Digital Healthcare System Research Articles

Security, Privacy, and Reliability in Digital Healthcare Systems Using Blockchain

According to the security breach level index, millions of records are stolen worldwide on every single day. Personal health records are the most targeted records on the internet, and they are considered sensitive, and valuable. Security and privacy are the most important parameters of cryptography and encryption. They reduce the availability of data on patients and healthcare to the appropriate personnel and ultimately lead to a barrier in the transfer of healthcare into a digital health system. Using a permission blockchain to share healthcare data can reduce security and privacy issues. According to the literature, most healthcare systems rely on a centralized system, which is more prone to security vulnerabilities. The existing blockchain-based healthcare schemes provide only a data-sharing framework, but they lack security and privacy. To cope with these kinds of security issues, we have designed a novel security algorithm that provides security as well as privacy with much better efficiency and a lower cost. Hence, in this research, we have proposed a patient healthcare framework that provides greater security, reliability, and authentication compared to existing blockchain-based access control.

Real-time interactive digital healthcare system for post-operative breast cancer patients: study protocol for a randomized controlled trial

BackgroundAfter receiving breast cancer surgery or reconstruction, shoulder dysfunctions including weakness, post-operative pain, shoulder joint instability, and limited range of motion (ROM) often occur. Due to limited ROM, patients may suffer difficulty in activities of daily living, and quality of life may be reduced. The objective of this study is to compare the effects on shoulder ROM of a real-time interactive digital healthcare system and brochure-based home rehabilitation program in post-operative breast cancer patients.MethodsThis study is a prospective, multi-center, assessor-blinded randomized controlled trial. The study aims to recruit 100 breast cancer patients exhibiting limited shoulder ROM after undergoing axillary lymph node dissection or breast reconstruction following mastectomy. Patients will be randomly assigned to two groups for 8 weeks of rehabilitation: a digital healthcare system rehabilitation (intervention) group and a brochure-based rehabilitation (control) group. The primary outcome is the change in ROM of the affected shoulder between baseline and 12 weeks after enrollment. Secondary outcomes include pain in the affected shoulder, as measured using a numerical rating scale, functional outcomes (QuickDASH scores), and quality of life (FACT-B and EQ-5D-5L scores), all of which will be measured on enrollment and 4, 8, and 12 weeks thereafter.DiscussionThis study will compare the effectiveness of a newly developed, augmented reality-based real-time interactive digital healthcare system with that of brochure-based home rehabilitation for improving the shoulder ROM, pain, functional outcomes, and quality of life of post-operative breast cancer patients.Trial registrationClinicalTrials.govNCT04316156. Registered on 20 March 2020.

Internet of things based vital signs monitoring system: A prototype validity test

The advent of the internet of things (IoT) has resulted in an upsurge in the deployment of digital health care systems enabling patients’ health conditions to be remotely monitored. This article presents an intelligent and automated IoT-based vital signs monitoring system to aid in patient care. A the oretical framework was established to guide the development of a prototype. It encompasses the patient, IoT sensors, input and storage unit and data processing, analysis and data transmission. The prototype is equipped with the capability of sensing a patient’s body temperature, heart rate, and respiration rate in real time and transmits the data to a cloud data repository for storage and analysis. Alerts are sent to caregivers using SMS, email and voice calls where urgent attention is required for the patient. The voice call isto ensure a caregiver does not miss the alert since SMS and email may not be checked on time. To ensure privacy of patients, a caregiver has to be biometrically verified by either fingerprint or facial pattern. The experimental results confirmed the accuracy of the data gathered by the prototype, privacy of patients is also guaranteed compared to other benchmark systems.

