Impact Health Care Research Articles

Neuro Receptor Signal Detecting and Monitoring Smart Devices for Biological Changes in Cognitive Health Conditions.

Currently, wearable sensors significantly impact health care through continuous monitoring and event prediction. The types and clinical applications of wearable technology for the prevention of mental illnesses, as well as associated health authority rules, are covered in the current review. The technologies behind wearable ECG monitors, biosensors, electronic skin patches, neural interfaces, retinal prosthesis, and smart contact lenses were discussed. We described how sensors will examine neuronal impulses using verified machine-learning algorithms running in real-time. These sensors will closely monitor body signals and demonstrate continuous sensing with wireless functionality. The wearable applications in the following medical fields were covered in our review: sleep, neurology, mental health, anxiety, depression, Parkinson's disease, epilepsy, seizures, and schizophrenia. These mental health conditions can cause serious issues, even death. Inflammation brought on by mental health problems can worsen hypothalamic-pituitary-adrenal axis dysfunction and interfere with certain neuroregulatory systems such as the neural peptide Y, serotonergic, and cholinergic systems. Severe depressive disorder symptoms are correlated with elevated Interleukin (IL-6) levels. On the basis of previous and present data collected utilizing a variety of sensory modalities, researchers are currently investigating ways to identify or detect the current mental state. This review explores the potential of various mental health monitoring technologies. The types and clinical uses of wearable technology, such as ECG monitors, biosensors, electronic skin patches, brain interfaces, retinal prostheses, and smart contact lenses, were covered in the current review will be beneficial for patients with mental health problems like Alzheimer, epilepsy, dementia. The sensors will closely monitor bodily signals with wireless functionality while using machine learning algorithms to analyse neural impulses in real time.

The shifting landscape of private healthcare providers before and during the COVID-19 pandemic: Lessons to strengthen the private sectors engagement for future pandemic and tuberculosis care.

COVID-19 pandemic changed many aspects of healthcare services and deliveries, including among private healthcare providers (i.e., private healthcare facilities [HCFs] and private practitioners [PPs]). We aimed to compare the spatial distribution of private providers and describe changes in characteristics and services offered during and before the COVID-19 pandemic, and explore the tuberculosis (TB) and COVID-19-related services offered by the private sector in Bandung, Indonesia. A cross-sectional study with historical comparison was conducted in 36 randomly selected community health centers areas (locally referred to as Puskesmas) in Bandung, Indonesia, during the COVID-19 pandemic from 5th April 2021 - 27th December 2021. Data pertaining to before the COVID-19 pandemic was abstracted from a similar survey conducted in 2017 (i.e., INSTEP study). We obtained latitude and longitude coordinates of private healthcare providers and then compared the geographical spread with data collected for INSTEP study. We also compared characteristics of, and services provided by private healthcare providers interviewed during the COVID-19 pandemic with those previously interviewed for INSTEP study. Differences were summarized using descriptive and bivariate analyses. From April-December 2021, we surveyed 367 private HCFs and interviewed 637 PPs. Compared to INSTEP study data, the number of operating HCFs was reduced by 3% during the COVID-19 pandemic (401 vs. 412 before COVID-19), although we observed increases in laboratory service (37.8% increase), x-ray service (66.7% increase), and pharmacy (18.1% increase). Among a subset of private HCFs managing patients with respiratory tract infection symptoms, a quarter (60/235, 25.3%) indicated that they had to close their facilities in response to the emerging situation during the COVID-19 pandemic. For PPs, the number of practicing PPs was reduced by 7% during the COVID-19 pandemic (872 vs. 936 before COVID-19). Interestingly, the number of practicing PPs encountering patients with TB disease increased during the COVID-19 pandemic (42.9% vs. 35.7% before COVID-19, p = 0.008). This study confirmed that the COVID-19 pandemic adversely impacted health care service deliveries in private sectors, largely marked by closures and shortened business hours. However, the increased service capacities (laboratory and pharmacy), as well as significant increase in the number of patients cared for TB disease by PPs during the COVID-19 pandemic, made a more compelling case to further the implementation of public-private mix model for TB care in Indonesia.

