Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Objectives Gerontechnology has great potential in promoting older adults’well-being.With the accelerated aging process,gerontechnology has a promising market prospect.However,most technological developers and healthcare professionals attached importance to products’effectiveness,and ignored older adults’demands and user experience,which reduced older adults'adoption intention of gerontechnology use.The inclusion of older adults in the design process of technologies is essential to maximize the effect.This study explored older adults’demands for a self-developed intelligent medication administration system and proposed optimization schemes,thus providing reference to developing geriatric-friendly technologies and products.Methods A cross-sectional survey was conducted to explore older adults’technological demands for the self-developed intelligent medication administration system,and data were analyzed based on the Kano model.A self-made questionnaire was administered from July 2020 to October 2020 after participants used this system for two weeks.The study was registered with the Chinese Clinical Trial Registry(ChiCTR2000040644).Results A total of 354 older adults participated in the survey.Four items,namely larger font size,simpler operation process,scheduled medication reminders and reliable hardware,were classified as must-be attributes;three items,namely searching drug instructions through WeChat,more sensitive system and longer battery life,as attractive attributes;one item,viewing disease-related information through WeChat,as the one-dimensional attribute;and the rest were indifferent attributes,including simple and beautiful displays,blocking advertisements automatically,providing user privacy protection protocol,viewing personal medical information only by logged-in users,recording all the medications,ordering medications through WeChat.The satisfaction values were between 0.24 and 0.69,and dissatisfaction values were between 0.06 and 0.94.Conclusion This study suggested that older adults had personalized technology demands.Including their technological demands and desire may assist in decreasing the digital divide and promoting the satisfaction of e-health and/or m-health.Based on older adults’demands,our study proposed optimization schemes of the intelligent medication administration system,which may help developers design geriatric-friendly intelligent products and nurses to perform older adults-centered and efficient medication management.

Adherence to cardiovascular medications in the South Asian population:A systematic review of current evidence and future directions

AIM: To review methods of assessing adherence and strategies to improve adherence to cardiovascular disease(CVD) medications,among South Asian CVD patients. METHODS: We conducted a systematic review of English language studies that examined CVD medication adherence in South Asian populations from 1966 to April 1,2015 in SCOPUS and Pub Med. Working in duplicate,we identified 61 studies. After exclusions,26 studies were selected for full text review. Of these,17 studies were included in the final review. We abstracted data on several factors including study design,study population,method of assessing adherence and adherence rate. RESULTS: These studies were conducted in India(n = 11),Pakistan(n = 3),Bangladesh(n = 1),Nepal(n = 1) and Sri Lanka(n = 1). Adherence rates ranged from 32%-95% across studies. Of the 17 total publications included,10 focused on assessing adherence to CVD medications and 7 focused on assessing the impact of interventions on medication adherence. The validated Morisky Medication Adherence Scale(MMAS) was used as the primary method of assessing adherence in five studies. Three studies used validated questionnaires similar to the MMAS,and one study utilized Medication Event Monitoring System caps,with the remainder of the studies utilizing pill count and self-report measures. As expected,studies using non-validated self-report measures described higher rates of adherence than studies using validated scale measurements and pill count. The included intervention studies examined the use of polypill therapy,provider education and patient counseling to improve medication adherence. CONCLUSION: The overall medication adherence rates were low in the region,which suggest a growing need for future interventions to improve adherence.

German critical incident reporting system database of prehospital emergency medicine: Analysis of reported communication and medication errors between 2005–2015

BACKGROUND: Communication failure in prehospital emergency medicine can affect patient safety as it does in other areas of medicine as well. We analyzed the database of the critical incident reporting system for prehospital emergency medicine in Germany retrospectively regarding communication errors.METHODS: Experts of prehospital emergency medicine and risk management screened the database for verbal communication failure, non-verbal communication failure and missing communication at all.RESULTS: Between 2005 and 2015, 845 reports were analyzed, of which 247 reports were considered to be related to communication failure. An arbitrary classifi cation resulted in six different kinds: 1) no acknowledgement of a suggestion; 2) medication error; 3) miscommunication with dispatcher; 4) utterance heard/understood improperly; 5) missing information transfer between two persons; and 6) other communication failure.CONCLUSION: Communication defi cits can lead to critical incidents in prehospital emergency medicine and are a very important aspect in patient safety.

