Search results

Connected Health is an emerging and rapidly developing field never before witnessed across the healthcare sector. It has the potential to transform healthcare service systems by increasing its safety, quality and overall efficiency. However, as healthcare technologies or medical devices continuously rely more on software development, one of the core challenges is examining how Connected Health is regulated – often impacting Connected Health innovation. The purpose of this paper is to present an understanding of how Connected Health is regulated. Many of these regulatory developments fall under “medical devices”, giving rise to Software-as-a-Medical Device (SaaMD).

Through an extensive literature review, this paper demystifies Connected Health regulation. It presents the outcome of expert discussions which explore the key regulatory developments in the context of Connected Health to provide a practical guide to understanding how regulation can potentially shape healthcare innovation.

Several key issues are identified, and the authors present a comprehensive overview of regulatory developments relating to Connected Health with a view to support the continued growth of IT-enabled healthcare service models. The authors also identify the key challenges in Connected Health and identify areas for future research.

A key outcome of this research is a clearer understanding of the opportunities and challenges that regulation and standards present to Connected Health. Furthermore, this research is of critical importance in a first attempt towards recognising the impact of regulation and standards compliance in Connected Health.

Medical device users are one of the principal medical device technology stakeholders. The involvement of users in medical device technology development and assessment is central to meet their needs. This study aims to examine this issue.

A structured review of the literature published from 1980 to 2005 in peer‐reviewed journals was carried out from a social science perspective to investigate user involvement practice in the development and assessment of medical device technologies. This was followed by a qualitative thematic analysis.

Medical device users include clinicians, patients, carers and others. Different kinds of medical devices are developed and assessed by user involvement. The user involvement occurs at different stages of the medical device technology lifecycle and the degree of user involvement is in the order of: design>testing and trials>deployment>concept stages. The methods most commonly used for capturing users' perspectives are usability tests, interviews and questionnaire surveys.

The relevant engineering, medical and nursing literature, which might have been useful, was not reviewed. However, useful findings emerge that apply to health care generally.

This study shows that medical device users are not homogeneous but heterogeneous in several aspects, such as needs, skills and working environments. This is an important consideration for incorporating users' perspectives in medical device technologies.

The purpose of this paper model and prioritizes barriers to product development in medical device manufacturing industries using an integrated “structural equation modelling” (SEM) and “fuzzy technique for order performance by similarity to ideal solution” (FTOPSIS) framework.

Barriers to medical device development (MDD) are adopted from literature. The initial structural model is proposed, exploratory factor analysis and confirmatory factor analysis are used to determine factor loading and model fit, respectively. Further, FTOPSIS is used to rank the barriers and sensitivity analysis is carried to check the robustness of results. The results are discussed in detail and the recommendations to overcome the barriers are presented.

Barriers analysed and prioritized in this research significantly hinder the MDD. The expert survey is used to develop an initial structural equation model of barriers to MDD, find the reliability and validity of the model. Based on the opinion of the experts, the barriers are divided into three categories – internal, policy and induced barriers. FTOPSIS is applied to rank and prioritize the barriers based on views from these three classes of experts. More reliance on imported devices leading to increased imports (B11) and lack of uniform regulatory standards (B6) are found to have the highest rank together, indicating these to be the most important barriers from the perspective considered here. Sensitivity analysis indicates that the factors are less sensitive to the weights of criteria further confirming the reliability of the initial solution.

The prioritization of barriers may vary based upon experts. Policymakers, existing and new device developers need to give utmost importance to these barriers, which will help to accelerate the indigenous development of medical devices to overcome the present dependence on imports.

This paper demonstrates an integrated structural based modelling and prioritization technique for statistical modelling and prioritization of barriers to MDD. The results and recommendations will help policymakers and manufacturers to increase the indigenous share of medical devices. The integrated methodology can be effectively applied where the need for the combined quantitative and qualitative approach is there.

This paper demonstrates an effective structural based modelling and prioritization technique. It can be effectively applied in various fields, it will help policymakers and manufacturers to increase the indigenous share of medical devices.

The purpose of this paper is to examine knowledge creation and technological diversity management by medical device manufacturers, to identify strategic directions for innovation in the medical device field.

