See also: MIME Phase 2
01 May 2010 - 31 March 2015
Future rural health policy expects that individual citizens will assume some responsibility for basic health provision and, together with professionals of varying levels of training, will participate in teams to deliver acute and chronic care.
Thus when an individual in a rural area requires acute medical assistance, the first person on scene may be a "first responder" (a lay person with some basic first aid training and limited equipment), a nurse, a paramedic or a doctor.
That person will assess the patient and their situation, will carry out initial measures and seek additional help as appropriate. From the moment the first carer arrives on the scene, an information stream is being developed, which may have significant relevance to the patient’s outcome. In the chain of events to definitive treatment, there may be several transfers of the patient between healthcare workers.
This new approach to handling acute care raises a number of challenges to which digital solutions may be able to contribute. MIME brings together computer scientists, clinicians and healthcare workers to explore these.
This new approach to handling acute care raises a number of challenges to which digital solutions may be able to contribute. These include:
a) Initial clinical and logistic challenges in managing the patient, e.g.: diagnosis; immediate management; time-critical events; need for urgent administration of treatment such as oxygen or drugs; transfer by road ambulance or helicopter?
b) Recording and interpretation of the patient’s history and physical signs, e.g.: key features in the history pointing to a diagnosis; clinical measurements, such as pulse and respiratory rate, blood pressure, blood oxygen level; trends in these measurements over time; safe limits for these parameters beyond which alarms should be activated; treatment actions that should be instituted on the basis of these parameters; treatment actions performed earlier in the chain; assisting individuals with differing levels of expertise to interpret these data.
c) Conserving important pieces of information and conveying these accurately during the journey of care, e.g.; as patients are passed from one member of the care team to another, especially where the training and level of expertise of these individuals may be widely divergent; where the environment makes simple verbal transfer of information unreliable, e.g. extreme weather conditions, helicopter noise etc.
The proposed study investigates ways to underpin reconfigured rural emergency response services, by examining how technology could support responders to incidents such as road accidents. It will explore the use of networked monitors to support decision making and information management in the management of (possibly multiple) casualties of road traffic accidents.
The following research questions will be addressed:
1) Can appropriate data collection mechanisms be devised to enable the capturing of both physiological developments and important historical event information?
2) Can digital technology be used to support clinical decision making by “first person on the scene” personnel with differing levels of medical expertise?
3) Can useful data summaries be generated for transfer of patients to definitive care?
- MIME project features as a Pathfinder Accelerator case study. View pdf of magazine article.
- MIME Research Fellow features on HIE website. Read more on HIE website.
See project website for details of news and events: http://www.dotrural.ac.uk
- Schneider, A., Mort, A., Mellish, C., and Wilson, P. (2013) High-tech monitoring helps hard-to-reach patients. In The Conversation (UK) http://theconversation.com/ published 21/08/2013.
- Schneider, A., Vaudry, P., Mort, A., Mellish, C., Reiter, E., and Wilson, P. (2013) MIME - NLG in Pre-hospital Care. In Proceedings of 14th European Natural Language Generation Workshop (ENLG'13), Annual meeting of the Association for Computational Linguistics 2013 (ACL 2013). Sofia, Bulgaria.
- Schneider, A., Vaudry, P., Mort, A., Mellish, C., Reiter, E., and Wilson, P. (2013) MIME - NLG Support for Complex and Unstable Pre-hospital Emergencies. In Proceedings of 14th European Natural Language Generation Workshop (ENLG'13), Annual meeting of the Association for Computational Linguistics 2013 (ACL 2013). Sofia, Bulgaria.
- Kindness, P., Dennis, M., Mellish, C., Masthoff, J., & Smith, K. (2013) Towards Affective Emotional Support for Community First Responders Experiencing Stress. In AFFINE workshop, Affective Computing and Intelligent Interaction. Geneva.
- Kindness, P., Mellish, C., & Masthoff, J. (2013). How virtual teammate support types affect stress. In Affective Computing and Intelligent Interaction. Geneva
- Kindness, P. (2013). Towards a virtual teammate whose support can help alleviate stress in the prehospital care domain. Doctoral Consortium, In Affective Computing and Intelligent Interaction. Geneva.
- Schneider, A., Sharma, N., Mort, A., Mellish, C., Reiter, E. & Wilson, P. (2013). Designing a Mobile Device for Pre-hospital Care. In Proceedings of 7th Annual Irish HCI Conference (iHCI 2013), Dundalk, Ireland.
- Kindness, P., Mellish, C., & Masthoff, J. (2013). Identifying and measuring stressors present in pre-hospital care. In Proceedings of Pervasive Health 2013, Venice.
- H. Nguyen, C. Mellish, A. Mort, P. Kindness, J. Knight, and E. Reiter, Using NLG to Manage Information in Medical Emergencies. In Proceedings of Digital Engagement 2011 - The Second Digital Economy All Hands Conference, Newcastle, November 2011
- Scottish Ambulance Service
- Dot.rural (The University of Aberdeen’s rural Digital Economy Hub, funded by RCUK)
- Research Council UK (RCUK)
- Highlands and Islands Enterprise (HIE)
- University of Aberdeen, Knowledge Exchange and Transfer Fund
- Professor Philip Wilson | +44 (0)1463 255 892 | email@example.com
- For enquiries regarding MIME, please contact Dr Alasdair Mort: firstname.lastname@example.org | +44 (0)1463 255 886.
- For general enquiries about dot.rural, please contact: email@example.com | (0) 1224 274 065.