Multimorbidity - SG ESRC studentship advert

Call for Applications – PhD Studentship
School of Social and Political Sciences, University of Glasgow
Project title: Health inequalities and multimorbidity: exploiting administrative data
to understand the role of social care
Type of award: Scottish Government/ESRC Collaborative Studentship (+3)
Closing date for applications: Friday 16 January 2015
Date for interviews: Thursday 29 January
Start date: by 1st October 2015
Summary: Applications are invited from outstanding quantitative social scientists (or
from other relevant disciplines) with an interest in pioneering the use of
administrative data to examine the problems of multimorbidity (the co-existence of
2 or more chronic conditions within an individual) and the role played by health and
social care services. The PhD studentship is funded collaboratively by the Scottish
Government and the Scottish Doctoral Training Centre on behalf of the ESRC.
The successful applicant will have an interest in the substantive problems of
multimorbidity and in the challenges of understanding the role of health and social
care services in the development of health conditions. They will be keen to exploit
the potential offered by rapidly-expanding access to linked administrative datasets
but also keen to explore critically the strengths and weaknesses of such data. They
will need to meet the ESRC research training and residency requirements (see
‘Eligibility’ below).
The studentship will provide an unrivalled opportunity to develop valuable expertise
and experience in this kind of work through close links with three major centres for
the analysis of administrative data:
• the ERSC-funded Urban Big Data Centre (UBDC), located in the University of
Glasgow and the base for this studentship, and focussed on local authority
and business data;
• the ESRC-funded Administrative Data Research Centre for Scotland (ADRC
Scotland), focussed on national administrative datasets, including those for
health and social care; and
• the Robertson Centre for Biostatistics, part of the Farr Institute for Scotland,
which provisions local health data for research.
The student will benefit from excellent supervisory support. The lead supervisor,
Professor Nick Bailey, is Associate Director of the UBDC and is also involved in the
ADRC Scotland. He is located within Urban Studies, one of Europe’s leading centres
for inter-disciplinary urban research, with a strong interest in the role played by
public services in producing equitable outcomes for citizens. The student will also be
supervised by: Professor Stewart Mercer, General Practice and Primary Care and
National Lead for Multimorbidity Research within the Scottish School of Primary
Care; and Professor Colin McCowan, Robertson Centre for Biostatistics with 10 years
experience working with routine health and care datasets.
Studentship award: Funding will be available for a 3 year PhD programme and will
cover fees, research and training expenses and an annual stipend of £14,002 (tbc).
Eligibility: Applicants must have a good first degree (2.1. or higher) in the social
sciences or another relevant discipline (such as statistics, psychology, or other
health-related subjects). They should also be able to demonstrate that they meet the
ESRC research training requirements: successful completion of Masters-level courses
in basic quantitative methods, in basic qualitative methods and in social theory for
social scientists. Students with strong quantitative skills who do not have the
required training in qualitative methods and/or social theory may be considered. In
these cases, the award of the studentship will be conditional on them successfully
completing agreed training during their first year. A good grounding in quantitative
methods is essential, however, given the nature of the PhD.
Students due to complete a Masters programme prior to October 2015 are
encouraged to apply although any award may be contingent on final results. In
exceptional cases, applicants may be exempt from the research training requirement
if they can demonstrate excellent research skills obtained through previous
employment.
The studentship has residency requirements in addition to academic requirements.
Funding for fees is only available to people who are ‘ordinarily resident in an EU
state’ while the stipend is only payable to people who are also ‘ordinarily resident in
the UK’. For further information on these requirements, please see:
http://www.esrc.ac.uk/funding-and-guidance/postgraduates/prospectivestudents/eligibility/index.aspx
The selected candidate will need to be approved by the Scottish Graduate School
Doctoral Training Centre.
How to apply:
The closing date for applications is Friday 16 January 2015 with interviews to be held
with short-listed candidates on Thursday 29 January. Applications should be made
online to the College of Social Sciences Graduate School and should include a twopage statement of your interest in the advertised topic.
http://www.gla.ac.uk/research/opportunities/howtoapplyforaresearchdegree/apply
online/
Please apply for the PhD Urban Studies programme of study.
Any applications which do not include the necessary supporting documents (2
references, transcripts, research proposal) will not be considered.
For general information including suitability of existing research training or eligibility,
please contact Dr Mhairi Mackenzie, Convenor of the Doctoral Programme at
[email protected]. For specific information on the PhD, please
contact Nick Bailey at [email protected].
