Healthcare System Framework Research Articles

Information and resources VA health system leaders need to manage enrollment and retention for Post-9/11 veterans.

To understand Veterans Health Administration (VA) leaders' information and resource needs for managing post-9/11 Veterans' VA enrollment and retention. Interviews conducted from March-May 2022 of VA Medical Center (VAMC) leaders (N = 27) across 15 sites, using stratified sampling based on VAMC characteristics: enrollment rates, number of recently separated Veterans in catchment area, and state Medicaid expansion status. Interview questions were developed using Petersen et al.'s Factors Influencing Choice of Healthcare System framework as a guide. Interviews were transcribed verbatim, and two coders analyzed the interviews using Atlas.ti, a qualitative software program. Coders followed the qualitative coding philosophy developed by Crabtree and Miller, a process of developing codes for salient concepts as they are identified during the analysis process. Two coders analyzed 22% (N = 6) of the interviews and discussed and adjudicated any discrepancies. One coder independently coded the remainder of the interviews. Several key themes were identified regarding facilitators and barriers for VA enrollment including reputation for high-quality VA care, convenience of VA services, awareness of VA services and benefits, and VA mental health services. Nearly every VA leader actively used tools and data to understand enrollment and retention rates and sought to enroll and retain more Veterans. To improve the management of enrollment and retention, VA leaders would like data shared in an easily understandable format and the capability to share data between the VA and community healthcare systems. Enrollment and retention information is important for healthcare leaders to guide their health system decisions. Various tools are currently being used to try to understand the data. However, a multifunctional tool is needed to better aggregate the data to provide VA leadership with key information on Veterans' enrollment and retention.

A unified component-based data-driven framework to support interoperability in the healthcare systems

Healthcare organizations must urgently prioritize interoperability to enhance the quality of care they provide. However, achieving this collaboration comes with numerous challenges, including differing approaches, data formats, and standards, as well as concerns about privacy, security, technical complexity, and legal and regulatory issues. To tackle these challenges, we determined a set of interoperability solutions. We also developed a comprehensive, component-based, data-driven framework for healthcare systems. Our study's approach involved three main steps: first, conducting a literature review to gather interoperability requirements and solutions from online databases and grey literature; second, carrying out a qualitative study to develop a framework based on the review results and focus group discussions; and third, using the Delphi method to validate the framework with experts. We extracted information from 36 articles during the screening and assessment process. Based on the proposed framework, we organized the identified themes into various categories, including architecture, architecture components, standards, platforms, policies, data sources, consumers, applications, level of interoperability, healthcare facilities, and considerations. Experts believe that establishing a comprehensive architecture for launching interoperability between health information systems can greatly facilitate this process. All framework components (totaling 197) received unanimous approval. The landscape of healthcare delivery is shifting from a focus on diseases to a patient-centered, data-driven approach. There is a growing demand for personalized healthcare systems, which necessitates increased interoperability among all healthcare stakeholders, particularly when dealing with diverse types of data. Our framework is designed to facilitate the implementation of various types of interoperability in healthcare systems.

Skilled nursing facility staffing shortages: Sources, strategies, and impacts on staff who stayed.

To examine skilled nursing facility (SNF) staffing shortages across job roles during the COVID-19 pandemic. We aimed to capture the perspectives of leaders on the breadth of staffing shortages and their implications on staff that stayed throughout the pandemic in order to provide recommendations for policies and practices used to strengthen the SNF workforce moving forward. For this qualitative study, we engaged a purposive national sample of SNF leaders (n = 94) in one-on-one interviews between January 2021 and December 2022. Using purposive sampling (i.e., Centers for Medicare & Medicaid quality rating, region, ownership) to capture variation in SNF organizations, we conducted in-depth, semi-structured qualitative interviews, guided a priori by the Institute of Medicine's Model of Healthcare System Framework. Interviews were conducted via phone, audio-recorded, and transcribed. Rigorous rapid qualitative analysis was used to identify emergent themes, patterns, and relationships. SNF leaders consistently described staffing shortages spanning all job roles, including direct care (e.g., activities, nursing, social services), support services (e.g., laundry, food, environmental services), administrative staff, and leadership. Ascribed sources of shortages were multidimensional (e.g., competing salaries, family caregiving needs, burnout). The impact of shortages was felt by all staff that stayed. In addition to existing job duties, those remaining staff experienced re-distribution of essential day-to-day operational tasks (e.g., laundry) and allocation of new COVID-19 pandemic-related activities (e.g., screening). Cross-training was used to cover a wide range of job duties, including patient care. Policies are needed to support SNF staff across roles beyond direct care staff. These policies must address the system-wide drivers perpetuating staffing shortages (i.e., pay differentials, burnout) and leverage strategies (i.e., cross-training, job role flexibility) that emerged from the pandemic to ensure a sustainable SNF workforce that can meet patient needs.

