Diagnosis and treatment protocol for COVID-19 patients(Tentative 10th Version)

To further improve the diagnosis and treatment of COVID-19,the National Health Commission of People's Republic of China and the National Administration of Traditional Chinese Medicine convened a group of experts to revise the relevant content of the Diagnosis and Treatment Protocol for COVID-19 Patients(Trial Version 9)and developed the Diagnosis and Treatment Protocol for COVID-19 Patients(Trial Version 10),summarizing the etiological characteristics,epidemiological characteristics,prevention,clinical features,diagnosis,clinical classification,population with high risk of severe/critical illnesses,early warning predictors for severe/critical illnesses,differential diagnosis,case identification and reporting,treatment,nursing,control of nosocomial infection in medical institutions,and discharge criteria for inpatients.

Automated labelling of radiology reports using natural language processing:Comparison of traditional and newer methods

Automated labelling of radiology reports using natural language processing allows for the labelling of ground truth for large datasets of radiological studies that are required for training of computer vision models.This paper explains the necessary data preprocessing steps,reviews the main methods for automated labelling and compares their performance.There are four main methods of automated labelling,namely:(1)rules-based text-matching algorithms,(2)conventional machine learning models,(3)neural network models and(4)Bidirectional Encoder Representations from Transformers(BERT)models.Rules-based labellers perform a brute force search against manually curated keywords and are able to achieve high F1 scores.However,they require proper handling of negative words.Machine learning models require preprocessing that involves tokenization and vectorization of text into numerical vectors.Multilabel classification approaches are required in labelling radiology reports and conventional models can achieve good performance if they have large enough training sets.Deep learning models make use of connected neural networks,often a long short-term memory network,and are similarly able to achieve good performance if trained on a large data set.BERT is a transformer-based model that utilizes attention.Pretrained BERT models only require fine-tuning with small data sets.In particular,domain-specific BERT models can achieve superior performance compared with the other methods for automated labelling.

Scientific and targeted prevention and control measures to optimize COVID-19 response

Since the outbreak of the COVID-19 pandemic,under the strong leadership of the Central Committee of the Communist Party of China and President Xi Jinping,China has made firm decisions to prioritize people's lives and health.Efforts have been made to avoid foreign imported infection and domestic rebound of COVID-19 cases;the“dynamic zero COVID”policy has been executed without wavering;and the prevention and control measures have been optimized and improved in response to changing circumstances,actively responding to the impact caused by multiple waves of COVID-19 surge globally.China has made extraordinary efforts to safeguard people's lives and health.Meanwhile,prevention and control measures were timely updated to coordinate with economic and social development.On November 10,the Standing Committee of the Central Political Bureau held a meeting to discuss the latest situation of the COVID-19 pandemic in China.Twenty measures(referred to as“the 20-point measures”)were officially announced to further optimize the COVID-19 response.The latest prevention and control measures involve the requirements and guidance for isolation at home,high-risk area delineation,nucleic acid testing,international inbound flights and travelers,vaccination rollout,medical resource preparedness,and protection for special places and vulnerable population.

Prevention and control measures to further optimize COVID-19 response

On November 11,2022,the Chinese government released the Scientific and Targeted Prevention and Control Measures to Optimize COVID-19 Response.Since that time,adjusted measures have been implemented throughout China,leading to major shifts in implementation of the national prevention and control strategy.On the basis of the current situation of the epidemic and the evolving SARS-Cov-2 variants,an additional 10 specifications(referred to as“the 10-point measures”)were officially released on December 7,2022,in an effort to further optimize the prevention and control measures.The latest adjustments pertain to the specification of:precise delineation of high-risk areas,nucleic acid testing scheme,isolation and health monitoring,restriction and lifting of high-risk areas,medicine supply,vaccination rollout among older people,health status of key populations,social functioning,and campus response.

