The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision

Kathrin Cresswell*, Michael Rigby, Farah Magrabi, Philip Scott, Jytte Brender, Catherine K Craven, Zoie Shui-Yee Wong, Polina Kukhareva, Elske Ammenwerth, Andrew Georgiou, Stephanie Medlock, Nicolette F De Keizer, Pirkko Nykänen, Mirela Prgomet, Robin Williams

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Despite the renewed interest in Artificial Intelligence-based clinical decision support systems (AI-CDS), there is still a lack of empirical evidence supporting their effectiveness. This underscores the need for rigorous and continuous evaluation and monitoring of processes and outcomes associated with the introduction of health information technology. We illustrate how the emergence of AI-CDS has helped to bring to the fore the critical importance of evaluation principles and action regarding all health information technology applications, as these hitherto have received limited attention. Key aspects include assessment of design, implementation and adoption contexts; ensuring systems support and optimise human performance (which in turn requires understanding clinical and system logics); and ensuring that design of systems prioritises ethics, equity, effectiveness, and outcomes. Going forward, information technology strategy, implementation and assessment need to actively incorporate these dimensions. International policy makers, regulators and strategic decision makers in implementing organisations therefore need to be cognisant of these aspects and incorporate them in decision-making and in prioritising investment. In particular, the emphasis needs to be on stronger and more evidence-based evaluation surrounding system limitations and risks as well as optimisation of outcomes, whilst ensuring learning and contextual review. Otherwise, there is a risk that applications will be sub-optimally embodied in health systems with unintended consequences and without yielding intended benefits.

Original languageEnglish
Article number104889
Number of pages5
JournalHealth policy (Amsterdam, Netherlands)
Early online date12 Aug 2023
Publication statusPublished - 1 Oct 2023

Keywords / Materials (for Non-textual outputs)

  • Artificial Intelligence (AI)
  • Health information technology
  • ehealth
  • Evidence
  • Evaluation


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