An Assessment of the Philippine Hospital Resources as Predictors of the Case Fatality Rate of COVID – 19

In the heightened effects of the pandemic, health resources have been in constant limbo as supplies and availability of hospital resources take a toll as COVID-19 cases surge, resulting in shortages. Thus, health systems are overwhelmed, resulting in a higher fatality rate since the capacity to provide medical attention is diminished. In this paper, hospital resources refer to mechanical ventilators, ICU, isolation, and ward beds which are the critical factors of the case fatality rate (CFR) of COVID-19 in the Philippines. Data were retrieved from the Department of Health (DOH) Case Bulletins from October 26, 2020, to June 30, 2021, with 248 total observations. This research used the Ordinary Least Squares (OLS) Multiple Regression to determine if hospital resources are the predictors of the case fatality rate of COVID-19. Furthermore, the results show a significant relationship between the hospital resources and the case fatality rate of COVID-19 in the Philippines. This study can become a framework for further research concerned about hospital resources as the predictors of case fatality rates of different diseases in a pandemic.

Virtual Healthcare Center for COVID-19 Patient Detection Based on Artificial Intelligence Approaches

At the end of 2019, the infectious coronavirus disease (COVID-19) was reported for the first time in Wuhan, and, since then, it has become a public health issue in China and even worldwide. This pandemic has devastating effects on societies and economies around the world, and poor countries and continents are likely to face particularly serious and long-lasting damage, which could lead to large epidemic outbreaks because of the lack of financial and health resources. The increasing number of COVID-19 tests gives more information about the epidemic spread, and this can help contain the spread to avoid more infection. As COVID-19 keeps spreading, medical products, especially those needed to perform blood tests, will become scarce as a result of the high demand and insufficient supply and logistical means. However, technological tests based on deep learning techniques and medical images could be useful in fighting this pandemic. In this perspective, we propose a COVID-19 disease diagnosis (CDD) tool that implements a deep learning technique to provide automatic symptoms checking and COVID-19 detection. Our CDD scheme implements two main steps. First, the patient’s symptoms are checked, and the infection probability is predicted. Then, based on the infection probability, the patient’s lungs will be diagnosed by an automatic analysis of X-ray or computerized tomography (CT) images, and the presence of the infection will be accordingly confirmed or not. The numerical results prove the efficiency of the proposed scheme by achieving an accuracy value over 90% compared with the other schemes.

Sidelined during COVID-19: a narrative inquiry into how simulationists experienced the pandemic

Background In the simulation community, colleagues who are no longer clinically practicing were often proximal to the COVID-19 response, not working in the frontlines of patient care. At the same time, their work as simulationists changed dramatically or was halted. This research explored the experiences of those simulationists who have clinical backgrounds but did not provide direct patient care during the initial pandemic response. The aim of this study was to allow those simulationists to share and have their stories heard. Methods This qualitative research used a narrative approach to answer the research question: What were the experiences of those in the simulation community who did not contribute to the frontline patient care response during the early stages of the pandemic? A semi-structured questionnaire aimed at eliciting a story was disseminated through online simulation discussion boards. Data was collected through PHONIC with options to type or speak responses. Responses were analyzed using an inductive analytical process to identify themes or patterns in the narratives. Results Thirty-six respondents completed the survey between August 1, 2020 and November 30, 2020. Narrative arcs were identified that illustrated the events, actions, thoughts and feelings representative of experiences shared by many simulationists. Two major themes emerged: Challenges and Opportunities. Challenges included feelings of guilt; frustration; overwhelmed, stressed and exhausted; being away from the action, being unused and underappreciated. Opportunities included leadership (evolution and innovation), personal development, and being a part of something. Conclusions The findings reflect a snapshot in time of how simulation was viewed and used in the world during a pandemic through the personal stories of simulationists with clinical backgrounds who did not provide direct patient care. Sharing these narratives may inform future simulation development; however, it is vitally important that the emotions are recognized and acknowledged. Managers should ensure mental health resources and support are available to all staff, including those not deployed to the frontline.

Delivering mental healthcare to patients with a depressive disorder alongside a life-limiting illness

The concurrent assessment and treatment of mental health disorders and palliative illnesses is complex. Affective disorders are more prevalent in people who need palliative care. Identifying the most suitable place of care and multi-professional multidisciplinary teams to provide support can be challenging and bewildering for professionals and patients. Mental health clinicians may be left with a sense of therapeutic nihilism, while palliative care teams can feel limited by the mental health resources available for treating those living with significant physical and mental health needs. We discuss the fictional case of a gentleman with metastatic bowel cancer who has developed symptoms of depressive disorder and identify how taking a pragmatic patient-centred approach can offer a route through potential dilemmas when seeking to provide individualised care based on needs. We used lay person experience alongside our own experiences of novel mechanisms for cross-specialty working in order to direct psychiatric trainees’ approaches to such cases.

