Search Results (12)

Background: The emergency department (ED) often represents the entry point to care for patients that require urgent medical attention or have no alternative for medical treatment. This has implications on scope of practice and how quality of care is measured. A diverse array of methodologies has been developed to evaluate the quality of clinical care and broadly includes quality improvement (QI), quality assurance (QA), observational research (OR) and clinical quality registries (CQRs). Considering the overlap between QI, QA, OR and CQRs, we conceptualized a modular framework for TECOR to effectively and efficiently streamline clinical quality evaluations. Streamlining is both appropriate and justified as it reduces redundancy, enhances clarity and optimizes resource utilization, thereby allowing clinicians to focus on delivering high-quality patient care without being overwhelmed by excessive data and procedural complexities. The objective of this study is to describe the process for designing a modular framework for ED CQRs using TECOR as a case study. Methods: We performed a scoping audit of all quality projects performed in our ED over a 1-year period (1 January 2021 to 31 December 2021) as well as data mapping and categorical formulation of key themes from the TECOR dataset with clinical data sources. Both these processes then informed the design of TECOR. Results: For the audit of quality projects, we identified 29 projects. The quality evaluation methodologies for these projects included 12 QI projects, 5 CQRs and 12 OR projects. Data mapping identified that clinical information was fragmented across 11 distinct data sources. Through thematic analysis during data mapping, we identified three extraction techniques: self-extractable, manual entry and on request. Conclusions: The modular framework for TECOR aims to enable an efficient streamlined approach that caters to all aspects of clinical quality evaluation to enable higher throughput of clinician-led quality evaluations and improvements. TECOR is also an essential component in the development of a learning health system to drive evidence-based practice and the subject of future research. Full article

Background: The COVID-19 pandemic has profoundly transformed the global scenario, marked by overwhelming infections, fatalities, overburdened healthcare infrastructures, economic upheavals, and significant lifestyle modifications. Concurrently, the Russian full-scale invasion of Ukraine on 24 February 2022, triggered a severe humanitarian and public health crisis, leading to healthcare disruptions, medical resource shortages, and heightened emergency care needs. Italy emerged as a significant refuge for displaced Ukrainians during this period. Aim: This research aims to discern the impact of the Russian full-scale invasion of Ukraine on the COVID-19 transmission dynamics in Italy. Materials and Methods: The study employed advanced simulation methodologies, particularly those integrating machine learning, to model the pandemic’s trajectory. The XGBoost algorithm was adopted to construct a predictive model for the COVID-19 epidemic trajectory in Italy. Results: The model demonstrated a commendable accuracy of 86.03% in forecasting new COVID-19 cases in Italy over 30 days and an impressive 96.29% accuracy in estimating fatalities. When applied to the initial 30 days following the escalation of the conflict (24 February 2022, to 25 March 2022), the model’s projections suggested that the influx of Ukrainian refugees into Italy did not significantly alter the country’s COVID-19 epidemic course. Discussion: While simulation methodologies have been pivotal in the pandemic response, their accuracy is intrinsically linked to data quality, assumptions, and modeling techniques. Enhancing these methodologies can further their applicability in future public health emergencies. The findings from the model underscore that external geopolitical events, such as the mass migration from Ukraine, did not play a determinative role in Italy’s COVID-19 epidemic dynamics during the study period. Conclusion: The research provides empirical evidence negating a substantial influence of the Ukrainian refugee influx due to the Russian full-scale invasion on the COVID-19 epidemic trajectory in Italy. The robust performance of the developed model affirms its potential value in public health analyses. Full article

