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Use of HL7 interface and capsule neuron for capturing data from monitors and devices in perioperative areas into OR information system in real-time to support better
patient outcomes
Betsy Kingston RN. BSN
Capital Health System, Pennington, NJ & MSN
Nursing Informatics student, Rutgers University, Newark, NJ
.
CapsuleTech Multi Bed Connection License $ 1332
CapsuleTech Single Bed Connection License $ 533
CapsuleTechNeuron $ 1423.75
CapsuleTech Device ID Module (DIM) $ 85
CapsuleTech Device Specific Serial Cable $ 93.5
CapsuleTech Patch Cable $ 18.7
Seismic 13"/33cm Wall Channel with Hardware $ 37.8
Flush/Fixed VESA Wall Mount $ 54
Power Supply Flush Channel Mount $ 45
Total cost of each Capsule Neuron $ 3537.5
Arms for connecting to Anesthesia Machines $ 1755
Medical Grade Touch Screen monitors $ 747
Workstation $ 643.5
Medical Grade Keyboards $ 337.5
Total cost of arm with other upgrades for each
Anesthesia machine $ 3483
Cost varies with individual facility and requirements
HL7 interface and capsule neuron enables instant collection of vitals and
sends key clinical data into Operating Room information system
Increase staff efficiency and accurate data being sent from point of care
device in care environment
Clinicians have fastest access to accurate data and also provide patient
surveillance and clinical decision capabilities
Assessment of Devices used in perioperative areas including hardware
and analyze the need for any other equipment from vendor done by walk
through
Analyze the need of capsule neuron and HL7 interfaces to capture data
from devices and monitors in perioperative areas
Collaborative effort with end user, vendor and nursing informatics
HL7Reader application is gateway between patient monitoring devices
network and hospital network and used to integrate, consolidate, filter and
store data.
Three steps in data acquisition and transformation process
1. Data acquired from monitor
2. Transformations to make it readable from applications
3. Export and archival in HL7 format
Clinical end user to accept and send the data ,yet to be determined
Capital health System planning to use capsule neuron in
operating room and HL7 interface in all other perioperative
areas where hospital based servers is available to capture
data from monitors and devices in real time and send into
General Electric Operating room information system to
support better patient outcomes
Automatic data entry is fast, accurate, flexible and free of
transcription errors
Health level 7 (HL7) standards are interoperable with
applications in healthcare domain and used to import vital
signs and prepare data for visualization in departmental
applications and archiving
Automatic acquisition eliminates transcription errors,
improves quality of records and allows large electronic
archives of data
Capsule helps capture vital signs for multiple patients,
validate these clinical measurements at the point of care
and automatically send them to the EMR
Timeline delayed. Spoke with other facilities about areas
learned upon like artifact impacts data reporting structure
Plan to include information in downtime policy
Testing is essential to monitor data flow and accuracy.
This would be done with clinical and IT staff thoroughly
prior to sending information on ill patient
The import of transcribed data from monitors and devices through HL7 based
interface and capsule neuron instant collection of data and sending it to GEORIS
will promote continuous collection of patient data and support clinical decisions
capabilities
Data flow directly into EMR reduces documentation errors and enhances patient
safety
Automating flow of data from patient monitors and other medical devices to the
EMR help nurses and physicians spend more time caring for the patient
System not live until July 2015. Data collection will be started then
Fonseca. T., Riberiro., C. Granja. C.2009. Vital signs in Intensive care: Automatic Acquisition and consolidation into
Electronic patient records. Journal of medical system. 33:47-57. DOI 10.1007/s10916-008-9163-7
Blazona. B., Koncar. M. 2007. HL7 and DICOM based integration of radiology departments with healthcare enterprise
information systems. International Journal of Medical Informatics. 76: 425-432. doi:10.1016/j.ijmedinf.2007.05.001
Yuksel.M., Dogac.A. 2011. Interoperability of Medical device information and clinical applications: An HL7 RMIM based
on the ISO/IEEE 11073 DIM. IEEE Transactions on Information Technology in Biomedicine. 15(4) 557-565. doi
10.1109/TITB.2011.2151868
Feb 22 2011 09:00 AM EDT GE Healthcare and Capsule Announce Relationship to Enhance Patient Monitoring and
Medical Device Connectivity
LB. Smith, et al. 2009.Reducing Errors through Automated Vital Signs Data Upload. Computers Informatics Nursing, Vol.
27, No. 5
In order to give high quality care to patients, clinical decision making is
critical in all patient care areas. Positive outcomes and management of
patients can be achieved by increasing real time data access and effective
clinical decisions whereas ineffective clinical decisions may result in various
consequences
Manual recording causes
Transcription errors
Time-consuming
Inflexible task
Error rates of 4.4% for vital signs captured on plain paper and entered into
EMR determined in a recent study
Acknowledgement and thanks to Barbara Grande MSN, RN-BC, BS,
Director of Nursing Informatics and the NI Department at Capital Health
System for involving me in this project.
Contact Information : [email protected]
Phone.No. 609-378-5170
