The integration of machine learning(ML)technology with Internet of Things(IoT)systems produces essential changes in healthcare operations.Healthcare personnel can track patients around the clock thanks to healthcare I...The integration of machine learning(ML)technology with Internet of Things(IoT)systems produces essential changes in healthcare operations.Healthcare personnel can track patients around the clock thanks to healthcare IoT(H-IoT)technology,which also provides proactive statistical findings and precise medical diagnoses that enhance healthcare performance.This study examines how ML might support IoT-based health care systems,namely in the areas of prognostic systems,disease detection,patient tracking,and healthcare operations control.The study looks at the benefits and drawbacks of several machine learning techniques for H-IoT applications.It also examines the fundamental problems,such as data security and cyberthreats,as well as the high processing demands that these systems face.Alongside this,the essay discusses the advantages of all the technologies,including machine learning,deep learning,and the Internet of Things,as well as the significant difficulties and problems that arise when integrating the technology into healthcare forecasts.展开更多
As a new type of production factor in healthcare,healthcare data elements have been rapidly integrated into various health production processes,such as clinical assistance,health management,biological testing,and oper...As a new type of production factor in healthcare,healthcare data elements have been rapidly integrated into various health production processes,such as clinical assistance,health management,biological testing,and operation and supervision[1,2].Healthcare data elements include biolog.ical and clinical data that are related to disease,environ-mental health data that are associated with life,and operational and healthcare management data that are related to healthcare activities(Figure 1).Activities such as the construction of a data value assessment system,the devel-opment of a data circulation and sharing platform,and the authorization of data compliance and operation products support the strong growth momentum of the market for health care data elements in China[3].展开更多
Background:The Indian healthcare sector has undergone significant transformations due to private equity(PE)investments.The influx of capital has facilitated the expansion of infrastructure and improvement in services,...Background:The Indian healthcare sector has undergone significant transformations due to private equity(PE)investments.The influx of capital has facilitated the expansion of infrastructure and improvement in services,particularly in urban and semi-urban areas.However,this transformation raises critical concerns regarding equity in healthcare access,rising health costs,and the potential commercialization of healthcare services.Methods:Employing a critical political economy approach,this study examines the effects of PE investments in Indian healthcare.It integrates theories from Antonio Gramsci,David Harvey and Nancy Fraser to analyze the implications of these investments.The research draws on secondary data from industry reports,government statistics and academic literature to assess the trends,impacts and policy responses related to PE in healthcare.Results:PE investments have led to increased privatization,rising healthcare costs and a focus on profit-driven models.Despite expanding infrastructure,access to quality healthcare remains inequitable,particularly for marginalized and rural populations.The analysis highlights the tension between capital accumulation and public health needs,showing how PE investments prioritize profitability over equity.The commodification of healthcare reflects broader neoliberal policies that undermine public health objectives and exacerbate inequalities.Conclusion:While PE investments drive innovation and expansion,they also pose challenges to affordability and equitable access.Policy interventions are necessary to regulate PE investments and ensure that healthcare remains accessible and equitable for all.展开更多
This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance.The system employs a transformer model to process sophist...This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance.The system employs a transformer model to process sophisticated,multilingual user inputs and gain improved contextual understanding compared to conventional models,including long short-term memory(LSTM)models.In contrast to LSTMs,which sequence processes information and may experience challenges with long-range dependencies,transformers utilize self-attention to learn relationships among every aspect of the input in parallel.This enables them to execute more accurately in various languages and contexts,making them well-suited for applications such as translation,summarization,and conversational Comparative evaluations revealed the superiority of the transformer model(accuracy rate:85%)compared with that of the LSTM model(accuracy rate:65%).The experiments revealed several advantages of the transformer architecture over the LSTM model,such as more effective self-attention,the ability for models to work in parallel with each other,and contextual understanding for better multilingual compatibility.Additionally,our prediction model exhibited effectiveness for disease diagnosis,with accuracy of 85%or greater in identifying the relationship between symptoms and diseases among different demographics.The system provides translation support from English to other languages,with conversion to French(Bilingual Evaluation Understudy score:0.7),followed by English to Hindi(0.6).The lowest Bilingual Evaluation Understudy score was found for English to Telugu(0.39).This virtual assistant can also perform symptom analysis and disease prediction,with output given in the preferred language of the user.展开更多
