Impact of community public health care on treatment effect,health cognition,and self-management in patients with type 2 diabetes

BACKGROUND At present,China has become the country with the largest number of individuals with diabetes mellitus(DM)in the world,with a total of approximately 140 million patients,the majority of whom have type 2 DM(T2DM).Based on conven-tional nursing methods,community home care has important clinical significance in controlling blood sugar and disease progression.AIM To explore the impact of community public health nursing on treatment effect,health cognition,and self-management in patients with T2DM.METHODS One hundred patients with T2DM were selected as the research subjects.The patients were divided into either a conventional nursing group or community nursing(CN)group using the random number table method.The conventional nursing group(50 cases)received routine care,while the CN group(50 cases)received community public health care in addition to routine care as that for the conventional nursing group.The rate of excellent and good blood glucose control,fasting blood glucose before and after care,2-h postprandial blood glucose,health cognition,and self-management ability,and patient satisfaction were compared between the two groups.RESULTS The CN group had a higher rate of excellent blood sugar control than the conventional nursing group(88%vs 70%,P<0.05).Before care,there was no significant difference in fasting blood glucose or 2-h postprandial blood glucose between the two groups of patients(P>0.05).After nursing,fasting blood glucose and 2-h postprandial blood glucose were reduced to varying degrees in both groups,and both blood glucose levels in the CN group were lower than those of the conventional nursing group(P<0.05).Compared with the scores before care,the cognitive level score for diabetes and self-management ability score improved after care in both groups.The cognitive level and self-management ability of patients in the CN group were higher than those of the conventional nursing group(P<0.05).The overall satisfaction of the CN group was better than that of the conventional nursing group(98%vs 86%,P<0.05).CONCLUSION Community public health care based on conventional care of T2DM can achieve better blood sugar control,and improve patients’health cognitive level and self-management ability.

Deep Learning-Driven Anomaly Detection for IoMT-Based Smart Healthcare Systems

The Internet of Medical Things(IoMT)is an emerging technology that combines the Internet of Things(IoT)into the healthcare sector,which brings remarkable benefits to facilitate remote patient monitoring and reduce treatment costs.As IoMT devices become more scalable,Smart Healthcare Systems(SHS)have become increasingly vulnerable to cyberattacks.Intrusion Detection Systems(IDS)play a crucial role in maintaining network security.An IDS monitors systems or networks for suspicious activities or potential threats,safeguarding internal networks.This paper presents the development of an IDS based on deep learning techniques utilizing benchmark datasets.We propose a multilayer perceptron-based framework for intrusion detection within the smart healthcare domain.The primary objective of our work is to protect smart healthcare devices and networks from malicious attacks and security risks.We employ the NSL-KDD and UNSW-NB15 intrusion detection datasets to evaluate our proposed security framework.The proposed framework achieved an accuracy of 95.0674%,surpassing that of comparable deep learning models in smart healthcare while also reducing the false positive rate.Experimental results indicate the feasibility of using a multilayer perceptron,achieving superior performance against cybersecurity threats in the smart healthcare domain.

Continuity of Care in Primary Health Care Affecting Control of Diabetes

Background: Continuity of care is a distinguishing feature of primary care. Better continuity of care program showed a significant effect in controlling diabetes and it is complications. This study explores the effect of continuity of care on control of diabetes mellites in primary health care centres. Objectives: 1) To assess the effect of Continuity of care on controlling haemoglobin (Hb A1C) and fasting blood Sugar (FBS);2) To compare the control of Diabetes by using (Hb A1C and FBS) indices on same patient before and after application of chronic illness clinic;3) To identify the relation between age and gender affecting continuity of care in diabetic patient. Methods: It is a Prospective cohort study design. Included both gender and diabetic patient age above 24 years old. The data extracted from health care specialty center (HCSC) clinics in National guard hospital at Riyadh, through HCSC data base on three phases: 1) Phase 1: the data extracted of diabetic patients from October to November 2022 including MRN, diabetic patient, age, Hb A1C, Fasting blood glucose. 2) Phase 2: the same MRN extracted from phase 1 was extracted again retrospectively for six months from April to September 2022, to compare the indices before implanting the chronic illness clinic including Hb A1C, Fasting blood glucose. 3) Phase 3: prospectively from December 2022 to September 2023. Results: Among diabetic patients aged 60 years old and above showed better control of HbA1C and FBS comparing to these patients below age of 60 years old, with significant improvement of HbA1C after implanting chronic illness clinic. Conclusion: The significant improvement in the control of diabetic patients followed in primary health care centers reinforce the evidence of the importance of continuity of care.