Nurses' and physicians' perceptions of the impact of eHealth and information systems on the roles of health care professionals: A qualitative descriptive study.

The increased use of eHealth and information systems impacts health care work broadly, including cultural and social aspects of work such as the roles of health care professionals. This qualitative descriptive study examined the perceptions of health care professionals in terms of how eHealth and information systems have changed their roles. The data was collected via 15 semi-structured thematic interviews and analysed using content analysis with an inductive approach. The analysis indicated mainly unconscious changes in the roles of professional groups. The professionals perceived that the role of digitally competent professionals in the working community was important. Moreover, high digital competency was seen to have led to an increase or change in work tasks. Professionals' own working environments and job opportunities were seen to have affected to their roles when using information systems. eHealth was perceived to have created inequalities in work tasks, increased skills gaps and complicated work. However, eHealth made cooperation between professionals easier than before. Organisations should pay more attention to equal opportunities to increase professional's digital competency, even out workloads between professionals, and provide equal access to eHealth and information systems.

Evaluation of Climate-Aware Metrics Tools for Radiology Informatics and Artificial Intelligence: Toward a Potential Radiology Ecolabel

Radiology is a major contributor to health care's impact on climate change, in part due to its reliance on energy-intensive equipment as well as its growing technological reliance. Delivering modern patient care requires a robust informatics team to move images from the imaging equipment to the workstations and the health care system. Radiology informatics is the field that manages medical imaging IT. This involves the acquisition, storage, retrieval, and use of imaging information in health care to improve access and quality, which includes PACS, cloud services, and artificial intelligence. However, the electricity consumption of computing and the life cycle of various computer components expands the carbon footprint of health care. The authors provide a general framework to understand the environmental impact of clinical radiology informatics, which includes using the international Greenhouse Gas Protocol to draft a definition of scopes of emissions pertinent to radiology informatics, as well as exploring existing tools to measure and account for these emissions. A novel standard ecolabel for radiology informatics tools, such as the Energy Star label for consumer devices or Leadership in Energy and Environmental Design certification for buildings, should be developed to promote awareness and guide radiologists and radiology informatics leaders in making environmentally conscious decisions for their clinical practice. At this critical climate juncture, the radiology community has a unique and pressing obligation to consider our shared environmental responsibility in innovating clinical technology for patient care.

Diverticulitis patient care during the Covid-19 pandemic in Germany—a retrospective nationwide population-based cohort study

PurposeCoronavirus disease 2019 (COVID-19) impacted health care systems around the world. Despite a decrease in emergency admissions, an increased number of complicated forms of diverticulitis was reported. It was the aim of this study to analyze the pandemic impact on diverticulitis management in Germany.MethodsThis is a retrospective population-wide analysis of hospital billing data (2012–2021) of diverticulitis in Germany. Patients were identified based on diagnosis (ICD10) and procedural codes to stratify by conservative and operative management. Primary outcome of interest was admission rates, secondary outcomes were rates of surgical vs conservative treatment and fraction of complicated clinical courses during the pandemic.ResultsOf a total of 991,579 cases, 66,424 (6.7%) were admitted during pandemic lockdowns. Conservative treatment was the most common overall (66.9%) and higher during lockdowns (70.7%). Overall admissions and population adjusted rates of surgically treated patients decreased, the latter by 12.7% and 11.3%, corrected to estimated rates, in the two lockdowns. Surgery after emergency presentation decreased by 7.1% (p=0.053) and 11.1% (p=0.002) in the two lockdowns with a higher rate of ostomy and/or revision (+5.6%, p=0.219, and +10.2%, p=0.030). In-hospital mortality was increased in lockdown periods (1.64% vs 1.49%). In detail, mortality was identical in case of conservative treatment during lockdown periods (0.5%) but was higher in surgically treated patients (4.4% vs 3.6%).ConclusionDuring lockdowns, there was an overall decrease of admissions for diverticulitis, especially non-emergency admissions in Germany, and treatment was more likely to be conservative. In case of surgery, however, there was increased risk of a complicated course (ostomy, re-surgery), possibly due to patient selection.