Shsp: A Scalable Framework for Healthcare System Using Polygon Blockchain

Shsp: A Scalable Framework for Healthcare System Using Polygon Blockchain

When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare

Data-driven Machine and Deep Learning (ML/DL) is an emerging approach that uses medical data to build robust and accurate ML/DL models that can improve clinical decisions in some critical tasks ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$e.g.,$</tex-math></inline-formula> cancer diagnosis). However, ML/DL-based healthcare models still suffer from poor adoption due to the lack of realistic and recent medical data. The privacy nature of these medical datasets makes it difficult for clinicians and healthcare service providers, to share their sensitive data ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$i.e.,$</tex-math></inline-formula> Patient Health Records (PHR)). Thus, privacy-aware collaboration among clinicians and healthcare service providers is expected to become essential to build robust healthcare applications supported by next-generation networking (NGN) technologies, including Beyond sixth-generation (B6G) networks. In this paper, we design a new framework, called HealthFed, that leverages Federated Learning (FL) and blockchain technologies to enable privacy-preserving and distributed learning among multiple clinician collaborators. Specifically, HealthFed enables several distributed SDN-based domains, clinician collaborators, to securely collaborate in order to build robust healthcare ML-based models, while ensuring the privacy of each clinician participant. In addition, HealthFed ensures a secure aggregation of local model updates by leveraging a secure multiparty computation scheme ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$i.e.,$</tex-math></inline-formula> Secure Multiparty Computation (SMPC)). Furthermore, we design a novel blockchain-based scheme to facilitate/maintain the collaboration among clinician collaborators, in a fully decentralized, trustworthy, and flexible way. We conduct several experiments to evaluate HealthFed; in-depth experiments results using public Breast Cancer dataset show the efficiency of HealthFed, by not only ensuring the privacy of each collaborator's sensitive data, but also providing an accurate learning models, which makes HealthFed a promising framework for healthcare systems.

Challenges of methadone maintenance treatment decentralisation from Vietnamese primary care providers' perspectives.

Decentralising methadone maintenance treatment to primary care improves patients' access to care and their drug and HIV treatment outcomes. However, primary care providers (PCP), especially those working in limited-resource settings, are facing great challenges to provide quality methadone treatment. This study explores the challenges perceived by PCP providing methadone treatment at commune health centres in a mountainous region in Vietnam. We conducted in-depth interviews with 26 PCP who worked as program managers, physicians, counsellors, pharmacists and medication dispensing staff at the methadone programs of eight commune health centres in Dien Bien, Vietnam, in November and December 2019. We used the health-care system framework in developing the interview guides and in summarising data themes. Participants identified major challenges in providing methadone treatment in commune health centres at the individual, clinic and environmental levels. Individual-level challenges included a lack of confidence and motivation in providing methadone treatment. Clinic-level factors included inadequate human resources, lack of institutional support, insufficient technical support, lack of referral resources and additional support for patients. Environment-level factors comprised a lack of reasonable policies on financial support for providers at commune health centres for providing methadone treatment, lack of regulations and mechanisms to ensure providers' safety in case of potential violence by patients and to share responsibility for overdose during treatment. PCP in Vietnam faced multi-level challenges in providing quality methadone treatment. Supportive policies and additional resources are needed to ensure the effectiveness of the decentralisation program.

A Qualitative Assessment of the Essential Health and Nutrition Service Delivery in the Context of COVID-19 in Bangladesh: The Perspective of Divisional Directors.