The growing demand for international travel has highlighted the critical need for reliable tools to verify travelers’healthcare status and meet entry requirements.Personal health passports,while essential,face signif...The growing demand for international travel has highlighted the critical need for reliable tools to verify travelers’healthcare status and meet entry requirements.Personal health passports,while essential,face significant challenges related to data silos,privacy protection,and forgery risks in global sharing.To address these issues,this study proposes a blockchain-based solution designed for the secure storage,sharing,and verification of personal health passports.This innovative approach combines on-chain and off-chain storage,leveraging searchable encryption to enhance data security and optimize blockchain storage efficiency.By reducing the storage burden on the blockchain,the system ensures both the secure handling and reliable sharing of sensitive personal health data.An optimized consensus mechanism streamlines the process into two stages,minimizing communication complexity among nodes and significantly improving the throughput of the blockchain system.Additionally,the introduction of advanced aggregate signature technology accommodates multi-user scenarios,reducing computational overhead for signature verification and enabling swift identification ofmalicious forgers.Comprehensive security analyses validate the system’s robustness and reliability.Simulation results demonstrate notable performance improvements over existing solutions,with reductions in computational overhead of up to 49.89%and communication overhead of up to 25.81%inmulti-user scenarios.Furthermore,the optimized consensus mechanism shows substantial efficiency gains across varying node configurations.This solution represents a significant step toward addressing the pressing challenges of health passport management in a secure,scalable,and efficient manner.展开更多
This study examines the integration of narrative medicine(NM)into primary healthcare(PHC)settings,evaluating its role in enhancing medical humanities education within grassroots healthcare institutions.Through a compr...This study examines the integration of narrative medicine(NM)into primary healthcare(PHC)settings,evaluating its role in enhancing medical humanities education within grassroots healthcare institutions.Through a comprehensive literature review and case analysis,the research investigates the current state,challenges,and practical barriers to embedding NM into PHC systems,while proposing targeted strategies for improvement.The findings suggest that NM fosters stronger doctor-patient trust,enhances healthcare quality,and promotes humanistic care.However,primary hospitals face numerous challenges in advancing medical humanities,including a lack of trust between doctors and patients,tensions arising from the commercialization of healthcare,institutional limitations,unequal distribution of resources,and issues related to physicians'professional competencies and stress management.These interrelated obstacles detract from the quality of PHC services and the overall patient experience.Drawing on successful case studies from primary hospitals,the paper outlines effective strategies for overcoming these challenges.The study provides both theoretical and practical insights for advancing medical humanities in PHC,contributing to improvements in healthcare service quality and supporting the development of high standards in the healthcare sector.Ultimately,the findings aim to promote the broader adoption and ongoing refinement of NM within PHC institutions.展开更多
In this editorial we comment on the article by Mohamed et al published in the recent issue of World Journal of Psychiatry.Globally,health care workers are facing a major problem called burnout syndrome,which is charac...In this editorial we comment on the article by Mohamed et al published in the recent issue of World Journal of Psychiatry.Globally,health care workers are facing a major problem called burnout syndrome,which is characterized by emotional alienation,burnout,and decreased personal fulfillment.This physical and mental stress has a significant impact on the quality of care and health of medical per-sonnel.This study delves into the challenges facing Somalia’s healthcare system,such as lack of resources,heavy workloads,long working hours,and high-pressure environments that make healthcare personnel particularly vulnerable to burnout.This situation further affects their mental health and the quality of care services.Research shows that about 25%of healthcare professionals are affected by burnout syndrome.By improving the quality of sleep,strengthening monitoring,and providing mental health support,the health status of medical personnel and patient care can be effectively improved.The findings highlight the need for interventions including improved sleep quality,enhanced mental health monitoring and support,appropriate workload management,a supportive work climate,and effective time management strategies in the workplace to enhance health staff well-being and the quality of patient care.These measures are critical to addressing the current challenges of the healthcare system,improving patient care and prioritizing the well-being of frontline healthcare staff.展开更多
Objective:Patient safety culture is a concern in every healthcare organization,therefore,the healthcare leadership is encountering issues related to patient safety across the globe.In India,there is limited research a...Objective:Patient safety culture is a concern in every healthcare organization,therefore,the healthcare leadership is encountering issues related to patient safety across the globe.In India,there is limited research and information about patient safety culture among healthcare stakeholders and there is relatively little qualitative research available that captures the factors of patient safety culture.Hence,this study aims to explore the perception of healthcare professionals on patient safety culture.Methods:An exploratory qualitative study design was adopted in a tertiary care hospital.Structured focus group discussion(FGD)(n=4)among healthcare professionals and two in-depth interview focus groups were audio-recorded and transcribed.Two coders reviewed transcripts using the editing approach and organized codes into themes.The data were analyzed through MAXQDA 2022(VERBI Software GmbH,Berlin,Germany),qualitative data analysis software,and descriptive analysis technique.The main codes and themes were generated using inductive and deductive method and smart coding was done.Results:Overall,there were 190 unique mentions of codes related to patient safety culture from 4 FGDs.They were categorized into 6 major themes and subcodes were derived via smart coding using the MAXQDA software.“Resources and constraints”was the most prominent code,followed by management support,manpower shortage,burnout,and lack of personnel commitment.Conclusions:The study highlights significant gaps in patient safety culture within the healthcare setting,with resource constraints,management support,and manpower shortages emerging as critical challenges.Burnout and lack of personnel commitment further exacerbate these issues,underscoring the need for targeted interventions.展开更多
