Search results

This paper seeks to report the key findings of two studies which were undertaken by Rare Disease UK to: understand patients' and their families' experiences of living with a rare disease; identify issues preventing research and access to good quality information, care, treatment and support; identify examples of good practice; and develop recommendations to improve service provision for patients with rare diseases and encourage research.

Across the two reports discussed, a range of methods were used including: a survey of patients/family members; five multi‐stakeholder working groups; conference workshops; a consultation paper; interviews; and desk research.

There are a number of detailed findings across the two reports. At a broad level, the findings identify that despite the diverse range of rare diseases each with different symptoms and prognoses, patients often face similar issues. The report also identifies a number of possible solutions to facilitate research, speed up diagnosis, improve co‐ordination of care and ensure high‐quality information is available to patients and professionals.

The findings and recommendations in the two reports discussed are informing the development of a UK plan for rare diseases by all four of the UK's health departments. This plan will be the first strategic approach to improving service provision for all patients with rare diseases in the UK.

Very little research has been conducted into the experiences of patients with rare diseases or on how to improve service provision for all rare diseases in the UK. As a result, the two reports offer a substantial body of new evidence.

The Orphan Drug Act has provided the pharmaceutical industry with incentives to research and develop drugs for orphan diseases: rare diseases with little profit potential. It is considered very successful legislation by legal scholars, the Food and Drug Administration (FDA), and orphan drug activists. The policy process of the Act provides an important model of the policy process for future incentive-based pharmaceutical legislation. The purpose of this paper is to summarize the important incentives of the Act and the historical events leading up to the Act. The paper applies three different theoretical models of the public policy process to understand the emergence of the Orphan Drug Act: Kingdon’s Multiple Streams Model, the Advocacy Coalition Framework, and Social Constructionism Theory. The paper then synthesizes the public policy process lessons from each perspective and provides four recommendations for other social activists seeking to propel incentive-based pharmaceutical legislation for under-researched diseases.

The author analyzes the history of the Orphan Drug Act based on publicly available scholarly research, government documents, and interest group publications. The author then applies three public policy theories to the history of the Orphan Drug Act to explain the emergence of the Act and to extract policy process lessons for future disease activists.

Regardless of which theoretical perspective the Orphan Drug Act is analyzed from, some common themes of the policy process emerge. First, focussing events are instrumental in capturing the public’s sympathy and Congress’s attention. Second, in its activities and proposed legislation, a coalition should provide a role for all relevant and important actors. Third, the target groups of the legislation were construed positively, increasing the pressure for Congressmen to pass some kind of bill. Finally, the proper construction of “the problem” is instrumental to passing effective legislation as a “solution.”

The Orphan Drug Act is widely considered successful incentive-based pharmaceutical legislation. However, because it was originally passed in 1983 and has not had public attention since the early 1990s (when it was amended), it has rarely been written about in recent years. However, its lessons are still highly relevant to policy activists, especially disease activists. Furthermore, existing articles focus on the impact of the legislation and ways to amend it, rather than on the passage of the Act.

The World Health Organization estimated that in 1999 roughly one-third of the world's population lacked access to essential medicines that would have saved or improved their lives. Our analysis focuses on how pharmaceutical product patents restrict access to essential medicines in developing countries. It is well established that pharmaceutical product patents provide little incentive for pharmaceutical companies to develop new medicines designed to treat diseases prevalent in developing countries or to market in developing countries those patented medicines developed to treat diseases prevalent in developed countries. Economists have developed theoretical models showing that these incentives could be changed if (1) developing countries provided intellectual property protection for new pharmaceutical innovations and (2) an international regulatory framework were established to facilitate pharmaceutical companies setting lower prices in developing countries and higher prices in developed countries for patented medicines. We develop an index of property rights in pharmaceutical innovations covering 129 countries from 1960 to 2005. It shows that in 1960 only a handful of countries provided significant protection for pharmaceutical innovations, but by 2005 over 95 percent of countries in our sample provided significant statutory protections. However, an international framework to allow pharmaceutical companies to price discriminate has not been put in place. We conclude that international price discrimination mechanisms, compulsory patent licenses, and regional patent buyouts are not viable mechanisms for providing access to essential medicines to patients in developing countries. Global patent buyouts are more likely to achieve this goal, as they are not founded on an impractical separation of pharmaceutical markets in developing and developed countries and they provide critical incentives to develop new essential medicines.

Epidemics not only affect the public health but also are a threat to a nation's growth and economy as well. Early prediction of epidemic can be beneficial to take preventive measures and to reduce the impact of epidemic in an area.

A deep neural network (DNN) based context aware smart epidemic system has been proposed to prevent and monitor epidemic spread in a geographical area. Various neural networks (NNs) have been used: LSTM, RNN, BPNN to detect the level of disease, direction of spread of disease in a geographical area and marking the high-risk areas. Multiple DNNs collect and process various data points and these DNNs are decided based on type of data points. Output of one DNN is used by another DNN to reach to final prediction.

The experimental evaluation of the proposed framework achieved the accuracy of 87% for the synthetic dataset generated for Zika epidemic in Brazil in 2016.

