Informing policy makers in developing countries:Practices and limitations of geriatric home medication review in Malaysia-A qualitative inquiry

Objective:To explore existing practices and challenges in the delivery of geriatric home medication review(HMR).The study was part of a larger study aimed to offer solution to expand the range of geriatric HMR.Methods:This study employed qualitative exploratory design through semi-structured individual in-depth interviews with the public pharmacists involved in the delivery of geriatric HMR at public hospitals.The purpose of the interviews was to explore challenges faced by them in the delivery of geriatric HMR.Results:Based on the emerging themes from the qualitative data,the study reveals that geriatric HMR in Malaysia is integrated as part of multidisciplinary home care visits,encompassing a diverse patient population with various healthcare needs.However,it faces challenges such as the lack of outcome monitoring,formal training,and workforce constraints.Despite these hurdles,there is a pressing need for the expansion of this service to better serve the community,and collaboration with community pharmacists holds potential to broaden its scope.Ultimately,the findings suggest that pharmacist-led HMR is both warranted and feasible within the Malaysian healthcare context.In order to optimize medicine-use among older people living in the community,approaches for expanding geriatric HMR services in Malaysia must be developed.Conclusions:This study holds profound implications as it attempts to illuminate policy makers in developing countries,enabling them to formulate effective HMR plans.By considering the challenges highlighted within this research,policy makers can design a comprehensive HMR service that caters adeptly to the healthcare needs of the mass population.

Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.

Neuroarchitecture Analysis in the Mis Abuelitos Nursing Home in Cochachinche, Huanuco, Peru - A Secondary Publication

Neuroarchitecture is a set of characteristics grouped into principles that seek to generate a certain behavior when applied.These principles will vary according to the type of user for whom the design is intended.In this research,these neuroarchitectural principles are identified in the nursing home Mis Abuelitos in Cochachinche,Huánuco.The home was designed and built with notions of nature and the Andean while emphasizing the occupants are the elderly.With this purpose,qualitative research was carried out using two sequential criteria,the first was to identify what these principles are and the second was to recognize the principles within the area.The principles that are assertively used for the elderly occupants were selected.The study observation was performed with observation and photographic sheets and was analyzed with ATLAS.ti processing software.It was obtained that the three neuroarchitectural principles are present in the nursing home which are 67%of the recommended characteristics for the elderly.

Stress perceptions of nurses serving in home healthcare services during the COVID-19 pandemic:A qualitative research

Objective:To investigate the stress perceptions of nurses serving in home healthcare services during COVID-19.Methods:This study was qualitative research with a phenomenological design.Data were collected and recorded through in-depth interviews with 6 nurses working in MuşState Hospital,Home Healthcare Services Unit using a form consisting of 12 questions on an online platform between May 2021 and July 2021.The audio recordings were transcribed by the researcher and content analysis was performed by creating codes,categories,and themes.Results:The interviews yielded 10 categories and 59 sub-codes.These codes were addressed under the theme of"COVID-19 pandemic".Under this main theme,nurses expressed the problems they experienced in issues such as stress,support mechanisms,and family and social problems during COVID-19.They mentioned that they experienced high stress in this process,as well as social isolation and negative thoughts of society about them and that they could not spare time for themselves and their families.Conclusions:Nurses working in home healthcare services frequently express negativities such as high stress,isolation from society,and increased workload.Therefore,actions should be taken to raise awareness of society on these issues,increase the number of personnel,conduct more research,and share the results with the public.