Physician ranking optimization based on patients' browse behaviors and resource capacities

PurposeDigital healthcare has become one of the most important Internet applications in the recent years, and digital platforms have been acting as interfaces between the patients and physicians. Although these technologies enhance patient convenience, they create new challenges in platform management. For instance, on physician rating websites, information overload negatively influences patients' decision-making in relation to selecting a physician. This scenario calls for an automated mechanism to provide real-time rankings of physicians. Motivated by an online healthcare platform, this study develops a method to deliver physician ranking on platforms by considering patients' browse behaviors and the capacities of service resources.Design/methodology/approachThe authors use a probabilistic model for explicitly capturing the browse behaviors of patients. Since the large volume of information in digital systems makes it intractable to solve the dynamic ranking problem, we design a ranking with value approximation algorithm that combines a greedy ranking policy and the value function approximation methods.FindingsThe authors found that the approximation methods are quite effective in dealing with the ranking optimization on the digital healthcare system, and it is mainly because the authors incorporate the patient behaviors and patient availability in the model.Originality/valueTo the best of the authors’ knowledge, this is one of the first studies to present solutions to the dynamic physician ranking problem. The ranking algorithms can also help platforms improve system and operational performance.

Why Are Digital Health Care Systems Still Poorly Designed, and Why Is Health Care Practice Not Asking for More? Three Paths Toward a Sustainable Digital Work Environment.

Knowledge of how to design digital systems that are ergonomically sound, high in usability, and optimized for the user, context, and task has existed for some time. Despite this, there are still too many examples of new digital health care systems that are poorly designed and that could negatively affect both the work environment of health care staff and patient safety. This could be because of a gap between the theoretical knowledge of design and ergonomics and the practical implementation of this knowledge in procuring and developing digital health care systems. Furthermore, discussions of digitalization are often at a general level and risk neglecting the nature of direct interaction with the digital system. This is problematic since it is at this detailed level that work environment and patient safety issues materialize in practice. In this paper, we illustrate such issues with two scenarios concerned with contemporary electronic health care records, based on field studies in two health care settings. We argue that current methods and tools for designing and evaluating digital systems in health care must cater both to the holistic level and to the details of interaction and ergonomics. It must also be acknowledged that health care professionals are neither designers nor engineers, so expectations of them during the development of digital systems must be realistic. We suggest three paths toward a more sustainable digital work environment in health care: (1) better tools for evaluating the digital work environment in the field; (2) generic formulations of qualitative requirements related to usability and for adaptation to the user, context, and task, to be used in procurement; and (3) the introduction of digital ergonomics as an embracing concept capturing several of the ergonomic challenges (including physical, cognitive, and organizational aspects) involved in implementing and using digital systems.

On the ultimate finishing line of the Human Genome Project

The Human Genome Project (HGP) has paved the way for the Digital Personal Genomes (DPG), whereby a person's complete genome sequence serves as the primary entry for the Digital Healthcare Systems (DHS). If the goal is to deliver PDG on demand, affordability, mainly the cost, becomes one of the primary issues. However, as a once-in-a-lifetime event, a total cost of US $100 is close to $1 per year contribution. Therefore, what remains is still largely an engineering challenge, since a multi-fold reduction of the current per-genome sequencing cost may be achievable by increasing the scale of operation and the degree of automation over 5–10 years.

The role of smart monitoring digital health care system based on smartphone application and personal health record platform for patients diagnosed with coronavirus disease 2019

BackgroundThe massive outbreak of the novel coronavirus disease 2019 (COVID-19) in Daegu city and Gyeongsangbuk-do, Republic of Korea (ROK), caused the exponential increase in new cases exceeding 5000 within 6 weeks. Therefore, the community treatment center (CTC) with a digital health care monitoring system based on the smartphone application and personal health record platform (PHR) was implemented. Thus, we report our experience in one of the CTCs to investigate the role of CTC and the feasibility of the digital health care monitoring system in the COVID-19 pandemic.MethodsThe Gyeongbuk-Daegu 2 CTC was set up at the private residential facility. Admission criteria were 1) patients < 65 years with COVID-19, 2) patients without underlying medical comorbidities, and 3) COVID-19 disease severity of mild class. Admitted patients were placed under monitoring of vital signs and symptoms. Clinical information was collected using the smartphone application or telephone communication. Collected information was displayed on the PHR platform in a real-time fashion for close monitoring.ResultsFrom Mar 3, 2020, to Mar 26, 2020, there was a total of 290 patients admitted to the facility. Males were 104 (35.9%). The median age was 37 years. The median time between the COVID-19 diagnosis and admission was 7 days. Five patients were identified and were transferred to the designed COVID-19 treatment hospital for their urgent medical needs. The smartphone application usage to report vital signs and symptoms was noted in 96% of the patients. There were no deaths of the patients.ConclusionsOur results suggest that implementation of the CTC using a commercial residence facility and digital health care technology may offer valuable solutions to the challenges posed by the COVID-19 outbreak.