Development and application of a closed-loop medication administration system in University of Hongkong-Shenzhen Hospital

Objective： This study aimed to develop and apply a closed-loop medication administration system in a hospital in order to reduce medication administration errors （MAEs）.Methods： The study was implemented in four pilot general wards. We used a before-and-after design to collect oral medication administration times before and after the implementation of the closed-loop medication administration system, evaluated MAE alert logs after the intervention, and conducted a survey of the nurses1 satisfaction with the system in the pilot wards.Results： （a） Nursing time of oral medication administration： before the adoption of the closed-loop medication administration system, the average nursing time was 31.56 ± 10.88 minutes （n = 78）; after the adoption of the system, the time was 18.74 ± 5.60 minutes （n = 54）. Independent sample Mests showed a significant difference between two groups（t= 8.85, P 〈0.00）. （b） Degree of nurses’ satisfaction with the closed-loop medication administration system： 60.00% （n = 42） of nurses considered the system to be helpful for their work and nearly half of the nurses （47.14%, n = 33） believed that the system could facilitate clinical work and reduce workload; 51.43% {n = 36） believed that the system could reduce checking time and enhance work efficiency; 82.86% （n = 58） believed that the system was helpful in improving checking accuracy to reduce MAEs and ensure patient safety. More than 60% of the nurses considered the system to be a method that could help to track MAEs to improve nursing quality, （c） The MAE alert logs during observation period： it revealed only 27 alerts from the repeated scans of 3,428 instances of medication administration.Conclusions： The nurses were satisfied with the closed-loop medication administration system because it improved their work efficiency and reduced their workload. The current investigation was limited by time; therefore, further research is needed to more closely examine the relationship between the system and MAEs.

Analysis on medication rule of traditional Chinese medicine treating chemotherapy-induced diarrhea based on traditional Chinese medicine(TCM) inheritance computing platform system

Objective:To dig deeper into the traditional Chinese medicine treatment rules of chemotherapy-induced diarrhea with traditional Chinese medicine(TCM)inheritance computing platform system.Methods:Taking“traditional Chinese medicine”,“chemotherapy”and“diarrhea”as the theme words,comprehensive search of the database of CNKI,Wanfang and VIP from its inception to November 2020 was conduct-ed.The formulas of external treatment of traditional Chinese medicine for chemotherapy-induced diarrhea were included and the association rule,clustering and factor analysis were carried out.Results:A total of 145 papers,57 prescriptions meeting the inclusion criteria were collected,among which high-frequency drugs including Baizhu(Atractylodis macrocephalae rhizoma),Fuling(Poria),Dangshen(Codonopsisradix),Huanglian(Coptidis rhizoma),Zhigancao(Glycyrrhizae radix et rhizoma praeparata cum melle)were the most commonly used.The confidence level was set as 0.7 and the support level was set as 10,12 core compatibility groups were obtained,and 6 categories were cluster analyzed.Conclusion:The principle of external treatment of chemotherapy-induced diarrhea is mainly“restore deficiency and benefiting qi”,“benefiting water infiltration and dampness”,“clearing heat”and“inducing astringency”.Prescription combination and new prescription combination based on traditional Chinese medicine(TCM)inheritance computing platform system can be used as reference for clinicians and applied in primary hospitals.

