We have submitted a response from the perspective of those who have worked with data supporting basic and translational research - we'll also be posting later a link to the NCIN and Department of health publication from December last year: An Intelligence Framework for Cancer - but for now, here's how we replied to the consultation:
The UK is currently supporting or considering the
development of several initiatives seeking to promote the skills and
infrastructure necessary to carry out health research based on linked large-scale
or population-level datasets generated through routine processes of data
collection.
In Wales, the Health Information Research Unit at the
University of Swansea maintains the Secure Anonymised Linkage System (SAIL); in
Scotland, the Scottish Health Informatics Programme (SHIP) supports the
“collation, management, dissemination and research analysis of anonymised
Electronic Patient Records”; in the UK, the Research Capability Programme of
the National Institute for Health Research have piloted a Health Research
Support Service which is due to be formally implemented as a full service: the Clinical Practice Research Datalink. The
Medical Research Council also recently issued a call for e-Health Informatics
Research Centres to “maximise the health research potential offered by linking
electronic health records with other forms of routinely collected data and
research datasets”.
Of the National Cancer Research Institute partners’ 2010 funding, however, over 50% was
spent on research which could be described as basic, translational or early
stage; 40% on Biology and Aetiology alone; and some proportion of the discovery
and development elements of spending under Common Scientific Outcome (CSO) 5
(Treatment), technology development and evaluation under CSO 4 (Early
Detection, Diagnosis and Prognosis), and CSO7 (Scientific and Model Systems)
can be ascribed to these types of research.
The infrastructure used to support this work is in many
cases intra-institutional, in some inter-institutional, rather than national –
although with appropriate standardization, integrated datasets from within
institutions could be submitted to national-scale repositories with greater
ease. Completeness, accuracy and granularity of the data are vital for this
research. Often the data which support and contextualize observations in the
laboratory during these research projects are drawn from multiple hospital
systems and collated with difficulty. This has an impact on timescales and the
validation of observations. Some proportion of the NCRI partners’ spend in each
of the CSOs is dedicated to Resources and Infrastructure (R&I) which may
include informatics, however, if we look at the other project types falling
under R&I for e.g. CSO 4 (Early Detection, Diagnosis and Prognosis) we may
reasonably conclude that the proportion dedicated to informatics is not the
majority – closer analysis of the NCRI CaRD database is required to confirm
this.
|
CSO4.4 Examples of science that would fit:
·
Informatics
and informatics networks; for example, patient databanks
·
Specimen
resources (serum, tissue, images, etc.)
·
Clinical
trials infrastructure
·
Epidemiological
resources pertaining to risk assessment, detection, diagnosis, or prognosis
·
Statistical
methodology or biostatistical methods
·
Centers,
consortia, and/or networks
·
Education
and training of investigators at all levels (including clinicians), such as
participation in training workshops, advanced research technique courses, and
Master's course attendance. This does not include longer term research based
training, such as Ph.D. or post-doctoral fellowships
|
The MRC, in their call for e-Health Informatics Research
Centres, adduce the key findings of the ABPI and UK research funders mapping exercise
reviewing the UK capability in e-Health records research – a number of these
can be applied to the intra-institutional situation:
·
There is a shortage of
people with the breadth of skills necessary to carry out the complex linkage
and analyses required in health informatics research.
·
There is an absence of
career structure in enabling roles such as data managers, software engineers,
informaticians and data analysts.
·
There are no clear
interfaces between researchers and industry, policy makers or the NHS and there
is no ready means for sharing best practice.
Certainly, my own experience of supporting even institutes
with strong reputations for research is that they lack the skills, focus and
confidence in informatics to make much progress in the development of their
infrastructure – and have been extremely glad of the opportunity to take advice
and receive support from experienced individuals with a research and
informatics background.
Perhaps the NCIN could consider devoting some resource to
skills development in this area, disseminating the acquired expertise and
knowledge of the NCIN of best practices in data management and handling and the
use of technology. Might this sit alongside the work currently envisaged by
Proposal 6 of the consultation?
