Digital Health Systems Research Articles

Sustaining digital health systems through key stakeholders engagement: a critical systems heuristics perspective

Abstract Evaluating the sustainability of a digital health system implemented in large-scale hospitals in a country is a complex scenario because it must obtain the sustainability requirements of a wide range of stakeholder groups consisting of thousands of people. Stakeholder participation in information system projects is becoming increasingly important for any organization seeking operational excellence. A comprehensive stakeholder analysis necessitates determining who these individuals are and how they relate to an organization. Based on Critical Systems Heuristics (CSH), this study presented a sustainability evaluation of a hospital digital health system called the Hospital Health Information Management System in Sri Lanka. The CSH perspective is recognized as a philosophical framework that uses boundary critiques to define the boundaries of social system design, considering the people involved and affected by it. The authors see this sustainability evaluation as an opportunity to identify and address sustainability gaps in the digital health system, with the goal of improving sustainability. It is argued that assessing the sustainability of a digital health system requires a holistic approach that includes obtaining multiple stakeholders’ perspectives informed by Ulrich’s concept of boundary consideration (boundary critique). CSH theoretical concepts were discovered to be applicable in the sustainability evaluation of digital health systems with diverse stakeholders. The inclusion of CSH would improve the efficacy of sustainability assessment by gaining multiple stakeholder perspectives from both the involved and affected categories.

Preventing Organizational Failures in the Digital Health Systems. Insights from Tuscany Regional Health System

The literature on analyzing organizations has devoted more to positive than failed cases. Nevertheless, the "dark side" represents one of the constituent elements of everyday organizational practices. Given these considerations, the paper focuses on the possible perverse effects, organizational myopias, and unexpected outcomes following "digital health" implementation. Through the Tuscany Regional Health System case study and qualitative methodologies based on in-depth interviews, we want to anticipate the critical issues and shortsightedness that could plausibly affect the Italian National Health Service.

Future Care Pathways – A report from the 1st workshop of the EHC Think Tank Workstream on Future Care Pathways

Abstract Introduction A care pathway is defined as “a complex intervention for the mutual decision-making and organisation of care processes for a well-defined group of patients during a well-defined period.” The European Haemophilia Consortium (EHC) established a Think Tank Workstream on Future Care Pathways to identify and address key challenges in shaping future pathways that meet the needs of people with rare diseases while remaining practicable and affordable to healthcare providers in countries with different budgets and resources. This workstream is particularly timely as the introduction of innovative therapies is adding to the complexity of care pathways in some rare conditions. Identifying key challenges During the first virtual workshop of the Future Care Pathways Workstream on 14 February 2023, stakeholders, including healthcare providers, patient groups, researchers, and industry representatives, agreed to focus on four workable themes/challenges: 1. Prioritisation (cost and evidence); 2. Agreeing on a baseline; 3. Digital health; 4. Fragmentation of healthcare. Summary Prioritisation relates to economic and financial challenges in justifying the optimisation of a care pathway for a rare disease within the context of other healthcare priorities. Currently, there is too much emphasis on costs to healthcare systems, and not enough on real-life patient experience and indirect costs to patients and their families. Innovation in pathways is generally considered unaffordable, and cost-effectiveness models are difficult to apply to rare diseases. Agreeing on a baseline for a minimum standard of care in a pathway should take into account variability in patient needs, agency and healthcare system resources. A baseline needs to be agreed upon for each stage of a pathway: first clinical presentation, diagnosis, treatment, and monitoring and follow-up. Lack of awareness, gender and resource inequalities and gaps in evidence are among the issues that need to be addressed. Digital health holds promise but also brings challenges for future care pathways and must be considered from the viewpoint of all major stakeholders: patients, healthcare providers, tech companies and payers. Digital health systems are often developed in silos and do not allow for effective integration and sharing of data. Collaboration from the beginning is essential to the successful integration of digital tool as in healthcare. Fragmentation of healthcare can arise because people with rare diseases may access care pathways through multiple entry points in primary and secondary care, and they may not experience holistic care that takes account of all their needs. Poor communication at multiple levels (e.g. between clinical stakeholders and between clinicians and patients) is a common problem leading to inadequate treatment and care. Fragmentation may also arise when care pathways do not allow for a patient’s evolving needs when he/she is already on a pathway.

