ArticleJournal of medical systems2017
Reliable Collection of Real-Time Patient Physiologic Data from less Reliable Networks: a "Monitor of Monitors" System (MoMs).
Article in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Rapid prediction of cerebral edema on CT scan after traumatic brain injury.Trauma surgery & acute care open · 2026Article
- Utilizing ultra-early continuous physiologic data to develop automated measures of clinical severity in a traumatic brain injury population.Scientific reports · 2024Article
- A Novel Continuous Real-Time Vital Signs Viewer for Intensive Care Units: Design and Evaluation Study.JMIR human factors · 2024Article
- Rapid prediction of secondary neurologic decline after traumatic brain injury: a data analytic approach.Scientific reports · 2023Article
- Leveraging Continuous Vital Sign Measurements for Real-Time Assessment of Autonomic Nervous System Dysfunction After Brain Injury: A Narrative Review of Current and Future Applications.Neurocritical care · 2022Review
- Adjunctive virtual reality pain relief following traumatic injury: protocol for a randomised within-subjects clinical trial.BMJ open · 2021Article
- A telediagnosis assistance system for multiple-lead electrocardiography.Physical and engineering sciences in medicine · 2021Article
- Traumatic cardiac arrest and resuscitative endovascular balloon occlusion of the aorta (REBOA): a preliminary analysis utilizing high fidelity invasive blood pressure recording and videography.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2019Article
- Design and Evaluation of a Real Time Physiological Signals Acquisition System Implemented in Multi-Operating Rooms for Anesthesia.Journal of medical systems · 2018Article
- Real-Time Fault-Tolerant mHealth System: Comprehensive Review of Healthcare Services, Opens Issues, Challenges and Methodological Aspects.Journal of medical systems · 2018Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Research and practice based on automated electronic patient monitoring and data collection systems is significantly limited by system down time. We asked whether a triple-redundant Monitor of Monitors System (MoMs) to collect and summarize key information from system-wide data sources could achieve high fault tolerance, early diagnosis of system failure, and improve data collection rates. In our Level I trauma center, patient vital signs(VS) monitors were networked to collect real time patient physiologic data streams from 94 bed units in our various resuscitation, operating, and critical care units. To minimize the impact of server collection failure, three BedMaster® VS servers were used in parallel to collect data from all bed units. To locate and diagnose system failures, we summarized critical information from high throughput datastreams in real-time in a dashboard viewer and compared the before and post MoMs phases to evaluate data collection performance as availability time, active collection rates, and gap duration, occurrence, and categories. Single-server collection rates in the 3-month period before MoMs deployment ranged from 27.8 % to 40.5 % with combined 79.1 % collection rate. Reasons for gaps included collection server failure, software instability, individual bed setting inconsistency, and monitor servicing. In the 6-month post MoMs deployment period, average collection rates were 99.9 %. A triple redundant patient data collection system with real-time diagnostic information summarization and representation improved the reliability of massive clinical data collection to nearly 100 % in a Level I trauma center. Such data collection framework may also increase the automation level of hospital-wise information aggregation for optimal allocation of health care resources.
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