Bangladesh suffered disruptions in the utilization of essential health and nutrition services (EHNS) during the COVID-19 pandemic. The magnitude of the pandemic has been documented, but little is known from the perspectives of health administrators. A rapid qualitative assessment of division-level capacity identified successes and bottlenecks in providing EHNS- and COVID-19-related services during the first months of the pandemic in Bangladesh. Semi-structured interviews were held with the Health and Family Planning Divisional Directors of the Ministry of Health and Family Welfare. The Primary Health Care System Framework guided the content analysis, focusing on (i) service delivery, (ii) communication and community outreach, and (iii) surveillance and service monitoring. Our findings identified low care seeking due to fears of getting infected and unawareness that EHNS were still available. Adaptations to telemedicine were highly heterogeneous between divisions, but collaboration with NGOs were fruitful in reinstating outreach activities. Guidelines were centered on COVID-19 information and less so on EHNS. The inflexibility of spending capacities at divisional and clinic levels hindered service provision. Misinformation and information voids were difficult to handle all around the country. Community health workers were useful for outreach communication. EHNS must be guaranteed during sanitary emergencies, and Bangladesh presented with both significant efforts and areas of opportunity for improvement.

Challenges to Scaling up Mhealth in Ghana. A Framework for Assessing the Health System

The promise for improving healthcare services has been confirmed by mobile device technology, but the decision-making process to acquire and use mHealth technologies on a scale is not directed. We apply a methodology to assess the potential and difficulties of efficient deployment of the mHealth at a scale in healthcare systems using the instance of Community Base Health Services (CBS) in Ghana. The advantage and difficulties of mHealth in community-based services in Ghana were examined in comprehensive research via a blend of key informant interviews, document reviews, and local project visits. The lessons gained from Ghana's local experience and elsewhere were based on a framework adjusted from 3 approaches to sustainable information and Communication Technology (ICT) evaluation. Four major characteristics of the system have been identified and evaluated: government stewardship and organizational, technical, and financial system. The prospects for successfully implementing mHealth in Ghana include the high penetration of mobile devices and a favorable e-health policy framework. Again, given a health system with a weal ICT setting and limited implementing ability, it is doubtful if the potential benefits of mHealth would benefit CBS through direct broad-scale adoption. The application of a healthcare system framework facilitates a systematic assessment of possible barriers to CBS growth in Ghana and is helpful for decision-making policy and practice for other small and medium enterprises.

Outlining the therapeutic itineraries of children with disabilities in the professional health care subsystem.

to identify the outlining of therapeutic itineraries of families of children with disabilities in the professional health care subsystem. qualitative research carried out in two specialized services in the state of Ceará, with 41 family members interviewed using the life path technique and reports submitted to descending hierarchical classification and similitude analysis, with the help of the IRaMuTeQ software and the theoretical framework of health care systems. the classes described the families' itineraries in five paths, related to faith, support structures, medical behaviors, professionals, and health services. The professional subsystem stood out as deficient in outlining the therapeutic itinerary for access to health care for children with disabilities, without promoting integration between services in the Care Network. the families' therapeutic itineraries showed homogeneous discourse with themes related to the care of professionals and spiritual aspects.

Introducing Cloud-Assisted Micro-Service-Based Software Development Framework for Healthcare Systems

In healthcare services, application development is considered the most complex and time-consuming phase. As it is difficult to plan and time-intense, it requires high maintenance. Healthcare applications need strict compliance and the scope of application is immense along with associates, classes in services, and classified system. Application designing in healthcare with the help of traditional approaches such as monolithic and service-oriented architecture (SOA) generate problems in different areas like service availability, remote access to services, service provisioning, scalability, healthcare systems integration with each other. That is why there is a need for less sophisticated and user-friendly healthcare systems, which are easy to plan and develop, inexpensive requirement maintenance, and agile testing. To overcome the aforesaid issues in the domain of healthcare application development, this paper develops a framework of micro services for the development of healthcare services using cloud computing infrastructure. Micro-service-based techniques provide lightly coupled and fine-grained methodology. With the use of micro services technique presented in this work, the efficiency, scalability, and performance are improved. In this research, an approach for development and deployment properly in the cloud for healthcare applications is developed. Thus, it contributes to the system design approach and system analysis. Quantitative and qualitative results are reported showing the advantages of micro services approach used.

