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4.
Contrast Media Mol Imaging ; 2021: 3257035, 2021.
Article in English | MEDLINE | ID: covidwho-1495706

ABSTRACT

The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a vital role in preventing the spread of the pandemic of COVID-19. AI and 5G technologies are advancing by leaps and bounds, further strengthening the intelligence and connectivity of IoT applications, and conventional IoT has been gradually upgraded to be more powerful AI + IoT (AIoT). For example, in terms of remote screening and diagnosis of COVID-19 patients, AI technology based on machine learning and deep learning has recently upgraded medical equipment significantly and has reshaped the workflow with minimal contact with patients, so medical specialists can make clinical decisions more efficiently, providing the best protection not only to patients but also to specialists themselves. This paper reviews the latest progress made in combating COVID-19 with both IoT and AI and also provides comprehensive details on how to combat the pandemic of COVID-19 as well as the technologies that may be applied in the future.


Subject(s)
Artificial Intelligence , COVID-19/prevention & control , Delivery of Health Care/standards , Internet of Things/statistics & numerical data , Machine Learning , SARS-CoV-2/isolation & purification , COVID-19/virology , Humans
6.
BMJ Open ; 10(1): e034400, 2020 01 21.
Article in English | MEDLINE | ID: covidwho-1455701

ABSTRACT

INTRODUCTION: The health workforce is an integral component of the healthcare system. Comprehensive, high-quality data on the health workforce are essential to identifying gaps in health service provision, as well as informing future health workforce and health services planning, and health policy. While many data sources are used in Australia for these purposes, the quality of the data sources with respect to relevance, accessibility and accuracy is not clear. METHODS AND ANALYSIS: This scoping review aims to identify and appraise publicly available data sources describing the Australian health workforce. The review will include any data source (eg, registry, administrative database and survey) or document reporting a data source (eg, journal article, report) on the Australian health workforce, which is publicly available and describes the characteristics of the workforce. The search will be conducted in 10 bibliographic databases and the grey literature using an iterative process. Screening of titles and abstracts will be undertaken by two investigators, independently, using Covidence software. Any disagreement between investigators will be resolved by a third investigator. Documents/data sources identified as potentially eligible will be retrieved in full text and reviewed following the same process. Data will be extracted using a customised data extraction tool. A customised appraisal tool will be used to assess the relevance, accessibility and accuracy of included data sources. ETHICS AND DISSEMINATION: The scoping review is a secondary analysis of existing, publicly available data sources and does not require ethics approval. The findings of this scoping review will further our understanding of the quality and availability of data sources used for health workforce and health services planning in Australia. The results will be submitted for publication in peer-reviewed journals and presented at conferences targeted at health workforce and public health topics.


Subject(s)
Delivery of Health Care/standards , Health Policy , Health Workforce/standards , Public Health , Workforce/statistics & numerical data , Australia , Humans , Peer Review
7.
Gerontologist ; 60(3): e200-e217, 2020 04 02.
Article in English | MEDLINE | ID: covidwho-1455299

ABSTRACT

BACKGROUND AND OBJECTIVES: In long-term care (LTC) facilities, nursing staff are important contributors to resident care and well-being. Despite this, the relationships between nursing staff coverage, care hours, and quality of resident care in LTC facilities are not well understood and have implications for policy-makers. This systematic review summarizes current evidence on the relationship between nursing staff coverage, care hours, and quality of resident care in LTC facilities. RESEARCH DESIGN AND METHODS: A structured literature search was conducted using four bibliographic databases and gray literature sources. Abstracts were screened by two independent reviewers using Covidence software. Data from the included studies were summarized using a pretested extraction form. The studies were critically appraised, and their results were synthesized narratively. RESULTS: The systematic searched yielded 15,842 citations, of which 54 studies (all observational) were included for synthesis. Most studies (n = 53, 98%) investigated the effect of nursing staff time on resident care. Eleven studies addressed minimum care hours and quality of care. One study examined the association between different nursing staff coverage models and resident outcomes. Overall, the quality of the included studies was poor. DISCUSSION AND IMPLICATIONS: Because the evidence was inconsistent and of low quality, there is uncertainty about the direction and magnitude of the association between nursing staff time and type of coverage on quality of care. More rigorously designed studies are needed to test the effects of different cutoffs of care hours and different nursing coverage models on the quality of resident care in LTC facilities.


