SBIR/STTR Research Award

An Interoperable HL7 FHIR-based Medical Device Data System (MDDS) For Accessing And Integrating Live Point-Of-Care Data From High-Acuity Bedside Patient Monitoring Equipment

Award identifier 151fd2138d3a5e5d1c06581042abdd7dc6777e1e149abf57e232e78150587cc1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$251,605

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
MEDICOLLECTOR LLC
Proposal award date
2020-09-30
Contract end date
2021-09-29
UEI
KEJBNBMDVSX5
Solicitation number
PA20-272
Topic code
NIBIB

Research abstract

Abstract The overall goal of this proposal is to combine expertise and approaches from biomedical engineering and critical care medicine to design a universal system to acquire, record and transmit physiological signals from bedside monitored patients. Patient monitors generate over a million datapoints of information per hour, however, only a tiny fraction of those data are transmitted or recorded. In order to improve data exchange in healthcare, the Fast Healthcare Interoperability Resources (FHIR) standard was published in 2014. However, it has yet to make a significant impact on Medical Device Integration (MDI), which is the process of automating the flow of clinical data from bedside medical devices, such as patient monitors, to external systems such as Electronic Medical Records (EMR). Also, MDI is a complex task because data from these devices are high-frequency and high- volume and because most devices use proprietary protocols and outdated interfaces such as serial cables. Hospitals and researchers have therefore been left with few options except to use expensive and vendor-specific MDI solutions to access these data or to use manual data entry into the patient EMR, which leads to data entry errors, late entry of data, and lost time for clinical care. Manual data entry only captures a tiny fraction of the available data, and with increased research interest in Artificial Intelligence (AI) and Machine Learning, there is a growing need for a standardized way to access the vast amounts of data from bedside devices. This project will develop a vendor-neutral software-based Medical Device Data System (MDDS) that acquires and records data from bedside devices across a hospital network and makes live data available to 3rd party systems using a FHIR application programming interface (API). The proposed proof-of-concept will consist of three elements: [i] a transmitter which encrypts and transmits patient signals across the network, [ii] an aggregator which receives, translates and records the signals to a central location, and [iii] a FHIR Server with API for allowing external systems to access live data as FHIR resources. This proposal seeks to create a novel design that will overcome a critical barrier in healthcare, medicine and research. The proposed MDDS will be valuable to hospitals, clinicians, researchers and app developers because it makes data accessible which were previously only available to clinicians at the bedside in real-time.Narrative MediCollector’s proposed vendor-neutral medical device data system (MDDS) will be a valuable research tool to access, acquire and record high-frequency bedside patient monitor data for facilitating clinical research in hospitals. In addition, it will make live patient monitor data accessible to external systems through an HL7 FHIR application programming interface (API), thereby improving interoperability in hospitals and opening the doors to the integration of live data into external systems, such as smartphone apps and artificial intelligence algorithms, which can improve clinical workflow and healthcare in general.

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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