Smart Home IoT Privacy and Security Preservation via Machine Learning Techniques

The development and use of Internet of Things(IoT)devices have grown significantly in recent years.Advanced IoT device characteristics are mainly to blame for the wide range of applications that may now be achieved with IoT devices.Corporations have begun to embrace the IoT concept.Identifying true and suitable devices,security faults that might be used for bad reasons,and administration of such devices are only a few of the issues that IoT,a new concept in technological progress,provides.In some ways,IoT device traffic differs from regular device traffic.Devices with particular features can be classified into categories,irrespective of their function or performance.Ever-changing and complex environments,like a smart home,demand this classification scheme.A total of 41 IoT devices were employed in this investigation.To build a multiclass classification model,IoT devices contributed 13 network traffic parameters.To further preprocess the raw data received,preprocessing techniques like Normalization and Dataset Scaling were utilized.Feature engineering techniques can extract features from the text data.A total of 117,423 feature vectors are contained in the dataset after stratification,which are used to further improve the classification model.In this study,a variety of performance indicators were employed to show the performance of the logiboosted algorithms.Logi-XGB scored 80.2%accuracy following application of the logit-boosted algorithms to the dataset for classification,whereas Logi-GBC achieved 77.8%accuracy.Meanwhile,Logi-ABC attained 80.7%accuracy.Logi-CBC,on the other hand,received the highest Accuracy score of 85.6%.The accuracy of Logi-LGBM and Logi-HGBC was the same at 81.37%each.Our suggested Logi-CBC showed the highest accuracy on the dataset when compared to existing Logit-Boosted Algorithms used in earlier studies.

Blockchain-based DDoS attack mitigation protocol for device-to-device interaction in smart home

Smart home devices are vulnerable to a variety of attacks.The matter gets more complicated when a number of devices collaborate to launch a colluding attack(e.g.,Distributed-Denial-of-Service(DDoS))in a network(e.g.,Smart home).To handle these attacks,most studies have hitherto proposed authentication protocols that cannot necessarily be implemented in devices,especially during Device-to-Device(D2D)interactions.Tapping into the potential of Ethereum blockchain and smart contracts,this work proposes a lightweight authentication mechanism that enables safe D2D interactions in a smart home.The Ethereum blockchain enables the implementation of a decentralized prototype as well as a peer-to-peer distributed ledger system.The work also uses a single server queuing system model and the authentication mechanism to curtail DDoS attacks by controlling the number of service requests in the system.The simulation was conducted twenty times,each with varying number of devices chosen at random(ranging from 1 to 30).Each requester device sends an arbitrary request with a unique resource requirement at a time.This is done to measure the system's consistency across a variety of device capabilities.The experimental results show that the proposed protocol not only prevents colluding attacks,but also outperforms the benchmark protocols in terms of computational cost,message processing,and response times.

Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique

Energy is essential to practically all exercises and is imperative for the development of personal satisfaction.So,valuable energy has been in great demand for many years,especially for using smart homes and structures,as individuals quickly improve their way of life depending on current innovations.However,there is a shortage of energy,as the energy required is higher than that produced.Many new plans are being designed to meet the consumer’s energy requirements.In many regions,energy utilization in the housing area is 30%–40%.The growth of smart homes has raised the requirement for intelligence in applications such as asset management,energy-efficient automation,security,and healthcare monitoring to learn about residents’actions and forecast their future demands.To overcome the challenges of energy consumption optimization,in this study,we apply an energy management technique.Data fusion has recently attracted much energy efficiency in buildings,where numerous types of information are processed.The proposed research developed a data fusion model to predict energy consumption for accuracy and miss rate.The results of the proposed approach are compared with those of the previously published techniques and found that the prediction accuracy of the proposed method is 92%,which is higher than the previously published approaches.

Sleeping Conditions of Older Adults with Delirium Receiving Home Care

We aimed to clarify the sleep status before delirium onset among older adults receiving home care. The sleep status of 21 participants aged ≥65 years was monitored while they slept with a sensor placed under their bedding, after ruling out insomnia and dementia. The incidence of delirium was 28.6%;delirium onset occurred within an average of 2.7 (SD = 12) days after the start of home care among those whose care environment was changed due to hospital discharge or moving. Increased interrupted sleep and activity during sleep indicated that sleep fragmentation occurred before delirium onset. In conclusion, individuals aged ≥65 years and those whose care environment has changed should be screened for delirium because the time to delirium onset is short. Further, interventions to monitor the sleep status and prevent delirium onset should be implemented from the day home care begins.