A Systematic Review of Factors Influencing Medication Adherence to Hypertension Treatment in Developing Countries

Background: Coronary heart disease (CHD), a complication of hypertension, is one of the most important and common causes of morbidity, hospitalisation, and mortality among hypertensive population. In recent decades, increased urbanisation and changes to lifestyle, diet and physical activity in developing countries have led to a major increase in the population incidence of chronic diseases including CHD. Poor medication adherence is one of the leading causes of failure to achieve hypertension control. The objective of this systematic review is to describe the prevalence of non-adherence to anti-hypertensive medications among hypertensive population in developing countries and identify factors associated with it. Methods: A literature search was conducted using the following scholarly electronic databases: Proquest, PubMed, JSTOR and Science Direct. The online search engine, Google Scholar was also used to search for and identify relevant papers. Peer-reviewed full-text articles published in English on hypertensive adults in developing countries that measured adherence to antihypertensive medications and their associations with different factors were eligible for inclusion. The review followed the PRISMA reporting and analytical guidelines for systematic reviews. Results: In all, 42 studies conducted across 19 developing countries were selected for the review. The mean prevalence of medication non-adherence (MNA) among the select hypertensive population was 47.34%. Very few studies were conducted in community settings and except for one, no study examined gender differences in MNA factors. The analysis revealed a range of factors that can influence MNA including low household income and socioeconomic status;knowledge and beliefs of hypertension and its management;avoiding side effects of medications;cost of medication;use of herbal preparations;absence of symptoms;irregular follow-up;and dissatisfaction with the treatment and health services provided. There was a general lack of consideration of role of health system in health care delivery, self-efficacy, cultural barriers, perceived individual risk of hypertension complications. There was also a lack of gender-specific research which is necessary at community settings given the social and economic vulnerabilities faced by women in developing countries that may affect adherence to antihypertensive medications. Conclusions: Future research in developing countries should consider individual risk perceptions, cultural barriers, gender and the role of local health system in health care delivery when assessing MNA among hypertensive population at community settings.

Impact of Bar-Code Medication Administration and Electronic Medication Administration Record System in Clinical Practice for an Effective Medication Administration Process

Clinical innovations are ideations resulting from collective experiences that enhance the “norm” and embrace an avenue for change with an invention. As such, collective data that were suggestive of increased medication errors that compromised patient safety initiated the exploration of methods that could reduce multifactorial human errors. The pursuit for an appropriate system followed with the discovery of barcode medication administration system (BCMA) and electronic medication administration system (e-MAR). Prior to the adoption of BCMA and e-MAR, it was crucial to assess the impact of the new medication administration system and the rate of medication administration errors recorded, specifically those that resulted in harm. The purpose of the study was to evaluate BCMA and e-MAR usage outcomes, clinical practices, policies, and processes impacting nurses administering medications in the clinical environment using BCMA and e-MAR system. Thus, an annotated literature review was conducted prior to the implementation of the innovation which analyzed various studies that elaborated on their study methods, data collection and analysis that deliberated on the advantages and disadvantages of barcode medication administration system. It is evident in the researched journals that increased compliance was observed with appropriate guidance, processes and policies in place. There was also a significant reduction in reported errors. The incorporation of barcode technology with electronic medication administration record (e-MAR) had greatly improved the efficiency of the BCMA system. BCMAs method was one of the proposed solutions to medication administration errors and to enhance patient safety measures. As such, the innovation could significantly reduce medication error resulting from intrinsic and extrinsic factors. This paper will further elaborate on the advantages and disadvantages of BCMA and e-MAR, the strategies assumed in the development of BCMA and e-MAR system and its implementation process by identifying and overcoming potential challenges that may arise.

Patient and Health System Related Factors Associated with Non-Adherence to Antihypertensive Medication among Patients at Chuka Referral Hospital, Kenya