A systematic review of emerging information technologies for sustainable data-centric health-care

BackgroundOf the Sustainable Development Goals (SDGs), the third presents the opportunity for a predictive universal digital healthcare ecosystem, capable of informing early warning, assisting in risk reduction and guiding management of national and global health risks. However, in reality, the existing technology infrastructure of digital healthcare systems is insufficient, failing to satisfy current and future data needs. ObjectiveThis paper systematically reviews emerging information technologies for data modelling and analytics that have potential to achieve Data-Centric Health-Care (DCHC) for the envisioned objective of sustainable healthcare. The goal of this review is to: 1) identify emerging information technologies with potential for data modelling and analytics, and 2) explore recent research of these technologies in DCHC. FindingsA total of 1619 relevant papers have been identified and analysed in this review. Of these, 69 were probed deeply. Our analysis found that the extant research focused on elder care, rehabilitation, chronic diseases, and healthcare service delivery. Use-cases of the emerging information technologies included providing assistance, monitoring, self-care and self-management, diagnosis, risk prediction, well-being awareness, personalized healthcare, and qualitative and/or quantitative service enhancement. Limitations identified in the studies included vendor hardware specificity, issues with user interface and usability, inadequate features, interoperability, scalability, and compatibility, unjustifiable costs and insufficient evaluation in terms of validation. ConclusionAchievement of a predictive universal digital healthcare ecosystem in the current context is a challenge. State-of-the-art technologies demand user centric design, data privacy and protection measures, transparency, interoperability, scalability, and compatibility to achieve the SDG objective of sustainable healthcare by 2030.

5G network slice for digital real-time healthcare system powered by network data analytics

In the wake of the COVID-19 pandemic, where almost the entire global healthcare ecosystem struggled to handle patients, it’s evident that the healthcare segment needs a virtual real-time digital support system. The recent advancements in technology have enabled machine-to-machine communication, enhanced mobile broadband, and real-time biometric data analytics. These could potentially fulfill the requirements of an end-to-end digital healthcare system. For building such a system, there is also a need for a dedicated and specialized communication network. Such a system will not only support dynamic throughput, latency and payload but also provide guaranteed QoS (Quality of Service) at every instant. The motive of our study was to define an implementable low-level architecture for the digital healthcare system by using the 5G Network Slice that incorporates all these features. Best-in-class wearable devices will collect the biometric data and transmit it via the 5G network slice. Data analytics is then applied to the collected data to build a knowledge graph used for quick predictions and prescriptions. The architecture also keeps in mind the security and integrity aspects of healthcare data.

Health Professional Digital Capabilities Frameworks: A Scoping Review.

