Challenges, Alternatives, and Paths to Sustainability: Better Public Health Promotion Using Social Networking Pages as Key Tools

Novel Federated Decision Making for Distribution of Anti-SARS-CoV-2 Monoclonal Antibody to Eligible High-Risk Patients

Context: When the epidemic first broke out, no specific treatment was available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The urgent need to end this unusual situation has resulted in many attempts to deal with SARS-CoV-2. In addition to several types of vaccinations that have been created, anti-SARS-CoV-2 monoclonal antibodies (mAbs) have added a new dimension to preventative and treatment efforts. This therapy also helps prevent severe symptoms for those at a high risk. Therefore, this is one of the most promising treatments for mild to moderate SARS-CoV-2 cases. However, the availability of anti-SARS-CoV-2 mAb therapy is limited and leads to two main challenges. The first is the privacy challenge of selecting eligible patients from the distribution hospital networking, which requires data sharing, and the second is the prioritization of all eligible patients amongst the distribution hospitals according to dose availability. To our knowledge, no research combined the federated fundamental approach with multicriteria decision-making methods for the treatment of SARS-COV-2, indicating a research gap. Objective: This paper presents a unique sequence processing methodology that distributes anti-SARS-CoV-2 mAbs to eligible high-risk patients with SARS-CoV-2 based on medical requirements by using a novel federated decision-making distributor. Method: This paper proposes a novel federated decision-making distributor (FDMD) of anti-SARS-CoV-2 mAbs for eligible high-risk patients. FDMD is implemented on augmented data of 49,152 cases of patients with SARS-CoV-2 with mild and moderate symptoms. For proof of concept, three hospitals with 16 patients each are enrolled. The proposed FDMD is constructed from the two sides of claim sequencing: central federated server (CFS) and local machine (LM). The CFS includes five sequential phases synchronised with the LMs, namely, the preliminary criteria setting phase that determines the high-risk criteria, calculates their weights using the newly formulated interval-valued spherical fuzzy and hesitant 2-tuple fuzzy-weighted zero-inconsistency (IVSH2-FWZIC), and allocates their values. The subsequent phases are federation, dose availability confirmation, global prioritization of eligible patients and alerting the hospitals with the patients most eligible for receiving the anti-SARS-CoV-2 mAbs according to dose availability. The LM independently performs all local prioritization processes without sharing patients’ data using the provided criteria settings and federated parameters from the CFS via the proposed Federated TOPSIS (F-TOPSIS). The sequential processing steps are coherently performed at both sides. Results and Discussion: (1) The proposed FDMD efficiently and independently identifies the high-risk patients most eligible for receiving anti-SARS-CoV-2 mAbs at each local distribution hospital. The final decision at the CFS relies on the indexed patients’ score and dose availability without sharing the patients’ data. (2) The IVSH2-FWZIC effectively weighs the high-risk criteria of patients with SARS-CoV-2. (3) The local and global prioritization ranks of the F-TOPSIS for eligible patients are subjected to a systematic ranking validated by high correlation results across nine scenarios by altering the weights of the criteria. (4) A comparative analysis of the experimental results with a prior study confirms the effectiveness of the proposed FDMD. Conclusion: The proposed FDMD has the benefits of centrally distributing anti-SARS-CoV-2 mAbs to high-risk patients prioritized based on their eligibility and dose availability, and simultaneously protecting their privacy and offering an effective cure to prevent progression to severe SARS-CoV-2 hospitalization or death.

A Model of Social Media Effects in Public Health Communication Campaigns: Systematic Review

BACKGROUND

Social media platforms are frequently used in health communication campaigns. Common understandings of campaign effects posit a sequential and linear series of steps from exposure to behavior change, commonly known as the hierarchy of effects model (HOE). These concepts need to be reevaluated in the age of social media, which are interactional and communal.

OBJECTIVE

This review aims to update the traditional HOE for health communication campaigns in the context of social media, including identifying indicators of effectiveness and how these are conceptualized to lead to health-related outcomes.

METHODS

We conducted a systematic review of studies following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines reporting on the use of social media as part of health communication campaigns, extracting campaign information such as objectives, platforms used, and measures of campaign performance. We used these data, combined with our understanding of the HOE, to develop an updated conceptual model of social media campaign effects.

RESULTS

We identified 99 eligible studies reporting on 93 campaigns, published between 2012 and 2022. The campaigns were conducted in over 20 countries, but nearly half (n=42) were conducted in the United States. Campaigns targeted a variety of health issues and predominantly used Facebook, Twitter, Instagram, and YouTube. Most campaigns (n=81) set objectives targeting awareness or individual behavior change. Process measures (n=68; eg, reach and impressions) and engagement measures (n=73; eg, likes and retweets) were reported most frequently, while two-fifths (n=42) did not report any outcomes beyond engagement, such as changes in knowledge, behavior, or social norms. Most campaigns (n=55) collected measures that did not allow them to determine if the campaign objective had been met; that is, they were process evaluations only. Based on our review, our updated model suggests that campaign exposure can lead to individual behavior change and improved health outcomes, either through a direct or indirect pathway. Indirect pathways include exposure through social and policy changes. "Engagement" is positioned as critical to success, replacing awareness in the traditional HOE, and all types of engagement are treated as equal and good. No consideration is being given to potential negative engagement, such as the distribution of misinformation. Additionally, the process is no longer linear and sequential, with circular pathways evident, such as engagement not only influencing behavior change but also generating additional exposure to campaign messages.

CONCLUSIONS

Our review has highlighted a change in conventional understandings of how campaigns can influence health outcomes in the age of social media. The updated model we propose provides social media campaigners with a starting point to develop and tailor campaign messages and allows evaluators to identify critical assumptions to test, including the role and value of "engagement."

TRIAL REGISTRATION

PROSPERO CRD42021287257; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=287257.

Intelligent Emotion and Sensory Remote Prioritisation for Patients with Multiple Chronic Diseases

An intelligent remote prioritization for patients with high-risk multiple chronic diseases is proposed in this research, based on emotion and sensory measurements and multi-criteria decision making. The methodology comprises two phases: (1) a case study is discussed through the adoption of a multi-criteria decision matrix for high-risk level patients; (2) the technique for reorganizing opinion order to interval levels (TROOIL) is modified by combining it with an extended fuzzy-weighted zero-inconsistency (FWZIC) method over fractional orthotriple fuzzy sets to address objective weighting issues associated with the original TROOIL. In the first hierarchy level, chronic heart disease is identified as the most important criterion, followed by emotion-based criteria in the second. The third hierarchy level shows that Peaks is identified as the most important sensor-based criterion and chest pain as the most important emotion criterion. Low blood pressure disease is identified as the most important criterion for patient prioritization, with the most severe cases being prioritized. The results are evaluated using systematic ranking and sensitivity analysis.

