课题基金 / 基金详情

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

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
基于 HL7 FHIR 的可互操作医疗设备数据系统 (MDDS),用于访问和集成来自高敏锐度床边患者监护设备的实时护理点数据
批准号:
10353084
负责人:
John Paul Osborne
金额:
$4.1万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-06-11 至 2022-09-29

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
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data from these devices are high-frequency and high- volume and because most devices use proprietary protocols and outdated interfaces such as serial cables.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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金