With the rapid development of medical and nursing combinations,the application of humanistic care in medical and nursing combination institutions is getting more attention.Elderly institutions are the main carrier of ...With the rapid development of medical and nursing combinations,the application of humanistic care in medical and nursing combination institutions is getting more attention.Elderly institutions are the main carrier of elderly services in China,and the demand for humanistic care among the elderly in elderly institutions is also getting higher and higher,but at present,the humanistic care ability of the nursing staff in China's medical and nursing combined institutions is low.In recent years,the state vigorously promoted the development of traditional Chinese medicine,traditional Chinese medicine nursing contains a wealth of humanistic ideas,which can provide another solution for the lack of humanistic care in healthcare institutions.This paper discusses the ideological value,practical value and talent cultivation value of TCM humanistic nursing in medical care combination,aiming to provide a reference basis for improving the quality of humanistic nursing in medical care combination organizations.展开更多
Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Num...Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.展开更多
In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper...In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper“From digits towards digitization:the past,present,and future of traditional Chinese medicine”by Academician&TCM National Master Qi WANG(王琦).展开更多
In the intricate landscape of healthcare,vicarious liability looms large,shaping the responsibilities and actions of healthcare practitioners and administrators alike.Illustrated by a poignant scenario of a medication...In the intricate landscape of healthcare,vicarious liability looms large,shaping the responsibilities and actions of healthcare practitioners and administrators alike.Illustrated by a poignant scenario of a medication error,this article navigates the complexities of vicarious liability in healthcare.It explains the legal basis and ramifications of this theory,emphasizing its importance in fostering responsibility,protecting patient welfare,and easing access to justice.The paper explores the practical effects of vicarious responsibility on day-to-day operations,leadership practices,and decision-making processes via the eyes of senior consultants,junior doctors,and hospital administrators.Through comprehensive insights and real-world examples,it underscores the imperative of fostering a culture of accountability,communication,and quality care to navigate the intricate web of liabilities inherent in modern healthcare.展开更多
BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confid...BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.展开更多
Large language models(LLMs)and natural language processing(NLP)have significant promise to improve efficiency and refine healthcare decision-making and clinical results.Numerous domains,including healthcare,are rapidl...Large language models(LLMs)and natural language processing(NLP)have significant promise to improve efficiency and refine healthcare decision-making and clinical results.Numerous domains,including healthcare,are rapidly adopting LLMs for the classification of biomedical textual data in medical research.The LLM can derive insights from intricate,extensive,unstructured training data.Variants need to be accurately identified and classified to advance genetic research,provide individualized treatment,and assist physicians in making better choices.However,the sophisticated and perplexing language of medical reports is often beyond the capabilities of the devices we now utilize.Such an approach may result in incorrect diagnoses,which could affect a patient’s prognosis and course of therapy.This study evaluated the efficacy of the proposed model by looking at publicly accessible textual clinical data.We have cleaned the clinical textual data using various text preprocessing methods,including stemming,tokenization,and stop word removal.The important features are extracted using Bag of Words(BoW)and Term Frequency-Inverse Document Frequency(TFIDF)feature engineering methods.The important motive of this study is to predict the genetic variants based on the clinical evidence using a novel method with minimal error.According to the experimental results,the random forest model achieved 61%accuracy with 67%precision for class 9 using TFIDF features and 63%accuracy and a 73%F1 score for class 9 using Bag of Words features.The accuracy of the proposed BERT(Bidirectional Encoder Representations from Transformers)model was 70%with 5-fold cross-validation and 71%with 10-fold cross-validation.The research results provide a comprehensive overview of current LLM methods in healthcare,benefiting academics as well as professionals in the discipline.展开更多
Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria sti...Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria still grapples with wide acceptance,key translational research and implementation of PM.This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.Methods:A cross‐sectional study was conducted in selected tertiary hospitals across the country.A 21‐item semi‐structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25.Descriptive statistics were used to summarize the data.A chi‐square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.Results:A total of 167 hospital pharmacists participated in the study.A high proportion of the participants are familiar with artificial intelligence(91.75%),Pharmacogenomics(84.5%),and precision medicine(61%).Overall,38.9%of the pharmacists had a good knowledge while 13.2%had a poor knowledge of PM and associated terms.The level of knowledge did not correlate significantly with gender(X^(2)=3.21,p=0.201),age(X^(2)=5,p=0.27),marital status(X^(2)=3.21,p=0.201),and professional level(X^(2)=6.85,p=0.144).The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine(49%)while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.Conclusions:There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria.Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM.Also,more research aimed at translating PM knowledge into clinical practice is recommended.展开更多
