ArticleJournal of medical systems2013
Adding intelligence to mobile asset management in hospitals: the true value of RFID.
Article in Journal of medical systems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- IoT Based Predictive Maintenance Management of Medical Equipment.Journal of medical systems · 2020Article
- Real-time location system-based asset tracking in the healthcare field: lessons learned from a feasibility study.BMC medical informatics and decision making · 2018Article
- Evaluation of Electromagnetic Fields in a Hospital for Safe Use of Electronic Medical Equipment.Journal of medical systems · 2016Article
- An Ambient Intelligence Framework for End-User Service Provisioning in a Hospital Pharmacy: a Case Study.Journal of medical systems · 2015Article
- Accuracy of patient's turnover time prediction using RFID technology in an academic ambulatory surgery center.Journal of medical systems · 2015Article
- The current and future needs of our medical systems.Journal of medical systems · 2015Article
- Determinants of RFID adoption in Malaysia's healthcare industry: occupational level as a moderator.Journal of medical systems · 2015Article
- A RFID specific participatory design approach to support design and implementation of real-time location systems in the operating room.Journal of medical systems · 2015Article
- RFID in the pharmaceutical industry: addressing counterfeits with technology.Journal of medical systems · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RFID (Radio Frequency Identification) technology is expected to play a vital role in the healthcare arena, especially in times when cost containments are at the top of the priorities of healthcare management authorities. Medical equipment represents a significant share of yearly healthcare operational costs; hence, ensuring an effective and efficient management of such key assets is critical to promptly and reliably deliver a diversity of clinical services at the patient bedside. Empirical evidence from a phased-out RFID implementation in one European hospital demonstrates that RFID has the potential to transform asset management by improving inventory management, enhancing asset utilization, increasing staff productivity, improving care services, enhancing maintenance compliance, and increasing information visibility. Most importantly, RFID allows the emergence of intelligent asset management processes, which is, undoubtedly, the most important benefit that could be derived from the RFID system. Results show that the added intelligence can be rather basic (auto-status change) or a bit more advanced (personalized automatic triggers). More importantly, adding intelligence improves planning and decision-making processes.
Indexed as
Identifiers
23943057What OpenQuestion holds
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.