Background: Non-adherence to hypertensive medication continues to become a contributing factor to hypertensive complications like stroke, heart attacks, kidney disease heart failure. Associated factors to non-adherence are complex, are both internal and external to the patient and are difficult to extrapolate. Reports from Chuka referral hospital records showed that in 2016 there were 140 patients with hypertensive complications from 560 patients who attended the medical clinic that year. Objective: This study sought to explore the patient’s related factors that are associated with non-adherence to hypertension medication. Methods: This is a descriptive study design of (N = 575) people among them doctors, pharmacists, nurses, record officers and hypertension patients. Simple random sampling for patients (n = 81) and census sampling for health care workers was done and data collected using questionnaires and interview schedules between April 4th-May 30th 2019. Inferential and descriptive statistics were used for data analysis, aided by SPSS version 25. Results: 64% of the patients stated that they had missed medication. A significant negative correlation (rpb = -0.23, p < 0.05) between age and non-adherence, significant positive correlation with monthly income (rpb = 0.24, p < 0.04), non-significant relationship between non-adherence and marital status (rpb = -0.13, p = 0.25) and patients’ level of education (rpb = -0.06, p = 0.57). The overall model of health system related factors were found to be significant (p < 0.05) and this included;quality of health service, physician patient relationship, stock out, health education, and availability of medicine (p = 0.012). Conclusion: Lacks of funds, unavailability of drugs are the leading factors to regimen completion. This could be easily be addressed by the government.

A study of TCM master Yan Zhenghua’s medication rule in prescriptions for digestive system diseases based on Apriori and complex system entropy cluster

Objective:To explore Yan Zhenghua’s drug selection rule for treating digestive system diseases using data mining.Methods:The 609 medical records of digestive system diseases treated by Yan Zhenghua were collected and the herbs in these recipes were examined using a data mining technique.The correlativity between herb pairs and association rules was studied using an Apriori algorithm and the correlativity among multi-herbs was studied using a complex system entropy cluster technique.Results:Yan Zhenghua’s treatment of digestive system diseases featured 15 herbs prescribed at least 159 times each,22 herb pairs prescribed at least 155 times each,and eight frequently used herb core combinations.A confidence greater than 0.91 and a support level greater than 20%were achieved using the modified mutual information method.Conclusion:The data mining results conformed to findings from clinical practice.The data mining method is a valuable technique with which to study the experience of famous,elderly traditional Chinese medicine physicians.

Failure to prevent medication errors: We need smarter nearly error proof systems

Purpose: To determine if nurses are able to identify medication errors that have the potential to bypass computer physician order entry (CPOE) and smart ordering systems. Background: Medical care systems employ computer “smart” systems to reduce medication errors by using artificial intelligence (preprogrammed methods of decision support and error reduction). However, these systems are not perfect and they can be bypassed. Nurses who carry out the order represent the last check point in error prevention prior to the administration of medication orders. Methods: A paper exercise was created with 513 physician orders. Nurses were asked to indicate whether they would carry out the order, refuse to carry out the order, consult a pharmacist for clarification, or carry out the order with special precautions. Nurses were given the option of using any nursing or medical reference. Results: The rate of correctly identifying 23 of the contraindicated orders was low. Both experienced and inexperienced nurses had high rates of not identifying the errors despite similar use of references and requests for assistance from pharmacists. Conclusions: This study demonstrates that if an error escapes a smart system, nurses were able to identify most of these errors, but not all of these. The current system features high stress, self-esteem issues, time pressure, high volume, and high risk. The system must change radically to meet the public’s expectations of being nearly error free which can only be achieved with smarter systems that are more resistant to human errors.

Analysis of the rule of medication for internal administration of gout by traditional Chinese medicine based on Traditional Chinese Medicine Inheritance System

Objective:Based on the TCMIS(traditional Chinese medicine inheritance system)V2.5 to explore the rule of medication used in internal TCM(traditional Chinese medicine)for gout in the national patent network.Method:Collect the internal administrations of gout in the national patent network,and enter them into the Chinese medicine inheritance system V2.5,adopt Frequency analysis,association rules,complex system entropy clustering and other data mining methods to analyse the internal traditional formula of traditional Chinese medicine for gout.Results:By inclusion,exclusion criteria,357 formulas are screened out,involving 494 medicine,63 medicine with frequency of use≥20,and 40 commonly used medicine pairs.The core medicine are:Huangbai(Cortex Phellodendri),Cangzhu(Rhizoma Atracylodis),Niuxi(Radix Acanthopanacis Bidentatae),Yiyiren(Semen Coicis),Tufuling(Rhizoma Smilacis Glabrae),Bixie(Rhizome Dioscoreae Hypoglaucae),Gancao(Radix Glycyrrhizae),Weilingxian(Radix Clematidis),Zexie(Rhizoma Alismatis),Danggui(Radix Angelicae Sinensis),Chuanxiong(Rhizoma Chuanxiong).There are 28 new combinations and 14 new formulas.Conclusion:In the national patent network,the internal traditional Chinese medicine for gout is based on clearing away heat and dampness,activating blood circulation to dredge collaterals,which provides reference for clinical treatment of gout.