Impact of a digital manual for guidance on malignant hyperthermia: patient education

Background

Malignant hyperthermia (MH) is a rare, hereditary disease with a hypermetabolic response to volatile anesthetics/succinylcholine. Susceptible patients face difficulties due to a lack of knowledge about MH. As informational materials could increase knowledge and adherence to prevention/therapy, digital information about rare diseases validated for patients is needed. Our objective was to evaluate the following: (1) the impact of digital manuals on the knowledge/quality of life of MH patients and (2) access to MH services.

Materials and methods

Fifty MH-susceptible patients filled out a virtual questionnaire twice (demographic/economic/clinical data, MH knowledge and impact on daily life, and SF-36 quality of life). Test groups 1 (n = 17) and 2 (n = 16) were evaluated 30 and 180 days after receiving a digital manual, and the control group (n = 17; without manual) was evaluated after 180 days. We collected the MH service data about the number of contacts.

Results

Twenty-four (48%) patients reported problems in personal/professional life, sports, clinical/surgical/dental treatments, and military service, in addition to concerns about emergency care and complaints of sequelae. The percentage of correct answers in the second MH knowledge questionnaire increased for test group 2 (62% vs. 74.1%; unpaired t test, p < 0.01), was significantly greater in test groups 1 (68.1%) and 2 (74.1%) than in the control group (56.5%; Kruskal–Wallis, p < 0.05), and correlated with more time studying the manual and reports of MH-related problems (multiple regression, p < 0.05).

Conclusions

The digital manual improved patients’ MH knowledge. Online contacts with the MH service increased, allowing greater information dissemination. As informational materials could increase knowledge/adherence to prevention/therapy, digital information about MH validated for patients should be implemented.

Impact of interprofessional service-learning on the effectiveness of knowledge transfer of antimicrobial resistance to Hong Kong elders: a quasi-experiment

Background

Community perception on antimicrobials plays a role in driving the development of antimicrobial resistance (AMR). The aim of the study was to evaluate the impact of interprofessional service-learning on the effectiveness of AMR knowledge transfer in Hong Kong elders aged 65 or above and students from university and secondary schools.

Methods

A quasi-experimental pretest–posttest controlled study was carried out from July 2018 to March 2019 for elderly subjects and a pre- and post-test were conducted in students from May to August 2018. Elderly subjects were recruited from the university-based community outreach program. The community outreach team consisted of both university and secondary school students. Students were provided with training of geriatric care and AMR before they reached out to the community. The one-to-one intervention with the aid of video and verbal explanation to educate the elderly about the definition, causes, and consequences of AMR, and preventive measures against AMR was provided. Questionnaires on knowledge of antibiotics and AMR were used as tools to reflect on the effectiveness for both students and elderly subjects. The questionnaire was completed twice, before and 1 week after the intervention. Chi-square test, t tests and regression analysis were used to analyze the data.

Results

A total of 93 Chinese elders, 61 of them in the intervention group and 32 in the control group participated in the study. The score obtained by the intervention group increased from 40.1 to 83.3% (p < 0.001) following intervention, while that of control group increased from 33.0 to 44.0% (p < 0.001). The increase attained in the intervention group was significantly greater than that of the control group (p < 0.001). A total of 95 secondary students and 88 university students have completed the pre-post questionnaires with 42.21% and 13% increment in AMR knowledge after the training (p < 0.001).

Conclusion

The significant change in knowledge level showed effective AMR knowledge transfer to both elders and students. The study could be used as a reference when allocating resources to implement effective interprofessional service-learning for better community health education in elderly populations.

Trial registration: This study was approved by the Chinese University of Hong Kong Survey and Behavioural Research Ethics Committee in December 2018 (Ref no. SBRE-18-214).

A Social Media-Promoted Educational Community of Joint Replacement Patients Using the WeChat App: Survey Study

Background

Much effort has been made to optimize the results of total hip arthroplasty and total knee arthroplasty. With the rapid growth of social media use, mobile apps, such as WeChat, have been considered for improving outcomes and patient satisfaction after total hip arthroplasty and total knee arthroplasty.

Objective

We aimed to evaluate the effectiveness of a WeChat-based community as an intervention for overall patient satisfaction.

Methods

The study was conducted among discharged in-hospital patients who received hip or knee procedures in the First Affiliated Hospital of the University of Science and Technology of China from April 2019 to January 2020. An educational online social community was constructed with the WeChat app. Participants willing to join the community were enrolled in a WeChat group and received 3 months of intervention and follow-up. Those who were not willing to use the account were included in a control group and received routine publicity via telephone, mail, and brochures. The Danish Health and Medicine Authority patient satisfaction questionnaire was used to score perioperative patient education and overall satisfaction. The contents in the group chat were analyzed using natural language processing tools.

Results

A total of 3428 patients were enrolled in the study, including 2292 in the WeChat group and 1236 in the control group. Participants in the WeChat group had higher overall satisfaction scores than those in the control group (mean 8.48, SD 1.12 vs mean 6.66, SD 1.80, P<.001). The difference between the two groups was significant for primary surgery based on subgroup stratification. To control confounding factors and explore the effects of WeChat participation as a mediating variable between perioperative patient education and overall satisfaction, hierarchical regression was utilized. An interpatient interaction model was found in the community group chat, and it contributed to overall satisfaction. Patients in the group with more interpatient interactions were more likely to have better overall satisfaction.

Conclusions

The social media–promoted educational community using WeChat was effective among joint replacement patients. Provision of more perioperative education is associated with more active patient participation in the community and therefore more patient satisfaction in terms of the overall joint procedure. Community group chat could facilitate interactions among patients and contribute to overall satisfaction.