Power Scheduling with Max User Comfort in Smart Home:Performance Analysis and Tradeoffs

The smart grid has enabled users to control their home energy more effectively and efficiently.A home energy management system(HEM)is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy.Here,we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm(GWA)and Harmony Search Algorithms(HSA).Moreover,a fusion initiated on HSA and GWA operators is used to optimize energy intake.Furthermore,many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge.Hybridization has proven beneficial in achieving numerous objectives simultaneously,decreasing the peak-to-average ratio and power prices.Widespread MATLAB simulations are cast-off to evaluate the routine of the anticipated method,Harmony GWA(HGWA).The simulations are for a multifamily housing complex outfitted with various cool gadgets.The simulation results indicate that GWA functions better regarding cost savings than HSA.In reputes of PAR,HSA is significantly more effective than GWA.The suggested method reduces costs for single and ten-house construction by up to 2200.3 PKR,as opposed to 503.4 in GWA,398.10 in HSA and 640.3 in HGWA.The suggested approach performed better than HSA and GWA in PAR reduction.For single-family homes in HGWA,GWA and HSA,the reduction in PAR is 45.79%,21.92%and 20.54%,respectively.The hybrid approach,however,performs better than the currently used nature-inspired techniques in terms of Cost and PAR.

Learning-Based Metaheuristic Approach for Home Healthcare Optimization Problem

This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon.Thus,a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint.Nevertheless,when the time horizon become large,practical-sized instances become very difficult to solve in a reasonable computational time.Therefore,a new Learning Genetic Algorithm for mTSP(LGA-mTSP)is proposed to solve the problem.LGA-mTSP is composed of a new genetic algorithm for mTSP,combined with a learning approach,called learning curves.Learning refers to that caregivers’productivity increases as they gain more experience.Learning curves approach is considered as a way to save time and costs.Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times.

Rural implementation of the perioperative surgical home:A case-control study

BACKGROUND Perioperative surgical home(PSH)is a novel patient-centric surgical system developed by American Society of Anesthesiologist to improve outcomes and patient satisfaction.PSH has proven success in large urban health centers by reducing surgery cancellation,operating room time,length of stay(LOS),and readmission rates.Yet,only limited studies have assessed the impact of PSH on surgical outcomes in rural areas.AIM To evaluate the newly implemented PSH system at a community hospital by comparing the surgical outcomes using a longitudinal case-control study.METHODS The research study was conducted at an 83-bed,licensed level-III trauma rural community hospital.A total of 3096 TJR procedures were collected retrospectively between January 2016 and December 2021 and were categorized as PSH and non-PSH cohorts(n=2305).To evaluate the importance of PSH in the rural surgical system,a case-control study was performed to compare TJR surgical outcomes(LOS,discharge disposition,and 90-d readmission)of the PSH cohort against two control cohorts[Control-1 PSH(C1-PSH)(n=1413)and Control-2 PSH(C2-PSH)(n=892)].Statistical tests including Chi-square test or Fischer’s exact test were performed for categorical variables and Mann-Whitney test or Student’s t-test were performed for continuous variables.The general linear models(Poisson regression and binomial logistic regression)were performed to fit adjusted models.RESULTS The LOS was significantly shorter in PSH cohort compared to two control cohorts(median PSH=34 h,C1-PSH=53 h,C2-PSH=35 h)(P value<0.05).Similarly,the PSH cohort had lower percentages of discharges to other facilities(PSH=3.5%,C1-PSH=15.5%,C2-PSH=6.7%)(P value<0.05).There was no statistical difference observed in 90-d readmission between control and PSH cohorts.However,the PSH implementation reduced the 90-d readmission percentage(PSH=4.7%,C1-PSH=6.1%,C2-PSH=3.6%)lower than the national average 30-d readmission percentage which is 5.5%.The PSH system was effectively established at the rural community hospital with the help of team-based coordinated multi-disciplinary clinicians or physician comanagement.The elements of PSH including preoperative assessment,patient education and optimization,and longitudinal digital engagement were vital for improving the TJR surgical outcomes at the community hospital.CONCLUSION Implementation of the PSH system in a rural community hospital reduced LOS,increased directto-home discharge,and reduced 90-d readmission percentages.

