investigating relationships between health need, primary care and social care using routine...
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Health & Place 10 (2004) 129–140
Investigating relationships between health need, primary careand social care using routine statistics
David Reeves*, Deborah Baker
National Primary Care Research and Development Centre, University of Manchester, 5th Floor, Williamson Building, Oxford Road,
Manchester, M13 9PL, UK
Abstract
Closer integration of primary and social care is central to the agenda of Primary Care Groups and Trusts (PCG/Ts)
in England. Relationships between the need for care and primary and social care provision at local levels are
investigated using routinely available statistics. Primary care provision is negatively associated with need resulting from
material deprivation, but positively associated with older age-related need. Conversely, provision of social care is
positively related to need resulting from deprivation but is unrelated to the size of local elderly populations. The ‘inverse
care law’ does not capture the complexity of the relationships between need and provision. A lack of boundary
coterminosity represents a serious impediment to the goal of establishing integrated health and social care systems for
local populations.
r 2003 Elsevier Ltd. All rights reserved.
Keywords: Primary care trust; Health and social care; Population need; Deprivation; Elderly; Inverse care law
Introduction
The introduction of Primary Care Groups (PCGs) in
England in April 1999 marked a significant shift towards
a more integrated form of planning and provision of
primary care. A PCG is a general practitioner and nurse
led organisation responsible for planning and delivering
services to a local population of registered patients. A
central aim of the new organisations is to achieve better
co-ordination of care through closer collaboration
between health and social services (DoH, 1998, 1999a).
PCGs can operate at different levels of responsibility to
their populations, at the higher levels establishing
themselves as Primary Care Trusts (PCTs) or—starting
with pilot schemes in 2002—Care Trusts (CTs). CTs
take the integration of health and social care to another
level by taking on responsibility for providing a fully
integrated service to selected client groups (DoH,
2002a).
The agenda to improve co-ordination between pri-
mary care and social care systems raises questions about
the relationships between each form of provision and
local population needs. In addition, the primary care
and social care systems could hardly be more contrast-
ing. GPs are essentially self-employed, and the pattern of
practice distribution has developed largely independent
of central government control. One consequence of this
may be the ‘inverse care law’, which holds that the
provision of primary care is inversely related to a local
population’s need for care. A number of studies have
provided supporting evidence for this phenomenon (e.g.
Benzeval and Judge, 1996; Birch and Maynard, 1986;
Gillam, 1992; Gravelle and Sutton, 2001; Waller et al.,
1990). For example, Gillam (1992) found that materially
deprived areas with a greater need for care tended to
have less provision in the way of health promotion
clinics; and on the basis of a number of need-adjusted
measures, Gravelle and Sutton (2001) found substantial
inequality in the distribution of GPs, practice nurses,
other practice staff, General Medical Service (GMS)
expenditure and pharmacies. Furthermore, levels of GP
inequality changed little over the period 1974–1995.
ARTICLE IN PRESS
*Corresponding author. Tel.: +44-161-275-3536; fax: +44-
161-275-7600.
E-mail address: [email protected] (D. Reeves).
1353-8292/03/$ - see front matter r 2003 Elsevier Ltd. All rights reserved.
doi:10.1016/S1353-8292(03)00053-4
Baker and Hann (2001) however, show that in more
recent years the ‘inverse care law’ with respect to
primary care based services for asthma, diabetes, child
health surveillance and minor surgery has been largely
confined to PCGs within the London area.
In contrast to primary care, social service provision is
a local authority function, though funded by central
government via an annual budget to each authority
known as the Personal Social Services Standard Spend-
ing Assessment (PSS SSA). The PSS SSA is calculated
in four parts (children’s services; residential elderly
services; domiciliary elderly services; and ‘other’ ser-
vices), summed to yield the total assessment. Each
component is calculated according to estimates of the
size and unit cost for each client group, and these in turn
are based on regression analysis of demographic and
economic indicators associated with being in receipt of
services. Some of the indicators used are: for children,
the proportion in lone-parent households and the
proportion in rented accommodation; and for the
elderly, the proportion over 75 and over 85 years, and
the proportions living alone, in rented accommodation,
on income support, and with long-standing illness
(DTLR, 1998). The fact that the PSS SSA formula is
based upon factors that predict those in receipt of
services means that inequities in provision may become
‘locked-in’ as a consequence. The PSS SSA determines
how budgets are allocated, but not precisely how they
are spent.
If Primary Care Groups and Trusts (PCG/Ts) are to
be successful in planning and commissioning for co-
ordinated health and social care, they will require good
quality information about the needs of the populations
they are responsible for, and also about existing levels
and patterns of provision to meet those needs. To meet
this challenge, a few organisations have developed local
joint health and social care information systems (e.g.
Godden and Pollock, 1998; Naish et al., 1998).
However, not every PCG/T is likely to possess the
resources to develop a local system, and a proliferation
of local systems is likely to result in a lack of
standardisation on data items and data definitions,
making inter-PCG/Ts comparisons difficult.