Incidence and risk prediction of post-Covid-19 cardiovascular disease in the general population: a multivariable prediction model development and validation study

Abstract Background Previous studies showed that relative risks of various cardiovascular events are increased after Covid-19, even in non-hospitalized individuals. The global burden of post-Covid-19 cardiovascular disease is large and not (yet) hospitalized Covid-19 infected adults may represent a potential target for prevention strategies to mitigate this burden. However, good estimates of individual absolute risks in the general population and risk stratification models are lacking, yet pivotal to assess its impact and direct health care policy. Purpose This study aimed to assess the absolute risk of post-Covid-19 cardiovascular events in the general population, and subsequently explore individual risk prediction in this domain. Methods Covid-19 diagnosed adults were identified from the United Kingdom’s Clinical Practice Research Datalink Aurum, a primary care electronic healthcare database. We assessed 180-day incidence rates of atherosclerotic events (acute coronary syndrome, stroke and transient ischaemic accident), venous thrombo-embolic events (pulmonary embolism and deep venous thrombosis), and newly diagnosed atrial fibrillation and heart failure. Multivariable logistic regression models using elastic net penalization were developed on a cohort of 220,751 adults with Covid-19 before 1 December 2020 (before the start of national vaccination campaigns). Candidate predictors included age, sex, body mass index, smoking, medical history and medication. Three models were fit for each endpoint, with increasing numbers of predictors. All models were validated in (1) 138,034 vaccinated and (2) 503,404 non-vaccinated adults with a first Covid-19 diagnosis after 1 December 2020. We evaluated discriminative and calibration performance upon internal cross-validation and in both validation cohorts. Results Post-Covid-19 cardiovascular event incidences ranged from 13 (venous thromboembolic events) down to 4 (heart failure de novo) per 1000 person-years. Incidences were relatively increased up to 50 days after Covid-19 infection. However, on an absolute scale, individual risks were very low: only less than one in twenty adults with Covid-19 had a predicted 180-day risk larger than 1% and these mainly included individuals aged 60 years or older. Even though the best models had high discriminative performance (AUC > 0.90), rare outcomes complicated predictive performance and calibration. Conclusions Risks of atherosclerotic events, venous thromboembolic events, and newly diagnosed atrial fibrillation and heart failure are increased after Covid-19 infection in the general population, notably within the first 50 days after infection and in individuals aged 60 years or older. However, individual risks are too low to be predictive or helpful to guide individual risk management. Risk mitigation strategies should therefore be aimed at population-based prevention (such as increasing vaccination uptake) and at individual management of Covid-19 hospitalized patients.Graphical abstractPredicted 180-day risk after Covid-19

Toward reducing racialized pain care disparities: Approaching cannabis research and access through the lens of equity and inclusion.

There is growing interest in cannabis use for cancer pain. This commentary aims to discuss the evidence surrounding cannabis use for cancer pain in the context of the long-racialized landscape of cannabis policies and the disparity in pain control among cancer patients holding minoritized racial identities. Much evidence surrounding both the benefits and harms of cannabis use in cancer patients, and all patients in general, is lacking. Although drawing on the research in cancer that is available, it is also important to illustrate the broader context about how cannabis' deep roots in medical, political, and social history impact patient use and health care policies. There are lessons we can learn from the racialized disparities in opioid risk mitigation strategies, so they are not replicated in the settings of cannabis for cancer symptom management. Additionally, the authors intentionally use the term "cannabis" here rather than "marijuana.: In the early 1900s, the lay press and government popularized the use of the word "marijuana" instead of the more common "cannabis" to tie the drug to anti-Mexican prejudice.

Surgical Team Structure: How Familiarity and Team Size Influence Communication Effectiveness in Military Surgical Teams.