A digital innovation typology: Navigating the complexity of emerging technologies to negotiate health systems research with young people.

This study aims to explore young people's perspectives of emerging technologies and health systems research in an adolescent health community of practice. The context of this integrated knowledge translation study is the Wellbeing Health & Youth Centre of Research Excellence in Adolescent Health. A theory-building, non-systematic review was conducted to examine the concepts and interrelationships of emerging technologies associated with digital innovation and health systems. This typology informed the design of an online workshop with young people to explore their views, concerns, and ideas about health systems research. A digital innovation typology was identified to differentiate and explain emerging technology concepts and interrelationships that can be applied to the health systems context. Aligned with this typology, youth perspectives about digital health challenges and opportunities were identified to support future research, policy, and practice. The integrated findings from this study can assist the navigation of complex emerging technologies, and the negotiation of equitable health systems research, between youth and adult stakeholders. Further, with these typology-related resources, mutual learning and the public involvement of young people in health systems research and priority setting agendas can be supported.

Community Medicine in Ayushman Bharat Digital Mission: The Hidden Cornerstone.

India has launched Ayushman Bharat Digital Mission (ABDM), to provide an integrated digital health infrastructure. The success of digital health systems lies in their ability to achieve universal healthcare and incorporate all levels of disease prevention. The objective of this study was to develop an expert consensus on how Community Medicine (Preventive and Social Medicine) can be integrated into ABDM. A total of 17 and 15 participants, who were Community Medicine professionals with more than 10 years experience in the Public Health Sector and/or Medical Education in various parts of India, participated in round 1 and 2 of this Delphi study respectively. The study explored three domains: 1. Advantages and challenges of ABDM, and possible solutions; 2. Intersectoral convergence in Unified Health Interface (UHI) and 3. Way ahead in medical education and research. Participants envisaged improved accessibility, affordability, and quality of care due to ABDM. However, awareness generation, reaching out to marginalized populations, human resource constraints, financial sustainability, and data security issues were anticipated challenges. The study identified plausible solutions addressing six broad challenges of ABDM and classified them based on the priority of implementation. Participants listed out nine key roles of Community Medicine professionals in digital health. The Study identified about 95 stakeholders who play direct and indirect roles in public health and can be connected to the general public through the Unified Health Interface of ABDM. Further, the study explored the future of medical education and research in the digital era. The Study contributes to broadening the scope of India's digital health mission, with elements of Community Medicine in its cornerstone.

Digital health systems: SMART-system for remote support of hybrid E-rehabilitation services and activities

The top-priority challenges were faced by the medical rehabilitation system in Ukraine. Particularly important tasks include, first of all, the rehabilitation of patients who have recovered from COVID-19 disease and people with Combat stress reaction. This fact is well understood both by the society and the leadership of the Ministry of Health of Ukraine, which is creating a special working group on this problem. Ukraine has a system of medical and prophylactic institutions designed for psychological and physical rehabilitation of military personnel; these use modern rehabilitation technologies. However, long-term rehabilitation in such centers is not available to everyone. Therefore, the use of telerehabilitation technology for patients with post-traumatic stress disorder and similar disorders in com- bination with a means of objective control of the functional state is extremely important. One of the most effective solutions in medical rehabilitation assistance is remote patient / person-centered rehabilitation. Rehabilitation also needs effective methods for the "Physical therapist – Patient – Multidisciplinary team" system, including the statistical processing of large volumes of data. Therefore, along with the traditional means of rehabilitation, as part of the "Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)" in this paper, we introduce and define: the revised and completed basic concepts of the hybrid e-rehabilitation notion and its fundamental foundations; the formalization concept of the new Smart-system for remote support of hybrid e-rehabilitation services and activities; and the methodological foundations for the use of services (UkrVectōrēs and vHealth) of the remote Patient / Person- centered Smart-system. The software implementation of the services of the Smart-system has been developed.