National standard data sets are clearly desirable, and
not just for PCG/TS themselves but also for research
and central government purposes. Many sources of
routinely collected statistics exist related to population
characteristics, need and provision. The organisational
units for which such data are available, however, varies
depending upon the source. Census information is
available for small areas, and can readily be combined
up to other levels, such as the PCG/T. Similarly, GMS
statistics provide details about individual GP practices
and can likewise be combined up. Routine data on social
services provision, on the other hand, is only available
for relatively large geographical units known as Social
Services Authorities (SSAs). Another organisational
geography for which many valuable health-related
statistics have been routinely reported over many years
is the Health Authority (HA). Clearly, the utility of such
sources from the point of view of combining health care
and social care information, either for research, govern-
mental or individual PCG/T purposes, depends upon the
extent to which populations of PCG/Ts, SSAs and HAs
are one and the same.
Coterminous population boundaries are important
for joint working, as well as data needs. The White
Paper ‘The New NHS: Modern, Dependable’ recognised
this and stated that when being formed, PCG/Ts should
try to take account of both social services and HA
boundaries (DoH, 1998, Section 5.15). It is, in fact,
general government policy to move towards cotermin-
osity of administrative areas (DoH, 1999a) with, in the
case of PCTs and CTs, an emphasis on coterminosity
with SSAs which ‘may prove to be particularly helpful in
enabling pooling of budgets, with the service delivery
benefits which that will bring’ (DoH, 1999a, p. 22).
In view of the growing recognition of the need to
integrate health and social care, both at organisational
and informational level, this study was undertaken with
a two-fold purpose. The first was to explore the
relationships between primary and social care provision
and the population need for care; the second was to
clarify the position regarding coterminosity between
health and social care organisational geographies.
Methodology
For the purposes of the study, we felt it important
that all measures pertain to the same calendar year.
Accordingly, the year 2000 was adopted, this being the
latest year for which the full range of relevant annually
updated data sources were available. Thus the study is
based on PCG/Ts as they stood in 2000, and year 2000
health and social service indicator data.
Relationships between social care, health care, and
population need
Indices of population need
In previous work we have shown that single, ‘global’
measures of health need, such as the Jarman index,
combine dimensions of health need which may not only
be quite different in character, but may even be
negatively correlated with one another on a geographi-
cal basis (Hann et al., 2002). For this study, we therefore
adopted a set of needs indices developed previously
(Hann et al., 2002) which seek to characterise three
distinct dimensions of the population need for health
ARTICLE IN PRESSD. Reeves, D. Baker / Health & Place 10 (2004) 129–140130
care. The ‘material deprivation’ score was derived from
an analysis of housing type. The pattern of residential
housing (owner-occupied, provided by employer, furn-
ished private rented, unfurnished private rented, local
authority/housing association rented) in each area was
derived from 1991 census data and subjected to a
correspondence analysis. The score generated for each
area reflects the relative proportions of each housing
type present, with high scores indicating greater
proportions of rented property, and by implication
greater material deprivation (Hann et al., 2002).
The age–sex indicator was derived by combining
national rates of GP consultation for men and women
(separately) in the age groups 0–4, 5–15, 16–44, 45–64,
65–74, and 75 plus years, with the age–sex distribution
of registered patients in each area. The resulting score
represents the expected demand for GP consultations
(per patient) in each area if national rates applied.
National consultation rates are highest amongst the
youngest and older age groups, and higher for women;
hence this measure is sensitive to need related to the age
and sex profile of each area. However, the main
determining factor of the score is the older age groups.
For convenience, age–sex and material deprivation
scores are expressed with a mean of 100 and standard
deviation of 10; where higher scores represent greater
need.
The ‘ethnic mix’ index represents the percentage of the
population in each area from an ethnic minority (taken
from the 1991 census). Ethnic minorities often demon-
strate different patterns of disease to the predominant
white population, and also differ with respect to
utilisation (e.g. Baker et al., 2002; Coopere et al., 1999;
Smaje and Le Grand, 1997; McCormick et al., 1996;
Gillam et al., 1989). In this study, the use of ethnic
minority membership as a needs indicator does not
necessarily imply that ethnic minority populations
possess a greater degree of health need—that may or
may not be true—rather, it is used as a marker that
types, but possibly also degrees, of health need differ in
these populations.
Indices of primary care provision
Primary care provision has been indexed by a number
of variables. These have been derived mainly from the
GMS data set for the year 2000, drawn from the data
holdings on the National Database for PCG/Ts website
(/http://www.primary-care-db.org.uk/S; Hann et al.,
2001). The number of GPs per 1000 population is taken
as a measure of general practitioner capacity in each
area. Other indicators are generally recognised as related
to service quality and range: the percentage of practices
that are group practices (‘group practice’ refers to a
practice with more than one GP); the percentage of
practices with a trainer GP; and the percentage of GPs
that are female. In addition, a ‘service score’ index has
been derived. The ‘service score’ refers to the average
number of services out of asthma, diabetes, minor
surgery and child health prevention available at each
practice. This is derived by calculating a score for each
practice, ranging from zero (none of these services) to
four (all of these services), and then computing the
average across all practices in the area.
Indices of social service provision
The indices of social care provision have been drawn
from routine figures reported in the Key Indicators
Graphical System (DoH, 2001a). This paper focuses on
‘global’ provision (i.e. to all client and age groups), and
provision for the elderly. Most routine social service
indicators are specific to a client group or form of service
(e.g. residential care), and so reliable ‘global’ indicators
are in short supply. The only global measure reasonably
comparable across SSAs was gross social services
expenditure per capita. This includes all staff and non-
staff expenditure on assessment and commissioning for
adults and children, residential accommodation and
non-residential services (including the private sector). A
certain amount of expenditure is reclaimed via fees and
charges, but it has not proved possible to adjust for this.
