The Use of Technology in Multidisciplinary Communication to Improve Patient-Centered Care Coordination: A Systemic Review

Background Effective interdisciplinary communication is a key component to providing holistic care in an inpatient setting. Poor communication can lead to poor patient outcomes and increased length of stay. Using artificial intelligence to improve the communication between interprofessional teams can lead to improved patient-centered care coordination and better patient outcomes.

Objective To gather information regarding the effect of using artificial intelligence or technology on multidisciplinary communication to improve patient navigation.

Methods A comprehensive search of PubMed, the Cochrane Library, and CINHAL was performed to create a systemic review of all research investigating the use technology to improve care coordination. Inclusion criteria included “technology or artificial intelligence or informatics,” “communication or communicating or communicate or conversation,” “interdisciplinary or multidisciplinary or interprofessional or transdisciplinary,” and “care coordination or navigation or patient centered care coordination.” Only articles written in the last 10 years in the English language from academic journals were included. Research articles were critiqued for validity and quality.

Results Twelve articles were included in the review: 4 systemic reviews, 4 qualitative studies, 2 quasi experimental designs, 1 randomized controlled trial, and 1 root cause analysis. Based on the appraised evidence, technology is an effective tool used to enhance the communication between multidisciplinary teams. Results indicated decreased length of stay, improved patient outcomes, and improved nursing care following the introduction of technology. However, data is not robust in this subject and more research must be completed to confirm the accuracy of the results.

Conclusions Although using technology to better communicate has demonstrated positive outcomes such as decreased length of stay, improved coordination of care, improved quality of care, decreased readmission rates, and increased patient satisfaction, more quality research is needed to confirm these results.

Implications for Practice Artificial intelligence can be implemented into practice in an inpatient oncology setting as a means to develop the communication between medical teams. Better communication can lead to better coordinated care and, ultimately, decreased length of stay and increased patient satisfaction. In a specialty where readmission rates are high and hospital admissions are long, techniques to enhance the navigation of oncology patients are imperative to the advancement of the field.