BACKGROUND Cytomegalovirus(CMV)prophylaxis with valganciclovir and ganciclovir is associated with elevated neutropenia and leukopenia risk in kidney transplant recipients,although the impact of these events on healthc...BACKGROUND Cytomegalovirus(CMV)prophylaxis with valganciclovir and ganciclovir is associated with elevated neutropenia and leukopenia risk in kidney transplant recipients,although the impact of these events on healthcare resource utilization(HCRU)and clinical outcomes is unclear.AIM To quantify clinical events and HCRU associated with neutropenia and leukope-nia among adults receiving valganciclovir and/or ganciclovir post-kidney trans-plantation.METHODS Adult kidney transplant recipients receiving valganciclovir and/or ganciclovir prophylaxis were identified in the TriNetX database from 2012 to 2021.Patient characteristics were evaluated in the 1-year period pre-first transplant.HCRU and adjusted event rates per person-year were evaluated in follow-up year 1 and years 2-5 after first kidney transplantation among cohorts with vs without neutropenia and/or leukopenia.RESULTS Of 15398 identified patients,the average age was 52.39 years and 58.70%were male.Patients with neutropenia and/or leukopenia had greater risk of clinical events for CMV-related events,opportunistic infections,use of granulocyte colony stimulating factor,and hospitalizations(relative risk>1 in year 1 and years 2-5).Patients with vs without neutropenia and/or leukopenia had higher HCRU in year 1 and years 2-5 post kidney transplantation,including the mean number of inpatient admissions(year 1:3.47 vs 2.76;years 2-5:2.70 vs 2.29)and outpatient visits(48.97 vs 34.42;31.73 vs 15.59,respectively),as well as the mean number of labs(1654.55 vs 1182.27;622.37 vs 327.89).CONCLUSION Adults receiving valganciclovir and/or ganciclovir prophylaxis post-kidney transplantation had greater risk of neutropenia and/or leukopenia,which were associated with higher clinical event rates and HCRU up to 5 years post-transplantation.These findings suggest the need for alternative prophylaxis options with lower myelosup-pressive effects to improve patient outcomes.展开更多
Digital health is transforming healthcare by integrating advanced technologies to make healthcare more accessible,efficient,and personalized.From electronic health records,telemedicine,wearable devices,and artificial ...Digital health is transforming healthcare by integrating advanced technologies to make healthcare more accessible,efficient,and personalized.From electronic health records,telemedicine,wearable devices,and artificial intelligence to the recent smart hospitals,digital health is improving patient care and outcomes while reducing healthcare costs.However,the integration of digital health faces several challenges,including data privacy,cybersecurity risks,and inequitable access to technology.This article provides an overview of the current state of digital health,key challenges in implementation,and potential solutions to maximize the benefits of digital health and ensure efficient,equitable,and patient‐centered healthcare in the future.展开更多
HIV-related stigma,discrimination,and other forms of oppression can severely undermine adherence to antiretroviral therapy(ART)among people living with HIV[1].For example,Kerr et al.reveal that perceived discriminatio...HIV-related stigma,discrimination,and other forms of oppression can severely undermine adherence to antiretroviral therapy(ART)among people living with HIV[1].For example,Kerr et al.reveal that perceived discrimination based on sexual orientation in healthcare settings significantly reduces ART adherence[1].This highlights the urgent need for targeted strategies to address stigma,discrimination,and social marginalization,especially within healthcare facilities,to improve HIV care outcomes.展开更多
Healthcare networks are transitioning from manual records to electronic health records,but this shift introduces vulnerabilities such as secure communication issues,privacy concerns,and the presence of malicious nodes...Healthcare networks are transitioning from manual records to electronic health records,but this shift introduces vulnerabilities such as secure communication issues,privacy concerns,and the presence of malicious nodes.Existing machine and deep learning-based anomalies detection methods often rely on centralized training,leading to reduced accuracy and potential privacy breaches.Therefore,this study proposes a Blockchain-based-Federated Learning architecture for Malicious Node Detection(BFL-MND)model.It trains models locally within healthcare clusters,sharing only model updates instead of patient data,preserving privacy and improving accuracy.Cloud and edge computing enhance the model’s scalability,while blockchain ensures secure,tamper-proof access to health data.Using the PhysioNet dataset,the proposed model achieves an accuracy of 0.95,F1 score of 0.93,precision of 0.94,and recall of 0.96,outperforming baseline models like random forest(0.88),adaptive boosting(0.90),logistic regression(0.86),perceptron(0.83),and deep neural networks(0.92).展开更多
文摘The integration of machine learning(ML)technology with Internet of Things(IoT)systems produces essential changes in healthcare operations.Healthcare personnel can track patients around the clock thanks to healthcare IoT(H-IoT)technology,which also provides proactive statistical findings and precise medical diagnoses that enhance healthcare performance.This study examines how ML might support IoT-based health care systems,namely in the areas of prognostic systems,disease detection,patient tracking,and healthcare operations control.The study looks at the benefits and drawbacks of several machine learning techniques for H-IoT applications.It also examines the fundamental problems,such as data security and cyberthreats,as well as the high processing demands that these systems face.Alongside this,the essay discusses the advantages of all the technologies,including machine learning,deep learning,and the Internet of Things,as well as the significant difficulties and problems that arise when integrating the technology into healthcare forecasts.