Expenditure may vary between areas depending upon
service costs as well as levels of provision. However,
correlations between gross expenditure and unit costs of
important service elements were all small (e.g. �0.14
with the hourly cost of home help/care; �0.15 with the
weekly cost of residential care; �0.16 with the weekly
cost of childrens’ homes and foster care), indicating that
costs are not a main determinant of per capita
expenditure.
The elderly have been identified as a client group for
whom the CT model of service delivery is particularly
appropriate (DoH, 2002a). Co-ordinated working be-
tween health and social care providers is especially
important in the case of elderly people (Naish et al.,
1998), and they constitute the largest proportion of the
work of social service departments, accounting for 57%
of the entire national PSS SSA for 2000-01 (DoH,
2000a). Four indicators have been selected that relate to
provision for the elderly. The first is gross SSA
expenditure on elderly people per capita 75 years or
over. The second is people supported in residential/
nursing care per 1000 65 or over (this includes staffed,
voluntary and private homes). The two remaining
indicators are concerned with home help/care: number
of home help/care contact hours (public, private and
voluntary sectors combined) per 1000 population 65
plus; and households receiving intense home care per
1000 population aged 65 plus (intense home care is
defined as a least six visits a week with a total contact
hours of 10 or more).
ARTICLE IN PRESSD. Reeves, D. Baker / Health & Place 10 (2004) 129–140 131
Health and social ‘interface’ indicators
As part of the Performance Assessment Framework,
the Department of Health has designated three indica-
tors of successful interfacing between the health and
social care systems. This study has included the two of
these ‘interface’ indicators that relate to the elderly
population: emergency admissions of people aged 75
and over to hospitals per 1000 population aged 75 and
over; and delayed discharge from hospital of people
aged 75 and over per 1000 people aged 75 and over not
in hospital.
The emergency admission rate is used as an indicator
of how well health and social service agencies are
working together, on the grounds that the measure is
influenced by the effectiveness of preventative strategies,
intermediate care, community care arrangements and
hospital discharge arrangements for older people, all of
which must be jointly agreed between health and social
services (DoH, 2001b, p. 30). The rationale for adopting
delayed discharge from hospital as an interface indicator
is that this can be a result of poor communication or co-
ordination between the relevant care organisations
(DoH, 2001b, p. 100).
This paper examines the relationships between the
interface indicators and the measures of population need,
primary care provision and social care provision. The
interface indicators are only published at HA level, and
therefore the analysis can only be undertaken at this level.
Coterminosity of organisational geographies
Coterminosity between health and social care organi-
sational geographies was examined using the National
Health Service Postcode Directory (NHSPD). The year
2000 NHSPD contains fields that link postcodes to local
authorities, HAs and PCG/Ts on the basis of geogra-
phical boundaries in December 1999. Other fields link
postcodes to local authority wards, and to the equivalent
ward at the time of the 1991 census. Coterminosity
between PCG/T and SSA populations was examined by
the creation of a look-up table. The table was based
upon identifying the extent to which current, residential,
postcodes were common across the two geographies.
For example, Plymouth SSA was fully coterminous in
terms of postcodes with Plymouth PCG, with a total of
5491 postcodes. In contrast, Enfield SSA encompassed
all of Edmonton PCG (with 1649 postcodes, covering
31% of the SSA), all of Enfield North PCG (1934, or
35% of the SSA), and all of Enfield Southgate PCG
(1866, or 34%).
For the purpose of analysing the health and social
care interface indicators, which were only available for
HAs, a similar look-up table was created to examine
coterminosity between SSAs and HAs.
The look-up tables were also used to transform
various data sources to the different geographies used
in this study. GMS statistics for 2000 (at the practice
level) were combined up to PCG, HA, and SSA areas on
the basis of the postcode area in which each practice
resides. Translation of the 1991 census data was
undertaken utilising ward-level census results, drawn
from the MIMAS system at the University of Manche-
ster /http://www.mimas.ac.uk/S.
Methods of analysis
The analysis presented here uses correlational and
regression methods to explore the relationships between
the indices of need, social care, and primary care
provision. Many of the measures being used exhibited
considerably skewed distributions. Therefore, all ana-
lyses were based upon ranks, in place of the data values
themselves. All analyses have been undertaken using
SPSS version 10.1. The use of statistical inference testing
with samples such as these, where there exists no wider
population about which inferences are being made, is
highly contentious. In addition, in studies such as this,
the primary interest is in the strength of any correlation
between variables, not simply whether that correlation
significantly exceeds zero. Accordingly, tests of statis-
tical significance are not presented, but for the purpose
of differentiating between stronger and weaker relation-
ships, a value of 0.4 or above is taken to represent a
correlation of ‘notable’ strength.
Missing values
For a small number of SSAs, data on social service
contact hours and delayed discharge rates was missing.
In these cases estimates were substituted based on the
values for the years on either side.