Wearable Healthcare and Continuous Vital Sign Monitoring with IoT Integration

Technical and accessibility issues in hospitals often prevent patients from receiving optimal mental and physical health care,which is essential for independent living,especially as societies age and chronic diseases like diabetes and cardiovascular disease become more common.Recent advances in the Internet of Things(IoT)-enabled wearable devices offer potential solutions for remote health monitoring and everyday activity recognition,gaining significant attention in personalized healthcare.This paper comprehensively reviews wearable healthcare technology integrated with the IoT for continuous vital sign monitoring.Relevant papers were extracted and analyzed using a systematic numerical review method,covering various aspects such as sports monitoring,disease detection,patient monitoring,and medical diagnosis.The review highlights the transformative impact of IoTenabled wearable devices in healthcare,facilitating real-time monitoring of vital signs,including blood pressure,temperature,oxygen levels,and heart rate.Results from the reviewed papers demonstrate high accuracy and efficiency in predicting health conditions,improving sports performance,enhancing patient care,and diagnosing diseases.The integration of IoT in wearable healthcare devices enables remote patient monitoring,personalized care,and efficient data transmission,ultimately transcending traditional boundaries of healthcare and leading to better patient outcomes.

Assessment of Breast Cancer Prevention Practices among Women Attending Primary Health Care in Abha City, Aseer Region, Saudi Arabia

Cancer is a leading cause of death worldwide, with breast cancer being the most common (2.26 million new cases and 685,000 deaths). In Saudi Arabia, breast cancer ranked the first among females in 2014, accounting for 15.9% of all cancers reported among Saudi nationals and 28.7% of all cancers reported among females of all ages. Early detection of breast cancer could decrease the risks, have a better prognosis, and have better outcomes/more successful treatments. Prevalence of breast cancer reached more than 25% of all diagnosed cancer in the kingdom among women. Aim: This study aims to assess the knowledge and performance of women attending primary care centers about breast self-examination and mammogram screening for prevention and early detection of breast cancer in Abha city primary healthcare centers, Kingdom of Saudi Arabia. Research Method: cross sectional design was conducted by using questionnaire, which was distributed to primary care center nurses. The collected data was statistically analyzed using the Statistical Package for Social Sciences, version 25. Results: The study found that participants had poor awareness and knowledge about breast self-examination, risk factors for breast cancer, and trends and practices in early diagnosis of breast cancer. Conclusion and Recommendations: It recommends increasing awareness campaigns and providing educational programs to improve knowledge and practices.

Practice and Determinants of Infection Prevention and Control Measures among Health Care Workers at Benjamin Mkapa Hospital, Dodoma-Tanzania

Introduction: Infection Prevention and Control are scientific approaches and practical solutions designed to prevent harm caused by infection to patients and health workers. The study aimed to assess Infection prevention and control practices and determinants. Method: The hospital-based analytical cross-sectional study design was employed through a convenience approach. The SPSS version 26 was used for data analysis. Results: 72.5% of healthcare workers at Benjamin Mkapa Hospital observed not performing hand hygiene before direct contact with the patient or before the procedure and 60.3% observed performing hand hygiene after direct contact with the patient or after removing gloves. Professionals (Doctors, Medical attendants, and Nurses) were significantly practiced more in infection prevention and control by 2.860, 2.923, and 3.237 units respectively compared to pharmacy personnel. Conclusion: The sustainable availability of Infection Prevention and Control resources is important to enhance a healthy working environment. The current study has shown that the availability of Equipment and Supplies was 100% for gloves, face masks, and sanitizer. The multivariate results showed a statistically significant relationship between those trained in IPC and those more likely to practice IPC than those not trained.

Evaluation of the mental health of COVID-19 patients discharged from the intensive care unit

In this editorial,I address the mental health status of patients who have been discharged from intensive care units(ICUs)after battling coronavirus disease 2019(COVID-19).An ICU admission is generally a stressful experience,and for severe COVID-19 survivors prolonged treatment in the ICU can lead to significant psychological consequences.These individuals may experience psychiatric distress,including symptoms such as insomnia,anxiety,depression,and even posttraumatic psychological issues.Research indicates that during the first 6 months to 1 year following an ICU stay,nearly one-third of survivors exhibit symptoms similar to those of depression and post-traumatic stress disorder.Several factors may have contributed to the development of depressive and anxious symptoms during the COVID-19 pandemic,particularly for those who underwent an ICU stay.The ICU environment itself is inherently stressful,filled with the constant noise of various medical devices.Studies have provided strong evidence that the prolonged need for ventilation support and the loss of freedom of movement are key factors in the development of psychological problems among COVID-19 patients who had been treated in the ICU.