Strengthening public health systems in China

Strengthening public health systems in China

Impact of Artificial Intelligence on the Automation of Digital Health System

Automating digital systems in healthcare plays a significant role in transforming the quality-of-care services delivered to patients across the board. This role is anticipated to be accomplished by the development and implementation of artificial intelligence in healthcare which has the potential to impact the provision of healthcare services. This paper sought to investigate the impact of adopting and implementing artificial intelligence on the automation of digital health systems within the different levels of healthcare. The general objective of the research study was to investigate the impact of artificial intelligence in the automation of digital health systems. The specific goals were to understand the concept of artificial intelligence and how it automates digital strategies, to determine the AI systems that have been developed and implemented in the healthcare systems, to establish the factors that influence the adoption of AI in healthcare, and to find out the outcomes of implementing AI in digital health systems. The research employed the descriptive research design. The study population included healthcare workers, policymakers, IT specialists, and management teams in the healthcare sector in the State of Kentucky. The sampling technique for the study was the purposive sampling technique. The study collected data using semi-structured interviews administered through Google Teams and Zoom. Data analysis was analyzed using the computer-assisted software for analyzing qualitative data, NVivo. The findings were that AI as a technological concept has the potential to impact the automation of digital health systems and is key to automating health services such as the diagnosis and treatment of illnesses and management of claims and payments. The study recommended that policy supports the application of artificial intelligence in healthcare, thus enabling the automation of several healthcare services and thus improving the delivery of care.

Digital health systems strengthening in Africa for rapid response to COVID-19.

The COVID-19 pandemic has painfully exposed the constraints of fragile health systems in low- and middle-income countries, where global containment measures largely set by high-income countries resulted in disproportionate collateral damage. In Africa, a shift is urgently needed from emergency response to structural health systems strengthening efforts, which requires coordinated interventions to increase access, efficiency, quality, transparency, equity, and flexibility of health services. We postulate that rapid digitalization of health interventions is a key way forward to increase resilience of African health systems to epidemic challenges. In this paper we describe how PharmAccess' ongoing digital health system interventions in Africa were rapidly customized to respond to COVID-19. We describe how we developed: a COVID-19 App for healthcare providers used by more than 1,000 healthcare facilities in 15 African countries from May-November 2020; digital loans to support private healthcare providers with USD 20 million disbursed to healthcare facilities impacted by COVID-19 in Kenya; a customized Dutch mobile COVID-19 triage App with 4,500 users in Ghana; digital diaries to track COVID-19 impacts on household expenditures and healthcare utilization; a public-private partnership for real-time assessment of COVID-19 diagnostics in West-Kenya; and an expanded mobile phone-based maternal and child-care bundle to include COVID-19 adapted services. We also discuss the challenges we faced, the lessons learned, the impact of these interventions on the local healthcare system, and the implications of our findings for policy-making. Digital interventions bring efficiency due to their flexibility and timeliness, allowing co-creation, targeting, and rapid policy decisions through bottom-up approaches. COVID-19 digital innovations allowed for cross-pollinating the interests of patients, providers, payers, and policy-makers in challenging times, showing how such approaches can pave the way to universal health coverage and resilient healthcare systems in Africa.

Real-world data for precision public health of noncommunicable diseases: a scoping review

BackgroundGlobal public health action to address noncommunicable diseases (NCDs) requires new approaches. NCDs are primarily prevented and managed in the community where there is little investment in digital health systems and analytics; this has created a data chasm and relatively silent burden of disease. The nascent but rapidly emerging area of precision public health offers exciting new opportunities to transform our approach to NCD prevention. Precision public health uses routinely collected real-world data on determinants of health (social, environmental, behavioural, biomedical and commercial) to inform precision decision-making, interventions and policy based on social position, equity and disease risk, and continuously monitors outcomes – the right intervention for the right population at the right time. This scoping review aims to identify global exemplars of precision public health and the data sources and methods of their aggregation/application to NCD prevention.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was followed. Six databases were systematically searched for articles published until February 2021. Articles were included if they described digital aggregation of real-world data and ‘traditional’ data for applied community, population or public health management of NCDs. Real-world data was defined as routinely collected (1) Clinical, Medication and Family History (2) Claims/Billing (3) Mobile Health (4) Environmental (5) Social media (6) Molecular profiling (7) Patient-centred (e.g., personal health record). Results were analysed descriptively and mapped according to the three horizons framework for digital health transformation.ResultsSix studies were included. Studies developed population health surveillance methods and tools using diverse real-world data (e.g., electronic health records and health insurance providers) and traditional data (e.g., Census and administrative databases) for precision surveillance of 28 NCDs. Population health analytics were applied consistently with descriptive, geospatial and temporal functions. Evidence of using surveillance tools to create precision public health models of care or improve policy and practice decisions was unclear.ConclusionsApplications of real-world data and designed data to address NCDs are emerging with greater precision. Digital transformation of the public health sector must be accelerated to create an efficient and sustainable predict-prevent healthcare system.