Results
Coterminosity between health and social service areas
As of 2000, GP practices in England were organised
into a total of 481 PCG/Ts, whilst provision of social
care was the remit of 150 SSAs. In terms of postcode
areas, just 22 PCGs were found to be exactly cotermi-
nous with a single SSA, while another four PCGs were
more than 90% coterminous (i.e. more than 90% of all
the postcodes within the PCG or SSA were common to
both). These results imply that, nationally, less than 6%
of all PCGs served (more or less) the same population as
an SSA.
ARTICLE IN PRESSD. Reeves, D. Baker / Health & Place 10 (2004) 129–140132
Out of a total of 99 HAs, 38 were fully coterminous
with a single SSA, and one other HA-SSA pair was more
than 90% coterminous.
Relationships between need, health care, and social care
In this section, we investigate relationships between
the measures of health need and social and primary
care provision. Relationships between need and social
care are examined for 148 SSAs (see below), and also for
the 26 PCG/Ts coterminous with an SSA by 90% or
more. Relationships between need and primary care are
examined for both these groups, and also for the full set
of 481 PCG/Ts. Use of the full set of PCG/Ts provides a
check on the representativeness of the results for the
smaller group of coterminous PCG/Ts. Repeating the
analysis for both SSAs and PCG/Ts allows the results to
be examined for consistency across different organisa-
tional geographies.
Two SSAs, Isles of Scilly and City of London, were
found to be outliers on a number of indices and were
therefore excluded. Both had very small populations—
2300 and 5000, respectively, when the next lowest was
over 30,000—and only a single GP practice. City of
London also had exceptionally high expenditure on
social care; nearly twice as high, per capita, as any other
SSA. Neither SSA was coterminous with a PCG/T or
HA.
Basic characteristics of the three samples are pre-
sented in Table 1. In comparison to all PCG/Ts, the
sample of coterminous PCG/Ts can be seen to have
rather larger populations and be over-representative of
ethnic minorities. The latter result is due to the inclusion
in this group of three London boroughs with particu-
larly high minority populations: Tower Hamlets, New-
ham and City & Hackney. Despite these differences,
however, the mean material deprivation and age–sex
scores (and their standard deviations) for the sample of
coterminous PCG/Ts are reasonably similar to the
values for the full set.
The sample of coterminous PCG/Ts possessed a good
degree of geographical spread, with at least two from
each of eight of the nine Government Office Regions
(North West 4; North East 2; Yorkshire and Humber 3;
East Midlands 0; West Midlands 2; South East 3; South
West 2; East of England 3; London 7).
Correlations between indices of need
Table 2 reveals that in the main the various indices of
health need correlated at moderate to high levels with
one another, for both organisational geographies. One
result of particular note is the pattern of high negative
correlations between age–sex scores and the other two
measures. This reflects the fact that elderly people are
more concentrated in areas with higher proportions of
owner-occupied property and smaller ethnic minority
populations. The health needs of ethnic minorities are
compounded by the tendency of such groups to be
materially disadvantaged, and this is shown in the table
in terms of associations with deprivation scores.
Need and primary care
The pattern of correlations between the indices of
need and those of primary care provision (Table 3) is
much the same for both SSAs and the full set of PCG/
Ts. Correlations for the sample of 26 coterminous PCG/
Ts are in many cases rather lower—most notably the
correlations between provision and material depriva-
tion. This suggests that the coterminous sample is a
somewhat atypical selection from the total group.
Nevertheless, despite being weaker, the correlations are
ARTICLE IN PRESS
Table 1
Means (and standard deviations) for characteristics of the samples
n Population
(in 1000s)
Material deprivation
score
Age–sex score Ethnic mix (% from
an ethnic minority)
Coterminous PCG/
Ts
26 172 (47) 102.6 (13.1) 96.5 (11.5) 9.1 (12.3)
All PCG/Ts 481 103 (39) 100.0 (10.0) 100.0 (10.0) 6.2 (10.1)
SSAs 148 336 (251) 100.0 (10.0) 100.0 (10.0) 7.5 (9.4)
Table 2
Spearman rank correlations between needs indicators
Material
deprivation
Age–sex Ethnic
mix
Material deprivation
Coterminous PCG/Ts (n ¼ 26) — �0.71 0.41
All PCG/Ts (n ¼ 481) — �0.58 0.38
SSAs (n ¼ 148) — �0.51 0.40
Age–sex
Coterminous PCG/Ts (n ¼ 26) — — �0.74All PCG/Ts (n ¼ 481) — — �0.64SSAs (n ¼ 148) — — �0.68
D. Reeves, D. Baker / Health & Place 10 (2004) 129–140 133
all in the same directions as for the total group and
demonstrate the same general pattern of relationships.
The results in Table 3 indicate that areas with a higher
material deprivation score tend to have fewer group
practices, and are less likely to have female or trainer
GPs; there is also a weak tendency for fewer services to
be on offer. Areas where there are large ethnic
populations exhibit a moderate to strong tendency
towards fewer group practices, and (to a moderate to
weak degree) fewer services on offer and fewer trainer
GPs. Conversely, areas with generally higher levels of
age–sex-related need (typically due to an older popula-
tion) demonstrate the opposite pattern: more group
practices and more female and trainer GPs, plus a wider
range of services on offer. Relationships between area
characteristics and GP numbers are for the most part
weak.