Analysis of medication law of treatment of cholelithiasis by internal traditional Chinese medicine based on traditional Chinese medicine inheritance system

Objective:Based on the Traditional Chinese Medicine Inheritance System version 2.5 to explore the rule of medication used in internal traditional Chinese medicine for cholelithiasis in the national patent network.Method:Collect the internal administrations of cholelithiasis in the national patent network,and enter them into the Chinese medicine inheritance system version 2.5,adopt frequency analysis,association rules,complex system entropy clustering and other data mining methods to analyze the prescription rule of traditional Chinese medicine cholelithiasis.Results:According to the inclusion and exclusion criteria,215 prescriptions were selected,involving 398 drugs,30 drugs with a frequency of>20,and 39 commonly used drug pairs.The core drugs are:Jinqiancao(Herba Lysimachiae),Yujin(Radix Curcumae),Chaihu(Radix Bupleuri),Yinchen(Herba Artemisiae Scopariae),Jineijin(Endothelium Corneum Gigeriae Galli),Dahuang(Radix et Rhizoma Rhei),Gancao(Radix Glycyrrhizae),Huangqin(Radix Scutellariae),Baishao(Raidix Paeoniae Alba),Muxiang(Radix Aucklandiae),Zhishi(Fructus Aurantii Immaturus),Yanhusuo(Rhizoma Corydalis),Huzhang(Rhizoma Polygoni Cuspidati),Haijinsha(Herba Lygodii).And 9 new prescriptions have been got.Conclusion:In the national patent network,the traditional Chinese medicine is used in the treatment of cholelithiasis.The main treatment is clearing heat and dampness,regulating Qi and relieving pain,and promoting gallbladder removing stone,providing reference for clinical treatment of cholelithiasis.

A cross-sectional study to assess medication safety,knowledge,attitude,and practices regarding nutrition and medication among pregnant women

Objective:To assess pregnant women's knowledge,attitude,and practice regarding nutrition and medication usage,analyse the prescribing pattern,and categorize them based on the Food and Drug Administration(FDA)guidelines.Methods:A cross-sectional study was conducted with 264 pregnant women in the obstetrics and gynaecology department of a tertiary care hospital from October 2022 to August 2023.A knowledge,attitude,and practice(KAP)questionnaire was prepared in English language by the researchers and validated by an expert panel consisting of 12 members.The validated questionnaire was then translated into regional languages,Kannada and Malayalam.The reliability of the questionnaire was assessed with test-retest method with a representative sample population of 30 subjects(10 subjects for each language).The subjects'knowledge,attitude,and practice were evaluated using the validated KAP questionnaire.The safety of the medication was assessed using the FDA drug safety classification for pregnancy.Results:The mean scores for nutritional and medication usage knowledge,attitude,and practice were 4.14±1.15,4.50±1.09,and 3.00±1.47,respectively.Among 30 prescribed medications,3 belong to category A(no risk in human studies),8 belong to category B(no risk in animal studies),18 belong to category C(risk cannot be ruled out)and 1 drug is not classified.A significant association was observed between medication knowledge and practice(r=0.159,P=0.010).Conclusions:Most of the study population knows the need to maintain good dietary and medication practices during pregnancy.Counselling pregnant women regarding diet and medication usage is crucial in maternal care.

