ArticleJAMA network open2022
Use of a Real-Time Locating System to Assess Internal Medicine Resident Location and Movement in the Hospital.
Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Education Research: A Qualitative Analysis of the Role of Social Media in Neurology Trainees' Professional Identity Formation.Neurology. Education · 2026Article
- From iPatient to Ai-Patient: a responsibility to medical education.BMJ digital health & AI · 2026Article
- Time-at-bedside and competency acquisition: a secondary analysis of GM-ITE domain scores in Japanese resident physicians.BMC medical education · 2025Article
- A Systems Approach to Improving Well-Being in Graduate Medical Education.Academic medicine : journal of the Association of American Medical Colleges · 2025Article
- Self-Reported Time-at-Bedside and Its Association with In-Training Examination Scores of Residents in Japan.Journal of general internal medicine · 2025Article
- How Data Analytics Can Be Leveraged to Enhance Graduate Clinical Skills Education.Journal of graduate medical education · 2025Article
- Machine Intelligence in Cerebrovascular and Endovascular Neurosurgery.Advances in experimental medicine and biology · 2024Review
- Three Missed Critical Nursing Care Processes on Labor and Delivery Units During the COVID-19 Pandemic.Journal of obstetric, gynecologic, and neonatal nursing : JOGNN · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: The patient-physician clinical encounter is the cornerstone of medical training, yet residents spend as little as 12% of their time in direct patient contact. Objectives: To use a real-time locating system (RTLS) to characterize intern work experiences in the hospital, understand factors associated with time spent at patients' bedsides, and inform future interventions to increase time spent with patients. Design, Setting, and Participants: This cross-sectional study was conducted from July 1, 2018, to June 30, 2019 (ie, the academic year 2018-2019). Internal medicine residents from postgraduate year 1 (interns) at an academic medical center wore an infrared badge that recorded location and duration (eg, patient room, ward hall, physician workroom). Data were analyzed from September 1, 2020, to August 30, 2021. Main Outcomes and Measures: Main outcome was time (in minutes) at the bedside; the unit of analysis was a 24-hour intern day or interval of time within the day (eg, rounding period). Descriptive statistics are reported overall, by intern, and for 5 clinical service categories. Multilevel modeling assessed the association of intern, service, and calendar time with time spent at the bedside. Results: Data from 43 of 52 interns (82.7%) encompassing 95 275 hours of observations were included for analyses. Twenty-six interns (60.5%) were women. Interns were detected for a mean (SD) of 722.8 (194.4) minutes per 24-hour period; 13.4% of this time was spent in patient rooms (mean [SD] time, 96.8 [57.2] minutes) and 33.3% in physician workrooms (mean [SD] time, 240.9 [228.8] minutes). Mean percentage of time at the bedside during a 24-hour period varied among interns from 8.8% to 18.3%. Mean (SD) percentage of time at the bedside varied by service for the 24-hour period from 11.7% (6.6%) for nononcology subspecialties to 15.4% (6.0%) for oncology, and during rounds from 8.0% (12.4%) for nononcology subspecialties to 26.5% (12.1%) for oncology. In multilevel modeling, the individual intern accounted for 8.1% of overall variance in time spent at the bedside during a 24-hour period, and service accounted for 18.0% of variance during rounds. Conclusions and Relevance: The findings of this cross-sectional study support previous evidence suggesting that interns spend only a small proportion of time with hospitalized patients. The differences in time spent in patients' rooms among interns and during rounds constitute an opportunity to design interventions that bring trainees back to the bedside.
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