Why most people with mental illness go untreated? economic perspectives and evidence from China

Due to the rapid economic growth and advancement in medical technology, many countries have experienced in the past decades an epidemiological transition from communicable to non- communicable dieses (NCDs). One of the challenges in the era of NCDs is the large treatment gap, measured by the difference between the need for treatment and the actual provision of treatment, among patients with NCDs. This paper investigates the causes of treatment gap in mental healthcare from the perspective of economics. Specifically, we hypothesizes that people with mental illness face four major hurdles in seeking appropriate healthcare, namely the high nonmonetary cost due to stigma, the high out-of-pocket payment due to insufficient public funds devoted to the mental health sector, the high time prices due to low mental healthcare resource availability, and the low treatment benefit due to slow technology diffusion. We then use China as a study setting to show the country-specific evidence. Our analysis supports the above theoretical argument on the four access barriers, which in turn sheds light on the effective approaches to mitigate the treatment gap. Four policy options are then discussed, including an information campaign for mental health awareness, increasing public investment in primary mental healthcare resources, transforming the healthcare system towards an integrated people-centered system and capitalizing on e-health technologies

Auto-Translation Instant Messenger using XMPP/Jabber Protocol

Effective communication is a vital component in decision making process. However, the language barrier established from the differences in culture and origin can interrupt the process of coming to an understanding. Various translation methods have been used to break this barrier. The traditional ways of using human translator or the usage of lingua franca imposed some problem and limitations. Auto-Translation Instant Messenger is an 1M program that aimed to provide instant translation to users when they communicate with people of different speaking language. It is developed under the XMPP protocol that provides standards and flexibilities at the same time. In the process of completing this project, Modified Waterfall methodology was chosen as guidance in the development of the working program. Important project activities and milestones are explained. As part of analysis process, a set of questionnaire have been distributed and its result will act as guidance in designing and developing the program. This project is aimed to learn in deep about XMPP, machine translation and instant messagin

The EPSRC's policy of responsible innovation from a trading zones perspective

Responsible innovation (RI) is gathering momentum as an academic and policy debate linking science and society. Advocates of RI in research policy argue that scientific research should be opened up at an early stage so that many actors and issues can steer innovation trajectories. If this is done, they suggest, new technologies will be more responsible in different ways, better aligned with what society wants, and mistakes of the past will be avoided. This paper analyses the dynamics of RI in policy and practice and makes recommendations for future development. More specifically, we draw on the theory of ‘trading zones’ developed by Peter Galison and use it to analyse two related processes: (i) the development and inclusion of RI in research policy at the UK’s Engineering and Physical Sciences Research Council (EPSRC); (ii) the implementation of RI in relation to the Stratospheric Particle Injection for Climate Engineering (SPICE) project. Our analysis reveals an RI trading zone comprised of three quasi-autonomous traditions of the research domain – applied science, social science and research policy. It also shows how language and expertise are linking and coordinating these traditions in ways shaped by local conditions and the wider context of research. Building on such insights, we argue that a sensible goal for RI policy and practice at this stage is better local coordination of those involved and we suggest ways how this might be achieved

Patient access to gene therapy medicinal products : a comprehensive review

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Background Gene therapies have the potential to be a curative approach to a large number of genetic diseases. However, granting of a positive marketing authorisation does not equal patient access to therapy. Objectives The purpose of this paper is to identify a full set of hurdles potentially preventing patient access to gene therapies based on the available literature. Methods A review of the literature using systematic approach in two distinct databases was performed by identifying relevant, peer-reviewed publications, between 2012 and 2018. Results Seven major topics were identified as potential patient access hurdles, namely affordability, assessment of value, development of therapy, ethical/social factors, evidence generation, operational implementation and regulatory hurdles. From these, 25 additional subthemes were further identified. The most frequently mentioned obstacle in the literature is related to the affordability aspect especially focusing on high cost of therapy (84%) and therapy payment/reimbursement (51%). Importantly, the evidence generation focusing on limited trial outcomes (81%) seems as a strong obstacle in patient access to these therapies. Conclusions A growing number of gene therapies are expected to be developed and made available to patients and healthcare professionals. Improvement of patient access to gene therapies can only be achieved by understanding all hurdles, in a complete and integrated fashion, so that strategies are timely established to ensure gene therapies’ benefits are provided to patients and to the society.info:eu-repo/semantics/publishedVersio

Barriers to Entry

Entry of firms into a market is an important economic mechanism that influences industry dynamics and contributes to allocative and dynamic efficiency. However, there are barriers that can prevent companies from entering a market, hampering the competitive process. Therefore, it is clear that barriers to entry are an important issue in competition policy. In this report, we studied a number of 37 different barriers with a special focus on the possible size effect of the barrier, the sustainability of the barrier, the way it can be measured and the relation with other barriers to entry.

Advancements in Medical Imaging and Diagnostics with Deep Learning Technologies

Medical imaging has long been a cornerstone in diagnostic medicine, providing clinicians with a non-invasive method to visualize internal structures and processes. However, traditional imaging techniques have faced challenges in resolution, safety concerns related to radiation exposure, and the need for invasive procedures for clearer visualization. With the advent of deep learning technologies, significant advancements have been made in the field of medical imaging, addressing many of these challenges and introducing new capabilities. This research seeks into the integration of deep learning in enhancing image resolution, leading to clearer and more detailed visualizations. Furthermore, the ability to reconstruct three-dimensional images from traditional two-dimensional scans offers a more comprehensive view of the area under examination. Automated analysis powered by deep learning algorithms not only speeds up the diagnostic process but also detects anomalies that might be overlooked by the human eye. Predictive analysis, based on these enhanced images, can forecast the likelihood of diseases, and real-time analysis during surgeries ensures immediate feedback, enhancing the precision of medical procedures. Safety in medical imaging has also seen improvements. Techniques powered by deep learning require reduced radiation, minimizing risks to patients. Additionally, the enhanced clarity and detail in images reduce the need for invasive procedures, further ensuring patient safety. The integration of imaging data with Electronic Health Records (EHR) has paved the way for personalized care recommendations, tailoring treatments based on individual patient history and current diagnostics. Lastly, the role of deep learning extends to medical education, where it aids in creating realistic simulations and models, equipping medical professionals with better training tools