How Artificial Intelligence Can Help in Quickly Translating Published Research in Real-World Practice and Policymaking?

BY Ahtisham Younas, PhD, RN

Published research needs to be used in real-world practice for making a meaningful difference in lives of patients, families, health care professionals, and other individuals whom the research affects. We know from research that it could take about 15 to 17 years for the published research to make it into real-world practice and policymaking, and about 85% of the research is never used in practice. A new scientific field called implementation science deals with designing innovative and effective behavior change methods and techniques for accelerating the transfer of high-quality published research in practice and policymaking.

In this era, Artificial Intelligence (AI) has been used in almost every field, but how it can help us improve the work we do within implementation science is not yet discussed. In our paper, we noted some concrete ways on how AI can be used at different stages of implementing high quality research in real-world practice in health care. These ways are briefly summarized below.

Health care organizations have access to a large amount of data about patients, health care procedures, processes, and outcomes. These large datasets are often used in implementation science to explore and understand variety of patient, unit, organizational, and system level factors, and health care approaches and their outcomes. AI can be useful in effectively and efficiently managing these large datasets for use.
Implementation scientists cannot translate high quality research into practice alone. They always work with teams (including practitioners, clinicians, leaders, and managers) to make it possible that research is used in real-world as quickly as possible. AI-based tools and guidelines can help these teams to work with real-world data and information on implementation interventions, strategies, processes, and challenges.
Implementation teams can use AI methods to design and develop implementation strategies with the highest potential to bringing change and optimize the effect of these strategies by tailoring them in accordance with organizations and individuals’ needs with more precision.

Translating published research in real-world practice and policymaking in a timely, efficient, and sustainable way is important for delivering high-quality health care. AI use from the beginning of implementation planning to the delivery and evaluation can help with more precise and accurate translation of published research into practice.

Article details

Leveraging Artificial Intelligence for Expediting Implementation Efforts
Ahtisham Younas & Staci S Reynolds
First Published: March 20, 2024
DOI: 10.1177/10784535241239059
Creative Nursing

About the Author

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Ahtisham Younas, PhD, RN, (he/him), is an Assistant Professor at Memorial University of Newfoundland, Canada. Dr. Ahtisham Younas’ program of research has two streams. The first stream focuses on developing nurses/nursing students’ caring and behavioral competencies (e.g., social justice, compassion, self-awareness, ethical sensitivity, ethical decision-making, and caregiving) to improve compassionate and person-centered care for marginalized and underserved populations.

The second stream focuses on understanding and addressing the impact of social and structural determinants on care and self-management of underserved populations. Dr. Younas is a research methodologist with expertise in mixed methods, Q-methodology, implementation science, advanced quantitative and qualitative methodologies, scoping, integrative, and qualitative research reviews.