Comprehensive Utilization Policies of Crop Straw at Home and Abroad and Its Implications for Xinjiang

This paper summarizes crop straw utilization policies at abroad from the aspects of investment support policies,tax revenue and unsecured loan policies,and reviewed China s crop straw utilization policies from the aspects of technical training,project subsidies,straw collection,storage and transportation system construction and socialized service system construction.Combined with the actual situation of Xinjiang,this paper puts forward policy formulation suggestions on crop straw comprehensive utilization.

Harvest Year for the Homestay Industry

This year has seen big success for China’s home stay industry,as more and more people have become the owners of homestays.According to the 2023 Insight into the Homestay Industry released by tujia.com,the number of homestay owners has increased by 77%from 2019.In addition,the booking volume of homestays with the labels of ceramic art,beachcombing and planting experiences has increased by 90-230%.

The 4th Smart Home Industry Development Forum held in Shenzhen

Jointly hosted by China Electronics Standardization Institute(CESI)and Shenzhen CESI Information Technology Co.,Ltd.,the 4th Smart Home Industry Development Forum was held in Shenzhen,Guangdong province.

Validation of LPD Scale for the Assessment of Pressure Ulcer at Home

Objectives: This study was designed to test and validate the new LPD scale in a home care setting. The specific objectives are to validate the LPD scale for subjects cared for at home;and to compare LPD to the Braden scale for internal validity. Method: This multicenter, cross-sectional study was conducted in the domestic environment of subjects cared for Home Care services from North to South of Italy. Data collection lasted 8 months, between June 2018 and September 2020, and consisted of the simultaneous compilation of the new LPD, and the Braden scale. Home Care Expert nurses could interface with the recruited subjects and/or caregivers. The parameters considered to validate the new scale were sensitivity (Se), specificity (Sp), positive predictive values (PPV), odds ratio (OR), and the area under the receiver operating characteristic (ROC) curve. Results: Of the 679 recruited subjects, 63.2% were women, and more than 50% did not have a pressure ulcer. 48.2% of the sample aged over 85 years old;69% was affected by multiple disease, and 76.6% took a lot of drugs. 91.6% of the subjects were affected by a partial or total functional dependency. Around 50% of subjects presented double incontinence, and 43% were conscious and collaborated. 85.4% of subjects lived in a healthy environment. The predictive validity parameters showed: Se 77.25%, Sp 84.04%, PPV 91.37%, and the area under the curve (AUC) 0.88% with a confidence interval (CI) 95%. These values mean a moderately accuracy of the test. Conclusions: The new LPD scale has demonstrated a good capacity for identifying the subjects at risk of pressure ulcer and had a better discriminatory power rather than Braden scale.

A Smart Home Energy Monitoring System Based on Internet of Things and Inter Planetary File System for Secure Data Sharing

Energy demand will continue to rise as a result of predicted population growth. In this work, a user-friendly home energy monitoring system based on IoT is described, which is capable of collecting, analyzing, and displaying data. Users register their sensors and devices on the monitoring platform. PostgreSQL and Elasticsearch databases are used to store the resulting measurements. In a smart home, the wireless sensor ACS712 was used to monitor the flow of electricity (current and voltage) for a household device. The user can share data about electricity consumption and costs with a third party via the private IPFS (InterPlanetary File System) network. A third party can download all the energy consumption data for a device or many devices from the platform for 1 day, 3 months, 6 months, and 1 year. The studies on the development of energy-efficient technology for home devices benefit greatly from the gathered data. For security in the system, it is preferred to run Keyrock Idm, Wilma Pep Proxy, and Orion Context Broker in HTTPS mode, and MQTTS is used to retrieve sensor data. The experimental results showed that the energy monitoring system accurately records voltage, current, active power, and the total amount of power used and offers low-cost solutions to the users using household devices in a day.

Pregnant Women with Diabetes under the Novel COVID-19 Pneumonia Epidemic Home Protection and Diet and Exercise Management

Under the epidemic situation of novel COVID-19 pneumonia, pregnant women belong to the susceptible population, and their physiological and psychological conditions are particularly worthy of attention. Diabetes patients during pregnancy may have a variety of complications, which can have a serious adverse impact on their own and fetal health. This article elaborates on home protection and diet and exercise guidance for pregnant women with diabetes in order to provide guidance for pregnant women with diabetes in a special period, and further prevent and control the pneumonia epidemic caused by novel COVID-19 infection in pregnant women.

