THE USEFULNESS OF USING GENERATIVE ARTIFICIAL INTELLIGENCE IN HEALTHCARE ORGANIZATIONS

Ivelina Simeonova, PhD Student

Department of Management and Social Activities University of Ruse “Angel Kanchev”

Abstract

The paper concerns the utility of using generative artificial intelligence in the field of medicine, specifically in health care settings, looking at how quasi-experimental approaches account for case-cause connection in health systems and healthcare analysis. Quasi-experimental studies provide significant chances to enlarge and improve the evidence for causal effects. First, they have the potential to generate causal evidence when randomised controlled trials are not possible. Second, they most often produce causal proofs with a high degree of external reliability. Third, they prevent the threats to internal validity that occur when participants in so-called „Non-blinded experiments" (e.g., in transgenic studies with different phenotypes) modify their behaviour in responding to the experimental task by copying any intervention or relative the control group. Fourth, it is a fact that they are appropriate for use both as evidence of generating long-term financial outcomes in health care and as evidence of adverse economic and social consequences. And fifth, they produce a faster result and frequently at a lower cost.

Keywords

Healthcare facilities, generative AI, quasi-experimental design

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