Balancing medical innovation and affordability in the new healthcare ecosystem in China:Review of pharmaceutical pricing and reimbursement policies

The China Basic Medical Insurance Program was created in 1999 with three objectives:equal accessibility,affordability,and quality.Today,it has become the biggest medical insurance program in the world,covering 95%of China's population.Since 2015,China's healthcare ecosystem has been reshaped by increasing innovation,which has in turn been driven by regulatory reform,enhancement of research and development capability,and capital market development.There has also been improved regulatory efficiency to reduce lags in launching drugs.In 2022,nearly 20%of novel active substances launched globally were from China.China has also risen to become the second biggest contributor to innovation in terms of pipelines.Using a“fast-follow”strategy,many locally developed innovative drugs can compete with products from multinational companies in their quality and pricing.However,China's pharmaceutical and biotechnology industry will continue to face challenges in pricing and reimbursement,as well as a shortened product lifecycle with rapid price erosion.The government has already accelerated the timeline for updating the drug reimbursement list and is willing to create a high-quality medical insurance program.However,some obstacles are hard to overcome,including reimbursement for advanced therapies,limited funding and an increasing burden of disease due to an aging population.This article reviews the trajectory of medical innovation in China,including the challenges.Looking forward,balancing affordability and innovation will be critical for China to continue the trajectory of growth.The article also offers some suggestions for future policy reform,including optimizing reimbursement efficiency with a focus on highquality solutions,enhancing the value assessment framework,payer repositioning from“value buyer”to“strategic buyer”,and developing alternative market access pathways for innovative drugs.

To what extent do disparities in economic development and healthcare availability explain between-province health inequalities among older people in China?

Background:Uneven economic development has led to substantial health inequalities between Chinese provinces.The extent of,and factors underlying,between-province health inequalities have received little attention.Methods:Data from 15,278 respondents in Wave 2(2013)of the China Health and Retirement Longitudinal Study(CHARLS)were used to investigate inequalities among people aged≥50 years in five health outcomes between 27 Chinese province-level administrative units.After characterizing the betweenprovince differences and the relevance of province effects,proportional change in variance between unadjusted and adjusted models was calculated to determine the percentage of between-province variance in health outcomes explained by province-level variables including measures of economic development and healthcare availability.Results:Although province effects explained<10%of overall variance in health outcomes,they underpinned large between-province inequalities among people aged≥50 years.Gross Regional Product per capita was more important than doctor density in explaining between-province variance in health outcomes,particularly depression symptoms and instrumental activities of daily living impairment.Conclusion:Policy efforts,including more equal distribution of healthcare personnel,may be warranted to reduce between-province health inequalities.

Exploring COVID-19 from the perspectives of healthcare personnel in Malawi

Background:The Coronavirus 2019 disease(COVID-19)brought many healthcare systems around the world to the point of collapse all the while putting the lives of healthcare workers at risk.This study forgoes an institutional look at healthcare to center individual healthcare personnel in Malawi to better understand(1)how the worldviews of healthcare workers impact their work in the context of COVID-19,(2)how COVID-19 impacted healthcare workers,and(3)the unique conditions faced by being a healthcare worker in a low-income nation.Methods:This research uses a hermeneutic phenomenological approach to qualitative methodology involving in-depth interviews(n=15)with health-care workers,traditional healers,and hospital leadership.The data collected were inductively coded and analyzed using the framework method,producing rich descriptions on how COVID-19 impacted the lifeworlds of healthcare workers in Malawi.Results:The findings reveal many of the struggles healthcare workers faced due to misaligned government policy and perceived proximity to COVID-19;outline their needs such as wanting better resources,funds,wages,and public health communication;and,exemplify the significant role that personal biases,worldviews,and sense of fear played in how healthcare workers perceived and interacted with COVID-19.Conclusion:Much of what was said echoes beyond borders,reflecting common global sentiments felt by healthcare personnel,and offers directions to explore building policies,strategies,and plans in preparation for any future disease outbreaks.

Lessons learned from the hospital to home community care program in Singapore and the supporting AI multiple readmissions prediction model

In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.

Health reform in China:Developments and future prospects

In 2009,China initiated a new round of health reform to establish a wellfunctioning health system.The 2009 health reform did make some significant achievements in improving affordability and accessibility.In particular,social health insurance has been expanded significantly and various social health insurance plans have covered over 95%of total population in China by 2011.The Chinese government also has significantly increased fiscal input for health financing.However,affordability remains a serious concern as the social health insurers,as purchasers,were not very effective in containing the growth of health expenditure.Accessibility to primary care and public health is another concern.In this context,health governance reforms are necessary to address affordability and accessibility issues.Health governance set rules for key actors of the health system(including service providers,health insurers and government departments)by taking into account the strategies and incentives of these actors in their interactions.In recent years,a series of reforms in health governance have been initiated.Some progresses have been achieved.For the next stage of health reform,issues including how to further reform the governance structure of medical institutions and how to improve resource allocation in the health system are critical.