基金supported by National Natural Science Foundation of China(Grants 72474022,71974011,72174022,71972012,71874009)"BIT think tank"Promotion Plan of Science and Technology Innovation Program of Beijing Institute of Technology(Grants 2024CX14017,2023CX13029).
文摘As a new type of production factor in healthcare,healthcare data elements have been rapidly integrated into various health production processes,such as clinical assistance,health management,biological testing,and operation and supervision[1,2].Healthcare data elements include biolog.ical and clinical data that are related to disease,environ-mental health data that are associated with life,and operational and healthcare management data that are related to healthcare activities(Figure 1).Activities such as the construction of a data value assessment system,the devel-opment of a data circulation and sharing platform,and the authorization of data compliance and operation products support the strong growth momentum of the market for health care data elements in China[3].
文摘Background:The Indian healthcare sector has undergone significant transformations due to private equity(PE)investments.The influx of capital has facilitated the expansion of infrastructure and improvement in services,particularly in urban and semi-urban areas.However,this transformation raises critical concerns regarding equity in healthcare access,rising health costs,and the potential commercialization of healthcare services.Methods:Employing a critical political economy approach,this study examines the effects of PE investments in Indian healthcare.It integrates theories from Antonio Gramsci,David Harvey and Nancy Fraser to analyze the implications of these investments.The research draws on secondary data from industry reports,government statistics and academic literature to assess the trends,impacts and policy responses related to PE in healthcare.Results:PE investments have led to increased privatization,rising healthcare costs and a focus on profit-driven models.Despite expanding infrastructure,access to quality healthcare remains inequitable,particularly for marginalized and rural populations.The analysis highlights the tension between capital accumulation and public health needs,showing how PE investments prioritize profitability over equity.The commodification of healthcare reflects broader neoliberal policies that undermine public health objectives and exacerbate inequalities.Conclusion:While PE investments drive innovation and expansion,they also pose challenges to affordability and equitable access.Policy interventions are necessary to regulate PE investments and ensure that healthcare remains accessible and equitable for all.
文摘This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance.The system employs a transformer model to process sophisticated,multilingual user inputs and gain improved contextual understanding compared to conventional models,including long short-term memory(LSTM)models.In contrast to LSTMs,which sequence processes information and may experience challenges with long-range dependencies,transformers utilize self-attention to learn relationships among every aspect of the input in parallel.This enables them to execute more accurately in various languages and contexts,making them well-suited for applications such as translation,summarization,and conversational Comparative evaluations revealed the superiority of the transformer model(accuracy rate:85%)compared with that of the LSTM model(accuracy rate:65%).The experiments revealed several advantages of the transformer architecture over the LSTM model,such as more effective self-attention,the ability for models to work in parallel with each other,and contextual understanding for better multilingual compatibility.Additionally,our prediction model exhibited effectiveness for disease diagnosis,with accuracy of 85%or greater in identifying the relationship between symptoms and diseases among different demographics.The system provides translation support from English to other languages,with conversion to French(Bilingual Evaluation Understudy score:0.7),followed by English to Hindi(0.6).The lowest Bilingual Evaluation Understudy score was found for English to Telugu(0.39).This virtual assistant can also perform symptom analysis and disease prediction,with output given in the preferred language of the user.