PSO-Blockchain-based image steganography: towards a new method to secure updating and sharing COVID-19 data in decentralised hospitals intelligence architecture

Secure updating and sharing for large amounts of healthcare information (such as medical data on coronavirus disease 2019 [COVID-19]) in efficient and secure transmission are important but challenging in communication channels amongst hospitals. In particular, in addressing the above challenges, two issues are faced, namely, those related to confidentiality and integrity of their health data and to network failure that may cause concerns about data availability. To the authors' knowledge, no study provides secure updating and sharing solution for large amounts of healthcare information in communication channels amongst hospitals. Therefore, this study proposes and discusses a novel steganography-based blockchain method in the spatial domain as a solution. The novelty of the proposed method is the removal and addition of new particles in the particle swarm optimisation (PSO) algorithm. In addition, hash function can hide secret medical COVID-19 data in hospital databases whilst providing confidentiality with high embedding capacity and high image quality. Moreover, stego images with hash data and blockchain technology are used in updating and sharing medical COVID-19 data between hospitals in the network to improve the level of confidentiality and protect the integrity of medical COVID-19 data in grey-scale images, achieve data availability if any connection failure occurs in a single point of the network and eliminate the central point (third party) in the network during transmission. The proposed method is discussed in three stages. Firstly, the pre-hiding stage estimates the embedding capacity of each host image. Secondly, the secret COVID-19 data hiding stage uses PSO algorithm and hash function. Thirdly, the transmission stage transfers the stego images based on blockchain technology and updates all nodes (hospitals) in the network. As proof of concept for the case study, the authors adopted the latest COVID-19 research published in the Computer Methods and Programs in Biomedicine journal, which presents a rescue framework within hospitals for the storage and transfusion of the best convalescent plasma to the most critical patients with COVID-19 on the basis of biological requirements. The validation and evaluation of the proposed method are discussed.

Leveraging Interdisciplinary Teams to Develop and Implement Secure Websites for Behavioral Research: Applied Tutorial

Behavioral researchers are increasingly using interactive digital platforms, either as standalone or supplementary intervention tools, to facilitate positive changes in research participants’ health habits. Research-oriented interactive websites optimally offer a variety of participatory mediums, such as blogs, user-driven content, or health activities. Owing to the multidirectional features of interactive websites, and a corresponding need to protect research participants’ identity and data, it is paramount that researchers design ethical platforms that ensure privacy and minimize loss of anonymity and confidentiality. Authentication (ie, digital verification of one’s identity) of interactive sites is one viable solution to these concerns. Although previous publications have addressed ethical requirements related to authenticated platforms, few applied guidelines in the literature facilitate adherence to ethical principles and legally compliant study protocols during all phases of research website creation (feasibility, design, implementation, and maintenance). Notably, to remain compliant with ethical standards and study protocols, behavioral researchers must collaborate with interdisciplinary teams to ensure that the authenticated site remains secure and usable in all stages of the project. In this tutorial, we present a case study conducted at a large research university. Through iterative and practical recommendations, we detail lessons learned from collaborations with the Institutional Review Board, legal experts, and information technology teams. Although the intricacies of our applied tutorial may require adaptations based on each institution’s technological capacity, we are confident that the core takeaways are universal and thus useful to behavioral researchers creating ethically responsible and compliant interactive websites.

Improving cancer survivors' e-health literacy via online health communities (OHCs): a social support perspective

PURPOSE

Cancer survivors should have adequate e-health literacy to help them better use online health information. Online health communities (OHCs) can offer cancer survivors different types of social support that can represent another resource to improve health outcomes. However, there is little knowledge of how these OHC are directly related to a cancer survivors' e-health literacy. This study explores how different types of social support in OHCs are associated with cancer survivors' e-health literacy.

METHODS

A questionnaire was developed to collect data from two Chinese OHCs used by cancer survivors. The questionnaire is composed of two parts: six sociodemographic variables (i.e., gender, age, city, education, tenure, and prior Internet experience), two scales for informational support behaviors (i.e., health knowledge seeking and provision of health knowledge), a measure of emotional support within such a setting, and a measure of e-health literacy. Based on 162 complete samples, we determined the measurement properties of the scales used, provided descriptive statistics on major sociodemographic variables and conducted bivariate and multivariable hierarchical regression.

RESULTS

For cancer survivors, females demonstrate higher levels of e-health literacy. Higher education level was related to higher e-health literacy. Health knowledge seeking, contributing to health knowledge, and emotional support were all positively associated with e-health literacy. The interaction effect between health knowledge and emotional support is positively associated with e-health literacy.

CONCLUSIONS

Informational support and emotional support, as two major subtypes of social support within resources available in OHCs, are positively associated with e-health literacy among cancer survivors.

IMPLICATIONS FOR CANCER SURVIVORS

Cancer survivors might benefit from an active strategy for improving personal e-health literacy that includes more active informational involvement and emotional support rather than a passive lurking through e-health information and seeking and reading postings in OHCs.

Novel technique for reorganisation of opinion order to interval levels for solving several instances representing prioritisation in patients with multiple chronic diseases

CONTEXT

Telemedicine has been increasingly used in healthcare to provide services to patients remotely. However, prioritising patients with multiple chronic diseases (MCDs) in telemedicine environment is challenging because it includes decision-making (DM) with regard to the emergency degree of each chronic disease for every patient.

OBJECTIVE

This paper proposes a novel technique for reorganisation of opinion order to interval levels (TROOIL) to prioritise the patients with MCDs in real-time remote health-monitoring system.

METHODS

The proposed TROOIL technique comprises six steps for prioritisation of patients with MCDs: (1) conversion of actual data into intervals; (2) rule generation; (3) rule ordering; (4) expert rule validation; (5) data reorganisation; and (6) criteria weighting and ranking alternatives within each rule. The secondary dataset of 500 patients from the most relevant study in a remote prioritisation area was adopted. The dataset contains three diseases, namely, chronic heart disease, high blood pressure (BP) and low BP.

RESULTS

The proposed TROOIL is an effective technique for prioritising patients with MCDs. In the objective validation, remarkable differences were recognised among the groups' scores, indicating identical ranking results. In the evaluation of issues within all scenarios, the proposed framework has an advantage of 22.95% over the benchmark framework.

DISCUSSION

Patients with the most severe MCD were treated first on the basis of their highest priority levels. The treatment for patients with less severe cases was delayed more than that for other patients.

CONCLUSIONS

The proposed TROOIL technique can deal with multiple DM problems in prioritisation of patients with MCDs.

