Literature DB >> 27817131

Reliable Collection of Real-Time Patient Physiologic Data from less Reliable Networks: a "Monitor of Monitors" System (MoMs).

Peter F Hu1, Shiming Yang2, Hsiao-Chi Li1, Lynn G Stansbury1, Fan Yang1, George Hagegeorge1, Catriona Miller3, Peter Rock1, Deborah M Stein1, Colin F Mackenzie1.   

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.

Entities:  

Keywords:  Data collection; Datastream; Diagnosis; Real-time; Triple redundant; Vital signs

Mesh:

Year:  2016        PMID: 27817131     DOI: 10.1007/s10916-016-0648-5

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  16 in total

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Review 5.  Real-Time Fault-Tolerant mHealth System: Comprehensive Review of Healthcare Services, Opens Issues, Challenges and Methodological Aspects.

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