Using Simple Tech to Improve Patient Transfers in the AI Age

Published Date : 01/08/2025 

Explore how low-complexity technological solutions are improving inpatient handovers, despite challenges in scalability and adoption. 

In the rapidly evolving landscape of healthcare, the integration of technological solutions into clinical workflows is becoming increasingly important. The strain on clinical care, exacerbated by escalating documentation demands, has led to a growing need for innovative solutions to streamline processes and improve patient outcomes. One critical area that has seen significant attention is inpatient handover, where the transfer of patient information between healthcare providers is crucial for maintaining continuity of care and patient safety.

The advent of artificial intelligence (AI) and other advanced technologies has opened new avenues for enhancing inpatient handovers. However, the maturity, adoption scale, and impact of these technologies on clinical practice remain areas of active research. To address this gap, a scoping review was conducted to summarize the current state of technological solutions for inpatient handovers.

This study, prospectively registered on the Open Science Framework, involved a comprehensive search of publications from January 1, 2010, to January 1, 2024, in major databases such as MEDLINE, Embase, Cochrane Library, and Scopus. The inclusion criteria were stringent, focusing on studies that addressed the implementation, assessment, or enhancement of healthcare provider handover workflows in an inpatient setting, with a particular emphasis on the proposal or implementation of technological solutions.

The review process involved independent abstract and full-text screenings by two reviewers, with conflicts resolved by a third reviewer. Data extraction and synthesis were performed by multiple authors and cross-reviewed for accuracy to ensure the reliability of the findings.

The search identified 779 publications, of which 53 met the inclusion criteria. The analysis revealed a predominance of low-complexity technologies, such as electronic checklists, with limited exploration of more advanced solutions like natural language processing (NLP). The majority of studies were in the pilot stage (33/53, 62%), while a smaller number described documented implementations (11/53, 21%).

The reported outcomes of these technological solutions were predominantly positive, with improvements noted in the completeness, accuracy, and consistency of critical information during patient transfers (20/53, 38%). However, the review also highlighted significant challenges, including scalability, inconsistent adoption, and difficulties in integrating advanced technologies into existing workflows.

Despite the potential of AI to bring transformative benefits to inpatient handovers, the review found that none of the included studies reported successful clinical implementations of AI solutions aimed at improving handover processes. This limitation underscores the need for further research and development in this area.

In conclusion, low-complexity technological solutions show promise in enhancing inpatient handovers, but they face significant barriers to scalability and sustained adoption. While the integration of AI and other advanced technologies holds the potential for significant improvements, the current state of research suggests that more work is needed to overcome the existing challenges and realize the full benefits of these innovations in clinical practice. 

Frequently Asked Questions (FAQS): 

Q: What are the primary challenges in adopting technological solutions for inpatient handovers?

A: The main challenges include scalability, inconsistent adoption, and difficulties in integrating advanced technologies into existing workflows.

Q: What types of technological solutions are most commonly used in inpatient handovers?

A: Low-complexity technologies such as electronic checklists are most commonly used, with limited exploration of advanced solutions like natural language processing.

Q: What are the reported benefits of using technological solutions in inpatient handovers?

A: The reported benefits include improvements in the completeness, accuracy, and consistency of critical information during patient transfers.

Q: Why is artificial intelligence (AI) important for inpatient handovers?

A: AI has the potential to bring transformative benefits to inpatient handovers by automating and enhancing the accuracy of information transfer, but its clinical implementation is still in the early stages.

Q: What is the current state of research on AI solutions for inpatient handovers?

A: The current state of research indicates that while AI holds significant promise, no studies have reported successful clinical implementations of AI solutions aimed at improving handover processes. 

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