Brain Tumor Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges

Deep Learning (DL) algorithms enabled computational models consist of multiple processing layers that represent data with multiple levels of abstraction. In recent years, usage of deep learning is rapidly proliferating in almost every domain, especially in medical image processing, medical image analysis, and bioinformatics. Consequently, deep learning has dramatically changed and improved the means of recognition, prediction, and diagnosis effectively in numerous areas of healthcare such as pathology, brain tumor, lung cancer, abdomen, cardiac, and retina. Considering the wide range of applications of deep learning, the objective of this article is to review major deep learning concepts pertinent to brain tumor analysis (e.g., segmentation, classification, prediction, evaluation.). A review conducted by summarizing a large number of scientific contributions to the field (i.e., deep learning in brain tumor analysis) is presented in this study. A coherent taxonomy of research landscape from the literature has also been mapped, and the major aspects of this emerging field have been discussed and analyzed. A critical discussion section to show the limitations of deep learning techniques has been included at the end to elaborate open research challenges and directions for future work in this emergent area.

Current status of official WeChat accounts for public health education

BACKGROUND

To investigate the current use status of official WeChat accounts for the Centers for Disease Control and Prevention in public health education and relevant factors that can impact the effectiveness of message delivery.

METHODS

A retrospective survey was conducted to evaluate the effectiveness of official WeChat accounts. About 531 official WeChat accounts and 50 939 articles were analyzed using a cluster sampling survey design. The Kruskal-Wallis test and multivariate logistic regression were used to explore factors associated with the usefulness of the number of views and "Likes" of the articles.

RESULTS

The study identified a total of 531 public WeChat accounts, including 19 province-level accounts, 179 municipal-level accounts and 333 county-level accounts. In the univariable analysis, the administrative level of the account, article order, time segment, article originality and thematic category were associated with the number of views and "Likes." Province-level accounts, first articles, the 5:00-6:00 time segment, original articles and theme 3 (emergencies) had higher numbers of views and "Likes" than the others (P < 0.05).

CONCLUSIONS

Promoting health education through Official WeChat account is an effective, sustainable and feasible strategy. Potential indicators of the impact of public health education suggest that administrators should effectively use official WeChat accounts for public health education.

A Systematic Review for Enabling of Develop a Blockchain Technology in Healthcare Application: Taxonomy, Substantially Analysis, Motivations, Challenges, Recommendations and Future Direction

Blockchain in healthcare applications requires robust security and privacy mechanism for high-level authentication, interoperability and medical records sharing to comply with the strict legal requirements of the Health Insurance Portability and Accountability Act of 1996. Blockchain technology in the healthcare industry has received considerable research attention in recent years. This study conducts a review to substantially analyse and map the research landscape of current technologies, mainly the use of blockchain in healthcare applications, into a coherent taxonomy. The present study systematically searches all relevant research articles on blockchain in healthcare applications in three accessible databases, namely, ScienceDirect, IEEE and Web of Science, by using the defined keywords 'blockchain', 'healthcare' and 'electronic health records' and their variations. The final set of collected articles related to the use of blockchain in healthcare application is divided into three categories. The first category includes articles (i.e. 43/58 scientific articles) that attempted to develop and design healthcare applications integrating blockchain, particularly those on new architecture, system designs, framework, scheme, model, platform, approach, protocol and algorithm. The second category includes studies (i.e., 6/58 scientific articles) that attempted to evaluate and analyse the adoption of blockchain in the healthcare system. Finally, the third category comprises review and survey articles (i.e., 6/58 scientific articles) related to the integration of blockchain into healthcare applications. The final articles for review are discussed on the basis of five aspects: (1) year of publication, (2) nationality of authors, (3) publishing house or journal, (4) purpose of using blockchain in health applications and the corresponding contributions and ⁽⁵⁾ problem types and proposed solutions. Additionally, this study provides identified motivations, open challenges and recommendations on the use of blockchain in healthcare applications. The current research contributes to the literature by providing a detailed review of feasible alternatives and identifying the research gaps. Accordingly, researchers and developers are provided with appealing opportunities to further develop decentralised healthcare applications through a comprehensive discussion of about the importance of blockchain and its integration into various healthcare applications.

Real-Time Remote-Health Monitoring Systems: a Review on Patients Prioritisation for Multiple-Chronic Diseases, Taxonomy Analysis, Concerns and Solution Procedure

Remotely monitoring a patient's condition is a serious issue and must be addressed. Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies, methods and installations that enable doctors or other medical professionals to work remotely to consult, diagnose and treat patients. The goal of RHMS is to provide timely medical services at remote areas through telecommunication technologies. Through major advancements in technology, particularly in wireless networking, cloud computing and data storage, RHMS is becoming a feasible aspect of modern medicine. RHMS for the prioritisation of patients with multiple chronic diseases (MCDs) plays an important role in sustainably providing high-quality healthcare services. Further investigations are required to highlight the limitations of the prioritisation of patients with MCDs over a telemedicine environment. This study introduces a comprehensive and inclusive review on the prioritisation of patients with MCDs in telemedicine applications. Furthermore, it presents the challenges and open issues regarding patient prioritisation in telemedicine. The findings of this study are as follows: (1) The limitations and problems of existing patients' prioritisation with MCDs are presented and emphasised. (2) Based on the analysis of the academic literature, an accurate solution for remote prioritisation in a large scale of patients with MCDs was not presented. (3) There is an essential need to produce a new multiple-criteria decision-making theory to address the current problems in the prioritisation of patients with MCDs.

Mobile-Based Patient Monitoring Systems: A Prioritisation Framework Using Multi-Criteria Decision-Making Techniques