文摘The growing demand for international travel has highlighted the critical need for reliable tools to verify travelers’healthcare status and meet entry requirements.Personal health passports,while essential,face significant challenges related to data silos,privacy protection,and forgery risks in global sharing.To address these issues,this study proposes a blockchain-based solution designed for the secure storage,sharing,and verification of personal health passports.This innovative approach combines on-chain and off-chain storage,leveraging searchable encryption to enhance data security and optimize blockchain storage efficiency.By reducing the storage burden on the blockchain,the system ensures both the secure handling and reliable sharing of sensitive personal health data.An optimized consensus mechanism streamlines the process into two stages,minimizing communication complexity among nodes and significantly improving the throughput of the blockchain system.Additionally,the introduction of advanced aggregate signature technology accommodates multi-user scenarios,reducing computational overhead for signature verification and enabling swift identification ofmalicious forgers.Comprehensive security analyses validate the system’s robustness and reliability.Simulation results demonstrate notable performance improvements over existing solutions,with reductions in computational overhead of up to 49.89%and communication overhead of up to 25.81%inmulti-user scenarios.Furthermore,the optimized consensus mechanism shows substantial efficiency gains across varying node configurations.This solution represents a significant step toward addressing the pressing challenges of health passport management in a secure,scalable,and efficient manner.
基金Supported by National Natural Science Foundation of China,No.82272204 and No.824721882022 Key Clinical Specialty of Zhejiang Province(Critical Care Medicine)+4 种基金“Pioneer”and“Leading Goose”R&D Program of Zhejiang,No.2023C03084Wenzhou Major Science and Technology Innovation Project,No.ZY2023005Central Guiding Local Technology Development,No.2024ZY01012Zhejiang Provincial College Students'Science and Technology Innovation Activity Program,No.2024R413A037National Innovation and Entrepreneurship Training Program for College Students,No.202410343030.
文摘This study examines the integration of narrative medicine(NM)into primary healthcare(PHC)settings,evaluating its role in enhancing medical humanities education within grassroots healthcare institutions.Through a comprehensive literature review and case analysis,the research investigates the current state,challenges,and practical barriers to embedding NM into PHC systems,while proposing targeted strategies for improvement.The findings suggest that NM fosters stronger doctor-patient trust,enhances healthcare quality,and promotes humanistic care.However,primary hospitals face numerous challenges in advancing medical humanities,including a lack of trust between doctors and patients,tensions arising from the commercialization of healthcare,institutional limitations,unequal distribution of resources,and issues related to physicians'professional competencies and stress management.These interrelated obstacles detract from the quality of PHC services and the overall patient experience.Drawing on successful case studies from primary hospitals,the paper outlines effective strategies for overcoming these challenges.The study provides both theoretical and practical insights for advancing medical humanities in PHC,contributing to improvements in healthcare service quality and supporting the development of high standards in the healthcare sector.Ultimately,the findings aim to promote the broader adoption and ongoing refinement of NM within PHC institutions.
基金Supported by the Science and Technology Program of Nantong City,No.Key003Nantong Young Medical Expert,No.46+2 种基金Science and Technology Program of Nantong Health Committee,No.MA2019003,No.MA2021017 and No.MSZ2024038Science and Technology Program of Nantong City,No.JCZ2022040Kangda College of Nanjing Medical University,No.KD2021JYYJYB025,No.KD2022KYJJZD022,and No.KD2024KYJJ289.
文摘In this editorial we comment on the article by Mohamed et al published in the recent issue of World Journal of Psychiatry.Globally,health care workers are facing a major problem called burnout syndrome,which is characterized by emotional alienation,burnout,and decreased personal fulfillment.This physical and mental stress has a significant impact on the quality of care and health of medical per-sonnel.This study delves into the challenges facing Somalia’s healthcare system,such as lack of resources,heavy workloads,long working hours,and high-pressure environments that make healthcare personnel particularly vulnerable to burnout.This situation further affects their mental health and the quality of care services.Research shows that about 25%of healthcare professionals are affected by burnout syndrome.By improving the quality of sleep,strengthening monitoring,and providing mental health support,the health status of medical personnel and patient care can be effectively improved.The findings highlight the need for interventions including improved sleep quality,enhanced mental health monitoring and support,appropriate workload management,a supportive work climate,and effective time management strategies in the workplace to enhance health staff well-being and the quality of patient care.These measures are critical to addressing the current challenges of the healthcare system,improving patient care and prioritizing the well-being of frontline healthcare staff.