Health information exchange policy and standards for digital health systems in africa: A systematic review.

Lack of interoperability and integration between heterogeneous health systems is a big challenge to realize the potential benefits of eHealth. To best move from siloed applications to interoperable eHealth solutions, health information exchange (HIE) policy and standards are necessary to be established. However, there is no comprehensive evidence on the current status of HIE policy and standards on the African continent. Therefore, this paper aimed to systematically review the status of HIE policy and standards which are currently in practice in Africa. A systematic search of the literature was conducted from Medical Literature Analysis and Retrieval System Online (MEDLINE), Scopus, Web of Science, and Excerpta Medica Database (EMBASE), and a total of 32 papers (21 strategic documents and 11 peer-reviewed papers) were selected based on predefined criteria for synthesis. Results revealed that African countries have paid attention to the development, improvement, adoption, and implementation of HIE architecture for interoperability and standards. Synthetic and semantic interoperability standards were identified for the implementation of HIE in Africa. Based on this comprehensive review, we recommend that comprehensive interoperable technical standards should be set at each national level and should be guided by appropriate governance and legal frameworks, data ownership and use agreements, and health data privacy and security guidelines. On top of the policy issues, there is a need to identify a set of standards (health system standards, communication, messaging standards, terminology/vocabulary standards, patient profile standards, privacy and security, and risk assessment) and implement them throughout all levels of the health system. On top of this, we recommend that the Africa Union (AU) and regional bodies provide the necessary human resource and high-level technical support to African countries to implement HIE policy and standards. To realize the full potential of eHealth in the continent, it is recommended that African countries need to have a common HIE policy, interoperable technical standards, and health data privacy and security guidelines. Currently, there is an ongoing effort by the Africa Centres for Disease Control and Prevention (Africa CDC) towards promoting HIE on the continent. A task force has been established from Africa CDC, Health Information Service Provider (HISP) partners, and African and global HIE subject matter experts to provide expertise and guidance in the development of AU policy and standards for HIE. Although the work is still ongoing, the African Union shall continue to support the implementation of HIE policy and standards in the continent. The authors of this review are currently working under the umbrella of the African Union to develop the HIE policy and standard to be endorsed by the head of states of the Africa Union. As a follow-up publication to this, the result will be published in mid-2022.

A NOVEL, DEEP-LEARNING ALGORITHM TO DETECT COUGH USING COMPUTER-AIDED AUSCULTATION (COUGH-CAAE)

A NOVEL, DEEP-LEARNING ALGORITHM TO DETECT COUGH USING COMPUTER-AIDED AUSCULTATION (COUGH-CAAE)

Digital health systems-let's talk about sex (and gender).

Historically, within digital health information systems, sex and gender have been conflated as a single concept and often have been limited to a binary answer. This has led to inappropriate care, erosion of client trust and avoidance of the healthcare system. Health leaders can improve care for all clients with technical and clinical information practice initiatives. While procurement processes could require digital health systems that utilize modern Gender, Sex, and Sexual Orientation (GSSO) terminology, for most health leaders, technical initiatives will focus on modernizing existing systems to the maximum extent possible. Terminology updates may not be immediately visible to clients, but providing the correct information to clinicians will support respectful client encounters. Simultaneously, clinical information practice initiatives can directly affect clinical encounters. Change management strategies need to include all levels of employees and redesign tools and workflows to support modernized information handling practices.

Remote Monitoring of COVID-19 Patients Using Multisensor Body Area Network Innovative System.