This study presents a prioritisation framework for mobile patient monitoring systems (MPMSs) based on multicriteria analysis in architectural components. This framework selects the most appropriate system amongst available MPMSs for the telemedicine environment. Prioritisation of MPMSs is a challenging task due to (a) multiple evaluation criteria, (b) importance of criteria, (c) data variation and (d) unmeasurable values. The secondary data presented as the decision evaluation matrix include six systems (namely, Yale-National Aeronautics and Space Administration (NASA), advanced health and disaster aid network, personalised health monitoring, CMS, MobiHealth and NTU) as alternatives and 13 criteria (namely, supported number of sensors, sensor front-end (SFE) communication, SFE to mobile base unit (MBU) communications, display of biosignals on the MBU, storage of biosignals on the MBU, intra-body area network (BAN) communication problems, extra-BAN communication problems, extra-BAN communication technology, extra-BAN communication protocols, back-end system communication technology, intended geographic area of use, end-to-end security and reported trial problems) based on the architectural components of MPMSs. These criteria are adopted from the most relevant studies and are found to be applicable to this study. The prioritisation framework is developed in three stages. (1) The unmeasurable values of the MPMS evaluation criteria in the adopted decision evaluation matrix based on expert opinion are represented by using the best-worst method (BWM). (2) The importance of the evaluation criteria based on the architectural components of the MPMS is determined by using the BWM. (3) The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is utilised to rank the MPMSs according to the determined importance of the evaluation criteria and the adopted decision matrix. For validation, mean ± standard deviation is used to verify the similarity of systematic prioritisations objectively. The following results are obtained. (1) The BWM represents the unmeasurable values of the MPMS evaluation criteria. (2) The BWM is suitable for weighing the evaluation criteria based on the architectural components of the MPMS. (3) VIKOR is suitable for solving the MPMS prioritisation problem. Moreover, the internal and external VIKOR group decision making are approximately the same, with the best MPMS being 'Yale-NASA' and the worst MPMS being 'NTU'. (4) For the objective validation, remarkable differences are observed between the group scores, which indicate the similarity of internal and external prioritisation results.

Multiclass Benchmarking Framework for Automated Acute Leukaemia Detection and Classification Based on BWM and Group-VIKOR

This paper aims to assist the administration departments of medical organisations in making the right decision on selecting a suitable multiclass classification model for acute leukaemia. In this paper, we proposed a framework that will aid these departments in evaluating, benchmarking and ranking available multiclass classification models for the selection of the best one. Medical organisations have continuously faced evaluation and benchmarking challenges in such endeavour, especially when no single model is superior. Moreover, the improper selection of multiclass classification for acute leukaemia model may be costly for medical organisations. For example, when a patient dies, one such organisation will be legally or financially sued for incidents in which the model fails to fulfil its desired outcome. With regard to evaluation and benchmarking, multiclass classification models are challenging processes due to multiple evaluation and conflicting criteria. This study structured a decision matrix (DM) based on the crossover of 2 groups of multi-evaluation criteria and 22 multiclass classification models. The matrix was then evaluated with datasets comprising 72 samples of acute leukaemia, which include 5327 gens. Subsequently, multi-criteria decision-making (MCDM) techniques are used in the benchmarking and ranking of multiclass classification models. The MCDM used techniques that include the integrated BWM and VIKOR. BWM has been applied for the weight calculations of evaluation criteria, whereas VIKOR has been used to benchmark and rank classification models. VIKOR has also been employed in two decision-making contexts: individual and group decision making and internal and external group aggregation. Results showed the following: (1) the integration of BWM and VIKOR is effective at solving the benchmarking/selection problems of multiclass classification models. (2) The ranks of classification models obtained from internal and external VIKOR group decision making were almost the same, and the best multiclass classification model based on the two was 'Bayes. Naive Byes Updateable' and the worst one was 'Trees.LMT'. (3) Among the scores of groups in the objective validation, significant differences were identified, which indicated that the ranking results of internal and external VIKOR group decision making were valid.

Mobile Patient Monitoring Systems from a Benchmarking Aspect: Challenges, Open Issues and Recommended Solutions

This paper presents comprehensive insights into mobile patient monitoring systems (MPMSs) from evaluation and benchmarking aspects on the basis of two critical directions. The current evaluation criteria of MPMSs based on the architectural components of MPMSs and possible solutions are discussed. This review highlights four serious issues, namely, multiple evaluation criteria, criterion importance, unmeasurable criteria and data variation, in MPMS benchmarking. Multicriteria decision-making (MCDM) analysis techniques are proposed as effective solutions to solve these issues from a methodological aspect. This methodological aspect involves a framework for benchmarking MPMSs on the basis of MCDM to rank available MPMSs and select a suitable one. The benchmarking framework is discussed in four steps. Firstly, pre-processing and identification procedures are presented. Secondly, the procedure of weight calculation based on the best-worst method (BWM) is described. Thirdly, the development of a benchmark framework by using the VIKOR method is introduced. Lastly, the proposed framework is validated.

Based Medical Systems for Patient's Authentication: Towards a New Verification Secure Framework Using CIA Standard

In medical systems for patient's authentication, keeping biometric data secure is a general problem. Many studies have presented various ways of protecting biometric data especially finger vein biometric data. Thus, It is needs to find better ways of securing this data by applying the three principles of information security aforementioned, and creating a robust verification system with high levels of reliability, privacy and security. Moreover, it is very difficult to replace biometric information and any leakage of biometrics information leads to earnest risks for example replay attacks using the robbed biometric data. In this paper presented criticism and analysis to all attempts as revealed in the literature review and discussion the proposes a novel verification secure framework based confidentiality, integrity and availability (CIA) standard in triplex blockchain-particle swarm optimization (PSO)-advanced encryption standard (AES) techniques for medical systems patient's authentication. Three stages are performed on discussion. Firstly, proposes a new hybrid model pattern in order to increase the randomization based on radio frequency identification (RFID) and finger vein biometrics. To achieve this, proposed a new merge algorithm to combine the RFID features and finger vein features in one hybrid and random pattern. Secondly, how the propose verification secure framework are followed the CIA standard for telemedicine authentication by combination of AES encryption technique, blockchain and PSO in steganography technique based on proposed pattern model. Finally, discussed the validation and evaluation of the proposed verification secure framework.

Smart Home-based IoT for Real-time and Secure Remote Health Monitoring of Triage and Priority System using Body Sensors: Multi-driven Systematic Review