At the beginning of 2020, coronavirus disease 2019 (COVID-19) emerged as a new pandemic, leading to a worldwide health crisis and overwhelming healthcare systems due to high numbers of hospital admissions, insufficient resources, and a lack of standardized therapeutic protocols. Multiple genetic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been detected since its first public declaration in 2020, some of them being considered variants of concern (VOCs) corresponding to several pandemic waves. Nevertheless, a growing number of COVID-19 patients are continuously discharged from hospitals, remaining symptomatic even months after their first episode of COVID-19 infection. Long COVID-19 or ‘post-acute COVID-19 syndrome’ emerged as the new pandemic, being characterized by a high variability of clinical manifestations ranging from cardiorespiratory and neurological symptoms such as chest pain, exertional dyspnoea or cognitive disturbance to psychological disturbances, e.g., depression, anxiety or sleep disturbance with a crucial impact on patients’ quality of life. Moreover, Long COVID is viewed as a new cardiovascular risk factor capable of modifying the trajectory of current and future cardiovascular diseases, altering the patients’ prognosis. Therefore, in this review we address the current definitions of Long COVID and its pathophysiology, with a focus on cardiovascular manifestations. Furthermore, we aim to review the mechanisms of acute and chronic cardiac injury and the variety of cardiovascular sequelae observed in recovered COVID-19 patients, in addition to the potential role of Long COVID clinics in the medical management of this new condition. We will further address the role of future research for a better understanding of the actual impact of Long COVID and future therapeutic directions. Full article

Objectives: In 2021, Thailand experienced its fourth and fifth waves of COVID-19, overwhelming the nation’s public health system. The significant gap between health resources and the demand for services from patients was one of the primary challenges in responding to the catastrophic COVID-19 pandemic. Hospitals were inundated with a surge in new patients, leading to a growing backlog of individuals suffering delayed care or even rejection from the healthcare system. To tackle this issue, strategies such as “outpatient self-isolation” (SI), “home-based isolation” (HI), and “community-based isolation” (CI) were implemented to stabilize COVID-19 cases with mild to moderate symptoms. This review aimed to explore the experiences in the management of COVID-19 care in patients with mild to moderate symptoms and identify challenges after the initial response of the Thailand health system to the pandemic. Methods: This study was conducted during the Delta pandemic (June–November 2021) and the Omicron pandemic (December 2021–15 March 2022). We present the lessons learned from the management of the HI system based on experiences gained at a university hospital, which provided remote professional-to-patient support during the pandemic. The study involved retrospective data from electronic medical records and qualitative analysis of responses provided during the pandemic using the HI system. Results: Data from a total of 2704 and 1912 participants were included in the analysis. The vast majority of patients were assigned to HI immediately after being diagnosed with COVID-19. This system facilitated remote consultations, provision of necessary medications, and delivery of survival kits to patients’ homes. Qualitative reviews indicated several key factors that could contribute to successful COVID-19 management under the HI system: (1) effective management and vaccine status, (2) establishment of home isolation using the find-test-trace-isolate-support system, and (3) adherence to home isolation guidelines and system support. Challenges included the digitalization of tools for securing isolation, team preparedness and adequate support system during HI, as well as hospital policies for psychological support for healthcare workers and measures to alleviate their workload. Conclusions: Our investigation suggests that the HI teleconsultation system was an effective approach to managing COVID-19. It allowed for a prompt response to patients’ needs and provided timely access to medical support, particularly for individuals with mild to moderate symptoms. Full article

It is of great significance to correctly infer the underlying cause of death for citizens, especially under the current worldwide situation. The medical resources of all countries are overwhelmed under the impact of coronavirus disease 2019 (COVID-19) and countries need to allocate limited resources to the most suitable place. Traditionally, the cause-of-death inference relies on manual methods, which require a large resource cost and are not so efficient. To address the challenges, in this work, we present a mixed inference method named Sink-CF. The Sink-CF algorithm is based on confidence measurement and is used to automatically infer the underlying cause of death of citizens. The method proposed in this paper combines a mathematical statistics method and a collaborative filtering and analysis algorithm in machine learning. Thus, our method can not only effectively achieve a certain accuracy, but also does not rely on a large quantity of manually labeled data to continuously optimize the model, which can save computer computing power and time, and has the characteristics of being simple, easy and efficient. The experimental results show that our method generates a reasonable precision (93.82%) and recall (90.11%) and outperforms other state-of-the-art machine learning algorithms. Full article