Preventable patient harm has persisted in health care despite recent advances to reduce errors. There is increasing recognition that non-technical skills, including communication and relationships, greatly impact interprofessional team performance and health care quality. Team familiarity and size are critical structural components that potentially influence information flow, communication, and efficiency. In this exploratory, prospective, cross-sectional study, we investigated the key structural components of surgical teams and identified how surgical team structure shapes communication effectiveness. Using total population sampling, we recruited surgical clinicians who provide direct patient care at a 138-bed military medical center. We used statistical modeling to characterize the relationship between communication effectiveness and five predictors: team familiarity, team size, surgical complexity, and the presence of surgical residents and student anesthesia professionals. We surveyed 137 surgical teams composed of 149 multidisciplinary clinicians for an 82% response rate. The mean communication effectiveness score was 4.61 (SD = 0.30), the average team size was 4.53 (SD = 0.69) persons, and the average surgical complexity was 10.85 relative value units (SD = 6.86). The surgical teams exhibited high variability in familiarity, with teams co-performing 26% (SD = 0.16) of each other's surgeries. We found for every unit increase in team familiarity, communication effectiveness increased by 0.36 (P ≤ .05), whereas adding one additional member to the surgical team decreased communication effectiveness by 0.1 (P ≤ .05). Surgical complexity and the influence of residents and students were not associated with communication effectiveness. For military surgical teams, greater familiarity and smaller team sizes were associated with small improvements in communication effectiveness. Military leaders can likely enhance team communication by engaging in a thoughtful and concerted program to foster cohesion by building familiarity and optimizing team size to meet task and cognitive demands. We suggest leaders develop bundled approaches to improve communication by integrating team familiarity and team size optimization into current evidence-based initiatives to enhance performance.

Neonatal Hyperbilirubinemia Admissions Following Clinical Practice Guideline Implementation.

Treatment of neonatal hyperbilirubinemia remains one of the most common reasons for readmission following delivery. Revised clinical practice guidelines (CPGs) for the treatment of neonatal hyperbilirubinemia were published on August 5, 2022. This report describes the preliminary outcomes following implementation of the new CPGs at Tripler Army Medical Center. A retrospective chart review was performed for the 12 months prior to implementation and the 5 months post implementation. Bilirubin admissions decreased from 15.6% of total admissions during the 12 months prior to the new guidelines (69/441) to 4.1% of admissions (8/194) during the 5 months after implementation of the new guidelines (P < 0.001). This corresponds to a 74% reduction (risk ratio = 0.26, 95% confidence interval [CI] 0.13 to 0.54). The decrease in admissions was found to correlate to greater than $140,000 in annual savings. Adhering to the revised CPGs has the potential to increase resource availability at a time when nursing shortages and financial instability are impacting health care systems nationwide. No short-term adverse events were noted; however, long-term follow up will be needed.

Health Care Providers' Experiences of a Mandatory Nationwide Transition to an Adalimumab Biosimilar.

Transitioning patients to biosimilars has become common to reduce costs and improve access. However, it is unclear how the transition process impacts health care providers at the frontline of the brand change. This study explores health care providers' experiences of a mandatory brand change to an adalimumab biosimilar. A cross-sectional study was conducted in Aotearoa New Zealand with 164 providers involved in the nationwide adalimumab brand change. Rheumatologists (n=39), rheumatology nurses (n=16), and pharmacists (n=109) completed a survey that assessed their satisfaction with logistics and supply, information and education, support, and administrative workload and reported what did and did not go well during the transition. The mean satisfaction score (0-10) with the transition was 5.7 (SD=2.6). Providers were the least satisfied with training for the biosimilar device, information from government agencies, and administrative workload during the transition. Satisfaction with adalimumab safety, efficacy and device quality, and the availability of sharps bins, alcohol wipes, and patient support was lower following the transition. Satisfaction with administrative workload (B=0.37, P < 0.001) and training for the device (B=0.20, P = 0.020) predicted overall satisfaction. Providers reported that a poorly implemented initial authorization process, loss of a patient support program, and insufficient communication between providers complicated the transition. The citrate-free preservative and longer authorization duration after the transition were viewed positively. Providers experienced an increased workload and reported less satisfaction with the biosimilar following the transition. Experiences may be improved by ensuring training for the device, a high-quality patient support program, and functioning authorization processes throughout the transition.

