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SIHI - Your Data, My Data, Our Data

(draft) Presentation for the Southern Institute for Health Informatics - 5th September 2012

Tim Davies

on 5 September 2012

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Transcript of SIHI - Your Data, My Data, Our Data

Big Data Raw data Real-time data Open data Personal data Linked data Data empowers Data reveals Data impacts Your Data, My Data, Our Data HM Treasury. (2011). Chancellors Autumn Statement 2011. But who? But also hides But how? Outline Problematising data
The social construction of (health) data
Concluding remarks Deconstructing the data deluge
Differentiation of data
How social, economic and political processes shape the construction of data infrastructures and potential outcomes - the politics of data and method (Savage 2010)
Sorting Things Out (Bowker and Starr 1999) The Social Construction of Data Shifting focus from the construction of already existing data to the production of these data
For example: Electronic Patient Records
Promise for organization and delivery of healthcare services
Potential value to researchers, policy makers and businesses The Social Production of Data The record is an artefact that requires some forms of information and not others (Halford and Obstelder 2010)
Much information entered is free-text and not readily analysable
Not all the information that is used to diagnose and treat a patient is in the record
Continued importance of informal information practices
Nurses 'scraps' (Hardey et al 2000)
Retained information (Engesmo and Tjora 2006)
Meaning is contextual (Garfinkel 1964; Hartswood 2003; Moser and Law 2006 What does a Patient Record Record?
(And what does it not record) Data generated from patient records is still interesting and useful
But we must appreciate what these data are, and are not.
This must inform our claims.
If we aim to simply clean up the inherent 'messiness' of information we risk the loss of important insights. So what? Your Data, My Data, Our Data Data producers Data consumers Opening data Implications of... Attention to encoding & technical choices
Transparency and documentation about how data is constructed Critical usage
Awareness of power dynamics
Maintaining balanced research driven by questions not data Building community capacity
Ensuring data is shared in context
Asking who is empowered
Embedding data alongside other resources for debate and action
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