We present a Hybrid Multiphase Porous Electrode Theory (Hybrid-MPET) model that accurately predicts the performance of Medtronic’s implantable medical device battery lithium/carbon monofluoride (CFx) ...- silver vanadium oxide (SVO) under both low-rate background monitoring and high-rate pulsing currents. The distinct properties of multiple active materials are reflected by parameterizing their thermodynamics, kinetics, and mass transport properties separately. Diffusion limitations of Li+ in SVO are used to explain cell voltage transient behavior during pulse and post-pulse relaxation. We also introduce change in cathode electronic conductivity, Li metal anode surface morphology, and film resistance buildup to capture evolution of cell internal resistance throughout multi-year electrical tests. We share our insights on how the Li+ redistribution process between active materials can restore pulse capability of the hybrid electrode, allow CFx to indirectly contribute to capacity release during pulsing, and affect the operation protocols and design principles of batteries with other hybrid electrodes. We also discuss additional complexities in porous electrode model parameterization and electrochemical characterization techniques due to parallel reactions and solid diffusion pathways across active materials. We hope our models can complement future experimental research and accelerate development of multi-active material electrodes with targeted performance.
•Hybrid-MPET model of Medtronic’s high-rate Li/CFx-SVO battery is presented.•Separate material properties, diffusion limitation, and aging are accounted for.•Model prediction accuracy is validated on large battery dataset.•Cell pulse capability restoration is explained by Li＋ redistribution across materials.•Li＋ redistribution impact on general cell operation and design principles are discussed.
In the heterogenous category of digital healthcare technologies, software with a medical purpose - i.e. therapy, diagnosis, prevention of a disease or monitoring of adherence to treatment - is ...expected have a strong impact. Indeed, it conforms to models of development and market access which are typical of information technology and unusual for healthcare. Avoiding any regulatory uncertainty is crucial for companies and competent authorities. In the European Union (EU), software with a medical purpose qualifies as a medical device, for which a strong regulatory framework is already in place. However, for patient-managed digital medical devices (pDMDs), i.e. software with a medical purpose intended to be used directly by patients, some open issues are still on the ground. These issues arise both at the EU level, related to risk-based classification and clinical evaluation, and the national level, related to prescription and reimbursement policies. The aim of this article is to analyse the classification and regulation of pDMDs in the EU, exploring the need of additional definitions, legislation or guidance.
This study investigates business models for frugal innovation (i.e. a specific form of resource-constrained innovation) in the medical device and laboratory equipment industry in the context of ...emerging markets. Based on original data from five case studies, we investigate how firms can set up value creation and value capturing mechanisms to reach new customer segments in remote rural areas with unprecedented value propositions. With this research, we contribute to the literature on frugal innovation and business models in emerging markets. It is among the first empirical studies to apply a fine-grained perspective on resource-constrained innovation in emerging markets. In doing so, we focus on its most disruptive form, which is when these innovations entail entirely new applications. We advance and detail the value proposition for frugal innovation in these industries and argue that frugal innovation create new markets. Further, we show how firms set up their value creation and value capturing mechanisms to achieve the value proposition and identify two distinct Research & Development (R&D) strategies for frugal innovation.
•Frugal innovations enable new, unprecedented applications.•There is a threefold value proposition in frugal innovations in the healthcare industry.•Firms need to tailor value creation and capturing mechanisms to implement frugal business models.•There are two specific R&D strategies for the development of frugal business models.
•A novel systematic method for medical device risk management during production and post-production using hybrid Bayesian networks (BNs).•The BN approach resolves the limitations of commonly used ...risk analysis methods.•The BN approach supports full benefit-risk analysis and individual risk assessment of medical devices.•The BN approach can produce quantified and auditable risk estimates with limited or no testing data.
Risk analysis methods for medical devices, including fault tree analysis, have limitations such as handling uncertainty and providing reasonable risk estimates with limited or no testing data. To address these limitations, this paper proposes a novel systematic method for medical device risk management using hybrid Bayesian networks (BNs). We apply the method to a Defibrillator device to demonstrate the process involved for risk management during production and post-production using 4 different scenarios: (1) where there are available testing data; (2) where there are limited or no testing data; (3) where it is a completely new device with no testing data; (4) where we are reassessing the risk of a previous model on the market based on reported hazards and injuries. In each scenario, the BN model, for the available data, provides the full probability of failure per demand distribution for each category of injury severity (fatal, critical, major, minor, negligible) and the probabilities associated with various risk acceptability criteria. The model results are validated using publicly available data for the LIFEPAK 1000 Defibrillator (PN: 320371500XX), which was recalled by Physio-Control in 2017. The results show that the device would fail the acceptability criteria for probability of fatal injury.