Revolutionizing education: A study on Intelligent Tutoring Systems in U.S education

Over the decades, AI has been drastically impacting health care, entertainment, finance,transportation, and many other industries, but specifically, how has it impacted educationsystems in the United States? With a better ability at examining data points, strengths, andweaknesses, in this study, we investigate how MATHia, an intelligent tutoring system, usesAI and how it has affected student performance in mathematics. AI-driven online tutoringoffers a human-like learning environment that encourages collaboration with the students inorder to learn from them and create individualized courses based on the students' emotions,progress, and learning preferences. MATHia was developed to resemble a human tutor andpersonalize learning based on each individual's area of weakness. Did these online tutorspresent a cost-effective and revolutionary solution to real-life tutors? Was MATHia effectivein enhancing students' knowledge of the mathematical concepts they had to learn? What canbe done in the future to further expand the benefits of these systems? This research answersall of these questions by taking three standpoints into consideration (educational, economic,and futuristic standpoints), each with its own unique data, problems, and solutions to theseproblems.

The Australian Genetic Heart Disease Registry: Protocol for a Data Linkage Study.

Genetic heart diseases such as hypertrophic cardiomyopathy can cause significant morbidity and mortality, ranging from syncope, chest pain, and palpitations to heart failure and sudden cardiac death. These diseases are inherited in an autosomal dominant fashion, meaning family members of affected individuals have a 1 in 2 chance of also inheriting the disease ("at-risk relatives"). The health care use patterns of individuals with a genetic heart disease, including emergency department presentations and hospital admissions, are poorly understood. By linking genetic heart disease registry data to routinely collected health data, we aim to provide a more comprehensive clinical data set to examine the burden of disease on individuals, families, and health care systems. The objective of this study is to link the Australian Genetic Heart Disease (AGHD) Registry with routinely collected whole-population health data sets to investigate the health care use of individuals with a genetic heart disease and their at-risk relatives. This linked data set will allow for the investigation of differences in outcomes and health care use due to disease, sex, socioeconomic status, and other factors. The AGHD Registry is a nationwide data set that began in 2007 and aims to recruit individuals with a genetic heart disease and their family members. In this study, demographic, clinical, and genetic data (available from 2007 to 2019) for AGHD Registry participants and at-risk relatives residing in New South Wales (NSW), Australia, were linked to routinely collected health data. These data included NSW-based data sets covering hospitalizations (2001-2019), emergency department presentations (2005-2019), and both state-wide and national mortality registries (2007-2019). The linkage was performed by the Centre for Health Record Linkage. Investigations stratifying by diagnosis, age, sex, socioeconomic status, and gene status will be undertaken and reported using descriptive statistics. NSW AGHD Registry participants were linked to routinely collected health data sets using probabilistic matching (November 2019). Of 1720 AGHD Registry participants, 1384 had linkages with 11,610 hospital records, 7032 emergency department records, and 60 death records. Data assessment and harmonization were performed, and descriptive data analysis is underway. We intend to provide insights into the health care use patterns of individuals with a genetic heart disease and their at-risk relatives, including frequency of hospital admissions and differences due to factors such as disease, sex, and socioeconomic status. Identifying disparities and potential barriers to care may highlight specific health care needs (eg, between sexes) and factors impacting health care access and use. DERR1-10.2196/48636.

No Visitors: Family Perceptions of Separation From Hospitalized Loved Ones.