Development trends of etiological research contents and methods of noncommunicable diseases

1|BACKGROUND Noncommunicable diseases(NCDs)are a significant public concern,greatly impacting the economic and social development in China.In 2019,NCDs accounted for a staggering 88.5%of total deaths in China,with cardiovas-cular diseases,cancer,chronic respiratory diseases,and diabetes—the four major chronic diseases—contributing to a premature mortality rate of 16.5%[1].The complexity of NCDs arises from the involvement of multiple genetic and environmental factors that interact in intricate ways.The complexity is characterized by a multitude of interactions among genes,proteins,and metabolic path-ways throughout the various stages of life.

COVID-19 retreats and world recovers:A silver lining in the dark cloud

The coronavirus disease(COVID-19),which the World Health Organization classified as the Sixth Public Health Emergency Of International Concern(PHEIC)on January 30,2020,is no longer a PHEIC.Millions were affected due to unawareness.The increase in fatalities and shortage of medicine was the first outrage of COVID-19.As per the Johns Hopkins COVID-19 resource center database,it was observed that the disease has spread dynamically across 200+nations worldwide affecting more than 600 million people from 2019 to 2023,and over thousands of people were victimized regularly at a 2%mortality rate(approx.).In the midway,the mutant variants of concern like omicron,and delta have also created havoc and caused significant impact on public health,global economy,and lifestyle.Since 2019,3 years now passed and the dynamic disease statistics seem decelerated;moreover,the prevalence of COVID-19 is also fading.The Johns Hopkins resource center has also stopped recording the data of the global pandemic recently from March 10,2023.Hence,based on the facts,we are presenting a concise report on the pandemic from 2019 to 2023,which includes a brief discussion of the global pandemic.We have highlighted global epidemiology,emphasizing the Indian COVID scenario,vaccination across the globe,and the psychosocial and geopolitical consequences of COVID-19 with a brief background to pathology,clinical management,and the worldwide response against triage.A lot has changed and still needs to change after three tough years of COVID-19.Even though science has progressed and advanced research in medicine is pointing toward future generations,there is no standard care supplied for COVID-19-like calamities.COVID-19 cases might have declined but its influence on the society is still stagnant.This COVID experience has taught us that,despite our bleak beginnings,there is always hope for the future and that we must act with foresight to improve things for future generations.

The development and impact of adopting electronic health records in the United States:A brief overview and implications for nursing education

1|DEVELOPMENT AND ADOPTION OF EHR IN THE UNITED STATES At present,health-care systems in the United States face enormous challenges in providing quality care,characterized by safe,effective,efficient,patientcentered,timely,and equitable care while containing health-care costs[1,2].To understand and address patients'increasingly complicated health-care needs,we need safe access to quality information that is characterized by integrity,reliability,and accuracy[3],and establish mutually beneficial relationships among a multidisciplinary team of professionals[4].Traditional paper-based clinical workflow produces many issues such as illegible handwriting,inconvenient access,the possibility of computational prescribing errors,inadequate patient hand-offs,and drug administration errors.These problems can lead to medical errors,omissions,and duplications and,ultimately,poor patient outcomes and compromised quality of care[2].

CardioLabelNet:An uncertainty estimation using fuzzy for abnormalities detection in ECG