This paper presents a novel approach for evaluating the smart medical device selection process in a group decision-making setting in an uncertain decision environment. Intuitionistic fuzzy Choquet ...integral (IFCI) approach is applied to treat the uncertainty and vagueness in the decision-making process. IFCI also considers the interactions among the decision criteria in the data provided by the decision makers. In this paper, the emphasis is placed upon the selection of wearable monitoring devices for cardiac patients. The goal is to present the complexity of the problem, raise interest among specialists in the healthcare industry and assess smart medical devices under different evaluation criteria. The problem is formulated as a multi-criteria decision model with ten criteria and eight alternatives. The results of the IFCI model are analyzed using 9 sensitivity analysis scenarios, which prove the adequacy of the obtained results. The result of the proposed method is also compared with the IF extensions of the VIKOR, TOPSIS, COPRAS, MOORA and MULTIMOORA models in order to validate and verify the obtained outcome. The Spearman coefficient of correlation is applied to check the stability of the variations in the rankings. The results indicate that the model and the rankings it generates are sufficiently stable.
•Medical device manufacturers apply artificial intelligence (AI) to innovate their products.•The European Medical Device Regulation (EU MDR) imposes stringent requirements on medical devices.•Under ...the EU MDR, one core requirement is the application of risk management.•Qualified medical physicist experts play a key role in the safety and performance assessment of such tools.•It is of paramount importance that the MPEs become familiar with the pillars of AI and EU MDR knowledge.
Medical device manufacturers are increasingly applying artificial intelligence (AI) to innovate their products and to improve patient outcomes. Health institutions are also developing their own algorithms, to address specific needs for which no commercial product exists.
Although AI-based algorithms offer good prospects for improving patient outcomes, their wide adoption in clinical practice is still limited. The most significant barriers to the trust required for wider implementation are safety and clinical performance assurance .
Qualified medical physicist experts (MPEs) play a key role in safety and performance assessment of such tools, before and during integration in clinical practice. As AI methods drive clinical decision-making, their quality should be assured and tested. Occasionally, an MPE may be also involved in the in-house development of such an AI algorithm. It is therefore important for MPEs to be well informed about the current regulatory framework for Medical Devices.
The new European Medical Device Regulation (EU MDR), with date of application set for 26 of May 2021, imposes stringent requirements that need to be met before such tools can be applied in clinical practice.
The objective of this paper is to give MPEs perspective on how the EU MDR affects the development of AI-based medical device software. We present our perspective regarding how to implement a regulatory roadmap, from early-stage consideration through design and development, regulatory submission, and post-market surveillance. We have further included an explanation of how to set up a compliant quality management system to ensure reliable and consistent product quality, safety, and performance .
To interpret the key contents of the guidance of
issued by the IMDRF, and provide reference for the improvement of China's medical device regulatory system.
The regulatory requirements of ...personalized medical devices and point-of-care manufacture of medical device were described respectively, and the feasibility of implementing the regulation of point-of-care manufacture of medical device in China was analyzed.
The different regulatory pathways of medical devices produced at point-of-care are feasible and have different regulatory risks.
In combination with the recommendations provided by the IMDRF guidance and the clinical and regulatory realities in China, we should accelerate the improvement of the regulations and supporting documents for point-of-care manufacture of medical device in China.
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•UDI has been introduced with the new European Regulations for medical devices.•The impact of UDI on software development is of particular interest.•Labeling, privacy, assignment ...criteria, and standards should be considered.•These aspects can be managed to effectively pursue the medical device traceability.
Similarly to what already established and implemented in the United States, the concept of the Unique Device Identification (UDI) system has been introduced with the European Regulations for medical devices MDR (EU) 2017/745 and in-vitro diagnostic medical devices IVDR (EU) 2017/746 and it is on the way to become a worldwide standard. The aim of this work was to provide a possible approach for the implementation of UDI and traceability in Europe for standalone software medical devices according to lifecycle and quality system standards.
The key points of the UDI regulation were determined and analyzed in order to identify the main issues related to the manufacturing of software medical devices and, in particular, labeling, privacy aspects, UDI assignment criteria, and international standards compliance.
An approach for the management of each key point was suggested, resulting in different levels of implementation for UDI and traceability.
Among the various types of medical devices, software is an increasingly large reality with very specific characteristics that must be taken into consideration. All the relevant aspects for the implementation of the UDI should be taken into consideration to combine safety and feasibility in order to effectively pursue the traceability of these medical devices.
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