This paper uses two types of data to assess the importance of multiple technologies and technological diversity in product development: patent applications and approvals of medical devices for sale and use in medical treatment. Additional perspective is provided by the results of a survey of management styles.

While knowledge‐creating innovation frequently combines multiple technologies, the scope of technological diversity, the variety of types of technology combined may be wider in low‐risk than in high‐risk innovation.

The sample size is too small to justify claims of statistical significance. This research should be extended to incorporate more cases and explore the theme in greater depth.

Companies that choose a high‐risk strategy are likely to be more focused on related multiple technologies with which their researchers are already familiar. Conversely, companies that choose a low‐risk strategy may have more room to experiment since, if something goes wrong, the risk to patient health is lower. Innovative medical device enterprise to seek high‐risk device development is proposed to manage optimal diversity for it.

This paper analyses two case studies relevant to growing interest in technological diversity and knowledge management in knowledge‐driven innovation in the medical device industry in Japan.

Successful device development brings substantial revenues to medical device manufacturing industries. This paper aims to evaluate factors contributing to the success of medical device development (MDD) using grey DEMATEL (decision-making trial and evaluation laboratory) methodology through an empirical case study.

The factors are identified through literature review and industry experts’ opinions. Grey-based DEMATEL methodology is used to establish the cause-effect relationship among the factors and develop a structured model. Most significant factors contributing to the success of MDD are identified. An empirical case study of an MDD and manufacturing organisation is presented to demonstrate the use of the grey DEMATEL method. Sensitivity analysis is carried out to check robustness of results.

The results of applying the grey DEMATEL methodology to evaluate success factors of MDD show that availability of experts and their experience (SF4) is the most prominent cause factor, and active involvement of stakeholders during all stages of MDD (SF3) and complete elicitation of end-user requirements (SF1) are the most prominent effect factors for successful MDD. A sensitivity analysis confirms the reliability of the initial solution.

The findings will greatly help medical device manufacturers to understand the success factors and develop strategies to conduct successful MDD processes.

In the past, few success factors to MDD have been identified by some researchers, but complex inter-relationships among factors are not analysed. Finding direct and indirect effects of these factors on the success of MDD can be a good future research proposition.

The purpose of this paper is to address three topical themes: user involvement in health services research; determining the value of new medical technologies in patient care pathways, furthering knowledge related to quality in health and social care; and knowledge exchange between manufacturers, health service supply chain networks and device users. The model is being validated in a case study in progress. The latter is a “proving ground” study for a translational research company. Medical devices play a pivotal role in the management of chronic diseases, across all care settings. Failure to engage users in device development inevitably affects the quality of clinical outcomes. A model of user engagement is presented, turning unmet needs for medical devices into viable commercial propositions.

A case study investigating the perceptions of individuals with Epidermolysis Bullosa (EB), their lay and professional carers into unmet needs. EB is an inherited condition affecting the skin and mucosal linings that leads to blistering and wounds.

Qualitative data are being collected to generate understanding of unmet needs and wound care products. These needs are being translated into new design concepts and prototypes. Prototypes will be evaluated in an n=1 experimental design, generating quantitative outcomes data.

There are generalisations from the case study, and the model outlined. New products for managing EB wounds can logically benefit other groups. The model is transferable to other clinical problems, which can benefit from research and technological advances that are integral to clinical needs and care.

This paper focuses on medical device university spin-offs (USOs), taking into account the peculiarities of financial and nonfinancial support and intellectual property rights (IPRs). The authors declare that these parameters play a significant role in business development at the early stages.

This empirical data consist of individual and group interviews in Finland and Sweden, which are later inductively analyzed.

The results show that public financial support contributes to the formation and start of sales stages in small countries and local markets. However, at the validation stage, approaches for supporting entrepreneurship in the field of medical devices may differ. The ownership of IPRs assists in the development of entrepreneurship in the region due to the transfer of research results and researchers to the industry and increases the number of spin-offs and the cooperation of universities with business.

This contribution is in the identification of the key parameters for the formation, support and development of the USOs from the point of view of the availability of financial resources and the ownership of IPRs.

The purpose of this study is to explore knowledge absorptive capacity (ACAP) (both potential and realized) and new product development (NPD) in bipolar entrepreneurial small- and medium-sized enterprises (SMEs).

