15.03.12 amia d cog webinar v1
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Exploring medical device design and use through layers of Distributed Cognition This presentation accompanies work presented in a paper by the same name: http://authors.elsevier.com/a/1QeZu5SMDQIJeU
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15.03.12 amia d cog webinar v1
- 1. Exploring medical device design and use through layers of Distributed Cognition Dominic Furniss
- 4. • Have a notion of ‘the medical device reaching out’ • Understand Distributed Cognition basics and its applicability to informatics • Know about methods to facilitate its application • Understand DiCoT-CL: a framework to evaluate how devices are coupled to layers of context Learning Aims
- 5. The Computer Reaches Out Grudin, J. (1990). The computer reaches out: the historical continuity of interface design. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 261-268). ACM.
- 7. Traditional View of Cognition
- 9. Distributed Cognition Two key principles distinguish DCog: 1. Delimiting unit of cognitive analysis – Not what’s just inside the brain – Accounting for brain, body and world 2. Expanding the range of mechanisms that can be involved in cognition – The world is not just stimuli – The body is not just an input device
- 10. Distributed Cognition How cognition is distributed: 1. Cognitive processes may be distributed across members of a social group 2. Cognitive processes may involve processes between internal and external (material or environmental) structure 3. Processes may be distributed through time in such a way that the products of earlier events can transform the nature of later events
- 11. DiCoT’s Five Models • Information Flow Model • Physical Model • Artefact Model • Social Model • Evolutionary Model Open Clip Art from Geralg_G 2010
- 12. DiCoT: From analysis to design 1. Understanding the basic mechanics of a system 2. Understanding some deeper conceptual insight 3. Considering incremental design possibilities 4. Considering revolutionary design possibilities
- 13. Method • About 150hrs of fieldwork, over 11days and 5nights. Detailed field notes were kept • Observations and interviews on oncology ward • 26 episodes of blood glucose monitoring were observed, plus more general ward observations • We also referred to the device’s manual • DiCoT was used to guide data gathering and analysis
- 15. Basic mechanics
- 16. Artefact
- 17. Evolutionary
- 19. Information Flow 1.#Go#to#the#[next]#pa; ent# 2.#Greet#pa; ent#and#get#consent# from#them#for#the#reading# 4.#Scan#pa; ent#wristband# 5.#Scan#a#vial,#retrieve#a# test#strip#from#it,#and#place# it#in#the#glucometer## Readings# 3.#Scan#staff#ID# 6.#Prick#pa; ent’s# finger#with#a#lance# 7.#Put#blood#on#test#strip# and#give#pa; ent#a#swab# 8.#Note#the#reading#in#pa; ent’s# notes,#tell#pa; ent,#tell#the#nurse# if#it#is#a#high#or#low#reading#
- 23. Design Consideration (Macro interactions) • Configuring the SAT lock feature so staff can override the need for a quality control check in an emergency • Also not knowing the patient hospital number was reported as an issue. DSN surprised as they should know 2222 or 9999 can be used as a proxy
- 24. Design Consideration (within different layers) • Information flow: Developing ability of the device to support a ward round rather than just one reading at a time. HCA seen writing bed numbers on their hands, tissue paper, etc. • Evolutionary: Data over months and years – new possibilities for data mining and analysis in the longer term
- 25. Design Consideration (between different layers) • Social: Note taking feature is currently underutilised by staff. Notes are monitored by DSN, who would like more information. Possibility of two way communication between staff to encourage further use?
- 26. Take home messages • As medical devices ‘reach out’ they can be coupled to their context in interesting ways • DiCoT-CL helps explore these different forms of coupling, through layers of distributed cognition • The performance of the glucometer is influenced both micro- and macro- interactions • DiCoT-CL can encourage one to think about novel design considerations (within & between)
- 27. • Have a notion of ‘the medical device reaching out’ • Understand Distributed Cognition basics and its applicability to informatics • Know about methods to facilitate its application • Understand DiCoT-CL: a framework to evaluate how devices are coupled to layers of context Learning Aims
- 28. • Furniss, D., Masci, P., Curzon, P., Mayer, A. & Blandford, A. (2015). Exploring Medical Device Design and Use Through Layers of Distributed Cognition: How a glucometer is coupled with its context. Journal of Biomedical Informatics. • Furniss, D., Masci, P., Curzon, P., Mayer, A., & Blandford, A. (2014). 7 Themes for guiding situated ergonomic assessments of medical devices: A case study of an inpatient glucometer. Applied Ergonomics, 45(6), 1668- 1677. Main References
- 29. Questions Dominic Furniss d.furniss@ucl.ac.uk @domfurniss Acknowledgements Co-authors: Paolo Masci, Paul Curzon, Astrid Mayer & Ann Blandford. Thank-you to the staff who gave their time for the study.
Hinweis der Redaktion
- Presenting work mainly from a recent paper of the same title – so read that for references and further details. Hopefully I’ll do a good enough job that you might want to read more about this. I work at UCLIC, I’m a researcher on CHI+MED supported by a grant from the EPSRC.
