The Evaluation of Decision Support Tools Needs to e Preference Context-Sensitive

Jack Dowie*, Mette Kjer Kaltoft

*Kontaktforfatter for dette arbejde

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingBidrag til bog/antologiForskningpeer review

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Resumé

Individuals have different preferences in how they wish to relate to healthcare professionals such as doctors. Given choice, they also have preferences in relation to the type and location of support they want for their health and healthcare decisions. We argue that preference-based clusters within this heterogeneity constitute different contexts and that evaluations of decision aids should be context-sensitive in this respect. We draw attention to two distinct preference-based clusters: individuals with a preference for 'intermediative' decision support as a patient, implemented in a largely qualitative deliberative model, on the one hand, and for 'apomediative' decision support as a person, implemented in a largely quantitative multi-criteria decision analytic model, on the other. For convenience, we refer to the latter as Person Decision Support Tools (PDSTs), leaving Patient Decision Aids (PDAs) for its former, conventional use. Seeking to establish proof of method, we present an online PDST that can help individuals establish which of these two types of decision support they would find optimal. It is based on nine key attributes on which PDAs and PDSTs can be contrasted. Within population heterogeneity, preference clusters should be identified, and acknowledged and respected as contexts relevant to the evaluation of decision support tools.

OriginalsprogEngelsk
TitelContext Sensitive Health Informatics : Sustainability in Dynamic Ecosystems
RedaktørerRomaric Marcilly, Craig E. Kuziemsky, Christian Nøhr, Sylvia Pelayo
Antal sider6
ForlagIOS Press
Publikationsdato1. jan. 2019
Sider163-168
ISBN (Trykt)9781643680040
ISBN (Elektronisk)9781643680057
DOI
StatusUdgivet - 1. jan. 2019
NavnStudies in Health Technology and Informatics
Vol/bind265
ISSN0926-9630

Fingeraftryk

Decision Support Techniques
Delivery of Health Care
Population Characteristics
Health

Citer dette

Dowie, J., & Kaltoft, M. K. (2019). The Evaluation of Decision Support Tools Needs to e Preference Context-Sensitive. I R. Marcilly, C. E. Kuziemsky, C. Nøhr, & S. Pelayo (red.), Context Sensitive Health Informatics: Sustainability in Dynamic Ecosystems (s. 163-168). IOS Press. Studies in Health Technology and Informatics, Bind. 265 https://doi.org/10.3233/SHTI190157
Dowie, Jack ; Kaltoft, Mette Kjer. / The Evaluation of Decision Support Tools Needs to e Preference Context-Sensitive. Context Sensitive Health Informatics: Sustainability in Dynamic Ecosystems. red. / Romaric Marcilly ; Craig E. Kuziemsky ; Christian Nøhr ; Sylvia Pelayo. IOS Press, 2019. s. 163-168 (Studies in Health Technology and Informatics, Bind 265).
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abstract = "Individuals have different preferences in how they wish to relate to healthcare professionals such as doctors. Given choice, they also have preferences in relation to the type and location of support they want for their health and healthcare decisions. We argue that preference-based clusters within this heterogeneity constitute different contexts and that evaluations of decision aids should be context-sensitive in this respect. We draw attention to two distinct preference-based clusters: individuals with a preference for 'intermediative' decision support as a patient, implemented in a largely qualitative deliberative model, on the one hand, and for 'apomediative' decision support as a person, implemented in a largely quantitative multi-criteria decision analytic model, on the other. For convenience, we refer to the latter as Person Decision Support Tools (PDSTs), leaving Patient Decision Aids (PDAs) for its former, conventional use. Seeking to establish proof of method, we present an online PDST that can help individuals establish which of these two types of decision support they would find optimal. It is based on nine key attributes on which PDAs and PDSTs can be contrasted. Within population heterogeneity, preference clusters should be identified, and acknowledged and respected as contexts relevant to the evaluation of decision support tools.",
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Dowie, J & Kaltoft, MK 2019, The Evaluation of Decision Support Tools Needs to e Preference Context-Sensitive. i R Marcilly, CE Kuziemsky, C Nøhr & S Pelayo (red), Context Sensitive Health Informatics: Sustainability in Dynamic Ecosystems. IOS Press, Studies in Health Technology and Informatics, bind 265, s. 163-168. https://doi.org/10.3233/SHTI190157

The Evaluation of Decision Support Tools Needs to e Preference Context-Sensitive. / Dowie, Jack; Kaltoft, Mette Kjer.

Context Sensitive Health Informatics: Sustainability in Dynamic Ecosystems. red. / Romaric Marcilly; Craig E. Kuziemsky; Christian Nøhr; Sylvia Pelayo. IOS Press, 2019. s. 163-168 (Studies in Health Technology and Informatics, Bind 265).

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingBidrag til bog/antologiForskningpeer review

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AU - Kaltoft, Mette Kjer

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N2 - Individuals have different preferences in how they wish to relate to healthcare professionals such as doctors. Given choice, they also have preferences in relation to the type and location of support they want for their health and healthcare decisions. We argue that preference-based clusters within this heterogeneity constitute different contexts and that evaluations of decision aids should be context-sensitive in this respect. We draw attention to two distinct preference-based clusters: individuals with a preference for 'intermediative' decision support as a patient, implemented in a largely qualitative deliberative model, on the one hand, and for 'apomediative' decision support as a person, implemented in a largely quantitative multi-criteria decision analytic model, on the other. For convenience, we refer to the latter as Person Decision Support Tools (PDSTs), leaving Patient Decision Aids (PDAs) for its former, conventional use. Seeking to establish proof of method, we present an online PDST that can help individuals establish which of these two types of decision support they would find optimal. It is based on nine key attributes on which PDAs and PDSTs can be contrasted. Within population heterogeneity, preference clusters should be identified, and acknowledged and respected as contexts relevant to the evaluation of decision support tools.

AB - Individuals have different preferences in how they wish to relate to healthcare professionals such as doctors. Given choice, they also have preferences in relation to the type and location of support they want for their health and healthcare decisions. We argue that preference-based clusters within this heterogeneity constitute different contexts and that evaluations of decision aids should be context-sensitive in this respect. We draw attention to two distinct preference-based clusters: individuals with a preference for 'intermediative' decision support as a patient, implemented in a largely qualitative deliberative model, on the one hand, and for 'apomediative' decision support as a person, implemented in a largely quantitative multi-criteria decision analytic model, on the other. For convenience, we refer to the latter as Person Decision Support Tools (PDSTs), leaving Patient Decision Aids (PDAs) for its former, conventional use. Seeking to establish proof of method, we present an online PDST that can help individuals establish which of these two types of decision support they would find optimal. It is based on nine key attributes on which PDAs and PDSTs can be contrasted. Within population heterogeneity, preference clusters should be identified, and acknowledged and respected as contexts relevant to the evaluation of decision support tools.

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Dowie J, Kaltoft MK. The Evaluation of Decision Support Tools Needs to e Preference Context-Sensitive. I Marcilly R, Kuziemsky CE, Nøhr C, Pelayo S, red., Context Sensitive Health Informatics: Sustainability in Dynamic Ecosystems. IOS Press. 2019. s. 163-168. (Studies in Health Technology and Informatics, Bind 265). https://doi.org/10.3233/SHTI190157