Electrocardiography(ECG)abnormalities are evaluated through several automatic detection methods.Primarily,real-world ECG data are digital signals those are stored in the form of images in hospitals.Also,the existing automated detection technique eliminates the cardiac pattern that is abnormal and it is difficult to multiple abnormalities at some instances.To address those issues in this paper conventional ECG image automated techniques CardioLabelNet model is proposed.The proposed model incorporates two stages for image abnormality detection.At first fuzzy membership is performed in the image for computation of uncertainty.In second stage,classification is performed for computation of abnormal activity.The proposed CardioLabelNet collect ECG image data set for the uncertainty estimation while taking the account of various image classes which includes the global and local entropy of image pixels.For each waveform,uncertainties are calculated on the basis of global entropy.The computation of uncertainty in the images is performed with the fuzzy membership function.The spatial likelihood estimation of a fuzzy weighted membership function is used to calculate local entropy.Upon completion of fuzzification,classification is performed for the detection of normal and abnormal patterns in the ECG signal images.Through integration of stacked architecture model classification is performed for ECG images.The proffered algorithm performance is calculated in terms of accuracy for segmentation,Dice similarity coefficient,and partition entropy.Additionally,classification parameters accuracy sensitivity,specificity,and AUC are evaluated.The proposed approach outperforms the existing methodology,according to the results of a comparative analysis.

Measuring quality of life at work for healthcare and social services workers:A systematic review of available instruments

Quality of life at work is an important and widely discussed concept in the literature.Several instruments can be used to measure it,but with regard to healthcare and social services,the existing instruments are not well known.A review of available instruments intending to capture the quality of life of healthcare and social services workers(QoLHSSW)is necessary to better assess their working conditions and promote programs/guidelines to improve these conditions.The aim of this study was to identify the existing instruments used in measuring QoLHSSW and explore their characteristics.Particular attention was given to instruments adapted to the province of Quebec,Canada,which enabled the determination of which instruments are adapted for the measurement of QoLHSSW in Quebec and possibly elsewhere.A systematic review of the literature was conducted according to the JBI methodological guide.The articles'selection procedure was performed according to the PRISMA flowchart.The search was conducted up to October 28,2021,and then updated on January 25,2023,in four databases:PsycINFO,Medline,Embase,and CINAHL.The selection and extraction were performed independently by two researchers.The analysis of the quality of the studies was performed with the COnsensus‐based Standards for the selection of health Measurement Instruments.From a total of 8178 entries,13 articles corresponding to 13 instruments were selected.Among these instruments,the common aspects that were considered were work conditions,job satisfaction,stress at work,relationship/balance,and career development.Most instruments used a 5‐point Likert scale.Various validation methods were used,including reporting Cronbach's alpha for overall scale reliability;factor analysis to test construct validity;different model fit indices to test model superiority;different language comparisons to test cross‐cultural validity;and qualitative expert reviews to assess content validity.

Investigating the relationships between emotional experiences and behavioral response

The Covid-19 pandemic produced a complex combination of intense negative emotions among the general public,influencing people's coping reactions toward the pandemic.Yet each discrete emotion may affect people's behaviors in different ways.Unveiling the specific emotion–behavior relationships can provide valuable implications for designing effective intervention programs.Through the lens of the appraisal theory of emotion,we assessed the relationships between negative emotions and pandemic-related behaviors among the Chinese population midst the early outbreak of the pandemic.An anonymous online survey was distributed to mainland of China participants(n=2976),which assessed individuals'emotional states and behavioral reactions to the pandemic.Consistent with the differential appraisal theme underlying each negative emotion as delineated by the appraisal theory,mixed relationships between emotions and pandemic-related behaviors were revealed.Specifically,anxiety was positively associated with behaviors of seeking pandemic-related information,sharing such information,and stockpiling preventive goods,yet,contrary to prediction,anxious people were reluctant to adopt preventive measures,which is maladaptive.Sad people sought information less frequently and exhibited lower intention to stockpile preventive goods;but,opposing prediction,they shared information less frequently.Angry people were more active in sharing information and in stockpiling preventive goods.These findings suggest that public health practitioners can utilize the emotion–behavior relationships to identify the vulnerable individuals who tend to adopt maladaptive coping behaviors,help them address emotional distress,and encourage their adoption of effective coping behaviors.