IntroductionThe term “digital healthcare professional” alludes to a health professional with the additional digital capabilities such as information and technology. The assumption that attaining technical knowledge and skills to meet the available professional standards in digital healthcare, will engage and empower healthcare users, thus deliver person-centered digital healthcare (PCDHc), is flawed. Identifying where digital healthcare and technologies can genuinely support person-centered care may lead to future discourse and practical suggestions to build person-centered integrated digital healthcare environments. This review examines current digital health and informatics capability frameworks and identifies the opportunity to include additional or alternative principles.MethodsA scoping review was conducted. Literature valuing person-centered digital healthcare requirements, digital health capabilities, and competencies were identified between 2000 and 2019 inclusive, then collated and considered. Using a PRISMA approach for eligibility screening, thirteen articles met the study inclusion criteria. Analysis used a thematic framework approach, which assisted in the data management, abstraction and description, and finally the explanations.ResultsAnalysis indexed fifty-nine (59) capabilities, charted thirteen (n13) categories, mapped four (n4) themes, which were then interpreted as findings.FindingsThe four themes identified were Change Management; User Application; Data, Information, and Knowledge; and Innovation. The themes recognize the opportunity to align the application of technical skills towards the capabilities required to deliver authentic PCDHc.DiscussionHolistic mindsets are imperative in maintaining the objective of PCDHc. The authors propose that debates regarding professional digital capability persist in being “siloed” and “paternalistic” in nature. They also recommend that the transition to authentic PCDHc requires refocusing (rather than rewriting) current capabilities. The realignment of capabilities towards individual healthcare outcomes, rather than professional obligation, can steer the perspective towards a genuine PCDHc system.ConclusionThis scoping review confirms the assumption that digital skills will empower all healthcare stakeholders is incorrect. This review also draws attention to the need for more research to enable digital healthcare systems and services to be designed to realize complex human behaviors and multiple person-centered care requirements. Now more than ever, it is imperative to align healthcare capabilities with technologies to ensure that the practice of PCDHc is the empowering journey for the healthcare user that theory implies.

Ghana Go Digital Agenda: The impact of Zipline Drone Technology on Digital Emergency Health Delivery in Ghana

Ghana has deployed high-speed technology and digital initiatives for the daily management of all the sectors of the country under the theme ‘’Ghana Go Digital Agenda’’ policy initiative. These digital governance initiatives include the electronic or digital-health care systems, e-justice system paperless clearing of goods at port-banking, and other online services. Paramount among the many digital initiatives is the introduction of drones for emergency digital health delivery. Access to medical supplies in Ghana has been hindered by the difficulty of getting the supplies from the central points to other areas that are remotely located to enable the patients who need the services to get them. To overcome this challenge and deliver affordable and accessible health care services to the Ghanaian populace, the Government of Ghana engaged a US-based company Zipline Technology to use Drones in the supply of medical supplies for emergencies and hard-to-reach areas of the country. Since the introduction of this initiative in 2019, it has attracted mix-reactions from various stakeholders on the relevance of the drone technology project on health delivery in Ghana. This study used the Diffusion of Innovation (DOI) and Technology Acceptance Model (TAM) to assess drone technology’s impact on Ghana’s emergency health delivery system. The study utilized an online survey questionnaire to solicit data from participants. From the hundred (100) health facilities, located within the operational zone of the drone, twenty (20) were purposively sampled. Out of 550 questionnaires distributed, a total of 533 health workers (participants) validly responded to the online questionnaire. One key finding of our study indicates that the introduction of drone technology for medical supplies in Ghana has significantly impacted positively on the emergency health delivery system in Ghana.

Artificial Intelligence in Ophthalmology: Evolutions in Asia.

Artificial intelligence (AI) has been studied in ophthalmology since availability of digital information in ophthalmic care. The significant turning point was availability of commercial digital color fundus photography in the late 1990s, which caused digital screening for diabetic retinopathy (DR) to take off. Automated Retinal Disease Assessment software was then developed using machine learning to detect abnormal lesions in fundus to screen DR. The use of this version of AI had not been generalized because the specificity at 45% was not high enough, although the sensitivity reached 90%. The recent breakthrough in machine learning is the invent of deep learning, which accelerates its performance to be on par with experts. The first 2 breakthrough studies on deep learning for screening DR were conducted in Asia. The first represented collaboration of datasets between Asia and the United States for algorithms development, whereas the second represented algorithms developed in Asia but validated in different populations across the world. Both found accuracy for detecting referable DR of >95%. Diversity and variety are unique strengths of Asia for AI studies. There are many more studies of AI ongoing in Asia not only as prospective deployments in DR but in glaucoma, age-related macular degeneration, cataract, and systemic disease, such as Alzheimer's disease. Some Asian countries have laid out plans for digital health care system using AI as one of the puzzle pieces for solving blindness. More studies on AI and digital health are expected to come from Asia in this new decade.