Restrictions on visitors during the coronavirus disease 2019 (COVID-19) pandemic had major implications for both patients and families, impacting health care outcomes. Policies included mandatory closures, masking, and visiting restrictions both in acute and long-term care. Despite visiting restrictions in health care systems, little is known about its effects. The objective of this study was to elicit perceptions of individuals who were separated from their loved ones during acute care hospitalization during the COVID pandemic. Individuals who experienced separation from hospitalized family members because of the "no-visitor policies" during the COVID-19 pandemic were asked to participate in a study to elicit their perceptions. After institutional review board approval, interviews were completed for those who had loved ones admitted to acute care facilities only. Audiotaped and transcribed interviews were conducted in person, via telephone, or virtually using a primary investigator-developed interview guide. Using the Colaizzi method of analysis, themes were derived. Of the 11 completed interviews, 100% of participants were female, and all were residents of Texas. Themes derived from this pilot project were advocacy, communication, emotional upheaval, human factors, isolation, and abandonment. Findings from patient interviews support previous published studies. Ideas for improved patient and family experience discussed by the authors include personal protective equipment for significant others, consideration of visitation policies for those patients without decision-making capabilities, and increased accessibility to communication aids for both patients and families.

TRANSFER LEARNING BASED CNN FOR COVID 19

Covid-19 has significantly impacted individuals and health care systems on a global scale. Finding COVID-19 is difficult because there aren't manytesting kits available. A deep transfer learning-based CNN technique is used to recognize Covid 19 in chest CTimages. Chest CT scans from both Covid and non-Covid sources are included in the dataset used to train themodel. Computed tomography (CT) is a faster and more precise means of infection diagnosis when compared to x-ray imaging. This is because CT scan pictures show more potential infection indicators than x-rays, which explains why. X-rays do, however, release less ionizing energy than a CT scan. Deep transfer learning approaches can both train and fine- tune the weights of networks that have previously been trained using datasets, which is why they are effective for this. Inorder to evaluate pictures, deep learning in computer vision especially uses convolutional neural networks (CNNs). For the classification of CT scan pictures to manage the complex structure, deep architecture is needed. We hypothesize that using radiographical fluctuations of covid-19 in CT images, pre-trained deep transfer learning-based CNN models may be able to extract certain graphical properties of covid-19 and provide a clinical diagnosis. The main advantages oftransfer learning include reduced training time, improved neural network performance, and the absence of a large amount of data. Key Words: Covid 19, CNN, ResNet101, Transfer Learning

Survey on IoT based Cyber Security Issues and Autonomous Solutions for Implantable Medical Devices

In today’s world the technology has got boomed up to the peak. So as a measure of this technology peak we could see that the enhancement of this has raised very large. This technology booming has also impacted health care sector. In our paper we are going to discuss much on implantable medical devices and its uses which plays a major role in patient’s life. This IMD’s are going to be the life changing aspect of each and every patient. These devices are highly controlled IoT devices (i.e.) those devices are connected through internet which will help doctors to track the details of the patients remotely. On the other hand since all these devices are connected to internet, these are easily hacked by the hackers. The factors of how those devices are much vulnerable and what are all the threats that will make these devices to malfunction and lead a problem to the patients is discussed. And also this will lead the health sector to fall in their reputation. IMD’s are of many types which are in existing in the Medical industry. But we are going to consider some IMD’s as example and we have planned to make a detailed study on the problems on those devices. All these devices are vulnerable since it is connected to internet. So our aim is to completely or partially reduce the risks on those devices via communication network. We have also showcased the possible threats and vulnerabilities chances on those devices. The main scenarios of device control issues and possible solutions have been discussed in this article.

Preparing Medical Students for Anti-racism at the Bedside: Teaching Skills to Mitigate Racism and Bias in Clinical Encounters.