Service Level Agreement Based Secured Data Analytics Framework for Healthcare Systems

Many physical objects are connected to the internet in this modern day to make things easier to work based on the convenience of the user, which reduces human involvement with the help of Internet of Things (IoT) technology.This aids in the capture of large amounts of data, the interchange of information via the internet, and the remote operation of machines. IoT health data is typically in the form of big data and is frequently coupled with the cloud for secure storage. Cloud technology provides a wide range of technological services via the internet, and it is a highly interoperable and on-demand network for a wide range of computing resources. The Service Level Agreement (SLA) is made between the cloud and the patient, and it outlines the services supplied as well as the level of security provided to the user. For fulfilling service, the deployed external cloud has challenges with load balancing and work scheduling. Furthermore, the gathered health data must be effectively processed by medical practitioners. To solve this issue, a Secure Cluster Naive Bayes (CNB) framework is proposed, both with and without Dimensionality Reduction. To preserve its anonymity, the obtained data is hashed and stored in the cloud using the blockchain technology. SLA sessions are organized to prioritize patient data for decryption and prediction. At the doctor’s end, the decrypted data is first filtered and dimensionally reduced before being clustered using a dual K-means clustering technique and classified using the Naive Bayes algorithm. The web-based graphical user interface server is responsible for connecting the IoT device, the cloud, and the doctor. The security performance of the DRCNB and CNB frameworks is evaluated using block chain characteristics, the frequency of SLA violations, and processing and execution time. The DRCNB framework is 91.1% accurate, while the CNB model is 80.73% accurate, making it more accurate than previous models. The new models exceed the prior ones in terms of both security and prediction performance.

Layered Architecture for Internet of Things-based Healthcare System: A Systematic Literature Review

Internet of Things (IoT), known as a new paradigm, has shown to have a significant role in healthcare domains including remote vital sign monitoring systems, physical activity tracking, early disease diagnosis, and prevention of disease risks. Therefore, designing an integrated healthcare system based on Internet of Things is highly dependent on designing a layered architecture pattern. However, there are no comprehensive studies on Internet of Things layered architecture in the healthcare industry. The purpose of this study was to identify and scrutinize different types of layered architecture of Internet of Things in healthcare in terms of functions, and technologies. We evaluated studies proposing layered architecture of Internet of Things based on security aspects (security requirements and solutions). A systematic literature review was conducted by searching IEEE, PubMed, Scopus and Web of Science between 2005 and 2019. We were able to find 47 academic studies based on inclusion and exclusion criteria. We systematically reviewed applied functions and technologies and categorized them into three main layers namely, the perception, network, and application layers. This study also presented a comprehensive classification of sensor types. Only 28 out of 47 studies proposing Internet of Things architecture addressed security aspects among which privacy, authentication, and access control, confidentiality, and integrity had the highest rank. The layered architecture of Internet of Things is needed to provide an integrated framework for healthcare system, make better communication, and enhance the information management process. We suggest several potential solutions for future research directions according to technical, management, and security challenges

Privacy-preserving Decentralized Learning Framework for Healthcare System

Clinical trials and drug discovery would not be effective without the collaboration of institutions. Earlier, it has been at the cost of individual’s privacy. Several pacts and compliances have been enforced to avoid data breaches. The existing schemes collect the participant’s data to a central repository for learning predictions as the collaboration is indispensable for research advances. The current COVID pandemic has put a question mark on our existing setup where the existing data repository has proved to be obsolete. There is a need for contemporary data collection, processing, and learning. The smartphones and devices held by the last person of the society have also made them a potential contributor. It demands to design a distributed and decentralized Collaborative Learning system that would make the knowledge inference from every data point. Federated Learning [21], proposed by Google, brings the concept of in-place model training by keeping the data intact to the device. Though it is privacy-preserving in nature, however, it is susceptible to inference, poisoning, and Sybil attacks. Blockchain is a decentralized programming paradigm that provides a broader control of the system, making it attack resistant. It poses challenges of high computing power, storage, and latency. These emerging technologies can contribute to the desired learning system and motivate them to address their security and efficiency issues. This article systematizes the security issues in Federated Learning, its corresponding mitigation strategies, and Blockchain’s challenges. Further, a Blockchain-based Federated Learning architecture with two layers of participation is presented, which improves the global model accuracy and guarantees participant’s privacy. It leverages the channel mechanism of Blockchain for parallel model training and distribution. It facilitates establishing decentralized trust between the participants and the gateways using the Blockchain, which helps to have only honest participants.