- I am interested in how people interact with devices. This is a picture of a car park ticket machine at a park near me – the flow of interaction quite poor as the user needs to jump back and forth between the different interface elements. Someone has thought to at least give the users a chance by adding numbers to denote the order one should attend to things. So I am interested in interface design, but also, more deeply, how devices fit or do not fit within the workplace.
- I’ve been working on CHI+MED for the last 5 years or so… looking at the design and use of medical devices in practice, e.g. infusion pumps. Over that time we’ve learnt a lot about how to organise fieldwork in healthcare – some of which has been noted down in these two recent books. Furniss, D., O’Kane, A., Randell, R., Taneva, S., Mentis, H. & Blandford, A. (Eds.). (2014). Fieldwork for Heathcare: Case studies investigating human factors in computing systems [Volume1] Morgan & Claypool Publishers. Furniss, D., Randell, R., O’Kane, A., Taneva, S., Mentis, H. & Blandford, A. (Eds.). (2015). Fieldwork for Healthcare: Guidance for investigating human factors in computing systems [Volume2] Morgan & Claypool Publishers.
- Grudin, J. (1990). The computer reaches out: the historical continuity of interface design. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 261-268). ACM. Medical devices are becoming more complex, interconnected and support by different management systems. E.g. infusion pumps, and blood glucose monitors
- These are the blood glucose monitors that I will be talking about. They were just being introduced on to the oncology ward at the time of my study. They differ from their predecessor in two regards: Barcode scanning of staff and patients Upload of data to a central database
- Left: Model Human Processor: Card SK, Moran TP, Newell A. The psychology of human–computer interaction; 1983. Right: Don Norman's execution-evaluation cycle – Human Action Cycle
- LEFT - Hutchins, E. (1995). How a cockpit remembers its speeds. Cognitive science, 19(3), 265-288. RIGHT - Hutchins, E. (1995). Cognition in the Wild. London: MIT Press.
- Hollan, J., Hutchins, E., Kirsh, D. 2000. Distributed Cognition: Toward a New Foundation for Human-Computer Interaction Research. ACM Transactions on Computer-Human Interaction 7: pp 174-196.
- Hollan, J., Hutchins, E., Kirsh, D. 2000. Distributed Cognition: Toward a New Foundation for Human-Computer Interaction Research. ACM Transactions on Computer-Human Interaction 7: pp 174-196.
- All of these models help to paint a picture of the socio-technical system. The models are overlapping, interdependent and complementary. Each model has associated principles, e.g. information hub, information buffer,… Blandford, A. & Furniss, D. (2006). DiCoT: a methodology for applying Distributed Cognition to the design of team working systems. In Gilroy, SW & Harrison MD (Eds.) Interactive Systems, Design, Specification, and Verification, 12th International Workshop, DSVIS 2005, Lecture Notes in Computer Science 3941, pp 26-38, Springer. DOI 10.1007/11752707_3 Furniss, D. & Blandford, A. (2006). Understanding Emergency Medical Dispatch in terms of Distributed Cognition: a case study. Ergonomics, Volume 49, Issue 12 & 13 October, pp 1174 – 1203 DOI 10.1080/00140130600612663 Taylor and Francis
- Furniss, D., Blandford, A. 2010. DiCoT Modeling: From Analysis to Design. Proc. CHI 2010 Workshop Bridging the Gap: Moving from Contextual Analysis to Design.
- Furniss, D., Masci, P., Curzon, P., Mayer, A. & Blandford, A. (2015). Exploring Medical Device Design and Use Through Layers of Distributed Cognition: How a glucometer is coupled with its context. Journal of Biomedical Informatics.
- First layer is the device itself. Second layer is the device, its case, the strips, lances, vials, etc. For readings and quality control checks. Third layer appeared when on a BG round – trolley so it could be wheeled, with shaprs bin, around the ward – clean on top and waste underneath.
- Differed from predecessor in two important regards: Barcode scanning of staff and patients Readings were uploaded to a central database When we asked staff about what happened to the readings many did not know if and how they transferred and to whom and why.
- Layer 1 patient and healthcare assistant Layer 2 nurse – who managed diabetes and needed to know of high and low readings (outside of parameters) Layer 3 biochemist and DSN – quality control across the hospital
- 1 – readings (there is a pause of about 5secs between 5-7) 2 – quality control checks every 24hrs 3 – training
- How does space impact cognition? Bedside /// Ward /// Hospital In open bed bays the trolley could be wheeled to the bedside. In private rooms preparation was largely down outside of the room before entering, this could disturb normal procedure as one HCA kept forgetting to wait Trying to find a nurse to tell about high/low readings could be problematic and disrupt BG round
- Small drop nit perceptually salient
- This is an example of DiCoT principles for the information flow model. These help the analyst colour the picture, and guide their observations.
- Devices are becoming more interconnected and supported by fragmented organisational systems.
- This is what we’ve covered.
- This link provides free access to the first paper unilt 24 April 2015: http://authors.elsevier.com/a/1QeZu5SMDQIJeU