Further particulars
PhD Studentship: “Health inequalities and multimorbidity: exploiting administrative
data to understand the role of social care”
School of Social and Political Sciences, University of Glasgow
Background
Multimorbidity (the co-existence of 2 or more chronic conditions within an individual)
is the norm rather than the exception in people with any long-term condition and
affects the majority of the population aged 65 years and over, representing a major
challenge to health and healthcare [1]. Socioeconomic deprivation also has a marked
effect on the prevalence and impact of multimorbidity [1-3]. The continuing existence
of an ‘inverse care law’ in the NHS is likely to negatively impact on deprived
multimorbid patients most of all [4]. Healthcare staff struggle to cope with their needs,
which are often social as well as medical [5]. However, little is known about the
amount, type or quality of health and social care received by people with
multimorbidity, nor the effects of such care on outcomes [6]. The extent to which
health and social care are currently integrated, and the effects of this on wellbeing
are also not known, but they are key issues as Scotland, and many other countries
try to develop more integrated systems of health and social care. These efforts come
at a time when local authorities, the main providers or commissioners of social care
services, face unprecedented budget cuts combined with rising demands and costs
which are likely to impact on care services [7]. Recent major investments in research
services providing access to linked administrative data provide a unique and
important opportunity to study these issues.
Aim and Objectives
The aim of this PhD is to explore the relationships between multimorbidity and health
and social care utilisation by age and socioeconomic status over time. The objectives
are:
1. To systematically review the international literature on the role and impact of
health and social care for people with multimoridity. This will include scoping
reviews of definitions and measurements of multimorbidity, social care and
integrated care.
2. To carry out stakeholder consultation and pilot work to assess to what extent
analysis of inequalities, multimorbidty, and health and social care use can be
operationalized using linked health and social care data – and in particular
comparison of possibilities using national versus local (Glasgow) data sources.
3. To develop measures to assess the ‘trajectory’ of multimorbidity over time in
different age and socioeconomic groups, and to assess the level of use of
different health and social care services across these trajectories.
4. To explore the potential of evidencing from ‘natural experiment cohorts’ (e.g.
differences in social care services between local authorities within same health
board or between different community healthcare partnerships) the longitudinal
effects of health and social care services on outcomes.
Plan of Action
•
Objective 1. Months 0-3 will focus on the scoping reviews of definitions and
measures of multimorbidity, social care, and integrated care in order to build
clarity around these terminologies which are widely used but often poorly defined.
This will be important for forming the background to the thesis. Months 3-9 will
•
•
•
focus on the systematic review on the published literature on the role and impact
of health and social care for people with multimorbidity. This will be carried out to
a high standard based on current PRISMA guidelines for conducting systematic
reviews [8].
Objective 2 will involve stakeholder consultations and pilot work of available
secondary data sources in health and social care. Given the novel nature of the
work, and the sensitivities around ‘big data’, we envisage holding consultation
meetings with a range of stakeholders, including the SG ‘sponsor’ (perhaps as a
project steering group) to discuss ideas, potential barriers, and ways forward.
This group would give advice in the early part of the project but continue to meet
throughout the life of the PhD. The emphasis of this phase will be on identifying
the available data sources nationally and locally, and piloting the possible
analyses of linked datasets. This objective will be carried out between months 915.
Objective 3 is to describe and then measure the ‘trajectory’ of multimorbidity and
how the utilisation of different types of health and social care changes over time.
This will be done using retrospective data from primary care, identifying when
patients first develop multimorbidity, how this evolves over time and how this
relates to health and social care service utilisation. Datasets that may be linked
from the patients’ CHI numbers include national datasets (e.g. the nationallyrepresentative primary care data on 1.8 million from 2006-2007 used in the
Lancet paper [1]) and local Greater Glasgow & Clyde Health Board datasets
(hospital admissions, community prescribing, death certificates, cancer registry,
General Practice Local Enhanced Service Data on stroke, heart failure, coronary
heart disease, chronic obstructive pulmonary disease, diabetes, and region-wide
disease cohorts). National datasets give access to larger but fewer datasets
whereas local datasets have smaller numbers (though still large) but more detail.
A similar picture exists with social care data, albeit less well developed at this
time, including the linked national health and social care data. Both health and
care data can be enriched with further linkage (e.g. to national data on benefits or
incomes).
Objective 4 will build on this work by identifying one or more natural experiments
arising out of variations in service availability within the Greater Glasgow area. It
would examine how multimorbidity trajectories vary between experimental
groups. Objectives 3 and 4 will be carried in months 15-30, leaving 6 months to
write up the thesis. (We would expect several publications to have been
submitted during Objectives 3 and 4).
