Barriers and facilitators of patient access to medical devices in Europe: A systematic literature review

Beck, Ann Jean C.C.; Retèl, Valesca P.; Bhairosing, Patrick A.; Brekel, M.W.M. van den; Harten, Wim H. van

doi:10.1016/j.healthpol.2019.10.002

Cited by 17 publications

(20 citation statements)

References 54 publications

(349 reference statements)

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“…More and more research is showing that newly developed algorithms can process specialized tasks just as well as experienced health professionals or can increase their efficiency and performance in daily care [ 53 , 54 , 55 , 56 ]. A crucial factor for the successful development of ML-based software and assistance systems is—besides medical and technological expertise—in particular, the testing and use of these applications in daily clinical routine [ 57 , 58 ]. With this in mind, it was our goal to find out more about the recent development and status of the clinical translation of ML-related software and applications into the clinical setting.…”

Section: Discussionmentioning

confidence: 99%

Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov

Zippel

Bohnet-Joschko

2021

IJERPH

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Although advances in machine-learning healthcare applications promise great potential for innovative medical care, few data are available on the translational status of these new technologies. We aimed to provide a comprehensive characterization of the development and status quo of clinical studies in the field of machine learning. For this purpose, we performed a registry-based analysis of machine-learning-related studies that were published and first available in the ClinicalTrials.gov database until 2020, using the database’s study classification. In total, n = 358 eligible studies could be included in the analysis. Of these, 82% were initiated by academic institutions/university (hospitals) and 18% by industry sponsors. A total of 96% were national and 4% international. About half of the studies (47%) had at least one recruiting location in a country in North America, followed by Europe (37%) and Asia (15%). Most of the studies reported were initiated in the medical field of imaging (12%), followed by cardiology, psychiatry, anesthesia/intensive care medicine (all 11%) and neurology (10%). Although the majority of the clinical studies were still initiated in an academic research context, the first industry-financed projects on machine-learning-based algorithms are becoming visible. The number of clinical studies with machine-learning-related applications and the variety of medical challenges addressed serve to indicate their increasing importance in future clinical care. Finally, they also set a time frame for the adjustment of medical device-related regulation and governance.

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Section: Discussionmentioning

confidence: 99%

Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov

Zippel

Bohnet-Joschko

2021

IJERPH

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“…Evidence base is relatively limited for the majority of MDs compared with pharmaceuticals due to several reasons. Regulatory agencies do not mandate confirmatory efficacy and safety data on MDs from randomised clinical trials (RCTs) (1,(9)(10)(11)(12)(13)(14). Hence, a substantial proportion of HTA reports rely on surrogate outcomes in estimating the health gain, often without proper validation (15).…”

Section: : Lower Level Of Evidence For Mdsmentioning

confidence: 99%

Quo Vadis HTA for Medical Devices in Central and Eastern Europe? Recommendations to Address Methodological Challenges

Daubner-Bendes¹,

Kovács

Niewada

et al. 2021

Front. Public Health

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Objectives: Methodological challenges in the evaluation of medical devices (MDs) may be different for early and late technology adopter countries, as well as the potential health technology assessment (HTA) solutions to tackle them. This study aims to provide guidance to Central and Eastern European (CEE) countries on how to address key challenges of HTA for MDs with special focus on the transferability of scientific evidence.Methods: As part of the COMED Horizon 2020 project, a comprehensive list of issues related to MD HTA were identified based on a targeted literature review. Health technology assessment issues which pose a greater challenge or require different solutions in late technology adopter countries were selected. Draught recommendations to address these issues were developed and discussed in a focus group. The recommendations were then validated with a wider group of experts, including HTA and reimbursement decision makers from CEE countries in May and June 2020.Results: A consolidated list of 11 recommendations were developed in 3 major areas: (1) clinical value assessment, focusing on the use of joint EU work, relying on real-world evidence, use of coverage with evidence development schemes, transferring evidence from foreign countries and addressing the challenges of learning curve and centre effect; (2) economic value assessment, covering cost calculation of complex medical devices and transferability of economic evaluations of MDs; (3) HTA processes, related to the frequent product modifications and various indications of MDs.Conclusions: Central and Eastern European countries with limited resources for conducting HTA, can benefit from HTA methods and evidence generated in early technology adopter countries. Considering the appropriate reuse of international HTA materials, late technology adopter countries can still implement HTA, even for MDs, which have a more limited evidence base compared with pharmaceuticals.

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“…The initial scoping literature search led to 38 results in PubMed, which were assessed based on title and abstract. Seven articles were included in the analysis (24,(31)(32)(33)(34)(35)(36). Within the additional search for strategic articles, six documents were identified based on the proposed strategies' intent and time frame (6,21,22,(37)(38)(39).…”

Section: Scoping Reviewmentioning

confidence: 99%

A Digital Innovation for the Personalized Management of Adherence: Analysis of Strengths, Weaknesses, Opportunities, and Threats

Hein

Vrijens

Hiligsmann

2020

Front. Med. Technol.

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Introduction: Personalized medicine and management of adherence are potential solutions for the suboptimal use of medicines. Digital medication management innovations currently under development combine both aspects. This research aims to investigate facilitators for and barriers to the translation of digital innovations for personalized medicine and adherence management into clinical practice from the policymaker and regulator perspective.Methods: A mixed-method study was used combining a scoping review to identify main interests, semi-structured interviews (n = 5) with representatives of European health policymaking and regulatory organizations, and a supplementary literature review to investigate key subthemes. The SWOT analysis was used for the qualitative analysis.Results: The literature reviews and the qualitative interviews suggested that digital solutions can facilitate the personalized management of medications and improve quality and safety, especially as the openness for digital health solutions is increasing. Digital solutions may, on the other hand, add complexity to the treatment, which can be perceived as a potential barrier for their uptake. As more multidisciplinary and participative structures are emerging, digital solutions can promote the implementation of new services. Nevertheless, change progresses slowly in the task-oriented structures of health systems. Integration of digital solutions depends on all stakeholders' willingness and abilities to co-create this change. Patients have different capabilities to self-manage their medical conditions and use digital solutions. Personalization of digital health solutions and integration in existing service structures are crucial to ensure equality among population segments. Developments in the digital infrastructure, although they are partly slow and not well-aligned, enable the implementation of innovations in clinical practice leading to further advances in data generation and usage for future innovations.Discussion: This study suggests that digital solutions have the potential to facilitate high-quality medication management and improve adherence to medications, enable new service structures, and are essential to drive further innovations in health care. Nevertheless, increasing the self-responsibility of patients can have undesirable effects on health outcomes, especially within vulnerable population segments. Digital health solutions can be an opportunity to optimize the use of medicines and thus their efficiency. Well-conceived development and implementation processes are needed to also realize improvements in equality and solidarity within health systems.

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Barriers and facilitators of patient access to medical devices in Europe: A systematic literature review

Cited by 17 publications

References 54 publications

Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov

Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov

Quo Vadis HTA for Medical Devices in Central and Eastern Europe? Recommendations to Address Methodological Challenges

A Digital Innovation for the Personalized Management of Adherence: Analysis of Strengths, Weaknesses, Opportunities, and Threats

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