As of late 2019, the COVID19 pandemic has been causing huge concern around the world. Such a pandemic posed serious threats to public safety, the well-being of healthcare workers, and the overall health of the population. If automation can be implemented in healthcare systems, patients could be better cared for and health industries could be less burdened. To combat such challenges, e-health requires apps and intelligent systems. Using WBAN sensors and networks, a doctor or medical professional can advise patients on the best course of action. Patients' fitness could be assessed using WBAN sensors without interfering with their daily activities. When designing a monitoring system, system performance reliability for competent healthcare is critical. Existing research has failed to create a large device capable of handling a large network or to improve WBAN topologies for fast transmitting and receiving patient data. As a result, in this research, we create a multisensor WBAN (MSWBAN) intelligent system for transmitting and receiving critical patient data. To gather information from all cluster nodes and send it to multisensor WBAN, a novel additive distance-threshold routing protocol (ADTRP) is proposed. In small networks where data are managed by the transmitting node and the best data route is determined, this protocol has less redundancy. An edge-cutting-based routing optimization (ES-EC-R ES-EC-RO) is used to find the best route. The Trouped blowfish MD5 (TB-MD5) algorithm is used to encrypt and decrypt data, and the encrypted data are stored in a cloud database for security. The performance metrics of our proposed model are compared to current techniques for the best results. End-to-end latency is 63 ms, packet delivery is 95%, security is 95.7%, and throughput is 9120 bps, according to the results. The purpose of this article is to encourage engineers and front-line workers to develop digital health systems for tracking and controlling virus outbreaks.

The requirements for performing artificial-intelligence-related research and model development.

Artificial intelligence research in health care has undergone tremendous growth in the last several years thanks to the explosion of digital health care data and systems that can leverage large amounts of data to learn patterns that can be applied to clinical tasks. In addition, given broad acceleration in machine learning across industries like transportation, media and commerce, there has been a significant growth in demand for machine-learning practitioners such as engineers and data scientists, who have skill sets that can be applied to health care use cases but who simultaneously lack important health care domain expertise. The purpose of this paper is to discuss the requirements of building an artificial-intelligence research enterprise including the research team, technical software/hardware, and procurement and curation of health care data.

Classification of Parkinson’s disease and its stages using machine learning

As digital health technology becomes more pervasive, machine learning (ML) provides a robust way to analyze and interpret the myriad of collected features. The purpose of this preliminary work was to use ML classification to assess the benefits and relevance of neurocognitive features both tablet-based assessments and self-reported metrics, as they relate to Parkinson’s Disease (PD) and its stages [Hoehn and Yahr (H&Y) Stages 1–5]. Further, this work aims to compare perceived versus sensor-based neurocognitive abilities. In this study, 75 participants (n = 50 PD; n = 25 control) completed 14 tablet-based neurocognitive functional tests (e.g., motor, memory, speech, executive, and multifunction), functional movement assessments (e.g., Berg Balance Scale), and standardized health questionnaires (e.g., PDQ-39). Decision tree classification of sensor-based features allowed for the discrimination of PD from healthy controls with an accuracy of 92.6%, and early and advanced stages of PD with an accuracy of 73.7%; compared to the current gold standard tools [e.g., standardized health questionnaires (78.3% accuracy) and functional movement assessments (70% accuracy)]. Significant features were also identified using decision tree classification. Device magnitude of acceleration was significant in 12 of 14 tests (85.7%), regardless of test type. For classification between diagnosed and control populations, 17 motor (e.g., device magnitude of acceleration), 9 accuracy (e.g., number of correct/incorrect interactions), and 8 timing features (e.g., time to between interactions) were significant. For classification between early (H&Y Stages 1 and 2) and advanced (H&Y Stages 3, 4, and 5) stages of PD, 7 motor, 12 accuracy, and 14 timing features were significant. Finally, this work depicts that perceived functionality of individuals with PD differed from sensor-based functionalities. In early-stage PD was shown to be 21.6% lower than sensor-based scores with notable perceived deficits in memory and executive function. However, individuals in advanced stages had elevated perceptions (1.57x) for executive and behavioral functions compared to early-stage populations. Machine learning in digital health systems allows for a more comprehensive understanding of neurodegenerative diseases and their stages and may also depict new features that influence the ways digital health technology should be configured.