Reading Toni Morrison’s Home From the Perspective of Medical Relationship Ethics

As the first black women Nobel laureate,Toni Morrison has drawn great attention with her fascinating and deep-thinking novels.Her 10th novel Home vividly shows the racial suffering and the post-war trauma of black veteran Frank,who has drawn critical attention from various perspectives.However,there is hardly any scholarly focus on another major character Cee,whose experience of medical and racial discrimination actually constitutes another important clue throughout the whole story.Therefore,this paper intends to analyze Home from the perspective of ethical relationship ethics,including doctor-patient relationship,doctor-society relationship,patient-society relationship,and patient-family relationship.The analysis indicates that Home not only reveals the history of medical racial discrimination and human experiment ethics problems under the rapid development of medical technology in the 1950s,but also inspire readers’thinking on the ethical problems and ethical dilemmas in the contemporary world.

Exploration moving beyond medical facility walls:opportunities,challenges and attitudes of midwives towards planned homebirth:a qualitative

Background:The establishment of Saudi Vision 2030 has led to a shift from obstetric care to midwifery-led care in maternity care,giving rise to planned home birth(PHB).This study may enable midwives to carry out PHB and achieve the goals of the Saudi health vision.The general aim is to explore Saudi midwives’attitudes towards the PHB,opportunities and challenges associated with PHB implementation in Saudi Arabia.Methods:We employed a qualitative study design and conducted interviews using open-ended questions with 19 Saudi midwives recruited from thirteen health regions.Thematic analysis was manually performed to analyze the qualitative data.Results:Thematic analysis revealed seven major themes:midwives as care providers in PHB,health institutions,academic institutions,national policy for PHB,Women’s health status,socio-economic and physical environment suitability,and maternal and neonatal health outcomes.However,Saudi midwives would exhibit a favorable attitude towards PHB if decision-makers from the Ministry of Health and the Ministry of Education addressed the challenges and promoted opportunities for providers,organizations,and the population.Conclusion:The findings of the thematic analysis shed light on several positive aspects,including job opportunities and high financial incomes for midwives.However,they also revealed challenges such as a shortage of midwifery staff,a scarcity of midwifery academic programs,and an ineffective administrative support system for midwives.Integrating both sets of findings enhances the understanding of the challenges and opportunities of planned home birth in Saudi Arabia from various perspectives,capturing the breadth and depth of the obtained data.

Consumer Perceptions of Noni Juice Health Benefits during a 90-Day In-Home Use Test

Noni juice, made from the fruit of Morinda citrifolia, is a health-promoting food from the Pacific Islands with an extensive history of traditional use. Human clinical trials have revealed that noni juice has antioxidant, immunomodulatory and anti-inflammatory properties. Previously, regular noni juice consumers in Europe and traditional healers in Fiji were surveyed to identify potential noni juice health benefits. But to better understand the perception of its health benefits among those with no previous experience with noni juice, an in-home study was conducted in the United States. Three hundred and nineteen adults with untreated chronic health conditions were provided with a 90-day supply of a blinded (unlabeled) commercial noni juice product (Tahitian Noni® Juice), instructed to consume 4 fluid ounces (1/2 cup) each day, and responded to a questionnaire given on days 30, 60 and 90 to evaluate product appeal and perceived effectiveness. A total of 299 people (94%) felt that their health improved in some way after drinking TNJ for 90 days. More than 80% of the subjects reported feeling better or healthier in general. Most participants also concurred with more than two dozen additional positive health perception statements, especially on days 60 and 90. More than 70% of consumers also indicated that noni juice helped them feel better than other wellness supplements they had tried in the past, including other so-called “super fruit” products. These findings seem to corroborate the results of clinical trials and previous consumer surveys regarding the potential for noni juice to provide discernable health benefits when used consistently over time. Such findings may help guide additional placebo-controlled clinical trials in which specific effects may be evaluated more rigorously.