Kevin M Overmann1,2, Danny T Y Wu2,3, Catherine T Xu3, Shwetha S Bindhu3, Lindsey Barrick1,2. 1. Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA. 2. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA. 3. Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
Abstract
OBJECTIVE: Modern health care requires patients, staff, and equipment to navigate complex environments to deliver quality care efficiently. Real-time locating systems (RTLS) are local tracking systems that identify the physical locations of personnel and equipment in real time. Applications and analytic strategies to utilize RTLS-produced data are still under development. The objectives of this systematic review were to describe and analyze the key features of RTLS applications and demonstrate their potential to improve care delivery. MATERIALS AND METHODS: We searched MEDLINE, SCOPUS, and IEEE following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Inclusion criteria were articles that utilize RTLS to evaluate or influence workflow in a healthcare setting. We summarized aspects of relevant articles, identified key themes in the challenges of applying RTLS to workflow improvement, and thematically reviewed the state of quantitative analytic methodologies. RESULTS: We included 42 articles in the final qualitative synthesis. The most frequent study design was observational (n = 24), followed by descriptive (n = 12) and experimental (n = 6). The most common clinical environment for study was the emergency department (n = 12), followed by entire hospital (n = 7) and surgical ward (n = 6). DISCUSSION: The focus of studies changed over time from early experience to optimization to evaluation of an established system. Common narrative themes highlighted lessons learned regarding evaluation, implementation, and information visibility. Few studies have developed quantitative techniques to effectively analyze RTLS data. CONCLUSIONS: RTLS is a useful and effective adjunct methodology in process and quality improvement, workflow analysis, and patient safety. Future directions should focus on developing enhanced analysis to meaningfully interpret RTLS data.
OBJECTIVE: Modern health care requires patients, staff, and equipment to navigate complex environments to deliver quality care efficiently. Real-time locating systems (RTLS) are local tracking systems that identify the physical locations of personnel and equipment in real time. Applications and analytic strategies to utilize RTLS-produced data are still under development. The objectives of this systematic review were to describe and analyze the key features of RTLS applications and demonstrate their potential to improve care delivery. MATERIALS AND METHODS: We searched MEDLINE, SCOPUS, and IEEE following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Inclusion criteria were articles that utilize RTLS to evaluate or influence workflow in a healthcare setting. We summarized aspects of relevant articles, identified key themes in the challenges of applying RTLS to workflow improvement, and thematically reviewed the state of quantitative analytic methodologies. RESULTS: We included 42 articles in the final qualitative synthesis. The most frequent study design was observational (n = 24), followed by descriptive (n = 12) and experimental (n = 6). The most common clinical environment for study was the emergency department (n = 12), followed by entire hospital (n = 7) and surgical ward (n = 6). DISCUSSION: The focus of studies changed over time from early experience to optimization to evaluation of an established system. Common narrative themes highlighted lessons learned regarding evaluation, implementation, and information visibility. Few studies have developed quantitative techniques to effectively analyze RTLS data. CONCLUSIONS: RTLS is a useful and effective adjunct methodology in process and quality improvement, workflow analysis, and patient safety. Future directions should focus on developing enhanced analysis to meaningfully interpret RTLS data.
Authors: Barbara Okoniewska; Alecia Graham; Marina Gavrilova; Dannel Wah; Jonathan Gilgen; Jason Coke; Jack Burden; Shikha Nayyar; Joseph Kaunda; Dean Yergens; Barry Baylis; William A Ghali Journal: J Am Med Inform Assoc Date: 2012-02-01 Impact factor: 4.497
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