offenders (MDOs) must
be addressed so that national clinical and service protocols can be
developed.
- A multi-perspective model should be applied to MDO outcome in order to
emphasise the complexity and interrelatedness of relevant concepts, and to
expose underlying policy determinants of particular measures chosen.
LIMITATIONS
- Given the inadequacy of available data relevant to outcome, the model is
currently of mainly theoretical and interpretative use.
- The model presented specifically for MDOs relies on synthesising a
variety of approaches adopted by previous researchers, rather than proposing
new approaches per se.
- The model may suggest a gold standard for addressing outcome that is
practically unapproachable within the constraints of likely National Health
Service resources directed at rational service commissioning.

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