The proposed framework is designed in a way that every data point is carefully processed and contributes to the final decision. These multiple DNNs will act as a single DNN for the end user.

Q‐analysis is a methodology for investigating a wide range of structural phenomena. Structures are defined in terms of relations between members of sets and their salient features are revealed using techniques of algebraic topology. However, the basic method can be mastered by non‐mathematicians. Q‐analysis has been applied to problems as diverse as discovering the rules for the diagnosis of a rare disease and the study of tactics in a football match. Other applications include some of interest to librarians and information scientists. In bibliometrics, Q‐analysis has proved capable of emulating techniques such as bibliographic coupling, co‐citation analysis and co‐word analysis. It has also been used to produce a classification scheme for television programmes based on different principles from most bibliographic classifications. This paper introduces the basic ideas of Q‐analysis. Applications relevant to librarianship and information science are reviewed and present limitations of the approach described. New theoretical advances including some in other fields such as planning and design theory and artificial intelligence may lead to a still more powerful method of investigating structure.

Diverticular disease of the colon is an acquired disorder of bowel muscle which hypertrophies, that is, it thickens. The hypertrophied muscle causes an increase in pressure in the bowel and the mucosal lining is pushed out (herniates) through the inherently weak points of the muscle to form pockets (diverticulae). The process is rather similar to the egg‐like distortions seen in the side wall of a defective tyre. In most cases, these diverticulae cause no trouble whatsoever, but in a few they may lead to complications of bleeding, infection, abscess formation and even perforation.

The paper aims to explore the nature of initiatives and strategies of inter-organizational cooperation to cross the valley of death in the biopharma industry.

The authors conducted an exploratory case study analysis in the Biopharma Innovation Ecosystem in Greater Boston Area (USA), which is one of the oldest, and most successful IE in the US, specialized in the Biopharma domain, by conducting a round of expert interviews with key informants in the area, chosen as representatives of the different types of actors engaged in the drug development processes at different stages.

Main findings suggest that cooperation can contribute to surviving the valley of death by reducing the barriers within the drug development pipeline through the promotion of strategic relationships among actors of different nature, including the establishment of government-led thematic associations or consortia, agreements between university and business support structures, proximity to venture capitalist and the promotion of a general culture of academic entrepreneurship within universities.

The authors believe that this paper contributes to the literature by shedding light on the nature of the specific cooperative initiative the barriers in drug development and help to survive the valley of the death.

Digital transformation holds promise for addressing one of the biggest challenges in health care – misdiagnosis. About 30 per cent of health spending in 2009, i.e. roughly $750bn, was wasted on unnecessary services, excessive administrative costs, fraud and other problems. Moreover, inefficiencies cause needless suffering, states the Institute of Medicine. Leveraging emerging digital technologies in this sector stands to save thousands of lives and billions of dollars. Digital technology is being applied to this field owing to the great demand for a solution. Misdiagnosis is causing a major hemorrhaging hundreds of billions of dollars in the health industry – an estimated 10-20 per cent of cases are misdiagnosed, sometimes resulting in death or permanent disability, according to studies cited by the National Center for Policy Analysis. Additionally, experts believe as many as 31 per cent of all breast cancer cases are misdiagnosed, according to the New England Journal of Medicine, and 90,000 women are misdiagnosed with invasive breast cancer, according to Susan G. Komen.

Digital technology is being applied to this field owing to the great demand for a solution. Misdiagnosis is causing a major hemorrhaging hundreds of billions of dollars in the health industry – an estimated 10-20 percent of cases are misdiagnosed, sometimes resulting in death or permanent disability, according to studies cited by the National Center for Policy Analysis. Additionally, experts believe as many as 31 percent of all breast cancer cases are misdiagnosed, according to the New England Journal of Medicine, and 90,000 women are misdiagnosed with invasive breast cancer, according to Susan G. Komen.

Advance Medical’s experience is that 39 per cent of a self-selecting group of medical advocacy seekers are misdiagnosed. Directly related to this challenge, a major battleground where the war on escalating healthcare costs is being fought is in the space of utilization management tools, which help ensure insurers are paying for the right care. These tools depend on the doctor making the right diagnosis and that the treatment matches the diagnosis. But these tools are broken. Instead of checking accuracy of diagnosis (e.g. the right test was done and interpreted accurately), they are at best checking to see if the “box was checked” for any testing being done. The solution is to not only to ensure that the diagnosis is correct by having it reviewed independently but also to use technology to aid diagnosis and the physician’s overall job. Using tools such as patient portals and data management technology can aid doctors to not burn out from sorting through data but rather using healthcare technology to reduce physician exhaustion and thus misdiagnosis.

New and old tools hold promise for addressing one of the costliest and most able-to-be-impacted challenges in health care – misdiagnosis. Because of misdiagnosis, the health industry is hemorrhaging hundreds of billions of dollars and causing patients undue stress and negative medical impact. Not only does misdiagnosis have a strong effect on the economy and the solvency of the US health care system, it also has a profound effect on the people who are being misdiagnosed, as well as their families and loved ones.

An in‐depth examination of the evolution of legislation, practice and thinking in food safety in the UK and Europe in general. Explores the reduced levels of confidence exhibited by consumers.