Fast Medical Image Security Using Color Channel Encryption

Abstract Evolution of digital Health-care Information System established Medical Image Security as the new contemporary research area. Most of the researchers used either image watermarking or image encryption to address medical image security. However, very few proposals focused on both issues. This paper has implemented a Fast Medial Image Security algorithm for color images that uses both watermarking and encryption of each color channel. The proposed method starts with embedding of a smoothened key image (K) and patient information over the original image (I) to generate a watermarked image (W). Then, each color channel of the watermarked image (W) is encrypted separately to produce an encrypted image (E) using the same smoothened key image (K). This image can be transmitted over the public network and the original image (I) can be achieved using decryption algorithm followed by de-watermarking using the same key image (K) at the receiver. Qualitative and quantitative results of the proposed method show good performance when compared with the existing method with high Mean, PSNR and Entropy.

COVID-19 What Have We Learned? The Rise of Social Machines and Connected Devices in Pandemic Management Following the Concepts of Predictive, Preventive and Personalised Medicine

Objectives: Review, compare and critically assess digital technology responses to the COVID-19 pandemic around the world. The specific point of interest in this research is on predictive, preventive and personalised interoperable digital healthcare solutions. This point is supported by failures from the past, where the separate design of digital health solutions, has led to lack of interoperability. Hence, this review paper investigates the integration of predictive, preventive and personalised interoperable digital healthcare systems. The second point of interest is the use of new mass surveillance technologies to feed personal data from health professionals to governments, without any comprehensive studies that determine if such new technologies and data policies would address the pandemic crisis.Method: This is a review paper. Two approaches were used: A comprehensive bibliographic review with R statistical methods of the COVID-19 pandemic in PubMed literature and Web of Science Core Collection, supported with Google Scholar search. In addition, a case study review of emerging new approaches in different regions, using medical literature, academic literature, news articles, and other reliable data sources.Results: Most countries’ digital responses involve big data analytics, integration of national health insurance databases, tracing travel history from individual’s location databases, code scanning, and individual’s online reporting. Public responses of mistrust about privacy data misuse differ across countries, depending on the chosen public communication strategy. We propose predictive, preventive and personalised solutions for pandemic management, based on social machines and connected devices.Solutions: The proposed predictive, preventive and personalised solutions are based on the integration of IoT data, wearables devices data, mobile apps data, and individual data inputs from registered users, operating as a social machine with strong security and privacy protocols. We present solutions that would enable much greater speed in future responses. These solutions are enabled by the social aspect of human-computer interactions (social machines) and the increased connectivity of humans and devices (internet of things).Conclusion: Inadequate data for risk assessment on speed and urgency of COVID-19, combined with increased globalisation of human society, led to the rapid spread of COVID-19. Despite an abundance of digital methods that could be used in slowing or stopping COVID-19 and future pandemics, the world remains unprepared and lessons have not been learned from previous cases of pandemics. We present a summary of predictive, preventive and personalised digital methods that could be deployed fast to help with the COVID-19 and future pandemics.

Real-time Interactive Digital Healthcare System in Post Operation Patients With Breast Cancer; Pilot Study

Real-time Interactive Digital Healthcare System in Post Operation Patients With Breast Cancer; Pilot Study

Exploring healthcare professionals' understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review.

The integration of artificial intelligence (AI) into our digital healthcare system is seen as a significant strategy to contain Australia's rising healthcare costs, support clinical decision making, manage chronic disease burden and support our ageing population. With the increasing roll-out of 'digital hospitals', electronic medical records, new data capture and analysis technologies, as well as a digitally enabled health consumer, the Australian healthcare workforce is required to become digitally literate to manage the significant changes in the healthcare landscape. To ensure that new innovations such as AI are inclusive of clinicians, an understanding of how the technology will impact the healthcare professions is imperative. In order to explore the complex phenomenon of healthcare professionals' understanding and experiences of AI use in the delivery of healthcare, an integrative review inclusive of quantitative and qualitative studies was undertaken in June 2018. One study met all inclusion criteria. This study was an observational study which used a questionnaire to measure healthcare professional's intrinsic motivation in adoption behaviour when using an artificially intelligent medical diagnosis support system (AIMDSS). The study found that healthcare professionals were less likely to use AI in the delivery of healthcare if they did not trust the technology or understand how it was used to improve patient outcomes or the delivery of care which is specific to the healthcare setting. The perception that AI would replace them in the healthcare setting was not evident. This may be due to the fact that AI is not yet at the forefront of technology use in healthcare setting. More research is needed to examine the experiences and perceptions of healthcare professionals using AI in the delivery of healthcare.

