This article focuses on the production side of clinical data work, or data recording work, and in particular, on its multiplicity in terms of data variability. We report the findings from two case studies aimed at assessing the multiplicity that can be observed when the same medical phenomenon is recorded by multiple competent experts, yet the recorded data enable the knowledgeable management of illness trajectories. Often framed in terms of the latent unreliability of medical data, and then treated as a problem to solve, we argue that practitioners in the health informatics field must gain a greater awareness of the natural variability of data inscribing work, assess it, and design solutions that allow actors on both sides of clinical data work, that is, the production and care, as well as the primary and secondary uses of data to aptly inform each other’s practices.

The elephant in the record: On the multiplicity of data recording work

Locoro A.;
2019-01-01

Abstract

This article focuses on the production side of clinical data work, or data recording work, and in particular, on its multiplicity in terms of data variability. We report the findings from two case studies aimed at assessing the multiplicity that can be observed when the same medical phenomenon is recorded by multiple competent experts, yet the recorded data enable the knowledgeable management of illness trajectories. Often framed in terms of the latent unreliability of medical data, and then treated as a problem to solve, we argue that practitioners in the health informatics field must gain a greater awareness of the natural variability of data inscribing work, assess it, and design solutions that allow actors on both sides of clinical data work, that is, the production and care, as well as the primary and secondary uses of data to aptly inform each other’s practices.
2019
data recording work; data work; inter-rater agreement; inter-rater reliability; observer variability; Cardiologists; Data Collection; Female; Humans; Male; Surveys and Questionnaires; Health Information Management; Observer Variation; Organizational Case Studies; Reproducibility of Results
Cabitza, F.; Locoro, A.; Alderighi, C.; Rasoini, R.; Compagnone, D.; Berjano, P.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2119272
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