The Solution

The NEO
A neonatal bedside surveillance device.

NEO is an IoT-based device connected to bedside medical devices irrespective of the brand enabling automatic capture of real-time data outputs and live camera feeds. This data is then seamlessly parsed and pushed to the iNICU computer intelligence via the local network or hospital protected WiFi.

It improves efficiency by reducing the time and effort for data entry and also enhances improved clinical outcome. The data produced every second by devices is stored permanently enabling timely correlation of clinical data and video streams to identify critical events

EMR Integration

iNICU combines data streamed from each neonate with EMR data including laboratory results, demographic patient background, nutrition, medication and charting inputs. This tight integration with EMR, enables care teams to visualize real time charting and personal history data in the context of the continuous flow data on the neonates’ condition.

The clinical interface on the iNICU platform presents the EMR information seamlessly inside the web and mobile NICU dashboard avoiding the need for care teams to switch between separate user consoles.

iNICU computer intelligence

The heart of the iNICU platform is its computer intelligence software core. Using the integrated flow of continuous data from the NEO device and the integration with EMR data, the iNICU is capable of streamlining the entire workflow of the Neonatal Intensive Care Unit.

Three key features of the iNICU Platform:

1)  iNICU collates and organizes data from each neonate and presents the information in a dashboard that reflects the state of each patient in real time. Care teams can drill down from the summary dashboard to selectively focus on any specific component of the data. This capability streamlines and automates NICU workflow for each neonate from the day of admission/birth until the discharge of the baby.

2)  iNICU also provides the doctors and nurses with a solution to the distraction from immediate care posed by the need to manually update many patient records (such as recording nutrition data, preparing progress notes and discharge summaries). iNICU automatically generates progress notes throughout the neonates stay in the NICU.

3)  iNICU aggregates data for each neonate across time and across all neonates in the NICU enabling a foundation of reliable data for NICU performance improvement through Quality Assurance bundles to optimize workflow, personnel performance and financial results in the Neonatal Intensive Care Unit.

Managing Quality Improvement

iNICU’s multidimensional time-series  dataset drawing from  physiological data provided by bedside medical devices, live video streaming and EMR when paired with machine learning capability enables automation of NICU Quality improvement functions.  Using various algorithms and machine learning models, iNICU is able to identify and highlight trends and alert care teams to better optimize NICU performance and compliance management.. iNICU Quality Improvement Bundles include capture and analysis of process indicators applicable to:

• Sepsis
• Necrotizing Enterocolitis (NEC)
• Broncopulmonary Displasia (BPD)
• Hypothermia and Hyperthermia
• Intraventricular Haemorrage
• Antimicrobial Stewardship

The iNICU software supports formating and design of QI alerts and reporting. It allows user customization of purpose, access parameters, inclusion criteria, data elements for compliance checks, targets and rules and recommendations to ensure compliance.  Real time status of each QI Bundle is available to care teams with authorized access from bedside, nursing station or doctor’s office.

Real time data streaming and iNICU’s highly configurable dashboard make it possible for care teams to understand instantaneous overall compliance status of any QI Bundle while also drilling down to individual neonate compliance status. iNICU also provides suggestions for  most probable reasons for non-compliance

Bedside video capture systems become more than a ‘babycam’

Web camera systems, used in many NICUs, allow virtual visitation by parents and family members.  These systems generally have been received favorably by parents and they have provided useful “babycam” images for care teams who cannot be constantly at the neonate’s side.  However, huge opportunities have been missed because video data is not matched with vitals already captured by other medical devices.

iNICU’s NEO device converts cribside web cameras into IoT peripherals streaming video together with other physiological parameters.  This data integration vastly expands the value of NICU bedside video.  iNICU’s autonomous detection and classification of the video-recorded neonatal journey and associated physiological parameters gives NICU care teams anytime, anywhere access to visuals of the neonate in the context of physiological data and what the neonate is actually experiencing.  Such events and manipulations include feeding, diaper change, patting, unattended extubation, central line status and other events core to QI parameters.  In short, iNICU’s simultaneous physiological signal monitoring and activity recognition informs care teams of the  neonate’s moment by moment condition while also documenting important QI processes.