Anticipated Outcomes
We would expect several high-quality publications from this work. The systematic
review, the work describing the population and their trajectories, and that on natural
experiments will lead to a number of high quality publications in the leading
international peer-reviewed journals. Additionally we will report findings to the
Scottish Government in regular short briefing reports which will be circulated to
national and local policy makers, managers and practitioners; the SG ‘sponsor’ could
advise on requirements and content. The student (with the support of his or her
supervisors) will be well placed to contribute to debates about the definition and
measurement of multimorbidity, and the impacts of health and social care services on
multimorbidity. The supervisory team (including the SG ‘sponsor’) will work with the
student to identify a range of such opportunities. The PhD will also lay the foundation
for future research in the areas of integrated care and the combined use of ‘big data’
from health and social care. The high-calibre student will have the opportunity to
apply for 3 month internship with the Scottish Government (in addition to the 3
years), enhancing the possibility of collaborative work post-PhD.
Research Training and Research Environment
The successful candidate will be located within the ESRC-funded Urban Big Data
Centre (UBDC) which is led by staff from Urban Studies, including the first
supervisor. As such, he/she will enjoy unrivalled access to the highest quality linked
administrative data on health, social care and other areas, from the widest range of
sources, national and local. The aim of the UBDC is to provide a world-class facility
for accessing multi-sectoral linked data from local government, business and other
sources, with a geographic focus on Greater Glasgow. It will cover data on a wide
range of functional areas, including health and social care, but also areas such as
transport, housing and the physical environment. The UBDC is part of the wider
ESRC-funded Administrative Data Research Network which includes the
Administrative Data Research Centre for Scotland (ADRC-S). The latter
complements the UBDC with a focus on data from UK- and Scottish-level public
bodies. This includes nationally-available data on health and social care, as well as a
range of other data which may be relevant to this study on areas such as individual
incomes, benefits status, labour market status, and education or training. There will
be very close working links between the UBDC and the ADRC-S, not least because
of shared leadership between the Centres as well as shared IT infrastructure, data
services, protocols and practices. The third supervisor leads capacity-building for the
Farr Institute in Scotland which has a focus on health informatics research. The
successful candidate will have access to the training opportunities and post-graduate
programmes being developed both in Scotland and across the UK. The Robertson
Centre for Biostatistics is the key academic partner hosting one of the Farr Institute’s
regional ‘safe havens’ which provides secure local access to national and local data.
The successful candidate will benefit from being at the centre of developments in
linked administrative data for research in health, social care and other sectors which,
along with clinical input from the second supervisor, will give them a unique skill set
and experience in this field.
References
1. Barnett B, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. The epidemiology
of multimorbidity in a large cross-sectional dataset: implications for health care,
research and medical education. The Lancet 2012, Jul 7;380(9836):37-43
2. Lawson KD, Mercer SW, Wyke S, Grieve E, Guthrie B, Watt GCM, Fenwick EAE.
Double trouble: The impact of multimorbidity and deprivation on preferenceweighted health related quality of life a cross sectional analysis of the Scottish
Health Survey. International Journal for Equity in Health 2013, 12:67
doi:10.1186/1475-9276-12-67
3. Payne R, Abel G, Guthrie B, Mercer SW. The impact of physical multimorbidity,
mental health conditions and socioeconomic deprivation on unplanned
admissions to hospital: a retrospective cohort study. CMAJ Feb19, 2013,
doi:10.1503/cmaj.121349
4. Mercer SW, Guthrie B, Furler J, Watt GCM, Hart JT. Multimorbidity and the
inverse care law in primary care. BMJ 2012, ;344:e4152. doi: 10.1136/bmj.e4152
5. O’Brien R, Wyke S, Guthrie B, Watt G, Mercer SW. An “endless struggle”: a
qualitative study of GPs’ and Practice Nurses’ experiences of managing
multimorbidity in socio-economically deprived areas of Scotland. Chronic Illness
2011, 7; 45-59
6. France EF, Wyke S, Gunn JM, Mair F, McLean G, Mercer SW. A systematic
review of prospective cohort studies of multimorbidity in primary care. Br J Gen
Pract 2012: Apr;62(597):e297-307
7. Hastings A, Bailey N, Besemer K, Bramley G, Gannon M, and Watkins D (2013)
Coping with the cuts: local authorities and poorer communities. York: JRF.
8. PRISMA. Transparent Reporting of Systematic Reviews and Meta-analyses.
http://www.prisma-statement.org/ Accessed 17th Feb 2014.