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Care Review

Care Review


Outline, including interdisciplinary dimension

More than 100000 patients require critical care support in England and Wales alone/year and most will survive their admission. Post ICU and hospital period is followed by a variable period of recuperation and disability. National Institute of Clinical Excellence has recommended post ICU rehabilitation including follow up to improve post ICU outcomes and improve their quality of life and also identify post ICU physical disability and mental disability including anxiety, depression and traumatic stress disorder. A follow-up clinic staffed by clinical specialists including doctors, nurses and physiotherapists can help these patients but it is resource and cost intensive. In this period of austerity, it is essential to identify services which will be cost beneficial. It is also known that not all patients will require follow up and there are cancellations and non-attendances. Identifying key sub-groups of patients will help decrease the workload of such follow up clinics and also enable us focus resources on patients who actually need follow-up and further intervention.

Use of an “app” based questionnaire using validated tools of measurement of physical mobility, anxiety, depression, post-traumatic stress disorder and nutrition could help identify the cohort of patients who will benefit from a structured follow up clinic. In this day of ubiquitous availability of technology, a web based application could allow patients to explore their physical and mental status which will enable them to be identified as a “patient in need”. There is also potential cost savings for NHS as follow up clinics will focus only on these patients.

The project will have the following objectives:

1. Systematic review of ICU follow up studies to identify current practise, patient benefits, cost benefits, tools to measure physical and mental disability and validation in the ICU population

2. Development of the application incorporating tools to detect at risk population who will benefit from ICU follow up and clinical intervention

3. A single centre trial to study

a. the ability of the application in identifying patients in need of ICU follow up

b. Patient feedback to assess ease of use

c. Health economic analysis to study the cost benefit of following up based on clinical criteria for e.g. duration of mechanical ventilation and using the “app”

Key words/descriptors

data analytics, high performance computing, ICU medicine, NHS, patient care, human physiology

First supervisor

Professor Dimitrios Nikolopolous - School of Electronics, Electrical Engineering and Computer Science

Secondary supervisor from a complementary discipline

Dr Murali Shyamsanar - School of Medicine, Dentistry and Biomedical Sciences

Supervisors’ track record of PhD completions, plus excellence and international standing in the project area

Professor Dimitrios Nikolopolous is research director of the HPDC group in EEECS at QUB.

Intersectoral exposure and/or international mobility

(e.g. secondments to/collaboration with partner organizations)

This project extends the collaboration between the High Performance and Distributed Computing Clusters (HPDC) in the School of EEECS and critical care specialists in the QUB School of Medicine. These groups already work together with the European Commission funded FP7 project NanoStreams.  The project proposed here, for COFUND, develops the data analytics capability to encompass post-discharge support.

Describe briefly the international profile of the partner

The external partner will be Belfast Trust, with which the QUB Medical School has strong links already.

Training that will be provided through the research project itself

The student will learn about state of the art computing techniques to analyse high volumes of data and will develop clinical expertise in regard to the analysis of the data.

Examples of additional training in non-research transferable skills

This project links Medicine and Computer Science, and provides training to the student on how these two areas are producing new outcomes.

Expected dissemination of results: peer-reviewed journals, seminars, workshop and conferences at European/international level

(e.g. public talks, visits to schools, open days, QUB impact showcase)

Potential Dissemination in: Journal of Critical Care Medicine, Concurrency in Computation Practice and Experience, HiPEAC Workshops, Supercomputing Workshops, ETP4HPC workshops.

Expected impact activities

(e.g. public talks, visits to schools, open days, QUB impact showcase)

 Post ICU recuperation can be prolonged and identification of patient in need of follow up will ensure care and resources are used appropriately. ICU follow up clinics have non-attenders and patients who might not need intervention. A follow up clinic appointment might be seen as an interruption of daily activities for these patients and will involve time and finance implications. By identifying only patients who will benefit from a follow up clinic appointment, we will ensure that the there is no unnecessary interruption to patients’ life.

Resource Impact

ICU follow up clinics are resource intensive and are usually led by a doctor with support from nursing staff, physiotherapists etc. There are also infrastructure implications as clinical rooms need to be organised for the clinics. A follow up clinic could end up reviewing patients who need no follow-up if their criteria for follow-up is not appropriate and may also miss patients who may actually need follow-up if they fall outside set criteria.

An app could be applied at no cost over multiple time points during a patient post ICU discharge. This enable us not only identify patients in need but also identify patients who might be otherwise denied the service based on clinical criteria and not their physical and mental health needs.

Computer Science

This project will widen the scope of applications in which research in the HPDC group is applied, specifically to further its work in clinical informatics, work that has be with the NanoStreams project.