Selecting a Passive Network Monitoring Solution for Medical Device Cybersecurity Management

2021 ◽  
Vol 55 (4) ◽  
pp. 121-130
Author(s):  
Priyanka Upendra
Keyword(s):  
Project Management ◽  
Network Security ◽  
Medical Device ◽  
Medical Devices ◽  
Care Delivery ◽  
Network Monitoring ◽  
Program Assessment ◽  
Lessons Learned ◽  
Effective Care ◽  
Passive Network

Abstract The number of cyberattacks and information system breaches in healthcare have grown exponentially, as well as escalated from accidental incidents to targeted and malicious attacks. With medical devices representing a substantial repository of all the assets in a healthcare system, network security and monitoring are critical to ensuring cyber hygiene of these medical devices. Because of the unique challenges of connected medical devices, a passive network monitoring (PNM) solution is preferred for its overall cybersecurity management. This article is intended to provide guidance on selecting PNM solutions while reinforcing the importance of program assessment, project management, and use of leading practices that facilitate the selection and further implementation of PNM solutions for medical devices. The article provides a detailed introduction to connected medical devices and its role in effective care delivery, an overview of network security types and PNM, an overview of the National Institute of Standards and Technology Cybersecurity Framework and its application for program assessment, essentials of project management for PNM solution selection and implementation, key performance indicators for measuring a solution's ability to meet critical cybersecurity needs for medical devices, and lessons learned from the author's professional experience, selective literature review, and leading practices. Rather than describing a complete list of guidelines for selecting PNM solutions, the current work is intended to provide guidance based on the author's experience and leading practices compiled from successful medical device cybersecurity programs.

CoSeMed

2016 ◽  
pp. 1406-1431
Author(s):  
Andreas Kliem
Keyword(s):  
Medical Device ◽  
Health Systems ◽  
Medical Devices ◽  
Care Delivery ◽  
Patient Treatment ◽  
Critical Data ◽  
Treatment Processes ◽  
Novel Approach ◽  
Medical Sensors ◽  
Mission Critical

E-health systems need to dynamically integrate heterogeneous types of medical sensors and provide access to streams of sensed medical data in order to properly support patient treatment. Treatment processes usually include several steps and medical departments, which means that sensors could be moved between networks of Care Delivery Operators instead of being reattached every time. Therefore, the authors propose a novel approach that allows sharing medical devices among different operators in this chapter. This means that each operator books a medical device as long as it delivers required data and is present in the operator's network, which the authors call the medical device cloud. Besides cost effectiveness, this approach can extend traditional cloud-based e-health systems, usually designed to share Electronic Health Records, by sharing the devices that emit the data. This mitigates judicial constraints because only the data sources and not the data itself are shared, and allows for more real-time access to mission-critical data.

CoSeMed

2014 ◽  
pp. 201-227 ◽  
Author(s):  
Andreas Kliem
Keyword(s):  
Medical Device ◽  
Health Systems ◽  
Medical Devices ◽  
Care Delivery ◽  
Patient Treatment ◽  
Critical Data ◽  
Treatment Processes ◽  
Novel Approach ◽  
Medical Sensors ◽  
Mission Critical

E-health systems need to dynamically integrate heterogeneous types of medical sensors and provide access to streams of sensed medical data in order to properly support patient treatment. Treatment processes usually include several steps and medical departments, which means that sensors could be moved between networks of Care Delivery Operators instead of being reattached every time. Therefore, the authors propose a novel approach that allows sharing medical devices among different operators in this chapter. This means that each operator books a medical device as long as it delivers required data and is present in the operator's network, which the authors call the medical device cloud. Besides cost effectiveness, this approach can extend traditional cloud-based e-health systems, usually designed to share Electronic Health Records, by sharing the devices that emit the data. This mitigates judicial constraints because only the data sources and not the data itself are shared, and allows for more real-time access to mission-critical data.

Regulating Medical Devices in the United States

2020 ◽  
Author(s):  
Patricia J. Zettler ◽  
Erika Lietzan
Keyword(s):  
United States ◽  
Medical Device ◽  
Medical Devices ◽  
Complete Information ◽  
The United States ◽  
Risk Level ◽  
Management Tools ◽  
Medical Technologies ◽  
The Us ◽  
Medical Device Regulation

This chapter assesses the regulation of medical devices in the United States. The goal of the US regulatory framework governing medical devices is the same as the goal of the framework governing medicines. US law aims to ensure that medical devices are safe and effective for their intended uses; that they become available for patients promptly; and that manufacturers provide truthful, non-misleading, and complete information about the products. US medical device law is different from US medicines law in many ways, however, perhaps most notably because most marketed devices do not require pre-market approval. The chapter explores how the US Food and Drug Administration (FDA) seeks to accomplish its mission with respect to medical devicecough its implementation of its medical device authorities. It starts by explaining what constitutes a medical device and how the FDA classifies medical devices by risk level. The chapter then discusses how medical devices reach the market, the FDA's risk management tools, and the rules and incentives for innovation and competition. It concludes by exploring case studies of innovative medical technologies that challenge the traditional US regulatory scheme to consider the future of medical device regulation.