In response to recent calls for research on knowledge ACAP and NPD in entrepreneurial SMEs, particularly in different contexts, this research aims to answer a specific question: What are the characteristics of ACAP (both potential and realized) and the salient issues concerning working complementarily between both types of ACAP to foster NPD in bipolar entrepreneurial SMEs (in this case, three new low-tech and three established high-tech cases)? The authors conduct case study research based on cross-case and within case analyses to answer the question.

The findings show that, in the established high-tech cases, realized ACAP plays an outsized role in developing new products and prior-related knowledge acts as a precondition for capturing useful knowledge from external sources (potential ACAP). On the contrary, in the new low-tech cases, potential ACAP is the key driver of NPD, so external knowledge from network ties becomes a crucial source of acquiring new knowledge, along with entrepreneurs’ level of skill at applying useful knowledge (realized ACAP) to achieve NPD.

On the basis of the bipolar entrepreneurial SMEs (i.e. established high-tech and new low-tech ventures), the characteristics of entrepreneurial SMEs (i.e. firm’s age, size and level of technology) affect the different roles of realized and potential ACAP in driving NPD successes. Realized ACAP plays a critical role for NPD in established high-tech SMEs, whereas potential ACAP is the main driver of NPD in new low-tech SMEs. This research has some limitations that future research should conduct quantitative research in other industries’ context as well as in other countries.

For new ventures, they should be aware that to strengthen their network ties with customers and suppliers can be an important tool for not only overcoming their limitations of existing knowledge but also acquiring tacit knowledge from the external sources. For established high-tech ventures, they should focus not only on the short-term NPD (the achievement of current NPD) but also the long-term NPD (e.g. series of new products and new strategic alliances) that can help avoid a not-invented-here syndrome situation.

The government should customize the policy to suit each targeted SME. Policymakers should play a crucial role of a linking pin among key external sources (e.g. R&D national and international institutions, SME banks and marketing agents) in different stages of the business cycle.

This research contributes to the literature of knowledge ACAP in SMEs to the understanding of the distinction roles of potential and realized ACAP as a mechanism in the different natures of entrepreneurial SMEs.

The purpose of this paper is to outline and prioritizes risk sources in medical device development (MDD) process using an integrated “structural equation modeling” (SEM) and fuzzy “technique for order performance by similarity to ideal solution (TOPSIS)” framework.

Risk sources which deter MDD process are explored through literature review. Initial structural model is proposed, factor loadings are determined by exploratory factor analysis and model fit is established by confirmatory factor analysis. Further, the sources are ranked using FTOPSIS, and sensitivity analysis is carried to check robustness of results.

The sources of risks have catastrophic effect on MDD process. The initial SEM model developed based on survey of experts is found reliable and valid which breaks up the risk sources into three categories – internal sources of risks, user-related sources of risks and third-party-related sources of risks. The risk sources are ranked and prioritized based on perspective of experts from the categories using FTOPSIS; unmet user needs/requirements is found as the most important source of risk. Results of sensitivity analysis confirm that the factors are relatively less sensitive to criteria weights confirming reliability of initial solution.

The proposed methodology combines qualitative and quantative approaches, making it little complex and lengthy, but results in dual confirmation.

The outcomes of this research will be of prime use for MDD industries to mitigate risk sources. It will help to increase the success rate of MDD.

Integrated SEM-FTOPSIS provides a unique and effective structural modeling-based decision support tool. The framework can be effectively utilized in other domains, and failure events of medical devices can be potentially controlled by applying risk mitigation measures.

Innovation is a critical factor in ensuring commercial success within the area of medical technology. Biotechnology and Healthcare developments require huge financial and resource investment, in-depth research and clinical trials. Consequently, these developments involve a complex multidisciplinary structure, which is inherently full of risks and uncertainty. In this context, early technology assessment and ‘proof of concept’ is often sporadic and unstructured. Existing methodologies for managing the feasibility stage of medical device development are predominantly suited to the later phases of development and favour detail in optimisation, validation and regulatory approval. During these early phases, feasibility studies are normally conducted to establish whether technology is potentially viable. However, it is not clear how this technology viability is currently measured. This paper aims to redress this gap through the development of a technology confidence scale, as appropriate explicitly to the feasibility phase of medical device design. These guidelines were developed from analysis of three recent innovation studies within the medical device industry.