There is growing interest in communicating clinically relevant DNA sequence findings to research participants who join projects with a primary research goal other than the clinical return of such ...results. Since Geisinger’s MyCode Community Health Initiative (MyCode) was launched in 2007, more than 200,000 participants have been broadly consented for discovery research. In 2013 the MyCode consent was amended to include a secondary analysis of research genomic sequences that allows for delivery of clinical results. Since May 2015, pathogenic and likely pathogenic variants from a set list of genes associated with monogenic conditions have prompted “genome-first” clinical encounters. The encounters are described as genome-first because they are identified independent of any clinical parameters. This article (1) details our process for generating clinical results from research data, delivering results to participants and providers, facilitating condition-specific clinical evaluations, and promoting cascade testing of relatives, and (2) summarizes early results and participant uptake. We report on 542 participants who had results uploaded to the electronic health record as of February 1, 2018 and 291 unique clinical providers notified with one or more participant results. Of these 542 participants, 515 (95.0%) were reached to disclose their results and 27 (5.0%) were lost to follow-up. We describe an exportable model for delivery of clinical care through secondary use of research data. In addition, subject and provider participation data from the initial phase of these efforts can inform other institutions planning similar programs.
OBJECTIVE:To calculate the current and projected financial burden of EGS hospital admissions in a single-payer healthcare system.
SUMMARY OF BACKGROUND DATA:EGS is an important acute care service, ...which demands significant healthcare resources. EGS admissions and associated costs have increased over time, associated with an aging demographic. The National Health Service is the sole provider of emergency care in Scotland.
METHODS:Principal, high and low Scottish population projections were obtained for 2016 until 2041. EGS admission data were projected using an ordinary least squares linear regression model. An exponential function, fitted to historical length of hospital stay (LOS) data, was used to project future LOS. Historical hospital unit cost per bed day was projected using a linear regression model. EGS cost was calculated to 2041 by multiplying annual projections of population, admission rates, LOS, and cost per bed day.
RESULTS:The adult (age >15) Scottish population is projected to increase from 4.5 million to 4.8 million between 2016 and 2041. During this time, EGS admissions are expected to increase from 83,132 to 101,090 per year, cost per bed day from £786 to £1534, and overall EGS cost from £187.3 million to £202.5 million.
CONCLUSIONS:The future financial burden of EGS in Scotland is projected to increase moderately between 2016 and 2041. This is in sharp contrast to previous studies from settings such as the United States. However, if no further reductions in LOS or cost per bed day are made, especially for elderly patients, the cost of EGS will rise dramatically.
Blockchain technology must have sparked widespread interest, applications associated with data monitoring, banking sectors, computer security, the Internet of Things, and food chemistry to the ...healthcare sector and cognitive science. The use of multimedia in the healthcare architecture also allows for the storage, processing and transmission of patient information in a wide range of formats such as images, text and audio over the Internet using various smart particles. However, managing large amounts of data, including findings and images of each individual, increases human effort and increases protection risks. In this paper, to address these problems by using IoT in healthcare improves the performance of patient care while lowering costs by efficiently distributing healthcare resources. Nevertheless, various attackers can cause a variety of risks in IoT devices. To avoid these problems, Blockchain technology has been identified as the most effective method for maintaining the secrecy and security of control systems in real-time. This should provide a security architecture for healthcare multimedia content using blockchain technology by producing the hash of every information so that any transition or modification in information, as well as any breaches of medicines, would be evidenced across the whole blockchain platform.
Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly expanded; however, clinical trials excluded patients taking immunosuppressive medications such as those ...with inflammatory bowel disease (IBD). Therefore, we explored real-world effectiveness of coronavirus disease 2019 (COVID-19) vaccination on subsequent infection in patients with IBD with diverse exposure to immunosuppressive medications.
This was a retrospective cohort study of patients in the Veterans Health Administration with IBD diagnosed before December 18, 2020, the start date of the Veterans Health Administration patient vaccination program. IBD medication exposures included mesalamine, thiopurines, anti-tumor necrosis factor biologic agents, vedolizumab, ustekinumab, tofacitinib, methotrexate, and corticosteroid use. We used inverse probability weighting and Cox’s regression with vaccination status as a time-updating exposure and computed vaccine effectiveness from incidence rates.
The cohort comprised 14,697 patients, 7321 of whom received at least 1 vaccine dose (45.2% Pfizer, 54.8% Moderna). The cohort had median age 68 years, 92.2% were men, 80.4% were White, and 61.8% had ulcerative colitis. In follow-up data through April 20, 2021, unvaccinated individuals had the highest raw proportion of SARS-CoV-2 infection (197 1.34% vs 7 0.11% fully vaccinated). Full vaccination status, but not partial vaccination status, was associated with a 69% reduced hazard of infection relative to an unvaccinated status (hazard ratio, 0.31, 95% confidence interval, 0.17–0.56; P < .001), corresponding to an 80.4% effectiveness.
Full vaccination (> 7 days after the second dose) against SARS-CoV-2 infection has an ∼80.4% effectiveness in a broad IBD cohort with diverse exposure to immunosuppressive medications. These results may serve to increase patient and provider willingness to pursue vaccination in these settings.
Moral distress occurs when professionals cannot carry out what they believe to be ethically appropriate actions. This review describes the publication trend on moral distress and explores its ...relationships with other constructs. A bibliometric analysis revealed that since 1984, 239 articles were published, with an increase after 2011. Most of them (71%) focused on nursing. Of the 239 articles, 17 empirical studies were systematically analyzed. Moral distress correlated with organizational environment (poor ethical climate and collaboration), professional attitudes (low work satisfaction and engagement), and psychological characteristics (low psychological empowerment and autonomy). Findings revealed that moral distress negatively affects clinicians’ wellbeing and job retention. Further studies should investigate protective psychological factors to develop preventive interventions.