Systemic racism perpetuates health disparities and negatively impacts health care delivery and patient outcomes. Racism and bias can affect every aspect of clinical care, including history-taking, physical examination, laboratory interpretation, note-writing, oral presentation, and decision-making. Medical students must learn racism- and bias-mitigation skills early in their professional development to provide high-quality, equitable care. In November 2021, senior medical students and faculty with expertise in promoting health equity and justice in medicine designed and cotaught a Zoom-based, 75-minute, interactive session for second-year medical students. Participants prepared by reading assigned articles. Breakout rooms were used to facilitate small-group discussions. Session topics included use of a structural vulnerability assessment tool, examples of how bias can impact the physical exam, demonstration of how language can transmit bias, and skill practice using neutral instead of stigmatizing language. Forty second-year medical students participated in the session. Thirty-one students (78%) completed Likert-type surveys evaluating reaction and learning. Results showed improvements in students' perceptions of their abilities to assess for structural factors that influence health, recognize ways bias can impact clinical encounters, and apply skills to minimize bias in clinical care and decision-making. Providing opportunities for health care learners to think critically about how bias impacts patients and communities and equipping them with tools to begin dismantling exclusionary, racist practices in medicine are achievable and crucial to actualizing a just and equitable health system. This educational session can be adapted for training across health care professions and the educational continuum.

Moving Toward Inclusion: Access to Care Models for Uninsured Immigrant Children.

Policy Points Models for access to care for uninsured immigrant children that mitigate structural and sociopolitical barriers to inclusive health care include funding structures (e.g., state-sponsored coverage) and care delivery systems (e.g., federally qualified health centers,). Although the quintessential model of access to care necessitates health coverage for all children regardless of immigration status or date of United States entry, incremental policy change may more realistically and efficiently advance equitable access to high-quality health care. Intentional advocacy efforts should prioritize achievable goals that are grounded in data, are attentive to the sociopolitical milieu, are inclusive of diverse perspectives, and would meaningfully impact health care access and outcomes.

Trends in the Incidence of End-Stage Kidney Disease in Type 1 and Type 2 Diabetes in Australia, 2010-2019

Trends in end-stage kidney disease (ESKD) among people with diabetes may inform clinical management and public health strategies. We estimated trends inthe incidence of ESKD among people with type 1 and type 2 diabetes in Australia from 2010-2019 and evaluated their associated factors. Cohort study. 71,700 people with type 1 and 1,112,690 people with type 2 diabetes registered on the Australian National Diabetes Services Scheme (NDSS). We estimated the incidence of kidney replacement therapy (KRT) via linkage to the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) and the incidence of KRT or death from ESKD by linking the NDSS to the ANZDATA and the National Death Index for Australia. Calendar time, sex, age, and duration of diabetes. Incidence of KRT and KRT or death from ESKD. Incidence of ESKD, trendsover time, and associations with factors related to these trends were modeled using Poisson regression stratified by diabetes type and sex. The median duration of diabetes increased from 15.3 to 16.8 years in type 1 diabetes, and from 7.6 to 10.2 years in type 2 diabetes between 2010 and 2019. The incidence of KRT and KRT or death from ESKD did not significantly change over this time interval among people with type 1 diabetes. Conversely, the age-adjusted incidence of KRT and KRT or death from ESKD increased among males with type 2 diabetes (annual percent changes [APCs]: 2.52% [95% CI, 1.54 to -3.52] and 1.27% [95% CI, 0.53 2.03], respectively), with no significant change among females (0.67% [95% CI,-0.68 to 2.04] and 0.07% [95% CI,-0.81 to 0.96], respectively). After further adjustment for duration of diabetes, the incidence of ESKD fell between 2010 and 2019, with APCs of-0.09% (95% CI,-1.06 to 0.89) and-2.63% (95% CI,-3.96 to-1.27) for KRT and-0.97% (95% CI,-1.71 to-0.23) and-2.75% (95% CI,-3.62 to-1.87) for KRT or death from ESKD among males and females, respectively. NDSS only captures 80%-90% of people with diabetes; lack of clinical covariates limits understanding of trends. While the age-adjusted incidence of ESKD increased for males and was stable for females over the last decade, after adjusting for increases in duration of diabetes the risk of developing ESKD has decreased for both males and females. Previous studies showed an increase in new cases of kidney failure among people with type 2 diabetes, but more recent data have not been available. Here, we report trends in the rate of kidney failure for people with type 2 diabetes from 2010 to 2019 and showed that while more people with type 2 diabetes are developing kidney failure, accounting for the fact that they are also surviving longer (and therefore have a higher chance of kidney failure) the growth in this population is not caused by a higher risk of kidney failure. Nevertheless, more people are getting kidney failure than before, which will impact health care systems for years to come.

