University of Central Lancashire
Research Project/Studentship Description
Project ref: RS/15/24
School
Proposed Director of Studies
Programme (e.g MPhil/PhD)
Duration of Studentship
Hours (Full or Part Time)
Tuition Fees
Maintenance Grant
Start Date
Entry Requirements Project 1
Entry Requirements Project 2
Any Special Requirements (e.g. driving
licence)
Closing Date: 28/03/2016
Health Sciences
Project 1 (Evaluating health technologies to
support development) Professor Andy Clegg
email aclegg3@uclan.ac.uk tel 01772 895545
Project 2 (Statistical methods in the evaluation
of the effectiveness of interventions) Dr Chris
Sutton email
cjsutton@uclan.ac.uk tel 01772
892783
PhD (via MPhil)
3 years
Full Time
Paid at UK/EU rate (currently £4052 pa)
£14057 p a (2015/16 rates
Expected 1 October 2016
UK Bachelor Degree at minimum 2:1 classification
(or equivalent qualification) in a relevant health,
social care or pertinent methodological subject
UK Bachelor Degree at minimum 2:1 classification
(or equivalent qualification) in mathematics,
statistics or other pertinent subject with substantial
methodological content
Non UK nationals should hold IELTS 7.0 with no
lower than 6.5 in all sub scores (or equivalent
qualification)
Project Title
[1] Evaluating health technologies to support policy development
[2] Statistical methods in the evaluation of the effectiveness of interventions
Project Description
In:
[1] Evaluating health technologies to support policy development
or
[2] Statistical methods in the evaluation of the effectiveness of interventions
[1] Evaluating health technologies to support policy development
Health technology assessment plays a vital role in the development of health policy and guidance on
the use of drugs, devices, procedures, screening programmes, health promotion and public health
policies nationally and internationally. In England and Wales the National Institute for Health and
Care Excellence (NICE) rely upon the provision of robust and timely evaluations of the clinical and
cost effectiveness of different health technologies to underpin their guidance to the NHS. Evidence
synthesis in the form of systematic reviews, meta-analyses and economic evaluations through
decision analytic models provide the basis for the assessment of the effectiveness of the different
technologies. Limitations in the evidence-base used for evaluating health technologies are well
recognised. The effects are reflected in uncertainties in the evaluations undertaken and the guidance
provided. The methods used for evaluating health technologies have continued to develop to address
these limitations. In encompassing a different evidence base, new challenges arise in the
assessment of the evidence, interpretation of its findings and the development of the ensuing
guidance. This PhD will provide the opportunity to examine the different sources of evidence, the
evolving methods for their evaluation, the effects on the outcomes of the assessment of health
technologies and the potential effects on the guidance developed. It will involve the use of systematic
review methods, meta-analysis (including network meta-analysis) and decision-analytic modelling,
applying the methods to different case studies to understand the possible consequences for decision
makers and policy development.
[2] Statistical methods in the evaluation of the effectiveness of interventions
A.
Cluster-randomised controlled trials are often used to avoid the contamination risk inherent
when using individual randomisation in many healthcare intervention trials. However, clusterrandomised trials introduce other problems, particularly selection bias and an increase in sample size
(due to clustering effects). It has been proposed that individual randomisation may still be preferable
if the degree of contamination is limited (Torgerson, 2001) or that more complex designs (e.g.
pseudo-cluster randomisation – Borm et al., 2005) should be used. If the contamination can be
measured, then causal inferential methods, such as instrumental variables, can be used to adjust
effectiveness estimates for contamination. However, the evidence regarding the optimal design and
the implications for evidence in relation to the evaluation of effectiveness and cost-effectiveness of
healthcare interventions remains limited. This research project will consider the optimal design and
analysis options for feasibility and effectiveness trials of complex healthcare interventions.
Or
B.
Large general practice and linked hospital datasets are increasingly being used to evaluate
the effectiveness of interventions in clinical practice. However, the limitations of these datasets are
that they were not collected for research purposes and careful consideration needs to be taken when
estimates of effectiveness and cost-effectiveness are required for technology assessments.
Methods, such as propensity score matching, exist for balancing intervention groups. However, the
extent to which these methods are optimal for such assessments are unknown, particularly given the
potential for unrecorded, incomplete or unreliable assessment of variables affecting allocation. This
research project will investigate the potential for using a large general practice database (e.g. THIN)
and linked hospital data (from HES) to assess the effect of anticoagulant medication on the risk of
stroke.
Research Student Specification
Studentship Ref
Number
RS/15/24
Project Title:
[1] Evaluating health technologies to support policy development
[2] Statistical methods in the evaluation of the effectiveness of
interventions
School:
Health Sciences
Contact:
Project 1 Professor Andy Clegg email aclegg3@uclan.ac.uk
Project 2 Dr Chris Sutton email cjsutton@uclan.ac.uk
Attributes
Essential
Closing Date:
Desirable
28/03/2016
Measured By
Education/Qualificati
ons
[1] 2:1 undergraduate
degree (or equivalent) in
a relevant health, social
care, or pertinent
methodological subject
[2] 2:1 undergraduate
degree (or equivalent) in
mathematics, statistics
or other pertinent subject
with substantial
methodological content
Master’s degree in
relevant area
Application
Form/Certificat
es
Experience
Click here to enter text.
Health Service
Experience
Application
form/Interview
[1] Understanding of
Improvement/Implement
ation Science
Application
form/Interview
Evidence of independent
research work
Application
form/Interview
Skills/Abilities
Excellent
communication/interpers
onal skills.
Application
form and
interview,
research
proposal
Good presentation and
writing skills.
Application
form and
interview
Self-motivated
Personal Details
Ability to work alone
Application
form and
interview
Good IT skills
particularly MS Office
software
Application
form and
interview
Non UK nationals will
require an overall IELTS
score of 7.
Effective time
management and
prioritisation of work
Click here to enter text.
Application
Form
Certificates
Application
form and
interview