COVID-19 continues to spread across the globe at an exponential speed, infecting millions and overwhelming even the most prepared healthcare systems. Concerns are looming that the healthcare systems ...in low- and middle-income countries (LMICs) are mostly unprepared to combat the virus because of limited resources. The problems in LMICs are exacerbated by the fact that citizens in these countries generally exhibit low trust in the healthcare system because of its low quality, which could trigger a number of uncooperative behaviors. In this paper, we focus on one such behavior and investigate the relationship between trust in the healthcare system and the probability of potential treatment-seeking behavior upon the appearance of the first symptoms of COVID-19. First, we provide motivating evidence from a unique national online survey administered in Armenia-a post-Soviet LMIC country. We then present results from a large-scale survey experiment in Armenia that provides causal evidence supporting the investigated relationship. Our main finding is that a more trustworthy healthcare system enhances the probability of potential treatment-seeking behavior when observing the initial symptoms.
The emergency medical response after a strong earthquake relies on a robust transportation-healthcare system and effective management. This article proposes a resilience assessment framework for the ...interdependent transportation-healthcare system (ITHS) integrating physical loss and organisational management during post-earthquake emergency response. Considering the earthquake-induced injured people, the seismic damage to transportation, and the quantification of the condition of the patients after being treated, a novel metric is proposed to evaluate the response effort during the first 72 h. Bi-objective optimisation is developed to solve the real-time dispatching and treating problems instead of overwhelming one single hospital. In addition, the separate impact of disrupted transportation and damaged healthcare on the interdependent system is calculated to measure the cascading effect. It is shown that proper resource allocation and practical management are crucial to guarantee the desired level of the response effort.
EPDF and EPUB available Open Access under CC-BY-NC-ND licence.It is often claimed that the UK is unusually attached to its National Health Service, and the last decade has seen increasingly visible ...displays of gratitude and love. While social surveys of public attitudes measure how much Britain loves the NHS, this book mobilises new empirical research to ask how Britain love its NHS. Ellen A. Stewart offers timely critique of both the potential, and the dysfunctions, of Britain’s complex love affair with its healthcare system.
Sexuality is considered to be an important aspect of holistic care, yet research has demonstrated that it is not routinely addressed in healthcare services. A greater understanding of this can be ...achieved through synthesizing qualitative studies investigating healthcare professionals' experiences of talking about sex. In doing so, policy makers and healthcare providers may be able to better address the sexual issues of service users.
To gain an in-depth understanding of healthcare professionals' subjective experience of discussing sexuality with service users by identifying the factors that impede and facilitate such discussions.
Review of healthcare professionals' experience of discussing sexuality with service users.
Electronic databases and reference lists of published articles were searched in July 2011. Primary research studies were included in the review if they explored health professionals' experiences of discussing sexuality with adult service users, used qualitative methods, and were conducted in the United Kingdom over the last 10 years. Each study was reviewed and assessed. A secondary thematic analysis method was used where key themes were extracted and grouped and key concepts were explored.
Nineteen interconnected themes emerged relating to healthcare professionals' experience of discussing sexuality with service users, including fear about “opening up a can of worms,” lack of time, resources, and training, concern about knowledge and abilities, worry about causing offense, personal discomfort, and a lack of awareness about sexual issues. Some themes were particularly marked relating to the sexuality of the opposite-gender, black and ethnic minority groups, older and nonheterosexual service users, and those with intellectual disabilities.
The majority of healthcare professionals do not proactively discuss sexuality issues with service users, and this warrants further attention. An understanding of the perceived barriers and facilitators indicates that interventions to improve the extent to which sexuality issues are addressed need to take organizational, structural, and personal factors into consideration. Dyer K and das Nair R. Why don't healthcare professionals talk about sex? A systematic review of recent qualitative studies conducted in the United Kingdom. J Sex Med 2013;10:2658–2670.
•Feature extraction for multi-model autoencoder is designed to process features.•A high-level structured feature is extracted to get time-related information.•Multi-feature sequence anomaly detection ...with residual learning is proposed.•Comprehensive experiments are conducted to prove the effectiveness of our method.
IoMT technology has many advantages in healthcare system, such as optimizing the medical service model, improving the efficiency of hospital operation and management, and improving the overall service level of the hospital. IoMT devices do not have a security authentication mechanism, and the trust between devices relies heavily on centralized third-party services. Blockchain can provide a secure interactive environment for the medical Internet of Things. However, security issues in the IoMT-Blockchain environment are also becoming increasingly prominent. Cyber-attacks targeting IoMT-Blockchain will not only compromise the security of IoT devices, but also seriously affect the security of the Internet. Therefore, how to detect abnormal traffic in the IoMT-Blockchain environment becomes particularly important. In this work, an abnormal traffic detection with deep neural network is designed for abnormal traffic detection in IoMT-Blockchain environment. First, this work proposes a feature extraction algorithm based on multi-model autoencoders. The algorithm processes the feature information in groups to reduce the complexity between traffic feature information. It builds a multi-model autoencoder to further extract fusion features between multi-model features. Second, to maximize use of traffic data information in detection network, this work proposes a multi-feature sequence anomaly detection algorithm. The algorithm extracts low-level fusion features and high-level temporal features in network traffic respectively, and applies the features to anomaly detection and classification tasks by means of residual learning.
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