Adam X Sang1, Rebecca L Tisdale2, Derek Nielsen3, Silvia Loica-Mersa2, Travis Miller4, Ian Chong5, Lisa Shieh6. 1. Department of Surgery, Stanford University School of Medicine, Stanford, California. 2. Department of Medicine, Stanford University School of Medicine, Stanford, California. 3. Clinical Technology, Stanford Hospital and Clinics, Stanford, California. 4. Division of Plastic Surgery, Stanford University School of Medicine, Stanford, California. 5. Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California. 6. Medical Director for Quality, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Abstract
BACKGROUND: Bedside rounding involving both nurses and physicians has numerous benefits for patients and staff. However, precise quantitative data on the current extent of physician-nurse (MD-RN) overlap at the patient bedside are lacking. OBJECTIVE: This study aimed to examine the frequency of nurse and physician overlap at the patient beside and what factors affect this frequency. DESIGN: This is a prospective, observational study of time-motion data generated from wearable radio frequency identification (RFID)-based locator technology. SETTING: Single-institution academic hospital. MEASUREMENTS: The length of physician rounds, frequency of rounds that include nurses simultaneously at the bedside, and length of MD-RN overlap were measured and analyzed by ward, day of week, and distance between patient room and nursing station. RESULTS: A total of 739 MD rounding events were captured over 90 consecutive days. Of these events, 267 took place in single-bed patient rooms. The frequency of MD-RN overlap was 30.0%, and there was no statistical difference between the three wards studied. Overall, the average length of all MD rounds was 7.31 ± 0.58 minutes, but rounding involving a bedside nurse lasted longer than rounds with MDs alone (9.56 vs 5.68 minutes, P < .05). There was no difference in either the length of rounds or the frequency of MD-RN overlap between weekdays and weekends. Finally, patient rooms located farther away from the nursing station had a lower likelihood of MD-RN overlap (Pearson's r = -0.67, P < .05). CONCLUSION: RFID-based technology provides precise, automated, and high-throughput time-motion data to capture nurse and physician activity. At our institution, 30.0% of rounds involve a bedside nurse, highlighting a potential barrier to bedside interdisciplinary rounding.
BACKGROUND: Bedside rounding involving both nurses and physicians has numerous benefits for patients and staff. However, precise quantitative data on the current extent of physician-nurse (MD-RN) overlap at the patient bedside are lacking. OBJECTIVE: This study aimed to examine the frequency of nurse and physician overlap at the patient beside and what factors affect this frequency. DESIGN: This is a prospective, observational study of time-motion data generated from wearable radio frequency identification (RFID)-based locator technology. SETTING: Single-institution academic hospital. MEASUREMENTS: The length of physician rounds, frequency of rounds that include nurses simultaneously at the bedside, and length of MD-RN overlap were measured and analyzed by ward, day of week, and distance between patient room and nursing station. RESULTS: A total of 739 MD rounding events were captured over 90 consecutive days. Of these events, 267 took place in single-bed patient rooms. The frequency of MD-RN overlap was 30.0%, and there was no statistical difference between the three wards studied. Overall, the average length of all MD rounds was 7.31 ± 0.58 minutes, but rounding involving a bedside nurse lasted longer than rounds with MDs alone (9.56 vs 5.68 minutes, P < .05). There was no difference in either the length of rounds or the frequency of MD-RN overlap between weekdays and weekends. Finally, patient rooms located farther away from the nursing station had a lower likelihood of MD-RN overlap (Pearson's r = -0.67, P < .05). CONCLUSION: RFID-based technology provides precise, automated, and high-throughput time-motion data to capture nurse and physician activity. At our institution, 30.0% of rounds involve a bedside nurse, highlighting a potential barrier to bedside interdisciplinary rounding.
Authors: Stacie Vilendrer; Mary E Lough; Donn W Garvert; Monique H Lambert; Jonathan Hsijing Lu; Birju Patel; Nigam H Shah; Michelle Y Williams; Samantha M R Kling Journal: J Med Internet Res Date: 2022-06-17 Impact factor: 7.076
Authors: Brandon Tang; Ryan Sandarage; Jocelyn Chai; Kristin Anne Dawson; Katrina Rose Dutkiewicz; Stephan Saad; Vanessa Kitchin; Rose Hatala; Iain McCormick; Barry Kassen Journal: CMAJ Date: 2022-02-14 Impact factor: 8.262