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Assuring measurement quality in person-centred healthcare
RISE - Research Institutes of Sweden, Safety and Transport, Measurement Science and Technology.ORCID iD: 0000-0003-4349-500X
2018 (English)In: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 29, p. 034003-Article in journal (Refereed) Published
Abstract [en]

Is it realistic to aspire to the same kind of quality-assurance of measurement in person-centred care, currently being implemented in healthcare globally, as is established in the physical sciences and engineering? Ensuring metrological comparability (‘traceability’) and reliably declaring measurement uncertainty when assessing patient ability or increased social capital are however challenging for subjective measurements often characterised by large dispersion. Drawing simple analogies between ‘instruments’ in the social sciences – questionnaires, ability tests, etc.–  and  engineering instruments such as thermometers does not go far enough. A possible way forward apparently equally applicable to both physical and social measurement, seems to be to model inferences in terms performance metrics of a measurement system. Person-centred care needs person-centred measurement and a full picture of the measurement process when Man acts as a measurement instrument is given in the present paper. This complements previous work by presenting the process, step by step, from the observed indication (e.g. probability of success, Psuccess, of achieving atask), through restitution with Rasch Measurement Theory, to the measurand (e.g. task difficulty). Rasch invariant measure theory can yield quantities –‘latent’ (or ‘explanatory’) variables such as task challenge or person ability – with characteristics akin to those of physical quantities. Metrological references for comparability via traceability and reliable estimates ofuncertainty and decision risks are then in reach even for perceptive measurements (and other qualitative properties). As a case study, the person-centred measurement of cognitive ability is examined, as part of the EUproject EMPIR 15HLT04 NeuroMet, for Alzheimer’s, where better analysis of correlations with brain atrophy is enabled thanks to the Rasch metrological approach.

Place, publisher, year, edition, pages
2018. Vol. 29, p. 034003-
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:ri:diva-32801DOI: 10.1088/1361-6501/aa9cd2OAI: oai:DiVA.org:ri-32801DiVA: diva2:1161627
Projects
EMPIR 15HLT04 NeuroMet
Funder
EU, Horizon 2020, EMPIR 15HLT04 NeuroMet
Available from: 2017-11-30 Created: 2017-11-30 Last updated: 2018-02-23

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Publisher's full texthttp://iopscience.iop.org/article/10.1088/1361-6501/aa9cd2

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