Digital Health and Future of Healthcare in Pakistan

In today's fast paced world, the use of Information Technology (IT) in dispensing quality healthcare forms a cornerstone for the development of any health system. While the standard of Medical Education and training is quickly gaining impetus within Pakistan, we are severely lacking in use of digital platforms and electronic records to aid the process of healthcare delivery. There's no dearth of talent in Pakistan; in the field of Medicine or IT. However, there is a considerable lack in the understanding of how IT can revolutionize healthcare delivery. We see that there is an urgent need for the governmental institutions and the private sector medical institutions to recognize the importance of digital health in making medical practice more effective, efficient and error proof; so that Pakistan can shake off the burden of a centuries old and obsolete system of healthcare delivery. Here, we propose our roadmap vision for development of digital health systems in Pakistan and propose basic initiatives that must be taken at the grass roots level to expedite this process.

Artificial Intelligence: Applications in Healthcare Industry

Artificial intelligence (AI) is becoming a core part of the digital health systems to shape and support modern medicine. The situations such as pandemic COVID-19 pressing health systems to consider technology, such as artificial intelligence powered clinical decision support for faster and more informed decisions. AI utilises machine learning models to search medical data and uncover insights to improve health outcomes and patient experiences. AI is mainly used for clinical decision support and imaging analysis. Clinical decision support tools help the physician to take decisions about treatments, medications, physical and psychological health and other patient needs by providing quick access to information or research that's relevant to their patient. In medical imaging, AI tools are used to analyze CT scans, X-rays, MRIs and other images/ findings that a human radiologist might miss. Many healthcare organizations around the world started field-testing new AI-supported technologies to overcome the challenges like COVID-19 pandemic created. Various healthcare applications with AI are presented in this article.

Middle East and North African Health Informatics Association (MENAHIA)

The region of the Middle East and North Africa (MENA) is diverse and retains a superior growth potential. It benefits from a privileged geographical location with big markets, a young and growing educated population, and competitive advantages in several industries. Regardless of their differences, countries face shared concerns, most notably in health. In response to the COVID-19 pandemic, MENA countries enact reforms to create a more robust and inclusive digital health systems to increase growth, development, and integrity. Throughout the coordinated containment and mitigation efforts, most of the countries have integrated digital technologies into the health systems. These procedures include digital government initiatives, the introduction of digital health training courses, live video surgeries and virtual patient monitoring, rural and remote telemedicine programs, and the development of a national electronic health records (EHR) system. Each country took necessary actions to address equity, literacy, and development of resilient health systems. The nine featured countries in this report illustrate the diversity among the MENA region and account for major opportunities and achievements as well as promises and challenges that “digital health” presents for its populations.

The Efficiency of Internet Base Healthcare System in Gastroenterological diseases: An Updated Systematic Review

Digital health systems such as tablet devices, smartphones, and online websites, are swiftly transforming the practice of medical science and reshaping health care approaches. A PRISMA guidelines-based systematic review was conducted using research databases (PubMed, Google Scholar, and Web of Science) to identify the applications and fill the literature gap in Gastroenterological disorders. A total of 212 articles were searched, excluding duplicate records, sixty nine articles were founded out of which only fifteen were selected using specific inclusion and exclusion criteria. Risk of a bias assessment tool called ROBVIS 2 is used to examine the risk of predisposition and precision of all the fifteen studies included. Most of the patients in these trials were females, educated, and have inflammatory bowel diseases. These clinical studies concentrated on Ulcerative colitis (n=5), Crohn's disease (n=4), and inflammatory bowel disease (n=6) with feedback of mostly 3 months (n=5) and 6 months (n=5). The internet-based intervention varied from study to study but the outcomes in each study were clear that either this system was efficient or not. Based on the searched literature and selected studies it was concluded that online health technologies can effectively cope with Gastroenterological disorders and patients with digestive disorders have shown good acceptability and pleasure in all the selected studies. Keywords: eHealth technologies, Digestive disorders, Ulcerative colitis, Crohn’s disease, Review