The Internet of Things (IoT) has been identified in various applications across different domains, such as in the healthcare sector. IoT has also been recognised for its revolution in reshaping modern healthcare with aspiring wide range prospects, including economical, technological and social. This study aims to establish IoT-based smart home security solutions for real-time health monitoring technologies in telemedicine architecture. A multilayer taxonomy is driven and conducted in this study. In the first layer, a comprehensive analysis on telemedicine, which focuses on the client and server sides, shows that other studies associated with IoT-based smart home applications have several limitations that remain unaddressed. Particularly, remote patient monitoring in healthcare applications presents various facilities and benefits by adopting IoT-based smart home technologies without compromising the security requirements and potentially large number of risks. An extensive search is conducted to identify articles that handle these issues, related applications are comprehensively reviewed and a coherent taxonomy for these articles is established. A total number of (n = 3064) are gathered between 2007 and 2017 for most reliable databases, such as ScienceDirect, Web of Science and Institute of Electrical and Electronic Engineer Xplore databases. Then, the articles based on IoT studies that are associated with telemedicine applications are filtered. Nine articles are selected and classified into two categories. The first category, which accounts for 22.22% (n = 2/9), includes surveys on telemedicine articles and their applications. The second category, which accounts for 77.78% (n = 7/9), includes articles on the client and server sides of telemedicine architecture. The collected studies reveal the essential requirement in constructing another taxonomy layer and review IoT-based smart home security studies. Therefore, IoT-based smart home security features are introduced and analysed in the second layer. The security of smart home design based on IoT applications is an aspect that represents a crucial matter for general occupants of smart homes, in which studies are required to provide a better solution with patient security, privacy protection and security of users' entities from being stolen or compromised. Innovative technologies have dispersed limitations related to this matter. The existing gaps and trends in this area should be investigated to provide valuable visions for technical environments and researchers. Thus, 67 articles are obtained in the second layer of our taxonomy and are classified into six categories. In the first category, 25.37% (n = 17/67) of the articles focus on architecture design. In the second category, 17.91% (n = 12/67) includes security analysis articles that investigate the research status in the security area of IoT-based smart home applications. In the third category, 10.44% (n = 7/67) includes articles about security schemes. In the fourth category, 17.91% (n = 12/67) comprises security examination. In the fifth category, 13.43% (n = 9/67) analyses security protocols. In the final category, 14.92% (n = 10/67) analyses the security framework. Then, the identified basic characteristics of this emerging field are presented and provided in the following aspects. Open challenges experienced on the development of IoT-based smart home security are addressed to be adopted fully in telemedicine applications. Then, the requirements are provided to increase researcher's interest in this study area. On this basis, a number of recommendations for different parties are described to provide insights on the next steps that should be considered to enhance the security of smart homes based on IoT. A map matching for both taxonomies is developed in this study to determine the novel risks and benefits of IoT-based smart home security for real-time remote health monitoring within client and server sides in telemedicine applications.

Sensor-Based mHealth Authentication for Real-Time Remote Healthcare Monitoring System: A Multilayer Systematic Review

The new and groundbreaking real-time remote healthcare monitoring system on sensor-based mobile health (mHealth) authentication in telemedicine has considerably bounded and dispersed communication components. mHealth, an attractive part in telemedicine architecture, plays an imperative role in patient security and privacy and adapts different sensing technologies through many built-in sensors. This study aims to improve sensor-based defence and attack mechanisms to ensure patient privacy in client side when using mHealth. Thus, a multilayer taxonomy was conducted to attain the goal of this study. Within the first layer, real-time remote monitoring studies based on sensor technology for telemedicine application were reviewed and analysed to examine these technologies and provide researchers with a clear vision of security- and privacy-based sensors in the telemedicine area. An extensive search was conducted to find articles about security and privacy issues, review related applications comprehensively and establish the coherent taxonomy of these articles. ScienceDirect, IEEE Xplore and Web of Science databases were investigated for articles on mHealth in telemedicine-based sensor. A total of 3064 papers were collected from 2007 to 2017. The retrieved articles were filtered according to the security and privacy of sensor-based telemedicine applications. A total of 19 articles were selected and classified into two categories. The first category, 57.89% (n = 11/19), included survey on telemedicine articles and their applications. The second category, 42.1% (n = 8/19), included articles contributed to the three-tiered architecture of telemedicine. The collected studies improved the essential need to add another taxonomy layer and review the sensor-based smartphone authentication studies. This map matching for both taxonomies was developed for this study to investigate sensor field comprehensively and gain access to novel risks and benefits of the mHealth security in telemedicine application. The literature on sensor-based smartphones in the second layer of our taxonomy was analysed and reviewed. A total of 599 papers were collected from 2007 to 2017. In this layer, we obtained a final set of 81 articles classified into three categories. The first category of the articles [86.41% (n = 70/81)], where sensor-based smartphones were examined by utilising orientation sensors for user authentication, was used. The second category [7.40% (n = 6/81)] included attack articles, which were not intensively included in our literature analysis. The third category [8.64% (n = 7/81)] included 'other' articles. Factors were considered to understand fully the various contextual aspects of the field in published studies. The characteristics included the motivation and challenges related to sensor-based authentication of smartphones encountered by researchers and the recommendations to strengthen this critical area of research. Finally, many studies on the sensor-based smartphone in the second layer have focused on enhancing accurate authentication because sensor-based smartphones require sensors that could authentically secure mHealth.

Real-Time Medical Systems Based on Human Biometric Steganography: a Systematic Review

In real-time medical systems, the role of biometric technology is significant in authentication systems because it is used in verifying the identity of people through their biometric features. The biometric technology provides crucial properties for biometric features that can support the process of personal identification. The storage of biometric template within a central database makes it vulnerable to attack which can also occur during data transmission. Therefore, an alternative mechanism of protection becomes important to develop. On this basis, this study focuses on providing a detailed analysis of the extant literature (2013-2018) to identify the taxonomy and research distribution. Furthermore, this study also seeks to ascertain the challenges and motivations associated with biometric steganography in real-time medical systems to provide recommendations that can enhance the efficient use of real-time medical systems in biometric steganography and its applications. A review of articles on human biometric steganography in real-time medical systems obtained from three main databases (IEEE Xplore, ScienceDirect and Web of Science) is conducted according to an appropriate review protocol. Then, 41 related articles are selected by using exclusion and inclusion criteria. Majority of the studies reviewed had been conducted in the field of data-hiding (particularly steganography) technologies. In this review, various steganographic methods that have been applied in different human biometrics are investigated. Thereafter, these methods are categorised according to taxonomy, and the results are presented on the basis of human steganography biometric real-time medical systems, testing and evaluation methods, significance of use and applications and techniques. Finally, recommendations on how the challenges associated with data hiding can be addressed are provided to enhance the efficiency of using biometric information processed in any authentication real-time medical system. These recommendations are expected to be immensely helpful to developers, company users and researchers.

