ArticleJournal of medical systems2015
Accuracy of patient's turnover time prediction using RFID technology in an academic ambulatory surgery center.
Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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.
The trial behind it
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Real-time locating systems to improve healthcare delivery: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Measuring provider-level differences in perioperative workflow using computer vision-based artificial intelligence.BMJ health & care informatics · 2025Article
- Surgical pit crew: initiative to optimise measurement and accountability for operating room turnover time.BMJ health & care informatics · 2023Article
- Clinical Interest and Economic Impact of Preoperative SMS Reminders before Ambulatory Surgery: A Propensity Score Analysis.Journal of medical systems · 2018Article
- The Impact of Overestimations of Surgical Control Times Across Multiple Specialties on Medical Systems.Journal of medical systems · 2016Article
- Evaluation of Electromagnetic Fields in a Hospital for Safe Use of Electronic Medical Equipment.Journal of medical systems · 2016Article
- RFID analytics for hospital ward management.Flexible services and manufacturing journal · 2016Article
- Combining the ASA Physical Classification System and Continuous Intraoperative Surgical Apgar Score Measurement in Predicting Postoperative Risk.Journal of medical systems · 2015Article
- Analysis of Managers' Perception Regarding the Use of Traceability Tools in the Context of Brazilian Health.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients flow in outpatient surgical unit is a major issue with regards to resource utilization, overall case load and patient satisfaction. An electronic Radio Frequency Identification Device (RFID) was used to document the overall time spent by the patients between their admission and discharge from the unit. The objective of this study was to evaluate how a RFID-based data collection system could provide an accurate prediction of the actual time for the patient to be discharged from the ambulatory surgical unit after surgery. This is an observational prospective evaluation carried out in an academic ambulatory surgery center (ASC). Data on length of stay at each step of the patient care, from admission to discharge, were recorded by a RFID device and analyzed according to the type of surgical procedure, the surgeon and the anesthetic technique. Based on these initial data (n = 1520), patients were scheduled in a sequential manner according to the expected duration of the previous case. The primary endpoint was the difference between actual and predicted time of discharge from the unit. A total of 414 consecutive patients were prospectively evaluated. One hundred seventy four patients (42%) were discharged at the predicted time ± 30 min. Only 24% were discharged behind predicted schedule. Using an automatic record of patient's length of stay would allow an accurate prediction of the discharge time according to the type of surgery, the surgeon and the anesthetic procedure.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.