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In Expert review of pharmacoeconomics & outcomes research

Introduction: Despite the number of systematic reviews on how artificial intelligence is being used in different areas of medicine, there is no study on the scope of artificial intelligence methods used in outcomes research, the cornerstone of health technology assessment (HTA). This systematic scoping review aims to systematically capture the scope of artificial intelligence methods used in outcomes research to enhance decision-makers' knowledge and broaden perspectives for health technology assessment and adoption. Areas covered: The review identified 370 studies, consisted of artificial intelligence methods applied to adult patients who underwent any health/medical intervention and reported therapeutic, preventive, or prognostic outcomes. Artificial intelligence was mainly used for the prediction/prognosis of more frequently reported outcomes, efficacy/effectiveness, among morbidity outcomes. The predictive analysis was common in neoplastic disorders. Neural networks algorithm was predominantly found in surgical method studies, but a mixture of artificial intelligence algorithms was applied to the studies with the rest of the interventions. Expert opinion: There are certain gaps in artificial intelligence applications used in outcomes research across therapeutic areas and further considerations are needed by decision-makers before incorporating artificial intelligence usage into HTA decision-making processes.

Graili Pooyeh, Ieraci Luciano, Hosseinkhah Nazanin, Argent-Katwala Mary


artificial intelligence, decision-making, machine learning, outcomes research, systematic review