Real-Time Remote Health Monitoring Systems Using Body Sensor Information and Finger Vein Biometric Verification: A Multi-Layer Systematic Review

The development of wireless body area sensor networks is imperative for modern telemedicine. However, attackers and cybercriminals are gradually becoming aware in attacking telemedicine systems, and the black market value of protected health information has the highest price nowadays. Security remains a formidable challenge to be resolved. Intelligent home environments make up one of the major application areas of pervasive computing. Security and privacy are the two most important issues in the remote monitoring and control of intelligent home environments for clients and servers in telemedicine architecture. The personal authentication approach that uses the finger vein pattern is a newly investigated biometric technique. This type of biometric has many advantages over other types (explained in detail later on) and is suitable for different human categories and ages. This study aims to establish a secure verification method for real-time monitoring systems to be used for the authentication of patients and other members who are working in telemedicine systems. The process begins with the sensor based on Tiers 1 and 2 (client side) in the telemedicine architecture and ends with patient verification in Tier 3 (server side) via finger vein biometric technology to ensure patient security on both sides. Multilayer taxonomy is conducted in this research to attain the study's goal. In the first layer, real-time remote monitoring studies based on the sensor technology used in telemedicine applications are reviewed and analysed to provide researchers a clear vision of security and privacy based on sensors in telemedicine. An extensive search is conducted to identify articles that deal with security and privacy issues, related applications are reviewed comprehensively and a coherent taxonomy of these articles is established. ScienceDirect, IEEE Xplore and Web of Science databases are checked for articles on mHealth in telemedicine based on sensors. A total of 3064 papers are collected from 2007 to 2017. The retrieved articles are filtered according to the security and privacy of telemedicine applications based on sensors. Nineteen articles are selected and classified into two categories. The first category, which accounts for 57.89% (n = 11/19), includes surveys on telemedicine articles and their applications. The second category, accounting for 42.1% (n = 8/19), includes articles on the three-tiered architecture of telemedicine. The collected studies reveal the essential need to construct another taxonomy layer and review studies on finger vein biometric verification systems. This map-matching for both taxonomies is developed for this study to go deeply into the sensor field and determine novel risks and benefits for patient security and privacy on client and server sides in telemedicine applications. In the second layer of our taxonomy, the literature on finger vein biometric verification systems is analysed and reviewed. In this layer, we obtain a final set of 65 articles classified into four categories. In the first category, 80% (n = 52/65) of the articles focus on development and design. In the second category, 12.30% (n = 8/65) includes evaluation and comparative articles. These articles are not intensively included in our literature analysis. In the third category, 4.61% (n = 3/65) includes articles about analytical studies. In the fourth category, 3.07% (n = 2/65) comprises reviews and surveys. This study aims to provide researchers with an up-to-date overview of studies that have been conducted on (user/patient) authentication to enhance the security level in telemedicine or any information system. In the current study, taxonomy is presented by explaining previous studies. Moreover, this review highlights the motivations, challenges and recommendations related to finger vein biometric verification systems and determines the gaps in this research direction (protection of finger vein templates in real time), which represent a new research direction in this area.

Systematic Review of an Automated Multiclass Detection and Classification System for Acute Leukaemia in Terms of Evaluation and Benchmarking, Open Challenges, Issues and Methodological Aspects

This study aims to systematically review prior research on the evaluation and benchmarking of automated acute leukaemia classification tasks. The review depends on three reliable search engines: ScienceDirect, Web of Science and IEEE Xplore. A research taxonomy developed for the review considers a wide perspective for automated detection and classification of acute leukaemia research and reflects the usage trends in the evaluation criteria in this field. The developed taxonomy consists of three main research directions in this domain. The taxonomy involves two phases. The first phase includes all three research directions. The second one demonstrates all the criteria used for evaluating acute leukaemia classification. The final set of studies includes 83 investigations, most of which focused on enhancing the accuracy and performance of detection and classification through proposed methods or systems. Few efforts were made to undertake the evaluation issues. According to the final set of articles, three groups of articles represented the main research directions in this domain: 56 articles highlighted the proposed methods, 22 articles involved proposals for system development and 5 papers centred on evaluation and comparison. The other taxonomy side included 16 main and sub-evaluation and benchmarking criteria. This review highlights three serious issues in the evaluation and benchmarking of multiclass classification of acute leukaemia, namely, conflicting criteria, evaluation criteria and criteria importance. It also determines the weakness of benchmarking tools. To solve these issues, multicriteria decision-making (MCDM) analysis techniques were proposed as effective recommended solutions in the methodological aspect. This methodological aspect involves a proposed decision support system based on MCDM for evaluation and benchmarking to select suitable multiclass classification models for acute leukaemia. The said support system is examined and has three sequential phases. Phase One presents the identification procedure and process for establishing a decision matrix based on a crossover of evaluation criteria and acute leukaemia multiclass classification models. Phase Two describes the decision matrix development for the selection of acute leukaemia classification models based on the integrated Best and worst method (BWM) and VIKOR. Phase Three entails the validation of the proposed system.

Real-Time Remote Health-Monitoring Systems in a Medical Centre: A Review of the Provision of Healthcare Services-Based Body Sensor Information, Open Challenges and Methodological Aspects

Promoting patient care is a priority for all healthcare providers with the overall purpose of realising a high degree of patient satisfaction. A medical centre server is a remote computer that enables hospitals and physicians to analyse data in real time and offer appropriate services to patients. The server can also manage, organise and support professionals in telemedicine. Therefore, a remote medical centre server plays a crucial role in sustainably delivering quality healthcare services in telemedicine. This article presents a comprehensive review of the provision of healthcare services in telemedicine applications, especially in the medical centre server. Moreover, it highlights the open issues and challenges related to providing healthcare services in the medical centre server within telemedicine. Methodological aspects to control and manage the process of healthcare service provision and three distinct and successive phases are presented. The first phase presents the identification process to propose a decision matrix (DM) on the basis of a crossover of 'multi-healthcare services' and 'hospital list' within intelligent data and service management centre (Tier 4). The second phase discusses the development of a DM for hospital selection on the basis of integrated VIKOR-Analytic Hierarchy Process (AHP) methods. Finally, the last phase examines the validation process for the proposed framework.

Real-Time Fault-Tolerant mHealth System: Comprehensive Review of Healthcare Services, Opens Issues, Challenges and Methodological Aspects

The burden on healthcare services in the world has increased substantially in the past decades. The quality and quantity of care have to increase to meet surging demands, especially among patients with chronic heart diseases. The expansion of information and communication technologies has led to new models for the delivery healthcare services in telemedicine. Therefore, mHealth plays an imperative role in the sustainable delivery of healthcare services in telemedicine. This paper presents a comprehensive review of healthcare service provision. It highlights the open issues and challenges related to the use of the real-time fault-tolerant mHealth system in telemedicine. The methodological aspects of mHealth are examined, and three distinct and successive phases are presented. The first discusses the identification process for establishing a decision matrix based on a crossover of 'time of arrival of patient at the hospital/multi-services' and 'hospitals' within mHealth. The second phase discusses the development of a decision matrix for hospital selection based on the MAHP method. The third phase discusses the validation of the proposed system.

