Kevin King1, John Quarles2, Vaishnavi Ravi2, Tanvir Irfan Chowdhury2, Donia Friday3, Craig Sisson1, Yusheng Feng4. 1. Department of Emergency Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States. 2. Department of Computer Science, University of Texas at San Antonio, San Antonio, Texas, United States. 3. Department of Pediatrics, San Antonio Uniformed Services Health Education Consortium, San Antonio, Texas, United States. 4. Department of Mechanical Engineering, University of Texas at San Antonio, San Antonio, Texas, United States.
Abstract
BACKGROUND: Through the Health Information Technology for Economic and Clinical Health Act of 2009, the federal government invested $26 billion in electronic health records (EHRs) to improve physician performance and patient safety; however, these systems have not met expectations. One of the cited issues with EHRs is the human-computer interaction, as exhibited by the excessive number of interactions with the interface, which reduces clinician efficiency. In contrast, real-time location systems (RTLS)-technologies that can track the location of people and objects-have been shown to increase clinician efficiency. RTLS can improve patient flow in part through the optimization of patient verification activities. However, the data collected by RTLS have not been effectively applied to optimize interaction with EHR systems. OBJECTIVES: We conducted a pilot study with the intention of improving the human-computer interaction of EHR systems by incorporating a RTLS. The aim of this study is to determine the impact of RTLS on process metrics (i.e., provider time, number of rooms searched to find a patient, and the number of interactions with the computer interface), and the outcome metric of patient identification accuracy METHODS: A pilot study was conducted in a simulated emergency department using a locally developed camera-based RTLS-equipped EHR that detected the proximity of subjects to simulated patients and displayed patient information when subjects entered the exam rooms. Ten volunteers participated in 10 patient encounters with the RTLS activated (RTLS-A) and then deactivated (RTLS-D). Each volunteer was monitored and actions recorded by trained observers. We sought a 50% improvement in time to locate patients, number of rooms searched to locate patients, and the number of mouse clicks necessary to perform those tasks. RESULTS: The time required to locate patients (RTLS-A = 11.9 ± 2.0 seconds vs. RTLS-D = 36.0 ± 5.7 seconds, p < 0.001), rooms searched to find patient (RTLS-A = 1.0 ± 1.06 vs. RTLS-D = 3.8 ± 0.5, p < 0.001), and number of clicks to access patient data (RTLS-A = 1.0 ± 0.06 vs. RTLS-D = 4.1 ± 0.13, p < 0.001) were significantly reduced with RTLS-A relative to RTLS-D. There was no significant difference between RTLS-A and RTLS-D for patient identification accuracy. CONCLUSION: This pilot demonstrated in simulation that an EHR equipped with real-time location services improved performance in locating patients and reduced error compared with an EHR without RTLS. Furthermore, RTLS decreased the number of mouse clicks required to access information. This study suggests EHRs equipped with real-time location services that automates patient location and other repetitive tasks may improve physician efficiency, and ultimately, patient safety. Georg Thieme Verlag KG Stuttgart · New York.
BACKGROUND: Through the Health Information Technology for Economic and Clinical Health Act of 2009, the federal government invested $26 billion in electronic health records (EHRs) to improve physician performance and patient safety; however, these systems have not met expectations. One of the cited issues with EHRs is the human-computer interaction, as exhibited by the excessive number of interactions with the interface, which reduces clinician efficiency. In contrast, real-time location systems (RTLS)-technologies that can track the location of people and objects-have been shown to increase clinician efficiency. RTLS can improve patient flow in part through the optimization of patient verification activities. However, the data collected by RTLS have not been effectively applied to optimize interaction with EHR systems. OBJECTIVES: We conducted a pilot study with the intention of improving the human-computer interaction of EHR systems by incorporating a RTLS. The aim of this study is to determine the impact of RTLS on process metrics (i.e., provider time, number of rooms searched to find a patient, and the number of interactions with the computer interface), and the outcome metric of patient identification accuracy METHODS: A pilot study was conducted in a simulated emergency department using a locally developed camera-based RTLS-equipped EHR that detected the proximity of subjects to simulated patients and displayed patient information when subjects entered the exam rooms. Ten volunteers participated in 10 patient encounters with the RTLS activated (RTLS-A) and then deactivated (RTLS-D). Each volunteer was monitored and actions recorded by trained observers. We sought a 50% improvement in time to locate patients, number of rooms searched to locate patients, and the number of mouse clicks necessary to perform those tasks. RESULTS: The time required to locate patients (RTLS-A = 11.9 ± 2.0 seconds vs. RTLS-D = 36.0 ± 5.7 seconds, p < 0.001), rooms searched to find patient (RTLS-A = 1.0 ± 1.06 vs. RTLS-D = 3.8 ± 0.5, p < 0.001), and number of clicks to access patient data (RTLS-A = 1.0 ± 0.06 vs. RTLS-D = 4.1 ± 0.13, p < 0.001) were significantly reduced with RTLS-A relative to RTLS-D. There was no significant difference between RTLS-A and RTLS-D for patient identification accuracy. CONCLUSION: This pilot demonstrated in simulation that an EHR equipped with real-time location services improved performance in locating patients and reduced error compared with an EHR without RTLS. Furthermore, RTLS decreased the number of mouse clicks required to access information. This study suggests EHRs equipped with real-time location services that automates patient location and other repetitive tasks may improve physician efficiency, and ultimately, patient safety. Georg Thieme Verlag KG Stuttgart · New York.
Authors: Eric L Singman; Chantal V Haberman; Jeffrey Appelbaum; Jing Tian; Karen Shafer; Matthew Toerper; Susanne Katz; Maureen Kelsay; Michael V Boland; Milton Greenbaum; Rebecca Adelman; Richard C Thomas; Sharif Vakili Journal: Qual Manag Health Care Date: 2015 Oct-Dec Impact factor: 0.926
Authors: Heather L Farley; Kevin M Baumlin; Azita G Hamedani; Dickson S Cheung; Michael R Edwards; Drew C Fuller; Nicholas Genes; Richard T Griffey; John J Kelly; James C McClay; Jeff Nielson; Michael P Phelan; Jason S Shapiro; Suzanne Stone-Griffith; Jesse M Pines Journal: Ann Emerg Med Date: 2013-06-21 Impact factor: 5.721