A critical analysis of health system in Nepal: Perspectives based on COVID-19 response

BackgroundNepal moved from a unitary government to a federal system of government in 2015 under its constitution. Nepal is a federal democratic republic governed by three levels of government: a federal, provincial, and local level. The response to COVID-19 in Nepal has been majorly led and controlled by the federal government. All three levels of government are performing their responsibilities; however, they face various challenges in responding to COVID-19. This study aimed to critically analyze Nepal's health system in the context of the COVID-19 response. MethodsWe conducted semi-structured in-depth interviews by telephone among the policymakers, health workers, and stakeholders at the federal, provincial, and local levels (n = 41) between January to July 2021. The interviews were audio recorded, transcribed into English, and coded using inductive-deductive approaches. ResultsCOVID-19 considerably impacted routine health care, mainly maternity services and immunization. Inadequate financial resources, inadequate human resources, and the lack of ventilators, ICUs, and X-ray services were the significant challenges in tackling and managing COVID-19 effectively. ConclusionThe study found that all three levels of government perform their roles and responsibilities and effectively manage the pandemic. The federal and provincial governments focused more on the plans and policy development, while the local government demonstrated greater accountability in implementing those plans and policies. Therefore, all three tiers of government need to coordinate together for preparing and communicating information in times of emergency. Besides, it is imperative to empower local governments to maintain Nepal's federal health system.

Changes in Healthcare Utilization Among Medicare Beneficiaries With Diabetes 2 Years Into the COVID-19 Pandemic

The coronavirus 2019 (COVID-19) pandemic abruptly impacted health care service delivery and utilization. However, the impact on older adults with diabetes in the United States is unclear. To estimate changes in health care utilization among older adults with diabetes during the initial 2 years of the COVID-19 pandemic compared to the 2 years before, and to examine the variation in utilization changes by demographic and socioeconomic characteristics. In this study, we analyzed changes in utilization, measured by the average use of health care services per 1,000 persons with diabetes, using medical claims for Medicare fee-for-service beneficiaries aged 67 years and above. Utilization changes by setting (acute inpatient, emergency room [ER], hospital outpatient, physician office, and ambulatory surgery center [ASC]) and by media (telehealth and in-person) were examined for 22 months of the pandemic (03/2020-12/2021) compared with pre-pandemic period (03/2018-12/2019). We also estimated utilization changes by beneficiaries' age group, sex, race/ethnicity, and residential urbanicity. The study sample consisted of approximately 6 million beneficiaries with diabetes each month. In the first 2 years of the pandemic, the average use of health care services by setting was 5-17% lower than the pre-pandemic level for all types of services. Phase 1 (03/2020-05/2020) had the largest decrease in utilization: physician office visits changed by -51.2% (95% CI, -55.0% to -47.5%), ASC procedures by -45.1% (95% CI, -49.8% to -40.4%), ER visits by -36.9% (95% CI, -39.0% to -34.7%), acute inpatient stays by -31.5% (95% CI, -33.6% to -29.3%), and hospital outpatient visits by -27% (95% CI, -29.3% to -24.8%). The reduction in utilization varied by sociodemographic subgroup. During the pandemic, the use of telehealth visits increased by 511.1% (95% CI, 502.2% to 520.0%) compared to the pre-pandemic period. The increase was smaller among rural residents. Medicare beneficiaries with diabetes experienced a reduction in the use of health care services during the COVID-19 pandemic, some of which persisted through two years into the pandemic. Telehealth visits increased, but not enough to overcome decreases in in-person visits. Understanding these patterns may help to optimize the use of health care resources for diabetes management in the post-pandemic era and during future emergencies.