Need and social care
There exist moderate to strong correlations between
material deprivation scores and nearly all measures of
social care, for both coterminous PCG/Ts and SSAs
(Table 4). Good correlations with the two measures of
expenditure may be expected given that housing type (on
which the deprivation measure is based) forms part of
the personal social services funding formula. However,
the correlations with contact hours and intense home
support are as strong or nearly as strong, demonstrating
that the funding allocations are translated into direct
contact with clients.
The relationships between age–sex-related need and
provision are mostly moderate-to-strong and negative.
This is a reversal of what was found with respect to
material deprivation and the two results together
demonstrate how strongly social services provision is
determined by factors related to deprivation rather than
by age and sex. Some caution is required, however, as
the strong negative association between deprivation and
age–sex scores is a confounding factor. This issue is
explored more fully later in the paper.
Ethnic mix demonstrates a pattern of relationships
with social care provision very similar to the pattern for
material deprivation. This is not surprising given the
correlation between ethnic mix and deprivation.
All the needs indices tend to possess associations
with the measure of residential care that are weaker than
their associations with any of the other indicators of
social care provision. To some, possibly not inconsider-
ably, extent home care and residential care are
substitutable forms of care, hence it is conceivable that
the lower level of relationship between need and
residential care results from area differences in policy
on admissions versus home care and the availability of
residential places.
ARTICLE IN PRESS
Table 3
Rank correlations between needs indicators and primary care
provision
Material
deprivation
Age–sex Ethnic
mix
GPs per 1000 patients
Coterminous PCG/Ts �0.11 0.08 �0.08
All PCG/Ts �0.20 0.41 �0.34
SSAs �0.25 0.33 �0.36
% of practices that are group practices
Coterminous PCG/Ts �0.22 0.44 �0.62All PCG/Ts �0.38 0.44 �0.43SSAs �0.41 0.47 �0.55
% of practices with a female GP
Coterminous PCG/Ts �0.32 0.47 �0.19
All PCG/Ts �0.35 0.27 �0.20
SSAs �0.42 0.34 �0.31
% of practices with a trainer GP
Coterminous PCG/Ts �0.02 0.17 �0.19
All PCG/Ts �0.31 0.40 �0.35
SSAs �0.44 0.42 �0.41
Services score
Coterminous PCG/Ts �0.10 0.37 �0.45All PCG/Ts �0.30 0.35 �0.41SSAs �0.37 0.42 �0.48
Table 4
Rank correlations between need and social care provision
Material
deprivation
Age–sex Ethnic
mix
Gross expenditure per capita
Coterminous PCG/Ts 0.25 �0.29 0.40
SSAs 0.54 �0.50 0.52
Gross expenditure on elderly per capita 75 plus
Coterminous PCG/Ts 0.75 �0.83 0.76
SSAs 0.71 �0.67 0.52
Home help/care contact hours
Coterminous PCG/Ts 0.71 �0.81 0.62
SSAs 0.63 �0.54 0.48
Households receiving intense home help/care
Coterminous PCG/Ts 0.74 �0.74 0.48
SSAs 0.55 �0.51 0.43
Residential/nursing care
Coterminous PCG/Ts 0.43 �0.33 �0.04
SSAs 0.29 �0.08 �0.09
D. Reeves, D. Baker / Health & Place 10 (2004) 129–140134
The ‘London effect’
The analysis so far has been concerned with England
taken as a whole. However, Baker and Hann (2001)
reported differences between PCG/Ts in London and
other areas of England in terms of the level of services
provided in primary care and how this relates to practice
characteristics and population need arising from depri-
vation. Specifically, they argued that the ‘inverse care
law’ with respect to service level was, by late 1990s,
largely limited to London. For this study, we have
examined relationships between the needs indicators and
primary care separately for PCG/Ts within and outside
London (using the total group of PCG/Ts only—there
were too few coterminous PCG/Ts to divide this
sample); and the relationships between need and both
primary and social care for SSAs within and outside
London. The findings for both PCG/Ts and SSAs with
respect to primary care provision were the same in all
their essentials, and therefore only the SSA results are
presented here. Table 5 presents rank correlations
between the needs indices and primary and social care
provision for those social service areas within the
Greater London area (n ¼ 32) and for those outside
(n ¼ 116).
The results concur with Baker and Hann in finding a
considerably higher negative correlation between mate-
rial deprivation and the services score for London
(r ¼ �0:59) than elsewhere (r ¼ �0:28). However, on
several other primary care measures (group practices,
female GPs and trainer GPs) the ‘inverse care law’ is if
anything more in evidence away from London. Another
revealing finding from Table 5 is that all the indicators
of social care demonstrate much stronger associations
with deprivation in London than in the rest of the
country. Social care provision is also more strongly
associated with age–sex scores (negatively) and ethnic
mix (positively) in the capital.
Material deprivation and age–sex-related need
All the results presented so far have been based on
simple correlations between provision and the various
needs indicators. The considerable negative association
between material deprivation and age–sex scores however,
means that caution has to be exercised in the interpreta-
tion of these correlations. One consistent finding for
example, has been of strong negative relationships
between age–sex need and social service provision.
However, without further analysis this should not be
taken to imply that social services do not target this form
of need: for instance, amongst areas with similar levels of
deprivation it is quite conceivable that provision is
positively associated with age–sex-related need.