Water, Sanitation and Hygiene in Lower-Level Health Care Facilities of Dar es Salaam Region in Tanzania: Status towards Achieving the Sustainable Development Goals and Way Forward

Background: Improving Water, Sanitation and Hygiene in health care settings is a critical prerequisite for achieving national health goals and Sustainable Development Goals (SDGs). The World Health Organization (WHO) has set a target for each United Nations member state to reach by 2030. Each member state is required to reach by 2022, 2025 and 2030 at least 60%, 80% and 100%, respectively of basic level of service of the five elements which are water, sanitation, hygiene, waste management and environmental cleaning. Methods: This study aimed to evaluate and document the current state of basic water, sanitation, and hygiene services in all lower-level health care facilities in the Dar es Salaam region of Tanzania as of July 2022. A cross-sectional study was conducted in 99 public dispensaries in the Dar es Salaam region’s five councils: Ubungo, Kigamboni, Kinondoni and Temeke Municipalities, and Ilala City. The interviewee form and observational checklists were both digitalized using the Kobo tool software. The respondents were health care facility in-charges or nurse in-charges. Data were downloaded, validated, and imported to Stata version 15 for analysis. Results: The basic WASH level per JMP is far below the target in 2022. Each member state by 2022 is required to reach at least 60% of the basic level of service of each element. We found a low coverage of basic WASH in the 99 dispensaries included in this study. The basic WASH coverage was met in only 10 (10.1%) of the dispensaries, while the remaining 89 (89.9%) dispensaries fall on limited WASH services. Conclusion: This study revealed lower coverage of basic WASH services in dispensaries. An urgent need is required to improve the status of WASH in all the dispensaries and facilitate the provision of quality health care services, patient safety and reduce health care associated infections.

Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and recovery.The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance.Although many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during analysis.Therefore,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare Monitoring.At first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction process.Here,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable devices.To attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced features.After that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and overhead.Experimental evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several instances.The quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

Ozone Sterilizer for Treatment and Health Care

Ozone is a green broad-spectrum bactericidal disinfectant, and a trace amount of ozone in the atmosphere makes many viruses and bacteria lose their biochemical activity and infectivity. Nature produces trace amounts of ozone in the air through lightning to purify the ecological environment. The product of ozone decomposition is oxygen, without secondary pollution. Ozone sterilizer is widely used in the epidemic prevention and control of intensive breeding farms and achieved remarkable results. If the concentration and action time of ozone can be accurately controlled, then ozone can quickly eliminate pathogens, without harming the normal cells in the human body. How to use medical ozone for epidemic prevention, treatment and health care is a subject worthy of serious study, which should arouse the attention of the experts in the field.

Surgical treatment of liver cancer and pancreatic cancer under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Data from the World Health Organization’s International Agency for Research on Cancer reported that China had the highest prevalence of cancer and cancer deaths in 2022.Liver and pancreatic cancers accounted for the highest number of new cases.Real-world data(RWD)is now widely preferred to traditional clinical trials in various fields of medicine and healthcare,as the traditional research approach often involves highly selected populations and interventions and controls that are strictly regulated.Additionally,research results from the RWD match global reality better than those from traditional clinical trials.AIM To analyze the cost disparity between surgical treatments for liver and pancreatic cancer under various factors.METHODS This study analyzed RWD 1137 cases within the HB1 group(patients who underwent pancreatectomy,hepatectomy,and/or shunt surgery)in 2023.It distinguished different expenditure categories,including medical,nursing,technical,management,drug,and consumable costs.Additionally,it assessed the contribution of each expenditure category to total hospital costs and performed cross-group comparisons using the non-parametric Kruskal–Wallis test.This study used the Steel–Dwass test for post-hoc multiple comparisons and the Spearman correlation coefficient to examine the relationships between variables.RESULTS The study found that in HB11 and HB13,the total hospitalization costs were significantly higher for pancreaticoduodenectomy than for pancreatectomy and hepatectomy.Although no significant difference was observed in the length of hospital stay between patients who underwent pancreaticoduodenectomy and pancreatectomy,both were significantly longer than those who underwent liver resection.In HB15,no significant difference was observed in the total cost of hospitalization between pancreaticoduodenectomy and pancreatectomy;however,both were significantly higher than those in hepatectomy.Additionally,the length of hospital stay was significantly longer for patients who underwent pancreaticoduodenectomy than for those who underwent pancreatectomy or liver resection.CONCLUSION China Healthcare Security Diagnosis Related Groups payment system positively impacts liver and pancreatic cancer surgeries by improving medical quality and controlling costs.Further research could refine this grouping system and ensure continuous effectiveness and sustainability.