Based on Real Time Remote Health Monitoring Systems: A New Approach for Prioritization "Large Scales Data" Patients with Chronic Heart Diseases Using Body Sensors and Communication Technology

This paper presents a new approach to prioritize "Large-scale Data" of patients with chronic heart diseases by using body sensors and communication technology during disasters and peak seasons. An evaluation matrix is used for emergency evaluation and large-scale data scoring of patients with chronic heart diseases in telemedicine environment. However, one major problem in the emergency evaluation of these patients is establishing a reasonable threshold for patients with the most and least critical conditions. This threshold can be used to detect the highest and lowest priority levels when all the scores of patients are identical during disasters and peak seasons. A practical study was performed on 500 patients with chronic heart diseases and different symptoms, and their emergency levels were evaluated based on four main measurements: electrocardiogram, oxygen saturation sensor, blood pressure monitoring, and non-sensory measurement tool, namely, text frame. Data alignment was conducted for the raw data and decision-making matrix by converting each extracted feature into an integer. This integer represents their state in the triage level based on medical guidelines to determine the features from different sources in a platform. The patients were then scored based on a decision matrix by using multi-criteria decision-making techniques, namely, integrated multi-layer for analytic hierarchy process (MLAHP) and technique for order performance by similarity to ideal solution (TOPSIS). For subjective validation, cardiologists were consulted to confirm the ranking results. For objective validation, mean ± standard deviation was computed to check the accuracy of the systematic ranking. This study provides scenarios and checklist benchmarking to evaluate the proposed and existing prioritization methods. Experimental results revealed the following. (1) The integration of TOPSIS and MLAHP effectively and systematically solved the patient settings on triage and prioritization problems. (2) In subjective validation, the first five patients assigned to the doctors were the most urgent cases that required the highest priority, whereas the last five patients were the least urgent cases and were given the lowest priority. In objective validation, scores significantly differed between the groups, indicating that the ranking results were identical. (3) For the first, second, and third scenarios, the proposed method exhibited an advantage over the benchmark method with percentages of 40%, 60%, and 100%, respectively. In conclusion, patients with the most and least urgent cases received the highest and lowest priority levels, respectively.

The Use of Social Networking Sites (SNSs) in Health Communication Campaigns: Review and Recommendations

The past decade has witnessed a rapid increase in the use of Social Networking Sites (SNSs) in health communication campaigns seeking to achieve an ambitious range of health-related impacts. This article provides a review of 40 studies and research protocols, with a focus on two key factors that differentiate SNSs from more traditional health communication approaches of the past. The first is the potential dualism between message sender and receiver, in which receivers become receiver-sources who forward and amplify the content and reach of health messages. The second is the potential dualism between message and message impact, in which the act of forwarding and modifying messages by receiver-sources itself becomes a measure of message impact. Each of these dualisms has implications for the design and evaluation of contemporary health communication campaigns. The review concludes with a series of observations and recommendations for future health communication research.

Based Real Time Remote Health Monitoring Systems: A Review on Patients Prioritization and Related "Big Data" Using Body Sensors information and Communication Technology

The growing worldwide population has increased the need for technologies, computerised software algorithms and smart devices that can monitor and assist patients anytime and anywhere and thus enable them to lead independent lives. The real-time remote monitoring of patients is an important issue in telemedicine. In the provision of healthcare services, patient prioritisation poses a significant challenge because of the complex decision-making process it involves when patients are considered 'big data'. To our knowledge, no study has highlighted the link between 'big data' characteristics and real-time remote healthcare monitoring in the patient prioritisation process, as well as the inherent challenges involved. Thus, we present comprehensive insights into the elements of big data characteristics according to the six 'Vs': volume, velocity, variety, veracity, value and variability. Each of these elements is presented and connected to a related part in the study of the connection between patient prioritisation and real-time remote healthcare monitoring systems. Then, we determine the weak points and recommend solutions as potential future work. This study makes the following contributions. (1) The link between big data characteristics and real-time remote healthcare monitoring in the patient prioritisation process is described. (2) The open issues and challenges for big data used in the patient prioritisation process are emphasised. (3) As a recommended solution, decision making using multiple criteria, such as vital signs and chief complaints, is utilised to prioritise the big data of patients with chronic diseases on the basis of the most urgent cases.

Mining Health Social Media with Sentiment Analysis

With the rapid development of the Internet, more and more users utilize health communities (known as forums) to find health-related information, share their medical stories and experiences, or interact with other people in the communities. In this paper, we propose a framework to analyze the user-generated contents in a health community. The proposed framework contains three phases. First, we extract medical terms, including conditions, symptoms, treatments, effectiveness and side effects to form a virtual document for each question in the community. Next, we modify Latent Dirichlet Allocation (LDA) by adding a weighted scheme, called conLDA, to cluster virtual documents with similar medical term distributions into a conditional topic (C-topic). Finally, we analyze the clustered C-topics by sentiment polarities, and physiological and psychological sentiment. The experiment results show that conLDA outperforms the original LDA, and can cluster relevant medical terms and relevant questions together. The C-topics clustered by conLDA are more thematic than those clustered by the original LDA. The results of sentiment analysis may provide a quick reference and valuable insights for patients, caregivers and doctors.

A security framework for nationwide health information exchange based on telehealth strategy

This study focuses on the situation of health information exchange (HIE) in the context of a nationwide network. It aims to create a security framework that can be implemented to ensure the safe transmission of health information across the boundaries of care providers in Malaysia and other countries. First, a critique of the major elements of nationwide health information networks is presented from the perspective of security, along with such topics as the importance of HIE, issues, and main approaches. Second, a systematic evaluation is conducted on the security solutions that can be utilized in the proposed nationwide network. Finally, a secure framework for health information transmission is proposed within a central cloud-based model, which is compatible with the Malaysian telehealth strategy. The outcome of this analysis indicates that a complete security framework for a global structure of HIE is yet to be defined and implemented. Our proposed framework represents such an endeavor and suggests specific techniques to achieve this goal.