_________
During a meeting with Oracle at the end of last year, an
ex-colleague who specialises in molecular and gynaecological oncology suggested
that their institute would not be seeking data integration services and
infrastructure supply from the likes of Oracle with such urgency if they felt
they could get ‘stage and grade’ at diagnosis from the Thames Cancer Registry.
The paucity of staging data in the registries is an
established weakness as discussed in the NCIN and Department of Health
document, An Intelligence Framework for
cancer and steps are being taken to address this, however, the perception
of the inadequacy of the dataset collected by the Thames Cancer Registry (and
by extension, despite shining examples such as the ECRIC, the amalgamated
registries’ dataset) extended beyond the known weaknesses unfairly to the
dataset as a whole in the case of this Professor. Such perceptions were not
uncommon at that centre and need to be overturned.
The vastly extended dataset which will be collected by the
registries in future sounds extremely promising in its potential to support not
only epidemiological and population-level research, but also basic and
small-scale clinical research. It will be vital, however, to create a sustained
‘sales’ initiative to establish a new level of confidence in the data in the
areas of the research community who have hitherto not engaged with these
datasets due to the concerns described in An
Intelligence Framework. Their concern may be that where a smaller dataset
was found wanting, will the collection of a larger one not push already
stretched resources beyond their elastic limit?
Having had first-hand experience of the way in which MDT
data is fed into the Somerset system and the ample opportunities, often taken
by overburdened MDT co-ordinators, to introduce error – it is inspiring to see
that a truly modern approach to data extraction and aggregation is being
implemented as described by Dr. Rashbass at, to give one instance, the NOCRI
Information Systems Workshop. As
described by Dr. Rashbass, various technologies including natural language
querying will take data from pathology full-text reports, from local imaging
systems and myriad other systems to create the amalgamated national dataset –
and this data will be quality controlled and assured. More information on how
the latter will be achieved would be welcome.
Similar initiatives and technologies are being employed by
healthcare delivery and research organisations themselves – for example, the
ORIS oncology platform being implemented intra-organisationally by King’s
Health Partners and the Acropolis platform being implemented
inter-organisationally. It is important to note that these implementations may be beyond the budget of smaller organisations who deliver oncology services and conduct research –
and here the value of a new ‘high-resolution’, quality assured, timely dataset
such as that envisaged by the registry modernisation team will have the
potential to deliver enormous benefit.
But this will depend on the quality of the data and ensuring
that this quality is recognised in the research community. “This service will
ensure that common standards and working practices are applied to data
extraction, linkage and quality assurance to both national feeds and a range of
local sources.” This assertion really needs to be backed up with a strong
communications and ‘marketing’ effort.
To this end, should the NCIN devote some resource to support
activities at the provider end of the process to ensure that where providers
are implementing their own data infrastructures, these can interface with and
provide bulk data to the unified registries to the appropriate standard; and
where they are not yet capable of developing their own infrastructures, that
they have support in the provision of accurate and complete data to the
registries and potentially support in the process of designing their own data architectures
and integration solutions; and then
to effectively communicate the work that they are doing to improve registry
data effectively to the community – concentrating not on the sophisticated use
of technology to capture and amalgamate data, but on the procedural changes
being implemented to assure quality?
Many of the proposals made in the consultation document
might be realised by the same infrastructural components – and many of these
components are similar to those which will hopefully be implemented by the
Clinical Practice Research Datalink (CPRD). Where respondents to the
consultation indicate that the proposed data linkage and notification services
would deliver great benefit to their work, it may be worth establishing what
level of awareness they have of the CPRD, the concern being that the overhead
involved in creating facilities which might duplicate some aspects of the CPRD
could be enormous given the proportion of the budget for the latter initiative
devoted to infrastructure. There might be a greater return on investment to be
had by focusing on data rather than infrastructure at the national level?
In conclusion, it might be worth considering if Proposal 6
(a research support service advising on the availability of and access to data)
could benefit from being expanded to include some work looking at supporting
data quality and intra-institutional infrastructural development - and engaging the basic and translational
research communities to overturn perceptions about the ability of the dataset
to support their work.
Let us know what you think - are we way off-beam?
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