Data ambiguity and clinical decision making: A qualitative case study of the use of predictive information technologies in a personalized cancer clinical trial

Research output: Contribution to journalArticlepeer-review

Abstract

Personalized medicine aims to tailor the treatment to the specific characteristics of the individual patient. In the process, physicians engage with multiple sources of data and information to decide on a personalized treatment. This article draws on a qualitative case study of a clinical trial testing a method for matching treatments for advanced cancer patients. Specialists in the trial used data and information processed by a specifically developed drug-efficacy predictive algorithm and other information artifacts to make personalized clinical decisions. While using high-resolution data in the trial was expected to provide a more accurate basis for action, sociomaterial engagements of oncologists with data and its representation by artifacts paradoxically hindered personalized clinical decisions. I contend that the engagement between human discretion, ambiguous data, and malleable artifacts in this non-standardized trial produced moments of contradiction within entanglement. Sociomaterial approaches should acknowledge such conflicts in further analyses of medical practice transitions.

Original languageEnglish
Pages (from-to)500-510
Number of pages11
JournalHealth Informatics Journal
Volume25
Issue number3
DOIs
Publication statusPublished - Sep 1 2019

Keywords

  • ambiguity
  • clinical decision-making
  • molecular data
  • personalized cancer medicine
  • predictive information technology

ASJC Scopus subject areas

  • Health Informatics

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