To explore this question, the data has been investi-
gated using partial correlation analysis. This method
yields estimates of correlations between provision and
age–sex scores, say, ‘as if’ all areas had equivalent levels
of deprivation. The results presented are for SSAs only;
the findings for PCG/Ts were quite similar. Also, we
present separate results for London and non-London
SSAs, as the simple correlations in Table 5 revealed
some differences between the two. For completeness,
partial correlations are given with respect to each of the
three sources of need in turn, controlling for the other
two sources (Table 6).
Material deprivation
The partial correlations between material deprivation
scores and primary and social care show the same
ARTICLE IN PRESS
Table 5
SSAs in London and outside; rank correlations between need, primary care and social care
Material deprivation Age–sex Ethnic mix
Outside
London
London
(n ¼ 32)
Outside
London
London
(n ¼ 32)
Outside
London
London
(n ¼ 32)
(n ¼ 116) (n ¼ 116) (n ¼ 116)
Primary care provision
GPs per 1000 patients �0.31 0.18 0.41 �0.25 �0.37 0.30
% of practices that are group practices �0.40 �0.24 0.42 0.15 �0.38 �0.16
% of practices with a female GP �0.40 �0.33 0.30 0.25 �0.22 �0.26
% of practices with a trainer GP �0.44 �0.26 0.40 0.23 �0.33 �0.17
Services score �0.28 �0.59 0.27 0.50 �0.24 �0.51
Social care provision
Gross expenditure per capita 0.44 0.91 �0.30 �0.79 0.22 0.58
Gross expenditure on elderly per capita 75 plus 0.64 0.90 �0.59 �0.76 0.34 0.56
Home help/care contact hours 0.55 0.86 �0.43 �0.64 0.26 0.45
Households receiving intense home help/care 0.48 0.65 �0.37 �0.58 0.20 0.48
Residential/nursing care 0.31 0.51 �0.15 �0.46 0.06 0.26
D. Reeves, D. Baker / Health & Place 10 (2004) 129–140 135
pattern of relationships as did the uncontrolled correla-
tions, in both London and outside, except that adjust-
ment for age–sex and ethnicity has reduced the size of
the correlations somewhat.
Age–sex
The partial correlations between age–sex and all
indicators of primary care provision are at a low
level—in most cases almost negligibly low. This result
contrasts somewhat with the uncontrolled correlations
(Table 5) which indicated a pattern of low-to-moderate
relationships between primary care provision and age–
sex-related need. The implication from the partial
correlation analysis is that the age and gender char-
acteristics of an area do not in themselves influence the
level or type of primary care available in that area.
Social care demonstrates mainly weak negative
relationships with age–sex, both within and outside
London. The fact that these correlations failed to
become positive after controlling for deprivation levels
and ethnicity is quite a significant finding. It implies that
distribution of social care provision takes no account of
the size of local elderly populations.
Ethnic mix
With just two exceptions, the partial correlations of
ethnic mix with indicators of primary and social care
were all low, mostly very low. The uncontrolled
correlations (Table 5) appeared to indicate that ethnic
mix had a negative relationship with primary care, and a
positive relationship with social care. These relation-
ships have all but disappeared in the partial correlation
analysis, suggesting that they were a function of the
tendency for ethnic minorities to reside in more deprived
areas and to have a younger age structure, than anything
to do with ethnicity itself. The only exception to this is a
negative correlation between ethnic mix and the services
score in London (r ¼ �0:42).
Health and social care interface indicators
There was a correlation of 0.12 between the two
interface indicators, emergency admissions and delayed
discharge, across the 39HAs that were coterminous with
social service areas. This implies that there exists very
little in the way of a relationship between the two.
Table 7 presents the correlations between the interface
indicators and the measures of need and provision.
Delayed discharge from hospital of the elderly demon-
strates very little in the way of association with any of
the indicators of need or provision, the largest correla-
tion being that with age–sex, at �0.27.
Emergency admissions demonstrate quite a different
pattern. These were positively associated with depriva-
tion-related need (r ¼ 0:51), expenditure on elderly
people (r ¼ 0:47) and home care contact hours
(r ¼ 0:4). Relationships with the measures of primary
care provision were mostly small and negative.
However, a face-value interpretation of these results
ARTICLE IN PRESS
Table 6
SSAs in London and outside; partial (rank) correlations between need, primary care and social care
Material deprivationa Age–sexb Ethnic mixc
Outside
London
London
(n ¼ 32)
Outside
London
London
(n ¼ 32)
Outside
London
London
(n ¼ 32)
(n ¼ 116) (n ¼ 116) (n ¼ 116)
Primary care provision
GPs per 1000 patients �0.15 0.08 0.20 0.06 �0.16 0.19
% of practices that are group practices �0.26 �0.23 0.18 �0.15 �0.17 �0.16
% of practices with a female GP �0.32 �0.30 0.12 �0.19 �0.03 �0.23
% of practices with a trainer GP �0.32 �0.11 0.17 0.05 �0.11 0.01
Services score �0.18 �0.52 0.10 �0.29 �0.09 �0.42
Social care provision
Gross expenditure per capita 0.36 0.77 �0.10 �0.20 0.03 0.08
Gross expenditure on elderly per capita 75 plus 0.54 0.77 �0.43 �0.11 �0.07 0.11
Home help/care contact hours 0.46 0.75 �0.24 0.12 �0.03 0.17
Households receiving intense home help/care 0.38 0.43 �0.22 0.03 �0.06 0.17
Residential/nursing care 0.28 0.18 �0.05 �0.25 �0.06 �0.20
aPartial correlation controlling for age–sex and ethnic mix.bPartial correlation controlling for deprivation and ethnic mix.cPartial correlation controlling for deprivation and age–sex.