Downsizing Health Care in the Community

This study reviewed recent changes in health care utilization in the health care providers of Syracuse, New York. The data indicated the largest decline in the numbers of inpatient volumes involved adult surgery and orthopedics. Numbers of inpatient discharges for this service declined by more than 2900 discharges for the combined Syracuse hospitals. The data also indicated that adult medicine discharges declined by more than 2600 during this time. For Diagnosis Related Groups with discharge differences of 30 or more, adult medicine discharges declined by 451 in neurology, 943 in respiratory medicine, and 625 in circulatory medicine. It was estimated that the value of the inpatient discharges amounted to approximately $1,740,000 in adult surgery and more than $1,560,000 for adult medicine. The savings that were achieved in this process related to staffing, pharmaceuticals, and testing.

Estimating the Future of Health Care at the Community Level

Developments in health care in the United States are changing the delivery of services for providers and payors. This study focused on inpatient hospital discharges in the Syracuse hospitals and other services. It demonstrated that, during the past five years, numbers of inpatient adult medicine discharges had increased while adult surgery discharges had declined. This information suggested that adult medicine discharges could be expected to increase and approach levels of five years ago. It also suggested adult surgery discharges could be expected to remain at previous levels or decline. This information indicated that the combined emergency department visits declined from 238,000 to 202,000 between 2019 and 2020, then increased from 218,000 to 228,000 visits between 2021 and 2023. These developments will probably result in greater efficiency at the community level. With a decline in numbers of inpatient beds, providers will be able to focus on the more efficient management by reducing numbers of staff as well as fewer pharmaceuticals and testing.

Affordability, Accessibility, and Quality of Maternal Health Care Services and Level of Satisfaction of Mothers in Rural Areas in China

Objective:This study aimed to understand the affordability,accessibility,and quality of maternal and child health services for postpartum mothers,and their impact on satisfaction.Methods:The study utilized the Anderson model and revised the Maternal Pregnancy and Perinatal Health Service Questionnaire.A survey was conducted among 289 mothers aged 20–49 in Feicheng City.Results:Regarding accessibility,most respondents(133)reported that travel time to healthcare services exceeded 60 minutes,while 99 respondents indicated a travel time of 16–30 minutes.The issue of affordability was highlighted,with 86.85%of participants perceiving maternal healthcare services as costly,indicating a significant financial burden.More than 50%of respondents were satisfied with two specific dimensions(P<0.05)regarding the quality of maternal healthcare services.Conclusion:The study found that accessibility,affordability,and quality significantly affect mothers’satisfaction with maternal health services.Future research should focus on developing more suitable service pathways for rural mothers.

A Study of Health Prescribing for Children with Tourette’s Disorders in Children’s Health Education Specialty Care Clinics

Objective:This study designs and implements the health prescription of children’s health education specialized nursing clinic based on the physical and mental characteristics of children with Tourette’s syndrome.Methods:Applying the evidence-based nursing model and nursing intervention theory based on the survey research by searching China Knowledge Network,Wanfang Database and Wipro Chinese Science and Technology Journal Database,the study collected the literature on the health prescription intervention research in children’s Tourette’s disorders health education in children’s health education of specialized nursing outpatient clinic for review and combined with the specialty characteristics to formulate“Children’s Tourette’s Disorder Health Education Prescription.”Results:Tourette’s syndrome in children is a common pediatric neurological disorder,mainly manifested as involuntary,rapid and repeated muscle twitching and vocal tics,which brings serious psychological pressure and life disturbance to the affected children.Conclusion:For children with Tourette’s syndrome,healthcare professionals should give enough care and understanding to the children and their parents,provide timely and effective health education to them,help them improve their bad behavioral habits,establish correct cognitive attitudes,enhance self-confidence,improve patient compliance,reduce the frequency of recurrence,reduce the incidence of complications and promote children’s physical and mental health development.