文摘Objective:Patient safety culture is a concern in every healthcare organization,therefore,the healthcare leadership is encountering issues related to patient safety across the globe.In India,there is limited research and information about patient safety culture among healthcare stakeholders and there is relatively little qualitative research available that captures the factors of patient safety culture.Hence,this study aims to explore the perception of healthcare professionals on patient safety culture.Methods:An exploratory qualitative study design was adopted in a tertiary care hospital.Structured focus group discussion(FGD)(n=4)among healthcare professionals and two in-depth interview focus groups were audio-recorded and transcribed.Two coders reviewed transcripts using the editing approach and organized codes into themes.The data were analyzed through MAXQDA 2022(VERBI Software GmbH,Berlin,Germany),qualitative data analysis software,and descriptive analysis technique.The main codes and themes were generated using inductive and deductive method and smart coding was done.Results:Overall,there were 190 unique mentions of codes related to patient safety culture from 4 FGDs.They were categorized into 6 major themes and subcodes were derived via smart coding using the MAXQDA software.“Resources and constraints”was the most prominent code,followed by management support,manpower shortage,burnout,and lack of personnel commitment.Conclusions:The study highlights significant gaps in patient safety culture within the healthcare setting,with resource constraints,management support,and manpower shortages emerging as critical challenges.Burnout and lack of personnel commitment further exacerbate these issues,underscoring the need for targeted interventions.
文摘With the rapid development of medical and nursing combinations,the application of humanistic care in medical and nursing combination institutions is getting more attention.Elderly institutions are the main carrier of elderly services in China,and the demand for humanistic care among the elderly in elderly institutions is also getting higher and higher,but at present,the humanistic care ability of the nursing staff in China's medical and nursing combined institutions is low.In recent years,the state vigorously promoted the development of traditional Chinese medicine,traditional Chinese medicine nursing contains a wealth of humanistic ideas,which can provide another solution for the lack of humanistic care in healthcare institutions.This paper discusses the ideological value,practical value and talent cultivation value of TCM humanistic nursing in medical care combination,aiming to provide a reference basis for improving the quality of humanistic nursing in medical care combination organizations.
文摘Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.
文摘In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper“From digits towards digitization:the past,present,and future of traditional Chinese medicine”by Academician&TCM National Master Qi WANG(王琦).
文摘In the intricate landscape of healthcare,vicarious liability looms large,shaping the responsibilities and actions of healthcare practitioners and administrators alike.Illustrated by a poignant scenario of a medication error,this article navigates the complexities of vicarious liability in healthcare.It explains the legal basis and ramifications of this theory,emphasizing its importance in fostering responsibility,protecting patient welfare,and easing access to justice.The paper explores the practical effects of vicarious responsibility on day-to-day operations,leadership practices,and decision-making processes via the eyes of senior consultants,junior doctors,and hospital administrators.Through comprehensive insights and real-world examples,it underscores the imperative of fostering a culture of accountability,communication,and quality care to navigate the intricate web of liabilities inherent in modern healthcare.
文摘BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.
基金funded by Princess Nourah bint Abdulrahman University and Researchers Supporting Project number(PNURSP2025R346),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Large language models(LLMs)and natural language processing(NLP)have significant promise to improve efficiency and refine healthcare decision-making and clinical results.Numerous domains,including healthcare,are rapidly adopting LLMs for the classification of biomedical textual data in medical research.The LLM can derive insights from intricate,extensive,unstructured training data.Variants need to be accurately identified and classified to advance genetic research,provide individualized treatment,and assist physicians in making better choices.However,the sophisticated and perplexing language of medical reports is often beyond the capabilities of the devices we now utilize.Such an approach may result in incorrect diagnoses,which could affect a patient’s prognosis and course of therapy.This study evaluated the efficacy of the proposed model by looking at publicly accessible textual clinical data.We have cleaned the clinical textual data using various text preprocessing methods,including stemming,tokenization,and stop word removal.The important features are extracted using Bag of Words(BoW)and Term Frequency-Inverse Document Frequency(TFIDF)feature engineering methods.The important motive of this study is to predict the genetic variants based on the clinical evidence using a novel method with minimal error.According to the experimental results,the random forest model achieved 61%accuracy with 67%precision for class 9 using TFIDF features and 63%accuracy and a 73%F1 score for class 9 using Bag of Words features.The accuracy of the proposed BERT(Bidirectional Encoder Representations from Transformers)model was 70%with 5-fold cross-validation and 71%with 10-fold cross-validation.The research results provide a comprehensive overview of current LLM methods in healthcare,benefiting academics as well as professionals in the discipline.