D. Reeves, D. Baker / Health & Place 10 (2004) 129–140136
could be misleading, as the correlations are con-
founded with relationships between provision and
deprivation.
To disentangle the effects, a stepwise multiple regres-
sion was conducted of emergency admissions against the
full set of indices of need, primary care and social care.
The only variable to enter the model, using a stopping
rule that the beta for entry be 0.3 or greater, was
material deprivation (beta=0.54). Thus, emergency
admissions are found to increase with rising material
deprivation, but after this factor has been taken into
account admissions are unaffected by any of the
measures of provision. The partial correlations in Table
7 illustrate just how little relationship remains after
controlling for material deprivation.
Discussion
Using needs profiling techniques, this paper highlights
the complexity of the relationships between different
forms of population ‘need’ for care, and different types
of provision. From this perspective, the existence or not
of ‘inverse care’ depends both on the way that
population need is conceptualised and the type of
provision that is being considered. This complexity also
has implications for how an equitable allocation of
resources can be achieved.
Need, provision and ‘inverse care’
The three sources of health need measured in this
study possessed some complex relationships with each
other; in particular, there was a pronounced negative
relationship between material deprivation and the age–
sex profile of an area, such that areas with greater need
due to material deprivation tend to be those with less
older-age and gender-related need, and vice versa. The
picture becomes even more complex when the relation-
ships between sources of need and types of provision are
considered. Areas with greater levels of material
deprivation possessed lower levels of primary care
provision, in terms of both GP numbers and services,
but higher levels of all forms of social care. These
relationships still held true, albeit in a weakened form,
after adjustment for differences in age–sex profiles and
ethnic mix. Conversely, areas with higher levels of older-
age and gender-related need possessed more extensive
primary care, but made less provision for social care.
However, these associations all but disappeared after
adjustment for other sources of need.
The absence of a relationship between primary care
provision and age–sex-related need, after adjustment for
deprivation, implies that patterns of primary care
provision have been influenced by relative affluence or
deprivation rather than directly by the age–sex needs of
populations. The most obvious interpretation is that
ARTICLE IN PRESS
Table 7
Rank correlations between interface indicators, need and care provision, for 39 health authorities
Delayed
discharge
Emergency
admissions
Emergency admissions—partial r
controlling for material deprivation
Needs indices
Material deprivation 0.07 0.51 —
Age–sex �0.27 �0.37 �0.08
Ethnic mix 0.22 0.08 �0.15
Primary care provision
GPs per 1000 patients �0.09 �0.25 �0.06
% of practices that are group practices 0.06 �0.33 �0.08
% of practices with a female GP 0.12 �0.35 �0.06
% of practices with a trainer GP �0.09 �0.24 0.08
Services score 0.09 �0.20 �0.02
Social services provision
Gross expenditure per capita �0.01 0.28 0.06
Gross expenditure on elderly per capita
75 plus
�0.02 0.47 0.17
Home help/care contact hours �0.15 0.40 0.16
Households receiving intense home
help/care
�0.11 0.38 0.15
Residential/nursing care �0.05 0.37 0.13
D. Reeves, D. Baker / Health & Place 10 (2004) 129–140 137
primary care resources have a tendency to gravitate to
areas of greater affluence, and these areas tend to have
larger elderly populations. The lack of association
between social services provision and the size of local
elderly populations (the biggest influence on age–sex
scores) is perhaps more surprising. However, as social
services have sought to address the needs of populations
with severe and complex disabilities within fixed
budgets, they have tended to restrict services to those
clients perceived to be in greatest need—the definition of
need in this sense including inability to pay. Thus the
elderly only qualify for services if their personal
resources fall below a certain level: i.e. provision is
dictated by material means rather than by age (or
gender) per se. In one sense social care could be said to
be meeting need by identifying the ‘worse off’ in the
elderly population, but sacrifices have been made in
doing this. Those with ‘low-level need’ tend to have
restricted access to state-supported care until they reach
crisis point; those with complex needs may be stripped
of meagre resources in order to pay for their care until
they reach the poverty line (Robinson, 2002).
If need is defined according to the levels of depriva-
tion, then our study showed variation in the extent and
geographical location of inverse care according to the
particular measures being used. For PCG/Ts the relation
between levels of primary care provision and population
need was indicative of inverse care, but correlations were
relatively weak, especially when area differences in age–
sex and ethnic mix were taken into account. In this
regard, it is interesting to consider the success or
otherwise of interventions to encourage a more even
distribution of primary health care provision. For
example, area inequality in the distribution of GPs has
been known about since before the inception of the NHS
(DoH, 2000b). The Medical Practitioners Committee
(MPC) was established in the late 1940s to address the
issue. The primary role of the MPC has been to control
the entry of GPs into areas already well served, and by
so doing influence the geographical distribution of GPs.
In a further bid to make areas of high need more
attractive to GPs, deprivation payments—by which GPs
receive a per capita fee for each patient who lives in an
area defined as deprived—were introduced in 1990.
