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

摘要 这项提案的总体目标是将生物医学工程和关键技术的专业知识和方法结合起来 护理医学设计一套通用的床边生理信号采集、记录和传输系统 监控病人。患者监视器每小时生成超过一百万个数据点的信息，然而，只有 这些数据中只有一小部分被传输或记录。为了改善医疗保健的数据交换，FAST 医疗保健互操作性资源(FHIR)标准于2014年发布。然而，它还没有做出一个 对医疗设备集成(MDI)产生重大影响，MDI是自动化临床流程的过程 从床边医疗设备(如患者监视器)到外部系统(如电子医疗)的数据 记录(电子病历)。此外，MDI是一项复杂的任务，因为来自这些设备的数据是高频和高频的。 因为大多数设备使用专有协议和过时的接口，如串口电缆。 因此，医院和研究人员别无选择，只能使用昂贵的和特定于供应商的 MDI解决方案，用于访问这些数据或使用手动数据录入患者电子病历，从而导致数据录入 错误、数据输入延迟以及临床护理时间的损失。手动数据录入只捕获了 可用的数据，随着对人工智能(AI)和机器学习的研究兴趣的增加，有 越来越需要一种标准化的方式来访问来自床边设备的海量数据。这个项目 将开发供应商中立的基于软件的医疗设备数据系统(MDDS)，该系统可获取和记录 来自医院网络的床边设备的数据，并使实时数据可供第三方系统使用 FHIR应用编程接口(API)。拟议的概念验证将由三个要素组成： [i]通过网络加密和传输患者信号的发送器，[ii]聚合器，其 接收、转换信号并将其记录到中央位置，以及[iii]带有API的FHIR服务器 外部系统将实时数据作为FHIR资源进行访问。这项提议旨在创造一种新颖的设计，将 克服医疗、医药和研究方面的关键障碍。拟议的MDDS将对 医院、临床医生、研究人员和应用程序开发人员，因为它使人们可以访问以前 仅提供给床边的临床医生实时使用。

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data from these devices are high-frequency and high- volume and because most devices use proprietary protocols and outdated interfaces such as serial cables.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.