Subject(s)
Homes for the Aged/standards , Nursing Homes/standards , Nursing Staff/statistics & numerical data , Personnel Staffing and Scheduling/statistics & numerical data , Quality of Health Care , Aged , Delivery of Health Care/standards , Humans , Long-Term Care , Workforce
9.
Healthc Policy ; 17(1): 17-24, 2021 08.
Article in English | MEDLINE | ID: covidwho-1431157

ABSTRACT

The unequal social and economic burden of the COVID-19 pandemic is evident in racialized and low-income communities across Canada. Importantly, social inequities have not been adequately addressed and current public policies are not reflective of the needs of diverse populations. Public participation in decision-making is crucial and there is, therefore, a pressing need to increase diversity of representation in patient partnerships in order to prevent the further exclusion of socially marginalized groups from research and policy making. Deliberate effort and affirmative action are needed to meaningfully engage and nurture diverse patient partnerships by broadening the scope of the patient community to include excluded or underrepresented individuals or groups. This will help us co-develop ways to enhance access and equity in healthcare and prevent the systematic reproduction of structural inequalities that have already been heightened by the COVID-19 pandemic.


Subject(s)
Biomedical Research/standards , COVID-19/therapy , Delivery of Health Care/standards , Health Equity/standards , Health Policy , Patient Selection , Research Design/standards , Adult , Aged , Aged, 80 and over , Canada , Female , Guidelines as Topic , Humans , Male , Middle Aged , Pandemics , SARS-CoV-2
10.
PLoS One ; 16(9): e0257127, 2021.
Article in English | MEDLINE | ID: covidwho-1430534

ABSTRACT

In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impact of the number of hospital admissions per day on a patient's length of stay (LOS) and hospital mortality rate using both ordinary least squares (OLS) and instrumental variable (IV) methods. To deal with potential endogeneity problems and accurately identify the impact of medical staff configuration on medical quality, the daily air quality index was selected as the IV. Furthermore, we examined the differential effects of hospital admissions on the quality of care across different hospital tiers. We used the data from a random sample of 10% of inpatients from a city in China, covering the period from January 2014 to June 2019. Our final regression analysis included a sample of 167 disease types (as per the ICD-10 classification list) and 862,722 patient cases from 517 hospitals. According to our results, the LOS decreased and hospital mortality rate increased with an increasing number of admissions. Using the IV method, for every additional hospital admission, there was a 6.22% (p < 0.01) decrease in LOS and a 1.86% (p < 0.01) increase in hospital mortality. The impact of healthcare staffing levels on the quality of care varied between different hospital tiers. The quality of care in secondary hospitals was most affected by the number of admissions, with the average decrease of 18.60% (p < 0.05) in LOS and the increase of 6.05% (p < 0.01) in hospital mortality for every additional hospital admission in our sample. The findings suggested that the supply of medical services in China should be increased and a hierarchical diagnosis and treatment system should be actively promoted.


Subject(s)
Delivery of Health Care/standards , Adolescent , Adult , Air Pollution/analysis , China , Cities , Female , Health Personnel , Hospital Mortality , Humans , Length of Stay , Male , Middle Aged , Regression Analysis , Young Adult
12.
J Infect Dev Ctries ; 15(8): 1048-1053, 2021 08 31.
Article in English | MEDLINE | ID: covidwho-1405475