A bio-inspired privacy-preserving framework for healthcare systems

Wireless computing has revolutionized our life with the technological advancement from the traditional networking into a new epoch for communication in ad hoc decorum. An energy efficient network of sensors based on wireless communication and networking principles can enhance the effectiveness of computing during unpredictable circumstances. If a computable required resource is readily available within the reachable region and it is identified to be idle and it is ready to share the corresponding information from its end without affecting the normal behavior of the device or the node, then there exists an opportunity to utilize those resources for computing. Opportunistic computing has a great potential of growth in the field of wireless ad hoc network computing. In traditional network computing technology, mobile computing, grid computing, distributed computing, ubiquitous computing and cloud computing, formerly ensues the communication with minimal resources currently available at the terminal point. This paper proposes a novel framework for an effective utilization of sharable resources, which are available within the reachable region, by creating an opportunity to frame an opportunistic computing while preserving the user’s privacy. The proposed framework adopts a bio-inspired technique for identifying and collecting resources information, and thereby recognizes which resource is ready to participate in the opportunistic computing. Experimental results of a system that implements the bio-inspired technique along with the natural behavior of the bee colony approach was analyzed and found that the proposed system shows comparatively high performance in terms of computation resource searching, identifying, emergency data transfer, and participative node privacy preserving.

Establishing a learning healthcare system to improve health outcomes for people with epilepsy

ObjectiveTo describe the organization of the Epilepsy Learning Healthcare System (ELHS), a network that aims to improve care outcomes for people with epilepsy (PWE). Materials and MethodsPatients and family partners, providers, researchers, epidemiologists, and other leaders collaborated to recruit epilepsy centers and community services organizations into a novel learning network. A multidisciplinary Coordinating Committee developed ELHS governance and organizational structure, including four key planning Cores (Community, Clinical, Quality Improvement, and Data). Through Quality Improvement (QI) methodology grounded in the Institute for Healthcare Improvement (IHI) model, including iterative Plan-Do-Study-Act (PDSA) rapid learning cycles and other learning and sharing sessions, ELHS equipped epilepsy centers and community organizations with tools to standardize, measure, share, and improve key aspects of epilepsy care. The initial learning cycles addressed provider documentation of seizure frequency and type, and also screening for medication adherence barriers. Rapid learning cycles have been carried out on these initial measures in both clinical centers and community-based settings. Additional key measures have been defined for quality of life, screening, and treatment for mental health and behavioral comorbidities, transition from pediatric to adult care, counseling for women and girls living with epilepsy, referral for specialty care, and prevention and treatment of seizure clusters and status epilepticus. ResultsIt is feasible to adopt a learning healthcare system framework in epilepsy centers and community services organizations. Through structured collaboration between epilepsy care providers, community support organizations, PWE, and their families/caregivers we have identified new opportunities to improve outcomes that are not available in traditional care models.

Privacy and security framework for health care systems in IoT: originating at architecture through application

The development of wearable medical devices with sensors has been triggered the health care system by the augmentation of IoT. Health monitoring system in the present scenario elicited and channeled the advancement of medical arena. For tracking health data in the field of IoT, a considerable amount of sensors are on deck right away. On the other hand, the data engender by IoT devices have to face multitudinous security outcomes. In order to tackle the same, some of the personal health monitoring systems still face an umpteen data insecurity. The electronic medical health data generated by IoT are encrypted and transferred to the cloud storage system. This aims to ensure the patient’s data security as well as to access control of the normal situation. Therefore the indulgent suffering from illness has to be served by a high quality assured services in a secure platform. It is been generated not only from the wearable device for getting health data but from multiple parameters collected from different agents also. The proposed model provides a secure architecture and an encrypted MEHR shared between all the actors are incorporated well in the system, and also a mobile application developed for the same will make the user more handy. A broad comparison and simulation tested results with the proposed algorithms make it more decisive and productive.