Investigating catastrophic health expenditure among people living with HIV and AIDS in South Western Nigeria

Background:This study aimed to determine the catastrophic healthcare expenditure(CHE)among people living with HIV(PLHIV)in Lagos and to identify factors associated with CHE among them.Methods:The study was a descriptive cross-sectional survey conducted between January and March 2021 among 578 PLHIVs drawn from various healthcare facilities in Lagos where HIV care and treatment services should be provided free of charge.Data were collected through pretested questionnaires and analyzed using Stata SE 12.Results:The mean monthly expenditure on food was N29,282($53.2),while expenditure on healthcare averaged N8364($15.2).Nearly 60%of respondents experienced CHE,while around 30%had to borrow money to pay for some aspect of their medical treatment.Almost all(96%)had no health insurance plan.Respondents'group,personal income,perception of current health status,and the number of people in their households were significantly associated with catastrophic health expenditure p<0.05.PLHIV in the racial/ethnic minority/migrants'group and those who earned less than₦30,000($55)were statistically significantly associated with CHE at p<0.001 with OR of 28.7 and 3.15,respectively.Conclusions:The study,therefore,highlights the widespread financial hardship faced by PLHIV in accessing healthcare,and the need for policies to increase financial risk protection.

The effect of older population on public health spending:Evidence from Spain

ackground:The gradual ageing of the population,and its effect on public spending,constitutes an urgent challenge for advanced economies.Through this study,we analyse the effect of older people,and their health and individual characteristics,on public health spending.Methods:Using logistic regression methods,we have analysed the use of different health services and health technologies by older people in Spain,controlled for several health,socioeconomic,and other individual factors.Results:The main factors that explain the consumption of both health services and health technology,above age,are related to the so-called need factors:self-reported health status,presence of chronic diseases,and disability.Conclusion:Knowing the main factors that imply greater public health spending is a topic of special interest for designing efficient health policies,in a context of growth in public health spending.In this way,preventive attention on the so-called need factors may be an important driver to improve the effectiveness of spending.

Diagnosis and treatment protocol for COVID-19 patients(Trial Version 9)

To further improve the diagnosis and treatment of COVID-19,China National Health Commission and the National Administration of Traditional Chinese Medicine convened a group of experts to revise the relevant content of the Diagnosis and Treatment Protocol for COVID-19 Patients(Trial Version 8)and developed the Diagnosis and Treatment Protocol for COVID-19 Patients(Trial Version 9),summarizing the etiological characteristics,epidemiological characteristics,pathological changes,clinical features,diagnosis,clinical classification,population with high risk of severe/critical illnesses,early warning predictors for severe/critical illnesses,differential diagnosis,case identification and reporting,treatment,nursing,discharge criteria and precautions after discharge,patient transfer,control of nosocomial infection in medical institutions,and disease prevention.

Challenges and opportunities of big data analytics in healthcare

Data science is an interdisciplinary discipline that employs big data,machine learning algorithms,data mining techniques,and scientific methodologies to extract insights and information from massive amounts of structured and unstructured data.The healthcare industry constantly creates large,important databases on patient demographics,treatment plans,results of medical exams,insurance coverage,and more.The data that IoT(Internet of Things)devices collect is of interest to data scientists.Data science can help with the healthcare industry's massive amounts of disparate,structured,and unstructured data by processing,managing,analyzing,and integrating it.To get reliable findings from this data,proper management and analysis are essential.This article provides a comprehen-sive study and discussion of process data analysis as it pertains to healthcare applications.The article discusses the advantages and dis-advantages of using big data analytics(BDA)in the medical industry.The insights offered by BDA,which can also aid in making strategic decisions,can assist the healthcare system.

Investigation of pelvic symmetry:A systematic analysis using computer aided design software

Objectives:This study aimed to investigate the symmetry of the Chinese pelvis.Methods:Computed tomography scan images of each of 50 Chinese pelvises were converted to 3D models and the left sides of the pelvises were reflected on Mimics software.Then,the reflected left side model was aligned with the right side using the closest point algorithm function of Geomagic software to perform symmetry analysis.The volume and surface area of either side of the pelvises were also calculated.The mean standard deviation(SD),the mean percentage of permissible deviations within the±2mm range,the percentage differences in volume and surface area were measured to compare pelvic symmetry.In addition,the distribution of pelvic bilateral symmetry associated with both age and sex were compared.Results:The mean SD was 1.15±0.16mm and the mean percentage of permissible deviations was 90.82%±4.67%.The deviation color maps showed that the specific areas of asymmetry were primarily localized to major muscle or ligament attachment sites and the sacroiliac joint surfaces.There was no significant difference between the bilateral sides of the pelvis in either volume or surface area.Additionally,no difference in any indexes was exhibited in relation to sex and age distribution.