Technological Solutions to Improve Inpatient Handover in the Era of Artificial Intelligence: Scoping Review - Louis Agha-Mir-Salim; Isabelle Rose Alberto; Nicole Rose Alberto; Leo Anthony Celi; Pia Gabrielle Alfonso; Rachel Hicklen; Katelyn Legaspi; Rajiv Hans Menghrajani; Faye Yu Ng; Patricia Therese Pile; Christopher M Sauer (Journal of Medical Internet Research)
Abstract BackgroundClinical care globally faces increasing strain due to escalating documentation demands. Simultaneously, technological solutions for clinical workflows, particularly inpatient handovers, are being developed to alleviate workforce stress. However, the maturity, adoption scale, and impact of these technologies on clinical practice remain unclear. ObjectiveTo address this gap, we conducted a scoping review to summarize current advancements in technological solutions for inpatient handovers. MethodsThis study was prospectively registered on Open Science Framework. Publications from January 1, 2010, to January 1, 2024, were retrieved from MEDLINE, Embase, Cochrane Library, and Scopus. To be included in this review, studies were required to focus on (1) the implementation, assessment, or enhancement of health care provider handover workflows; (2) inpatient setting; and (3) the proposal or implementation of one or more technological solutions. Abstract and full-text screenings were conducted independently by 2 reviewers, with conflicts resolved by a third reviewer. Data extraction and synthesis were performed by multiple authors and cross-reviewed for accuracy. ResultsThe search identified 779 publications, of which 53 met the inclusion criteria. Analysis revealed a predominance of low-complexity technologies, such as electronic checklists, with limited exploration of advanced solutions like natural language processing. Most studies were in the pilot stage (33/53, 62%), while some described documented implementations (11/53, 21%). Reported outcomes included improvements in the completeness, accuracy, and consistency of critical information during patient transfers (20/53, 38%). Challenges included scalability, inconsistent adoption, and difficulties integrating advanced technologies into existing workflows. ConclusionsLow-complexity technological solutions show potential for enhancing inpatient handovers but face barriers to scalability and sustained adoption. While artificial intelligence (AI) has the potential to bring transformative benefits, a limitation of this review is that none of the included studies reported successful clinical implementations of AI solutions aimed at improving handover processes.