Greater Reduction of Blood Pressure with Exercise Intervention Than Standard Care After Recent Ischaemic Atroke: A Randomized Clinical Trial

Context and Objectives: Ischaemic stroke (IS) causes disability and uses massive public health resources. Cumulative disability from recurrence may be reduced with cardiometabolic risk reduction strategies e.g., lowering blood pressure (BP). We hypothesized that intensive exercise plus best available care in adults with recent IS improves fitness, glucose metabolism, muscle protein synthesis in paretic limbs compared to controls. BP changes were compared between intervention (INT) and controls (CON). Research Design and Setting: A randomised, interventional clinical trial conducted in Jamaican adults subjects: We investigate 103 adults with recent IS and residual weakness. Forty-nine subjects (24 women: mean age 61.5; 25 men: mean age 63.8) received task-oriented exercise training (TEXT) plus best available care. Fifty-four subjects (23 women: mean age 60.2; 31 men: mean age 61.3) received best care, including exercise advice. Measurements: We measured baseline, 3-month and 6-month BP. Results: After recent IS, TEXT plus best available care reduced systolic BP by 21 mmHg and diastolic by 12 mmHg compared to controls, independent of medication adherence, body composition; stroke severity. Men in the TEXT group had increased lean mass (P < 0.007), VO2 max (P = 0.03); 6-minute walk distance (P = 0.003). Leg press on paretic (P = 0.004) and non-paretic (P < 0.001) increased with TEXT vs CON over 6 months, in both sexes (P-values for sex difference > 0.2). Time-to-chair-rise decreased in both sexes who received intervention vs controls (P <0.04) Conclusions: TEXT results in significant blood pressure reduction in adults with recent ischaemic stroke and residual weakness when compared with best available medical care only.

Developing a Public Health Maternal and Child Health Training Program: Lessons Learned from Five Schools of Public Health

Maternal and child health (MCH), as a core sub-field of public health, continues to be an essential area in which additional workforce development and investment are needed. Recent public health workforce assessments in the United States reveal there will be a significant number of vacancies in MCH public health positions in the near future, creating the need for a well-trained and skilled public health MCH workforce. In order to address this potential critical workforce gap, the U.S. Department of Health and Human Services, Health Resources and Services Administration’s Maternal and Child Health Bureau initiated the Maternal and Child Health Public Health Catalyst Program in 2015 to support the creation of MCH training programs in accredited schools of public health that previously did not have a MCH concentration. This article details the accomplishments and lessons learned from the first five MCH Catalyst Program grantees: Drexel University; Florida International University; Rutgers, The State University of New Jersey; Texas A&M University; and the University at Albany.

Applying Salutogenesis in Community-Wide Mental Health Promotion

This chapter highlights the relevance of mental health as a resource and risk for population health and describes mental health problems and related financial and social implications for society, which has led to an increased focus on prevention of mental health problems in health policy lately. Using the river metaphor of salutogenesis and a mental health ease–disease continuum, mental health is seen not as a stable trait but rather as a constant process, which needs to be protected and promoted. Thus, mental health promotion is foremost focused on protective factors and promoting mental health resources at different levels of society and is relevant to everyone.The authors also present and describe the ‘Act-Belong-Commit’/‘ABCs of Mental Health’ Campaign, a world-first comprehensive, population-wide, community-based mental health promotion campaign designed to promote mental health and prevent mental ill health.

Big Data, Data Mining, and Data Analytics in IoT-Based Healthcare Applications

IoT seriously impacts every industry. The healthcare industry has experienced progression in digitizing medical records. Healthcare services are costlier than ever. Data mining is one of the largest challenges to face IoT. Big Data is an accumulation of data. IoT devices receive lots of data. Big data systems can do a lot of data analytics. The tools can also be used to perform these operations. The big health application system can be built by integrating medical health resources using intelligent terminals, internet of things (IoT), big data, and cloud computing. People suffer from many diseases. A big health system can be applied to scientific health management by detecting risk factors for the occurrence of diseases. Patients can have special attention to their health requirements and their devices can be tuned to remind them of their appointments, calorie count, exercise check, blood pressure variations, symptoms of any diseases, and so much more.