文摘Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria still grapples with wide acceptance,key translational research and implementation of PM.This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.Methods:A cross‐sectional study was conducted in selected tertiary hospitals across the country.A 21‐item semi‐structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25.Descriptive statistics were used to summarize the data.A chi‐square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.Results:A total of 167 hospital pharmacists participated in the study.A high proportion of the participants are familiar with artificial intelligence(91.75%),Pharmacogenomics(84.5%),and precision medicine(61%).Overall,38.9%of the pharmacists had a good knowledge while 13.2%had a poor knowledge of PM and associated terms.The level of knowledge did not correlate significantly with gender(X^(2)=3.21,p=0.201),age(X^(2)=5,p=0.27),marital status(X^(2)=3.21,p=0.201),and professional level(X^(2)=6.85,p=0.144).The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine(49%)while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.Conclusions:There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria.Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM.Also,more research aimed at translating PM knowledge into clinical practice is recommended.
文摘BACKGROUND Cytomegalovirus(CMV)prophylaxis with valganciclovir and ganciclovir is associated with elevated neutropenia and leukopenia risk in kidney transplant recipients,although the impact of these events on healthcare resource utilization(HCRU)and clinical outcomes is unclear.AIM To quantify clinical events and HCRU associated with neutropenia and leukope-nia among adults receiving valganciclovir and/or ganciclovir post-kidney trans-plantation.METHODS Adult kidney transplant recipients receiving valganciclovir and/or ganciclovir prophylaxis were identified in the TriNetX database from 2012 to 2021.Patient characteristics were evaluated in the 1-year period pre-first transplant.HCRU and adjusted event rates per person-year were evaluated in follow-up year 1 and years 2-5 after first kidney transplantation among cohorts with vs without neutropenia and/or leukopenia.RESULTS Of 15398 identified patients,the average age was 52.39 years and 58.70%were male.Patients with neutropenia and/or leukopenia had greater risk of clinical events for CMV-related events,opportunistic infections,use of granulocyte colony stimulating factor,and hospitalizations(relative risk>1 in year 1 and years 2-5).Patients with vs without neutropenia and/or leukopenia had higher HCRU in year 1 and years 2-5 post kidney transplantation,including the mean number of inpatient admissions(year 1:3.47 vs 2.76;years 2-5:2.70 vs 2.29)and outpatient visits(48.97 vs 34.42;31.73 vs 15.59,respectively),as well as the mean number of labs(1654.55 vs 1182.27;622.37 vs 327.89).CONCLUSION Adults receiving valganciclovir and/or ganciclovir prophylaxis post-kidney transplantation had greater risk of neutropenia and/or leukopenia,which were associated with higher clinical event rates and HCRU up to 5 years post-transplantation.These findings suggest the need for alternative prophylaxis options with lower myelosup-pressive effects to improve patient outcomes.
文摘Digital health is transforming healthcare by integrating advanced technologies to make healthcare more accessible,efficient,and personalized.From electronic health records,telemedicine,wearable devices,and artificial intelligence to the recent smart hospitals,digital health is improving patient care and outcomes while reducing healthcare costs.However,the integration of digital health faces several challenges,including data privacy,cybersecurity risks,and inequitable access to technology.This article provides an overview of the current state of digital health,key challenges in implementation,and potential solutions to maximize the benefits of digital health and ensure efficient,equitable,and patient‐centered healthcare in the future.
文摘HIV-related stigma,discrimination,and other forms of oppression can severely undermine adherence to antiretroviral therapy(ART)among people living with HIV[1].For example,Kerr et al.reveal that perceived discrimination based on sexual orientation in healthcare settings significantly reduces ART adherence[1].This highlights the urgent need for targeted strategies to address stigma,discrimination,and social marginalization,especially within healthcare facilities,to improve HIV care outcomes.
基金funded by the Northern Border University,Arar,KSA,under the project number“NBU-FFR-2025-3555-07”.
文摘Healthcare networks are transitioning from manual records to electronic health records,but this shift introduces vulnerabilities such as secure communication issues,privacy concerns,and the presence of malicious nodes.Existing machine and deep learning-based anomalies detection methods often rely on centralized training,leading to reduced accuracy and potential privacy breaches.Therefore,this study proposes a Blockchain-based-Federated Learning architecture for Malicious Node Detection(BFL-MND)model.It trains models locally within healthcare clusters,sharing only model updates instead of patient data,preserving privacy and improving accuracy.Cloud and edge computing enhance the model’s scalability,while blockchain ensures secure,tamper-proof access to health data.Using the PhysioNet dataset,the proposed model achieves an accuracy of 0.95,F1 score of 0.93,precision of 0.94,and recall of 0.96,outperforming baseline models like random forest(0.88),adaptive boosting(0.90),logistic regression(0.86),perceptron(0.83),and deep neural networks(0.92).
