Reliable Collection of Real-Time Patient Physiologic Data from less Reliable Networks: a "Monitor of Monitors" System (MoMs).
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.
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Peter F
PF
Hu
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA. syang@anes.umm.edu.
Shiming
http://orcid.org/0000-0003-0338-4268
S
Yang
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Hsiao-Chi
HC
Li
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Lynn G
LG
Stansbury
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Fan
F
Yang
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
George
G
Hagegeorge
US Air Force Center for the Sustainment of Trauma and Readiness Skills, Baltimore, MD, USA.
Catriona
C
Miller
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Peter
P
Rock
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Deborah M
DM
Stein
Department of Anesthesiology and Program in Trauma, University of Maryland School of Medicine, 11 S. Paca St. Suite LL01, Baltimore, MD, 21201, USA.
Colin F
CF
Mackenzie
D003625:Data Collection / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D004868:Equipment Failure; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation* / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D014193:Trauma Centers; D055986:Vital Signs
Data collection; Datastream; Diagnosis; Real-time; Triple redundant; Vital signs