The effect of high-fidelity simulation in medical nursing based on the healthcare simulation standards of best practice

Background:High-fidelity simulation has been demonstrated to make great progress in learning.However,there is still ongoing exploration on how to fully harness the advantages of this teaching method and enhance its effectiveness.This study conducted high-fidelity simulation in medical nursing based on the Healthcare Simulation Standards of Best Practice and evaluated its effect.Methods:The study was conducted from September 2019 to June 2020.A total of 82 undergraduate nursing students from a university in Shanghai participated in the high-fidelity simulation in medical nursing.The simulation design scale,educational practices in simulation scale,and students’satisfaction and self-confidence were used to evaluate the effect.Results:The mean score of simulation design scale was 4.06±0.63 with the mean scores of all dimensions being over 3.0.The mean score of educational practices in simulation scale was 4.14±0.56 with the mean scores of all dimensions being over 4.0.The mean scores of students’satisfaction and self-confidence were 4.07±0.72 and 3.89±0.58,respectively.Conclusion:Students reported high levels of simulation design and educational practices in simulation.They were also satisfied with learning and reported high levels of self-confidence.Some key points need to be considered so that the learning effects might be optimized.

Beyond statistical significance:Embracing minimal clinically important difference for better patient care

The minimal clinically important difference(MCID)represents a pivotal metric in bridging the gap between statistical significance and clinical relevance,addressing the direct impact of medical interventions from the patient's perspective.This comprehensive review analyzes the evolution,applications,and challenges of MCID across medical specialties,emphasizing its necessity in ensuring that clinical outcomes not only demonstrate statistical significance but also offer genuine clinical utility that aligns with patient expectations and needs.We discuss the evolution of MCID since its inception in the 1980s,its current applications across various medical specialties,and the methodologies used in its calculation,highlighting both anchor-based and distribution-based approaches.Furthermore,the paper delves into the challenges associated with the application of MCID,such as methodological variability and the interpretation difficulties that arise in clinical settings.Recommendations for the future include standardizing MCID calculation methods,enhancing patient involvement in setting MCID thresholds,and extending research to incorporate diverse global perspectives.These steps are critical to refining the role of MCID in patient-centered healthcare,addressing existing gaps in methodology and interpretation,and ensuring that medical interventions lead to significant,patient-perceived improvements.

Physiology and health assessment,risk balance,and model for endstage liver disease scores:Postoperative outcome of liver transplantation

BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.

The Next Era:Flourish of National Health Care & Medicine with the World Leading Artificial Intelligence

MODERN medical diagnosis and practice heavily rely on biological data and information from patients’ body.The progress of biomedical sensor,material and mathematical technology provided ever-increasing methods to gather data.While providing more choices and more comprehensive picture of patients’ conditions to doctors and practitioners,these progresses also require more labor efforts to read,analyze,and make decisions based on those data.It is very difficult for the medical human resources to grow at a speed that matches such need for diagnosis-related expert knowledge.The shortage of expertise has caused long waiting time for check report and fatal misjudged diagnosis in public health system,and it will compromise our ability to move towards a more precise,more personalized and more efficient future of medicine.

Primary Health Care-基础医疗卫生服务应该在中国新医改中得到正确理解和全面实施

英文"primary health care"(PHC)-基础(基本)医疗卫生服务这个概念在中国被错误地理解和翻译成"初级卫生保健"已经有半个多世纪。而专科医疗则被认为是"先进的高级医疗服务"。这种对PHC的错误理解渗透到中国政府和医疗卫生各个部门,在国家的医疗卫生服务宗旨和宏观发展战略决策中造成广泛的影响,如政府的卫生政策制定,医疗服务保障制度建立,医疗卫生基础设施布局,以及医疗卫生服务专业人才队伍的培养等。本文全面阐述了PHC的概念在中国是如何被错误地理解并被翻译成中文"初级卫生保健"的,并从多个角度分析为什么这样理解和翻译是不合理的和错误的:"primary"和"health care"英文单词的基本含义,关于综合性PHC的概念,全球PHC的正反历史经验和上述错误理解对中国医疗卫生服务的发展以及对整个社会造成了部分伤害。中国正在进行的以基础医疗卫生服务为中心的新医改已经取得了很大的前期进展,但是也面临着一系列困难和挑战,包括对基础医疗卫生服务这个概念还存在广泛而根深蒂固的错误理解。我们希望医疗卫生领域的学者、医疗卫生专业人员和政府部门的官员能够充分理解和接受PHC-基础医疗卫生服务这个正确概念,消除"初级卫生保健"错误观念在发展中国基础医疗卫生服务事业中的各种影响,促进新医改的健康发展,使广大人民群众能真正享受到新医改的好处。