The spread of emerging self-limiting infectious diseases is closely related to medical resources. This paper introduces the concept of safe medical resources, i.e., the minimum medical resources that are needed to prevent the overburden of medical resources, and explores the impacts of medical resources on the spread of emerging self-limiting infectious diseases. The results showed that when the isolation rate of hospitalized patients who have mild infections is low, increasing the isolation rate of patients with severe infections requires safe more medical resources. On the contrary, when the isolation rate of hospitalized patients with mild infections is at a high level, increasing the isolation rate of patients with severe infections results in a decrease in safe medical resources. Furthermore, when the isolation rates of patients with mild and severe infections increase simultaneously, safe medical resources decrease gradually. That is to say, when the medical resources are at a low level, it is more necessary to improve the isolation rates of infected individuals so as to avoid the phenomenon of overburdened medical resources and control the spread of emerging infectious diseases. In addition, overwhelmed medical resources increase the number of deaths. Meanwhile, for different emerging self-limiting infectious diseases, as long as the recovery periods are the same, safe medical resources also remain the same. Full article

Despite the overwhelming interest in clinical genomics, uptake has been slow. Implementation science offers a systematic approach to reveal pathways to adoption and a theory informed approach to addressing barriers presented. Using case study methodology, we undertook 16 in-depth interviews with nongenetic medical specialists to identify barriers and enablers to the uptake of clinical genomics. Data collection and analysis was guided by two evidence-based behaviour change models: the Theoretical Domains Framework (TDF), and the Capability, Opportunity Motivation Behaviour model (COM-B). Our findings revealed the use of implementation science not only provided a theoretical structure to frame the study but also facilitated uncovering of traditionally difficult to access responses from participants, e.g., “safety in feeling vulnerable” (TDF code emotion/COM-B code motivation). The most challenging phase for participants was ensuring appropriate patients were offered genomic testing. There were several consistent TDF codes: professional identity, social influences, and environmental context and resources and COM-B codes opportunity and motivation, with others varying along the patient journey. We conclude that implementation science methods can maximise the value created by the exploration of factors affecting the uptake of clinical genomics to ensure future interventions are designed to meet the needs of novice nongenetic medical specialists. Full article

Acute respiratory distress syndrome (ARDS) remains a serious illness with significant morbidity and mortality, characterized by hypoxemic respiratory failure most commonly due to pneumonia, sepsis, and aspiration. Early and accurate diagnosis of ARDS depends upon clinical suspicion and chest imaging. Coronavirus disease 2019 (COVID-19) is an important novel cause of ARDS with a distinct time course, imaging and laboratory features from the time of SARS-CoV-2 infection to hypoxemic respiratory failure, which may allow diagnosis and management prior to or at earlier stages of ARDS. Treatment of ARDS remains largely supportive, and consists of incremental respiratory support (high flow nasal oxygen, non-invasive respiratory support, and invasive mechanical ventilation), and avoidance of iatrogenic complications, all of which improve clinical outcomes. COVID-19-associated ARDS is largely similar to other causes of ARDS with respect to pathology and respiratory physiology, and as such, COVID-19 patients with hypoxemic respiratory failure should typically be managed as other patients with ARDS. Non-invasive respiratory support may be beneficial in avoiding intubation in COVID-19 respiratory failure including mild ARDS, especially under conditions of resource constraints or to avoid overwhelming critical care resources. Compared to other causes of ARDS, medical therapies may improve outcomes in COVID-19-associated ARDS, such as dexamethasone and remdesivir. Future improved clinical outcomes in ARDS of all causes depends upon individual patient physiological and biological endotyping in order to improve accuracy and timeliness of diagnosis as well as optimal targeting of future therapies in the right patient at the right time in their disease. Full article

