Data as promise: reconfiguring Danish public health through personalized medicine

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Data as promise : reconfiguring Danish public health through personalized medicine. / Høyer, Klaus Lindgaard.

In: Social Studies of Science, Vol. 49, No. 4, 2019, p. 531-555.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Høyer, KL 2019, 'Data as promise: reconfiguring Danish public health through personalized medicine', Social Studies of Science, vol. 49, no. 4, pp. 531-555. https://doi.org/10.1177/0306312719858697

APA

Høyer, K. L. (2019). Data as promise: reconfiguring Danish public health through personalized medicine. Social Studies of Science, 49(4), 531-555. https://doi.org/10.1177/0306312719858697

Vancouver

Høyer KL. Data as promise: reconfiguring Danish public health through personalized medicine. Social Studies of Science. 2019;49(4):531-555. https://doi.org/10.1177/0306312719858697

Author

Høyer, Klaus Lindgaard. / Data as promise : reconfiguring Danish public health through personalized medicine. In: Social Studies of Science. 2019 ; Vol. 49, No. 4. pp. 531-555.

Bibtex

@article{a88bff55007a4aa981a00c0cf733f919,
title = "Data as promise: reconfiguring Danish public health through personalized medicine",
abstract = "‘Personalized medicine’ might sound like the very antithesis of population science and public health, with the individual taking the place of the population. However, in practice, personalized medicine generates heavy investments in the population sciences – particularly in data-sourcing initiatives. Intensified data sourcing implies new roles and responsibilities for patients and health professionals, who become responsible not only for data contributions, but also for responding to new uses of data in personalized prevention, drawing upon detailed mapping of risk distribution in the population. Although this population-based ‘personalization’ of prevention and treatment is said to be about making the health services ‘data-driven’, the policies and plans themselves use existing data and evidence in a very selective manner. It is as if data-driven decision-making is a promise for an unspecified future, not a demand on its planning in the present. I therefore suggest interrogating how ‘promissory data’ interact with ideas about accountability in public health policies, and also with the data initiatives that the promises bring about. Intensified data collection might not just be interesting for what it allows authorities to do and know, but also for how its promises of future evidence can be used to postpone action and sidestep uncomfortable knowledge in the present.",
author = "H{\o}yer, {Klaus Lindgaard}",
year = "2019",
doi = "10.1177/0306312719858697",
language = "English",
volume = "49",
pages = "531--555",
journal = "Social Studies of Science",
issn = "0306-3127",
publisher = "SAGE Publications",
number = "4",

}

RIS

TY - JOUR

T1 - Data as promise

T2 - reconfiguring Danish public health through personalized medicine

AU - Høyer, Klaus Lindgaard

PY - 2019

Y1 - 2019

N2 - ‘Personalized medicine’ might sound like the very antithesis of population science and public health, with the individual taking the place of the population. However, in practice, personalized medicine generates heavy investments in the population sciences – particularly in data-sourcing initiatives. Intensified data sourcing implies new roles and responsibilities for patients and health professionals, who become responsible not only for data contributions, but also for responding to new uses of data in personalized prevention, drawing upon detailed mapping of risk distribution in the population. Although this population-based ‘personalization’ of prevention and treatment is said to be about making the health services ‘data-driven’, the policies and plans themselves use existing data and evidence in a very selective manner. It is as if data-driven decision-making is a promise for an unspecified future, not a demand on its planning in the present. I therefore suggest interrogating how ‘promissory data’ interact with ideas about accountability in public health policies, and also with the data initiatives that the promises bring about. Intensified data collection might not just be interesting for what it allows authorities to do and know, but also for how its promises of future evidence can be used to postpone action and sidestep uncomfortable knowledge in the present.

AB - ‘Personalized medicine’ might sound like the very antithesis of population science and public health, with the individual taking the place of the population. However, in practice, personalized medicine generates heavy investments in the population sciences – particularly in data-sourcing initiatives. Intensified data sourcing implies new roles and responsibilities for patients and health professionals, who become responsible not only for data contributions, but also for responding to new uses of data in personalized prevention, drawing upon detailed mapping of risk distribution in the population. Although this population-based ‘personalization’ of prevention and treatment is said to be about making the health services ‘data-driven’, the policies and plans themselves use existing data and evidence in a very selective manner. It is as if data-driven decision-making is a promise for an unspecified future, not a demand on its planning in the present. I therefore suggest interrogating how ‘promissory data’ interact with ideas about accountability in public health policies, and also with the data initiatives that the promises bring about. Intensified data collection might not just be interesting for what it allows authorities to do and know, but also for how its promises of future evidence can be used to postpone action and sidestep uncomfortable knowledge in the present.

U2 - 10.1177/0306312719858697

DO - 10.1177/0306312719858697

M3 - Journal article

C2 - 31272287

VL - 49

SP - 531

EP - 555

JO - Social Studies of Science

JF - Social Studies of Science

SN - 0306-3127

IS - 4

ER -

ID: 224026328