Medical Device Regulation: Requirements for Dental Professionals Who Prescribe and Manufacture Custom-Made Devices

2021 ◽  
Vol 10 (1) ◽  
pp. 64-88
Author(s):  
James I. J. Green
Keyword(s):  
Medical Device ◽  
Medical Devices ◽  
Transition Period ◽  
Eu Directive ◽  
Custom Made ◽  
Dental Setting ◽  
The Uk ◽  
Dental Professionals ◽  
The Eu ◽  
Medical Device Regulation

A custom-made device (CMD) is a medical device intended for the sole use of a particular patient. In a dental setting, CMDs include prosthodontic devices, orthodontic appliances, bruxism splints, speech prostheses and devices for the treatment of obstructive sleep apnoea, trauma prevention and orthognathic surgery facilitation (arch bars and interocclusal wafers). Since 1993, the production and provision of CMDs have been subject to European Union (EU) Directive 93/42/EEC (Medical Device Directive, MDD) given effect in the UK by The Medical Devices Regulations 2002 (Statutory Instrument 2002/618), and its subsequent amendments. Regulation (EU) 2017/745 (Medical Device Regulation, EU MDR) replaces the MDD and the other EU Directive pertaining to Medical Devices, Council Directive 90/385/EEC (Active Implantable Medical Device Directive, AIMDD). The EU MDR was published on 5 April 2017, came into force on 25 May 2017 and, following a three-year transition period was due to be fully implemented and repeal the MDD on 26 May 2020, but was deferred until 26 May 2021 due to the coronavirus disease 2019 (COVID-19) pandemic. In the UK, in preparation for the country’s planned departure from the EU, the EU MDR, with necessary amendments, was transposed into UK law (Medical Devices (Amendment etc.) (EU Exit) Regulations 2019, UK MDR). The UK left the Union on 31 January 2020 and entered a transition period that ended on 31 December 2020, meaning that, from 1 January 2021, dental professionals in Great Britain who prescribe and manufacture CMDs are mandated to do so in accordance with the new legislation while Northern Ireland remains in line with the EU legislation and implementation date. This paper sets out the requirements that relate to the production and provision of CMDs in a UK dental setting.

scholarly journals In silico imaging clinical trials: cheaper, faster, better, safer, and more scalable

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Aldo Badano
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Medical Devices ◽  
In Silico ◽  
Lessons Learned ◽  
Patient Access ◽  
High Quality ◽  
Virtual Imaging ◽  
Regulatory Evaluation

AbstractImaging clinical trials can be burdensome and often delay patient access to novel, high-quality medical devices. Tools for in silico imaging trials have significantly improved in sophistication and availability. Here, I describe some of the principal advantages of in silico imaging trials and enumerate five lessons learned during the design and execution of the first all-in silico virtual imaging clinical trial for regulatory evaluation (the VICTRE study).

Are Communities Willing to Transition Into Learning Health Care Communities? A Community-Based Participatory Evaluation of Stakeholders’ Receptivity

2021 ◽  
pp. 104973232199864
Author(s):  
Nabil Natafgi ◽  
Olayinka Ladeji ◽  
Yoon Duk Hong ◽  
Jacqueline Caldwell ◽  
C. Daniel Mullins
Keyword(s):  
Health Care ◽  
Health Care Delivery ◽  
Health Care Professionals ◽  
Care Delivery ◽  
Lessons Learned ◽  
Community Members ◽  
Community Based ◽  
Care Community ◽  
Care Experience ◽  
National Initiative

This article aims to determine receptivity for advancing the Learning Healthcare System (LHS) model to a novel evidence-based health care delivery framework—Learning Health Care Community (LHCC)—in Baltimore, as a model for a national initiative. Using community-based participatory, qualitative approach, we conducted 16 in-depth interviews and 15 focus groups with 94 participants. Two independent coders thematically analyzed the transcripts. Participants included community members (38%), health care professionals (29%), patients (26%), and other stakeholders (7%). The majority considered LHCC to be a viable model for improving the health care experience, outlining certain parameters for success such as the inclusion of home visits, presentation of research evidence, and incorporation of social determinants and patients’ input. Lessons learned and challenges discussed by participants can help health systems and communities explore the LHCC aspiration to align health care delivery with an engaged, empowered, and informed community.

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