Project Aims : 2ENRICH Project

Faculty of Technology and Environment

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The proposed work aims to investigate disciplined approaches to modelling evolving users? cross-cutting decision concerns to enable high-assurance breast cancer clinician?s decision activities in specialist referral centres, and to better inform patients of choice of treatment following surgery. Our specific objectives are:

To understand and characterise patients' and clinicians' cross-cutting concerns and their impact on decision and information provision within specialist breast cancer referral centres.
To investigate how to augment clinicians' decision validation using a triangulation of evidences from statistical modelling, knowledge-based reasoning models and visual self-organising data-maps.
To investigate improved methods for user interfaces and information presentation for clinicians and patients decision activities.
To generalise the project?s results and disseminate them to UK NHS cancer centres and other specialist cancer research networks.

The proposed work addresses key priorities of healthcare informatics, listed in the call for proposals, in a number of ways including;

Modelling current decision practices and reasoning models in specialist breast cancer referral centres. This will underpin the introduction of informatics systems.
Modelling the evolutionary and cross-cutting nature of both users information and evidence throughout a high-assurance decision process. This will be centred around a robust results obtained with statistical survival models, combined with a supervisory rule-based system modelling knowledge about the disease and the effects of treatment.

Objectives

To understand and characterise patient?s and clinician?s cross-cutting concerns and their impact on decision and information provision in specialist breast cancer referral units
To augment clinician?s decision validation by triangulation of statistical evidence from statistical modelling, knowledge-based reasoning and data visualisation.
To investigate methods for user interfaces and information presentation for clinicians and patients.
To generalise the results and disseminate them to other cancer centres and specialist cancer research networks.

Key priorities for healthcare informatics in the call for proposals:

Modelling current decision practices and reasoning models in specialist breast cancer referral centres
Modelling the evolutionary and cross-cutting nature of users information and evidence throughout a high-assurance decision process. This will be centred around robust results obtained with statistical survival models combined with a supervisory rule-based system modelling knowledge about the disease and the effects of treatment.

Required research

The basis of the required research is:

Evidence-based delivery of medical care. Currently this is centred on action-based prognosis using the Nottingham and Manchester staging systems. Patients receive information during a pre-set appointment with the clinician and perhaps a breast care nurse.

We will address:

Integration of support models for clinicians and patients within a common reasoning framework.
Identification and fetching of evidence relevant to a clinician or patient?s decision point, validated by the reasoning models.
How evidence and decision traceability is best presented to clinicians and patients.

Scientific/technological relevance

Design of high-assurance decision support for clinicians and patients. We will make research contributions in:
Process understanding and adaptive software architecture to support adaptive decision-support systems
Flexible access to decision support models and patient databases
Approach to decision support needs to be integrated with clinical processes, apply to the majority of patients encountered by the clinician and use specific clinical variables defined across clinical centres.
The background to the proposal is a pilot study of a composite prognostic index of survival that has proved reliable for patients from one clinical centre.

Research process

Incremental prototyping so that demonstrator versions of the software will be available at an early stage, improving with feedback from system users, to derive a transferable result ? how to create usable decision support systems for breast cancer.

Relevance to beneficiaries

Insight into the use of compositional reasoning tools to support cancer design support (?)
Requirements of user interfaces to provide decision support also for patients.
Design of adaptive decision support systems to inform the validation and verification.
Insight into design and interoperation of underdevelopment NHS infrastructure.

Exploitation of results

Adoption of the results through the adoption of the project results by our clinical partners. Medium-term exploitation depends on the initial take-up.

Project Title

Towards a Disciplined Approach to Integrating Decision-Support Systems for Breast Cancer Care Activities