Other longitudinal work has shown that inverse care in
the distribution of GPs nevertheless persists so that these
attempts to redistribute resources have not, as yet, been
entirely successful (e.g. Gravelle and Sutton, 2001).
However, evidence of how the ratio of GPs to patients
actually impacts on health and health inequality is
inconclusive. In contrast, services such as child health
surveillance, chronic disease management and minor
surgery are more evenly spread in relation to need
associated with deprivation. These services are incenti-
vised so that a general practice receives an extra
payment if they are provided and this seems to have
led to greater equity in their distribution. Inverse care in
relation to such services is geographically specific and
largely confined to London (Baker and Hann, 2001).
Such geographical differences in the extent and nature
of inverse care can also be observed in relation to social
care. Social care provision was found to correlate
strongly with need arising from material deprivation
and the relationships were stronger in London than
elsewhere. The observed strong relationship between
need arising from deprivation and social services
expenditure may be expected from the nature of the
personal social services funding formula; however, the
analysis also demonstrated that expenditure is converted
(via the services funded or purchased) into equally
strong relationships with the levels of physical contact
and support provided to client populations, at least in
the case of the elderly living at home.
Similar patterns were found for areas with a higher
percentage of ethnic minority groups, although inter-
pretation of this result is not straightforward, since the
relationship between the ethnic composition of an area
and total health need is largely an unknown. Of
necessity, we have combined all non-white groups
together because of small numbers, yet different
minority ethnic groups may have different patterns of
disease and ill-health, and different cultural perceptions
about appropriate care, and hence different types and
degrees of need. Thus the important question for
provision may be whether the mix of specific services,
and the mode of delivery, matches the specific needs of
local ethnic minorities, more so than whether there is
‘more’ or ‘less’ total provision.
The substantial negative relationship between age–sex
and deprivation as sources of need adds considerable
complexity to the task of achieving an equitable
distribution of resources; more so than if these factors
were operating in the same direction, since an over-
emphasis on meeting one type of need must inevitably
result in underprovision for the other. The new revenue
allocation formulae for PCTs, due to be implemented by
the DoH from 2003 (DoH, 2002b), make heavy use of
variables directly related to age and area deprivation.
The formulae have been produced with the specific aim
that ‘the healthcare needs of populations, including the
impact of deprivation, will be the driving force in
determining where cash goes’ (DoH, 1999b). However, it
remains to be seen whether the authors have managed to
achieve the fine balance that is required between the
competing sources of need.
The co-ordination of primary health and social care and
population need
Measurement of the extent to which primary health
and social care services co-ordinate to provide for the
needs of PCG/T populations is also problematic. The
ARTICLE IN PRESSD. Reeves, D. Baker / Health & Place 10 (2004) 129–140138
two ‘interface’ indices put forward by the Department of
Health that specifically relate to care for the elderly are
delayed discharge from hospital and emergency admis-
sions to hospital. Both proved to be unrelated to any of
the measures of primary health or social care provision.
When subjected to stepwise regression, the only pre-
dictive factor to emerge was material deprivation.
Several previous studies have reported a relationship
between emergency admissions and material depriva-
tion, at the practice, PCG/T or area level (e.g. Bernard
and Smith, 1998; Blatchford et al., 1999; Majeed et al.,
2000; Struthers et al., 2000). In addition, Majeed et al.
(2000) in a study of London PCGs, related emergency
admissions to much the same set of practice character-
istics as has been used in the present study and found a
very similar pattern of only weak associations. In all
probability, these measures are simply not sensitive or
specific enough to monitor the impact of joint working.
Only a small proportion of the elderly are in receipt of
social services (e.g. in 2000 less than 15% of all people
over 75 years of age received home help/care or were
permanent residents in residential/nursing homes), hence
any impact that ‘joint working’ may have on hospital
admissions or discharge within this small sub-group
might not show up on such global indicators.
A barrier to full integration of primary health and
social care provision is low levels of population
coterminosity between PCG/Ts and social service
authorities. This study found that only a very small
number of PCG/Ts and SSAs—as they existed in 2000—
shared a common boundary. A wave of mergers has
taken place in the period since this research was
conducted, and as of April 2002 the number of
individual PCTs (all PCGs were replaced by PCTs)
was 302 (DoH, 2002c), down from 481 at the time of this
study. Our analyses indicate that 66 PCTs are now
coterminous with a social service authority, and a
further 15 are almost coterminous (90% or greater).
While this shows some progress being towards bringing
the two organisational geographies into line, the great
majority of PCTs—nearly 75%—still lack common
boundaries. This lack of coterminosity has detrimental
consequences for all the stakeholders involved: for
government, wishing to advance the agenda of inte-
grated care and combined budgets, and desiring to
monitor progress via routinely collected health and
social care indicators; for PCG/Ts seeking to develop co-
ordinated working and who require basic information
about social care provision within their boundaries for
planning and commissioning purposes; for researchers
interested in the relationships between health care, social
care and public health; and not least for client
populations, many of whom fall into the current cracks
between health and social care providers. Over the next
few years, many PCTs will be involved in further
mergers and others will redefine their boundaries as they
evolve into CTs. During this period, while the shape of
the final organisations is still in flux and before
boundaries become too rigid, it will be important
that this rare opportunity to establish coterminous
primary and social care populations is seized and not
lost.
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