A Doctor Patient Portal for Effective Healthcare

This paper presents a noble approach to develop a digital healthcare system for Bangladesh, a country which is soon going to become a developing country. We made an online application to help the masses to get access to healthcare easily and effectively. The application consists of two modules, doctor/hospital information system and emergency services. It has user-friendly features for doctor appointment making. Also, it has a blood donor search option, ambulance calling option, patient’s report view option, doctors ranking options etc. The doctors ranking is a special feature which was calculated based on doctor’s educational qualification, experience, average count of appointments made by patients and patient’s feedback. Feedback form real users showed that this information system was very helpful for them. If implemented countrywide, this system of digital healthcare may pave the way for an effective healthcare service in Bangladesh.

Latent Dirichlet Analysis Based Opinion Mining of Healthcare Report

Intelligent abstraction of knowledge from Social blogs has gained immense attention from Biomedical and online health communities. Healthcare re- views through public opinion platforms not only helped in improving the health- care but also reducing the costs. Advancement in digital healthcare systems enables patients access to Online Health Communities (OHC) through their views, opinions and remedial information. In the current study reviews provided by patients on OHC related to diabetes has been chosen to understand the community effort to address the health care issues of these patients. Reviews shared by patients at various levels of diabetic conditions have been selected and analyzed using LDA text mining techniques. In the current study we have also analyzed the gender specific differences among the diabetic community based on the opinions shared by them on public OHC platforms. Sample for the study has been gathered from a prominent online diabetic community in UK. Community members wrote on different topics from food habits, lifestyle, physical exercise and dis- ease symptoms to predict and possible remedial measures to be taken has been discussed in online health communities. Results of our study show that male users are information-centric than the female users, while female users are more emotionally attached as compared to males. Study also reveals several other findings related to community support and state of healthcare sector with reference to treatment, medication and facilities available to the community.

Assessing usability of eHealth technology: A comparison of usability benchmarking instruments

BackgroundIt is generally assumed that usability benchmarking instruments are technology agnostic. The same methods for usability evaluations are used for digital commercial, educational, governmental and healthcare systems. However, eHealth technologies have unique characteristics. They need to support patients’ health, provide treatment or monitor progress. Little research is done on the effectiveness of different benchmarks (qualitative and quantitative) within the eHealth context. ObjectivesIn this study, we compared three usability benchmarking instruments (logging task performance, think aloud and the SUS, the System Usability Scale) to assess which metric is most indicative of usability in an eHealth technology. Also, we analyzed how these outcome variables (task completion, system usability score, serious and critical usability issues) interacted with the acceptance factors Perceived benefits, Usefulness and Intention to use. MethodsA usability evaluation protocol was set up that incorporated all three benchmarking methods. This protocol was deployed among 36 Dutch participants and across three different eHealth technologies: a gamified application for older adults (N = 19), an online tele-rehabilitation portal for healthcare professionals (N = 9), and a mobile health app for adolescents (N = 8). ResultsThe main finding was that task completion, compared to the SUS, had stronger correlations with usability benchmarks. Also, serious and critical issues were stronger correlated to task metrics than the SUS. With regard to acceptance factors, there were no significant differences between the three usability benchmarking instruments. ConclusionsWith this study, we took a first step in examining how to improve usability evaluations for eHealth. The results show that listing usability issues from think aloud protocols remains one of the most effective tools to explain the usability for eHealth. Using the SUS as a stand-alone usability metric for eHealth is not recommended. Preferably, the SUS should be combined with task metrics, especially task completion. We recommend to develop a usability benchmarking instrument specifically for eHealth.

Sharing information safely and securely: the foundation of a modern health care system.

Sharing information safely and securely: the foundation of a modern health care system.