Co-design open-source medical devices: how to minimize the human error using UBORA e-infrastructure*

Pupils can provide important neurological information that can aid in the diagnosis of a range of conditions, including aneurysms, impending strokes and tumors in the lung (Gale, et al). In a research context, there is increasing interest in studying the intrinsically photosensitive Retinal Ganglion cells (ipRGC), which respond to intense blue light thanks to a photo pigment called melanopsin. Studying these cells could lead to a better understanding of sleep disorders and a range of optic nerve diseases. Although commercially available pupil testing devices do exist, all cost upwards of $10,000, and suffer from either poor portability or limitations in the tests they can perform. Specifically, the ipRGC require a specific intensity of blue light to be activated and measured, which most devices cannot produce. In recent years, the open source movement has enabled users from around the world to freely collaborate on the development and distribution of their own products. At first, only software could be produced using this approach, however the continued improvement of 3D printing technology has enabled the same model to be applied to physical products as well. From a medical perspective, this is particularly exciting. The aim of this research was to produce an inexpensive, open source pupilometer that runs on widely available components, can be distributed online and manufactured using 3D printing technology. In doing so, this thesis asks the question; How can an open source development and distribution model be used in conjunction with online 3D printing services and widely available parts and components to produce an inexpensive and open source pupilometer? To answer this, a range of practice based methodologies, including research for design and research through design were used to explore this new potential. The resulting design proposal demonstrates how online file sharing platforms, in conjunction with distributed 3D printing services and online supply chains can be combined to develop new medical devices. The ability to collect pupil data using an open source pupilometer may lead to expanded data collection and diagnostic capabilities from doctors in a number of clinical settings, while a cloud based data collection system taking the form of a smartphone app will create a large biometric database and cooperative online research community.

Download Full-text

Medical device safety: Investigating contributions of human factors

10.7287/peerj.preprints.1840 ◽

2016 ◽

Author(s):

Kathrin Lange

Keyword(s):

Adverse Events ◽

Human Factors ◽

Medical Device ◽

Medical Devices ◽

Human Error ◽

Long Term Memory ◽

Serious Adverse Events ◽

True Value ◽

Federal Institute ◽

Medical Device Safety

The core tasks of the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte [BfArM]) with respect to medical device safety include evaluating risks arising from the use or application of medical devices (based on incident reports), assessing and coordinating the counter-measures to be taken (i.e. corrective actions), and authorizing clinical trials of medical devices and evaluating the corresponding serious adverse events. Additionally, the BfArM also conducts research on medical device safety, specifically on the possibilities and challenges of data-driven approaches to detect and evaluate risk and on the contribution of human factors to device safety – i.e. factors that may have an impact on how users interact with a device. The present talk focuses on this latter issue. The significance of addressing human factors relating to the use of medical devices results from the contribution of human error to adverse events. For instance, an involvement of human error could be identified in a good 10% of the reports of suspected device-related incidents evaluated by the BfArM between 2005 and 2014. For several reasons, it may be assumed that the true value of device-related incidents involving human error is even larger and that the potential for human error is likely to increase in the future. To effectively reduce the risk for human error – or block its negative outcome - it is imperative to not only identify human error as a significant cause of adverse events, but rather understand the causation of the error, including the conditions under which errors are likely to occur. This requires the analysis of the perceptual, cognitive (e.g. attention, working memory, long term memory), motor or motivational processes involved and the identification of relevant factors at the various levels of the socio-technical system. In our research, we currently pursue two selected human factors issues, selected based on the incident-data collected at the BfArM and on the current literature: Insufficient device knowledge and the multi-faceted issue of device alarms, the latter including both the users’ interactions with alarming devices and their perceptual, cognitive, or motor responses to the devices’ alarms.

Download Full-text

Open-source medical devices: Healthcare solutions for low-, middle-, and high-resource settings

Clinical Engineering Handbook ◽

10.1016/b978-0-12-813467-2.00002-x ◽

2020 ◽

pp. 7-14

Author(s):

Carmelo De Maria ◽

Licia Di Pietro ◽

Alice Ravizza ◽

Andres Diaz Lantada ◽

Arti Devi Ahluwalia

Keyword(s):

Open Source ◽

Medical Devices ◽

High Resource

Download Full-text

MEDICAL EQUIPMENT RELIABILITY: A REVIEW, ANALYSIS METHODS AND IMPROVEMENT STRATEGIES

International Journal of Reliability Quality and Safety Engineering ◽

10.1142/s0218539311004317 ◽

2011 ◽

Vol 18 (04) ◽

pp. 391-403 ◽

Cited By ~ 3

Author(s):

B. S. DHILLON

Keyword(s):

Reliability Analysis ◽

Medical Devices ◽

Medical Equipment ◽

Human Error ◽

Equipment Maintenance ◽

Equipment Failure ◽

Related Data ◽

Equipment Reliability ◽

Review Analysis ◽

Improvement Strategies

This paper presents facts and figures, directly or indirectly, related to medical equipment reliability and reviews various important aspects, directly or indirectly, concerned with medical equipment reliability including classifications of medical devices/equipment, human error in medical equipment, useful guidelines for reliability and other professionals to improve medical equipment reliability, and medical equipment maintenance. A number of methods considered useful for performing medical equipment reliability analysis are also presented. Useful sources and organizations for obtaining medical equipment failure-related data are listed.

Download Full-text

Open-Source Medical Devices (OSMD) Design of a Small Animal Radiotherapy System

Journal of Physics Conference Series ◽

10.1088/1742-6596/489/1/012017 ◽

2014 ◽

Vol 489 ◽

pp. 012017 ◽

Cited By ~ 1

Author(s):

S Prajapati ◽

T R Mackie ◽

R Jeraj

Keyword(s):

Open Source ◽

Medical Devices ◽

Small Animal ◽

Small Animal Radiotherapy

Download Full-text

Human Factors Applications to Health Care Systems

Proceedings of the Human Factors Society Annual Meeting ◽

10.1518/107118189786757923 ◽

1989 ◽

Vol 33 (17) ◽

pp. 1167-1167

Author(s):

Susan Meadows

Keyword(s):

Human Factors ◽

Medical Device ◽

Medical Devices ◽

Human Error ◽

Health Care Systems ◽

Healthcare Systems ◽

Instructional Materials ◽

Design Standards ◽

Demonstration Program ◽

Care Systems

This demonstration program shows how human factors design and evaluation principles can be applied to the area of medical device and healthcare systems. The objective is to provide examples of evaluations and new designs for healthcare products which reduce human error and improve medical devices and instructional materials. International performance and design standards incorporating human factors principles are gaining more attention because of the efforts of the European medical device industry to standardize products.

Download Full-text

TH-C-204B-09: Development of a Small Animal Imaging and Therapy System: An Open Source Medical Devices (OSMD) Concept

Medical Physics ◽

10.1118/1.3469501 ◽

2010 ◽

Vol 37 (6Part13) ◽

pp. 3457-3457

Author(s):

S Prajapati ◽

T Mackie ◽

R Jeraj

Keyword(s):

Open Source ◽

Medical Devices ◽

Small Animal Imaging ◽

Small Animal ◽

Animal Imaging

Download Full-text