The Understanding of Dignity Among In-Hospital Patients Living With Incurable Esophageal Cancer.

Dignity is an inherent value in palliative care, but understanding dignity among people living with and hospitalized for incurable esophageal cancer has not been explored. The aim of this study was to empirically explore the meaning of dignity in people hospitalized with incurable esophageal cancer. A qualitative hermeneutic approach, inspired by Gadamer, guided the research process and interpretation of the transcribed interviews. Eighteen patients participated in the study. The meaning of dignity was revealed as reverential response in care relationships and eating as an undignifying activity. A balance of the healthcare system's framework with the lifeworld of the patient was significant in preserving dignity and gave patients a sense of reverent response. Patients were unable to eat ordinary daily meals, which affected their perception of own body and identity, including interactions with others. The resulting bodily changes and social consequences were of crucial importance to the perceived dignity. A dialogical and understanding approach is significant in making the patient feel worthy, consequently helping to uphold a sense of dignity. The changing and decaying body due to eating difficulties bears witness to illness, altering the individual's sense of self, in turn threatening the dignity of identity. The care should be based on a reverential response based on the patients' lifeworld. In doing so, storytelling might be a way. Palliative care for these people needs to stress that patients share other aspects of life that is not totally dominated by their illness, inability to eat, and unrecognizable body.

Rational perspectives on risk and certainty for dentistry during the COVID-19 pandemic

Rational perspectives on risk and certainty for dentistry during the COVID-19 pandemic

The EMIRATES Framework: Emergency Management Integrated Roadmap Aimed Towards Every Healthcare System A conceptual framework

Healthcare systems play a key role in the response to everything from day-to-day events to overwhelming disasters. There are common challenges worldwide which include the presence of multiple players, a lack of clarity with regard to the chain of command, the absence of important components to make the system work, and a lack of specialized training and education. Given these challenges, the ability to respond adequately requires an integrated emergency management system. Several countries may have different components of the emergency services but occasionally not well integrated. The Emergency Management Integrated Roadmap Aimed Toward Every healthcare System framework is a simplified conceptual framework to help the healthcare decision-makers in different systems to plan the approach to any day-to-day emergencies or disasters with a structured system that can be customized further according to their needs.

HOUT-24. CHALLENGES AND SUCCESSES IN THE GLOBAL REIMBURSEMENT OF A BREAKTHROUGH MEDICAL TECHNOLOGY FOR TREATMENT OF GLIOBLASTOMA MULTIFORME

Abstract OBJECTIVE To highlight the challenges and differences regarding the reimbursement of breakthrough medical device technologies, by example of a novel cancer treatment using Tumor Treating Fields (TTFields). BACKGROUND TTFields is a breakthrough cancer treatment modality. The treatment is delivered through a medical device with the brand name Optune. Its efficacy was first established in glioblastoma multiforme. Reimbursement challenges for medical devices vary by. Common issues for novel device technologies like Optune however, are the difficulties to classify the treatment in the respective country’s health care system with the ability to develop a value-based reimbursement pathway. MATERIALS/METHODS We reviewed reimbursement decisions of payers for Optune from a total of 6 countries. We assessed their classification of the device, the flexibility of their health care framework and how Optune was implemented. RESULTS All 6 countries implemented Optune in their respective health care systems. 3 countries consider Optune to be an outpatient treatment delivered by durable medical equipment, one country classifies Optune as a hospital dispensed medical device, one country classifies Optune as an extended medical service and the last country as rehab services.The differential fitting of Optune in the respective country’s health care system allows each of the countries to take a positive, value-based reimbursement decision for this breakthrough technology. Generally, the speed of payer adoption for Optune varied based on the ability to assess the clinical data, rather than the more technical aspects of how the device is delivered to patients. CONCLUSIONS Classification of a breakthrough technology like Optune in the traditional framework of health care systems is challenging and handled differently by each country. Countries with a flexible approach regarding this novel oncological treatment modality however, were able to reach positive reimbursement decisions by classifying Optune in the category most suitable in the respective country’s health care system.