A rapid increase in the number of patients with coronavirus disease 19 (COVID-19) may overwhelm the available medical resources. We aimed to evaluate risk factors for disease severity in the early stages of COVID-19. The cohort comprised 293 patients with COVID-19 from 5 March 2020, to 18 March 2020. The Korea Centers for Disease Control and Prevention (KCDC) classification system was used to triage patients. The clinical course was summarized, including the impact of drugs (angiotensin II receptor blockers [ARB], ibuprofen, and dipeptidyl peptidase-4 inhibitors [DPP4i]) and the therapeutic effect of lopinavir/ritonavir. After adjusting for confounding variables, prior history of drug use, including ARB, ibuprofen, and DPP4i was not a risk factor associated with disease progression. Patients treated with lopinavir/ritonavir had significantly shorter progression-free survival than those not receiving lopinavir/ritonavir. KCDC classification I clearly distinguished the improvement/stabilization group from the progression group of COVID-19 patients (AUC 0.817; 95% CI, 0.740–0.895). Full article

Refugees frequently face extended delays in their efforts to enter the United States (U.S.) and those who are successful, in many cases, encounter overwhelming obstacles, inadequate resources, and a complex system of legal barriers. Travel restrictions based on equivocal health concerns and a drop in refugee admittance ceilings have complicated the situation. The authors retrieved and analyzed peer-reviewed journal articles, government agency press releases, media postings, epidemiologic factsheets, and relevant lay publications to critically assess U.S. policy regarding refugee resettlement based on health-related grounds. While refugees arguably exhibit an increased incidence of measles and tuberculosis compared with the U.S. population, the legitimacy of the medical examination will be undermined if other diseases that are endemic to refugee populations, yet currently deemed admissible, are used to restrict refugees from entering the U.S. This paper addressees the historic refugee policy of the U.S. and its consequent effect on the health of this vulnerable population. The needs of refugees should be carefully considered in the context of increased disease burden and the associated health care challenges of the country as a whole. Full article

Dementia results in brain dysfunction, disability and dependency among affected people, causing an overwhelming burden for caregivers. China has the largest number of people with dementia worldwide and is facing severe challenges with respect to dementia care, including poor awareness of dementia in the public, inadequate knowledge of dementia for medical professionals and caregivers, an underdeveloped dementia service system, and high costs of dementia care. To address these challenges, China is taking action to increase dementia awareness and education among the public and care providers, and develop policies, services and resources for dementia care. Full article

The problem of an ageing population has become serious in the past few years as the degeneration of various physiological functions has resulted in distinct chronic diseases in the elderly. Most elderly are not willing to leave home for healthcare centers, but caring for patients at home eats up caregiver resources, and can overwhelm patients’ families. Besides, a lot of chronic disease symptoms cause the elderly to visit hospitals frequently. Repeated examinations not only exhaust medical resources, but also waste patients’ time and effort. To make matters worse, this healthcare system does not actually appear to be effective as expected. In response to these problems, a wireless remote home care system is designed in this study, where ZigBee is used to set up a wireless network for the users to take measurements anytime and anywhere. Using suitable measuring devices, users’ physiological signals are measured, and their daily conditions are monitored by various sensors. Being transferred through ZigBee network, vital signs are analyzed in computers which deliver distinct alerts to remind the users and the family of possible emergencies. The system could be further combined with electric appliances to remotely control the users’ environmental conditions. The environmental monitoring function can be activated to transmit in real time dynamic images of the cared to medical personnel through the video function when emergencies occur. Meanwhile, in consideration of privacy, the video camera would be turned on only when it is necessary. The caregiver could adjust the angle of camera to a proper position and observe the current situation of the cared when a sensor on the cared or the environmental monitoring system detects exceptions. All physiological data are stored in the database for family enquiries or accurate diagnoses by medical personnel. Full article