Mediating role of inner strength in the relationship between medication literacy and medication adherence among kidney transplant patients

Objective:Compared with long-term renal replacement therapy,kidney transplantation is the ideal treatment for end-stage renal disease(ESRD),significantly extending patient life and improving quality of life.Kidney transplant patients need to adhere to lifelong immunosuppressive medication regimens,but their medication adherence is generally poor compared with other organ transplant recipients.Medication adherence is closely related to medication literacy and psychological status,yet related studies are limited.This study aims to investigate the current status of medication adherence,inner strength,and medication literacy in kidney transplant patients,analyze the relationships among these 3 factors,and explore the mediating role of inner strength in the relationship between medication literacy and medication adherence.Methods:A cross-sectional survey was conducted from March to October 2023 involving 421 patients aged≥18 years who visited kidney transplantation outpatient clinics at 4 tertiary hospitals in Hunan Province.The inner strength,medication literacy,and medication adherence of kidney transplant patients were investigated using the Inner Strength Scale(ISS),the Chinese version of the Medication Literacy Assessment in Spanish and English(MedLitRxSE),and the Chinese version of the Morisky Medication Adherence Scale-8(C-MMAS-8),respectively.Univariate analysis was performed to examine the effects of demographic and clinical data on medication adherence.Correlation analysis was conducted to explore the relationships among medication literacy,medication adherence,and inner strength.Significant variables from univariate and correlation analyses were further analyzed using multiple linear regression,and the mediating effect of inner strength was explored.Results:Among the 421 questionnaires collected,408 were valid,with an effective rate of 96.91%.The scores of C-MMAS-8,MedLitRxSE,and ISS were 6.64±1.16,100.63±14.67,and 8.47±4.03,respectively.Among the 408 patients,only 86(21.08%)patients had a high level of medication adherence,whereas 230(56.37%)patients had a medium level of medication adherence,and 92(22.55%)patients had poor medication adherence.Univariate analysis indicated that the kidney transplant patients’age,marital status,education levels,years since their kidney transplant operation,number of hospitalizations after the kidney transplant,and adverse drug reactions showed significant differences in medication adherence(all P<0.05).Correlation analysis showed that inner strength positively correlated with both medication literacy(r=0.183,P<0.001)and medication adherence(r=0.201,P<0.001).Additionally,there was a positive correlation between medication adherence and medication literacy(r=0.236,P<0.001).Inner strength accounted for 13.22%of the total effect in the mediating role between medication literacy and medication adherence.Conclusion:The level of medication adherence among kidney transplant patients needs improvement,and targeted intervention measures are essential.Inner strength mediates the relationship between medication literacy and medication adherence in these patients.Healthcare professionals should focus on enhancing medication literacy and supporting patients’inner strength to improve medication adherence.

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.

A multi-feature-based intelligent redundancy elimination scheme for cloud-assisted health systems

Redundancy elimination techniques are extensively investigated to reduce storage overheads for cloud-assisted health systems.Deduplication eliminates the redundancy of duplicate blocks by storing one physical instance referenced by multiple duplicates.Delta compression is usually regarded as a complementary technique to deduplication to further remove the redundancy of similar blocks,but our observations indicate that this is disobedient when data have sparse duplicate blocks.In addition,there are many overlapped deltas in the resemblance detection process of post-deduplication delta compression,which hinders the efficiency of delta compression and the index phase of resemblance detection inquires abundant non-similar blocks,resulting in inefficient system throughput.Therefore,a multi-feature-based redundancy elimination scheme,called MFRE,is proposed to solve these problems.The similarity feature and temporal locality feature are excavated to assist redundancy elimination where the similarity feature well expresses the duplicate attribute.Then,similarity-based dynamic post-deduplication delta compression and temporal locality-based dynamic delta compression discover more similar base blocks to minimise overlapped deltas and improve compression ratios.Moreover,the clustering method based on block-relationship and the feature index strategy based on bloom filters reduce IO overheads and improve system throughput.Experiments demonstrate that the proposed method,compared to the state-of-the-art method,improves the compression ratio and system throughput by 9.68%and 50%,respectively.

