TY - JOUR
T1 - Achieving veracity
T2 - A study of the development and use of an information system for data analysis in preventive healthcare
AU - Mønsted, Troels Sune
PY - 2019/9
Y1 - 2019/9
N2 - Within healthcare, information systems are increasingly developed to enable automatic analysis of the large amounts of data that are accumulated. A prerequisite for the practical use of such data analysis is the veracity of the output, that is, that the analysis is clinically valid. Whereas most research focuses on the technical configuration and clinical precision of data analysis systems, the purpose of this article is to investigate how veracity is achieved in practice. Based on a study of a project in Denmark aimed at developing an algorithm for stratification of citizens in preventive healthcare, this article confirms that achieving veracity requires close attention to the clinical validity of the algorithm. It also concludes, however, that the veracity in practice hinges critically on the citizens’ ability to report high-quality data and the ability of the health professionals to interpret the outcome in the context of existing care practices.
AB - Within healthcare, information systems are increasingly developed to enable automatic analysis of the large amounts of data that are accumulated. A prerequisite for the practical use of such data analysis is the veracity of the output, that is, that the analysis is clinically valid. Whereas most research focuses on the technical configuration and clinical precision of data analysis systems, the purpose of this article is to investigate how veracity is achieved in practice. Based on a study of a project in Denmark aimed at developing an algorithm for stratification of citizens in preventive healthcare, this article confirms that achieving veracity requires close attention to the clinical validity of the algorithm. It also concludes, however, that the veracity in practice hinges critically on the citizens’ ability to report high-quality data and the ability of the health professionals to interpret the outcome in the context of existing care practices.
KW - clinical decision-making
KW - data analysis
KW - preventive healthcare
KW - qualitative study
KW - risk behavior change
KW - clinical decision-making
KW - data analysis
KW - preventive healthcare
KW - qualitative study
KW - risk behavior change
U2 - 10.1177/1460458218796665
DO - 10.1177/1460458218796665
M3 - Journal article
VL - 25
SP - 491
EP - 499
JO - Health Informatics Journal
JF - Health Informatics Journal
SN - 1460-4582
IS - 3
ER -