ABSTRACT

INTRODUCTION: In Africa, the first case of COVID-19 was reported in February 2020. Mauritania's first case was confirmed in March 2020. METHODOLOGY: We provide an update of the COVID-19 epidemic in Mauritania as of December 2020, and describe the country's Health System Response. RESULTS: In total, 133,749 diagnostic tests were performed, 14,364 (10.7%) were positive (309 cases/100,000 inhabitants). Case fatality rate was 2.4%. The 20-39 year-olds (41%) and males (59.1%) were most commonly affected. Comorbidities among fatal cases included cardiovascular diseases (44.8%) and diabetes (37.1%). Clinical symptoms included fever (57%), cough (52%), running nose (47%) and headache (26%). After the first case, prevention measures were progressively tightened, and quarantine implemented for all suspected cases. Schools and universities were closed, and flights to Mauritania suspended. Restaurants and cafeterias were closed, and night curfews installed. Friday prayers were suspended nationwide, and movements between regions restricted. These measures helped to contain the spread of SARS-CoV-2 during the first pandemic wave, which peaked in June 2020 with low rates. However, the number of daily cases reached high levels in December 2020, during the second wave (40.1% of all cases and 48.9% of deaths). During the first wave, there were 38 ICU beds nationwide, but the ICU's capacity increased in short time. CONCLUSIONS: Mauritania has passed through the first pandemic wave with relatively low case fatality rates, currently being at the end of the second wave. As the country's health system is very vulnerable, there is a need for strict public health measures during epidemics.


Subject(s)
COVID-19/epidemiology , Delivery of Health Care/statistics & numerical data , Delivery of Health Care/standards , Adolescent , Adult , Aged , COVID-19/mortality , COVID-19/prevention & control , Child , Child, Preschool , Community Health Planning , Delivery of Health Care/methods , Female , Humans , Infant , Infant, Newborn , Male , Mauritania/epidemiology , Middle Aged , Public Health , Young Adult
13.
J Korean Acad Nurs ; 51(4): 395-407, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1403932

ABSTRACT

The COVID-19 curve seesawed and reached the fourth pandemic in July 2021. Since the first three waves, the focus has been on achieving herd immunity through vaccination while a lot of manpower is used for quarantine. However, we have not been able to prevent the fourth wave. The causes are thought to be related to people who doubt the safety of the vaccine and refuse it or violate quarantine guidelines such as social distancing. This study examined guidelines for preventing and controlling COVID-19, the accuracy of vaccination-related information, and described quarantine measures including for those who completed vaccination. In conclusion, prevention and vaccination are the most effective countermeasures against COVID-19. We recommend people vaccination with self-quarantine. Also, it is necessary to make large investments to protect and support nurses in future pandemics.


Subject(s)
COVID-19 Vaccines , COVID-19 , Delivery of Health Care/standards , Guidelines as Topic , Health Personnel/psychology , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/psychology , COVID-19 Vaccines/administration & dosage , Delivery of Health Care/methods , Humans , Pandemics , Quarantine , SARS-CoV-2
14.
Nurs Adm Q ; 45(2): 83-84, 2021.
Article in English | MEDLINE | ID: covidwho-1398192
16.
Diabetes Metab Syndr ; 15(5): 102242, 2021.
Article in English | MEDLINE | ID: covidwho-1397297

ABSTRACT

INTRODUCTION: Emergence of COVID-19 pandemic has led to increased use of telemedicine in health care delivery. Telemedicine facilitates long-term clinical care for monitoring and prevention of complications of diabetes mellitus. GUIDELINES: Precise indications for teleconsultation, clinical care services which can be provided, and good clinical practices to be followed during teleconsultation are explained. Guidance on risk assessment and health education for diabetes risk factors, counselling for blood glucose monitoring, treatment compliance, and prevention of complications are described. CONCLUSION: The guidelines will help physicians in adopting teleconsultation for management of diabetes mellitus, facilitate access to diabetes care and improve health outcomes.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus, Type 2/therapy , Remote Consultation/standards , Biomedical Research/organization & administration , Biomedical Research/standards , COVID-19/prevention & control , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/standards , Delivery of Health Care/organization & administration , Delivery of Health Care/standards , Diabetes Mellitus, Type 2/epidemiology , Expert Testimony , Humans , India/epidemiology , Pandemics , Remote Consultation/methods , Remote Consultation/organization & administration , Telemedicine/organization & administration , Telemedicine/standards
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