Clinical effects of detailed nursing management interventions on medication adherence and disease perception in patients with drugresistant tuberculosis

BACKGROUND Tuberculosis(TB)is a chronic respiratory infectious disease that considerably jeopardizes human health,and there is no effective vaccine suitable for its prevention in the entire population.AIM To investigate the promotion of medication adherence and disease cognition in patients with drug-resistant(DR-)TB using detailed nursing management.METHODS In total,114 patients with DR-TB who were diagnosed and treated at our hospital between January 2019 and January 2023 were included in this study.Patients in the control group(n=57)were managed with conventional nursing care,while those in the observation group(n=57)were managed with detailed nursing care.Medication adherence,disease awareness scores,medication safety,and nursing satisfaction were compared between the two groups after the intervention.RESULTS The post-intervention medication compliance rate was 91.23%in the observation group and 75.44%in the control group,with the former being 15.79%higher than the latter(P<0.05).There was no statistically significant difference in the disease awareness scores between the two groups before the intervention;the disease awareness scores of the observation group were significantly higher than those of the control group after the intervention(P<0.05).The incidence of gastrointestinal reactions,joint swelling and pain,hearing loss,electrolyte disorders,and liver and kidney function abnormalities were lower in the observation group than those in the control group.The total nursing satisfaction of the observation group was higher than that of the control group(P<0.05).CONCLUSION Implementation of detailed nursing management for patients with DR-TB can effectively improve medication adherence,enhance awareness of the disease,ensure safety of medication,and improve satisfaction with nursing care.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

A novel medical image data protection scheme for smart healthcare system

The Internet of Multimedia Things(IoMT)refers to a network of interconnected multimedia devices that communicate with each other over the Internet.Recently,smart healthcare has emerged as a significant application of the IoMT,particularly in the context of knowledge‐based learning systems.Smart healthcare systems leverage knowledge‐based learning to become more context‐aware,adaptable,and auditable while maintain-ing the ability to learn from historical data.In smart healthcare systems,devices capture images,such as X‐rays,Magnetic Resonance Imaging.The security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of AI.Moreover,in knowledge‐driven systems,the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel,leading to data trans-mission delays.To address the security and latency concerns,this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos theory.The results of the experiment yield entropy,energy,and correlation values of 7.999,0.0156,and 0.0001,respectively.This validates the effectiveness of the encryption system proposed in this paper,which offers high‐quality encryption,a large key space,key sensitivity,and resistance to statistical attacks.

A Comprehensive Systematic Review: Advancements in Skin Cancer Classification and Segmentation Using the ISIC Dataset

The International Skin Imaging Collaboration(ISIC)datasets are pivotal resources for researchers in machine learning for medical image analysis,especially in skin cancer detection.These datasets contain tens of thousands of dermoscopic photographs,each accompanied by gold-standard lesion diagnosis metadata.Annual challenges associated with ISIC datasets have spurred significant advancements,with research papers reporting metrics surpassing those of human experts.Skin cancers are categorized into melanoma and non-melanoma types,with melanoma posing a greater threat due to its rapid potential for metastasis if left untreated.This paper aims to address challenges in skin cancer detection via visual inspection and manual examination of skin lesion images,processes historically known for their laboriousness.Despite notable advancements in machine learning and deep learning models,persistent challenges remain,largely due to the intricate nature of skin lesion images.We review research on convolutional neural networks(CNNs)in skin cancer classification and segmentation,identifying issues like data duplication and augmentation problems.We explore the efficacy of Vision Transformers(ViTs)in overcoming these challenges within ISIC dataset processing.ViTs leverage their capabilities to capture both global and local relationships within images,reducing data duplication and enhancing model generalization.Additionally,ViTs alleviate augmentation issues by effectively leveraging original data.Through a thorough examination of ViT-based methodologies,we illustrate their pivotal role in enhancing ISIC image classification and segmentation.This study offers valuable insights for researchers and practitioners looking to utilize ViTs for improved analysis of dermatological images.Furthermore,this paper emphasizes the crucial role of mathematical and computational modeling processes in advancing skin cancer detection methodologies,highlighting their significance in improving algorithmic performance and interpretability.