Challenges and Facilitation Approaches for the Participatory Design of AI-Based Clinical Decision Support Systems: Protocol for a Scoping Review
- PMID: 39235846
- PMCID: PMC11413541
- DOI: 10.2196/58185
Challenges and Facilitation Approaches for the Participatory Design of AI-Based Clinical Decision Support Systems: Protocol for a Scoping Review
Abstract
Background: In the last few years, there has been an increasing interest in the development of artificial intelligence (AI)-based clinical decision support systems (CDSS). However, there are barriers to the successful implementation of such systems in practice, including the lack of acceptance of these systems. Participatory approaches aim to involve future users in designing applications such as CDSS to be more acceptable, feasible, and fundamentally more relevant for practice. The development of technologies based on AI, however, challenges the process of user involvement and related methods.
Objective: The aim of this review is to summarize and present the main approaches, methods, practices, and specific challenges for participatory research and development of AI-based decision support systems involving clinicians.
Methods: This scoping review will follow the Joanna Briggs Institute approach to scoping reviews. The search for eligible studies was conducted in the databases MEDLINE via PubMed; ACM Digital Library; Cumulative Index to Nursing and Allied Health; and PsycInfo. The following search filters, adapted to each database, were used: Period January 01, 2012, to October 31, 2023, English and German studies only, abstract available. The scoping review will include studies that involve the development, piloting, implementation, and evaluation of AI-based CDSS (hybrid and data-driven AI approaches). Clinical staff must be involved in a participatory manner. Data retrieval will be accompanied by a manual gray literature search. Potential publications will then be exported into reference management software, and duplicates will be removed. Afterward, the obtained set of papers will be transferred into a systematic review management tool. All publications will be screened, extracted, and analyzed: title and abstract screening will be carried out by 2 independent reviewers. Disagreements will be resolved by involving a third reviewer. Data will be extracted using a data extraction tool prepared for the study.
Results: This scoping review protocol was registered on March 11, 2023, at the Open Science Framework. The full-text screening had already started at that time. Of the 3,118 studies screened by title and abstract, 31 were included in the full-text screening. Data collection and analysis as well as manuscript preparation are planned for the second and third quarter of 2024. The manuscript should be submitted towards the end of 2024.
Conclusions: This review will describe the current state of knowledge on participatory development of AI-based decision support systems. The aim is to identify knowledge gaps and provide research impetus. It also aims to provide relevant information for policy makers and practitioners.
International registered report identifier (irrid): DERR1-10.2196/58185.
Keywords: AI; CDSS; artificial intelligence; challenges; clinical decision support system; clinical staff; co-creation; decision support; participation; participatory design; scoping review.
©Tabea Rambach, Patricia Gleim, Sekina Mandelartz, Carolin Heizmann, Christophe Kunze, Philipp Kellmeyer. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 05.09.2024.
Conflict of interest statement
Conflicts of Interest: None declared.
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