Digital Healthcare Revolution Research Articles

How the digital healthcare revolution leaves the most vulnerable behind.

How the digital healthcare revolution leaves the most vulnerable behind.

The Importance of an Innovation Culture in the NHS

Keynote on 'Global trends in healthcare sustainability Digital Revolution in Health Care

Capacity Building, Knowledge Enhancement, and Consultative Processes for Development of a Digital Tool (Ni-kshay SETU) to Support the Management of Patients with Tuberculosis: Exploratory Qualitative Study.

Achieving the target for eliminating tuberculosis (TB) in India by 2025, 5 years ahead of the global target, critically depends on strengthening the capacity of human resources as one of the key components of the health system. Due to the rapid updates of standards and protocols, the human resources for TB health care suffer from a lack of understanding of recent updates and acquiring necessary knowledge. Despite an increasing focus on the digital revolution in health care, there is no such platform available to deliver the key updates in national TB control programs with easy access. Thus, the aim of this study was to explore the development and evolution of a mobile health tool for capacity building of the Indian health system's workforce to better manage patients with TB. This study involved two phases. The first phase was based on a qualitative investigation, including personal interviews to understand the basic requirements of staff working in the management of patients with TB, followed by participatory consultative meetings with stakeholders to validate and develop the content for the mobile health app. Qualitative information was collected from the Purbi Singhbhum and Ranchi districts of Jharkhand and Gandhinagar, and from the Surat districts of Gujarat State. In the second phase, a participatory design process was undertaken as part of the content creation and validation exercises. The first phase collected information from 126 health care staff, with a mean age of 38.4 (SD 8.9) years and average work experience of 8.9 years. The assessment revealed that more than two-thirds of participants needed further training and lacked knowledge of the most current updates to TB program guidelines. The consultative process determined the need for a digital solution in easily accessible formats and ready reckoner content to deliver practical solutions to address operational issues for implementation of the program. Ultimately, the digital platform named Ni-kshay SETU (Support to End Tuberculosis) was developed to support the knowledge enhancement of health care workers. The development of staff capacity is vital to the success or failure of any program or intervention. Having up-to-date information provides confidence to health care staff when interacting with patients in the community and aids in making quick judgments when handling case scenarios. Ni-kshay SETU represents a novel digital capacity-building platform for enhancing human resource skills in achieving the goal of TB elimination.

The Digitalization of India's Healthcare System: A Paradigm Shift amidst the COVID-19 Pandemic

Aim: This study examines the paradigm shift in India's healthcare sector due to the COVID-19 epidemic, explicitly focusing on adopting digital healthcare. The study explores the innovative initiatives undertaken by both the government and commercial sectors in virtual health and analyzes the long-term benefits of this transition.
 Methodology: The study utilizes a secondary research approach to investigate the development of India's digital healthcare system. Various sources such as reports, surveys, and official documents are reviewed to gather information on implementing digital health solutions. The study examines intelligent devices, telemedicine websites, and platforms like Arogya Setu that have played a crucial role in the digital healthcare revolution. Government programs such as the National Digital Health Mission (NDHM) and the establishment of e-hospitals are also analyzed to understand their impact. The study emphasizes the significance of data mining, the development of digital health records, and the necessary infrastructure to support digital healthcare.
 Results: The results indicate that the COVID-19 pandemic has accelerated the digitization of India's healthcare sector. Adopting digital health solutions, including telemedicine, wearable technology, and artificial intelligence, has gained significant momentum. Initiatives like the NDHM and the establishment of e-hospitals have contributed to the successful implementation of digital healthcare. The study highlights the benefits of digital healthcare, such as improved accessibility, cost-effectiveness, and accuracy of services. The importance of data mining and the development of digital health records are underscored as critical drivers of this transformation.
 Conclusion: To conclude, the COVID-19 pandemic has served as a driving force for the digital transformation of India's healthcare industry. The adoption of digital health solutions and the initiatives taken by the government lay the foundation for a more accessible and patient-centred healthcare future. The study emphasizes the significant implications of digital innovations in healthcare for healthcare organizations, medical device manufacturers, and remote care providers. While acknowledging that in-person treatment is still necessary and that comprehensive digitalization takes time, the study highlights the transformative potential of digitizing healthcare to improve access to care and enhance delivery methods. This digital revolution can potentially revolutionize the healthcare industry and improve healthcare outcomes.

Data Governance and Privacy Challenges in the Digital Healthcare Revolution

Data Governance and Privacy Challenges in the Digital Healthcare Revolution

Mapping the Digital Healthcare Revolution

Mapping the Digital Healthcare Revolution

Machine Learning-Reinforced Noninvasive Biosensors for Healthcare.

The emergence and development of noninvasive biosensors largely facilitate the collection of physiological signals and the processing of health-related data. The utilization of appropriate machine learning algorithms improves the accuracy and efficiency of biosensors. Machine learning-reinforced biosensors are started to use in clinical practice, health monitoring, and food safety, bringing a digital revolution in healthcare. Herein, the recent advances in machine learning-reinforced noninvasive biosensors applied in healthcare are summarized. First, different types of noninvasive biosensors and physiological signals collected are categorized and summarized. Then machine learning algorithms adopted in subsequent data processing are introduced and their practical applications in biosensors are reviewed. Finally, the challenges faced by machine learning-reinforced biosensors are raised, including data privacy and adaptive learning capability, and their prospects in real-time monitoring, out-of-clinic diagnosis, and onsite food safety detection are proposed.

P156 Myositis flares are associated with reduced work productivity and fewer hours worked: illustration of the future potential of digital healthcare solutions in rheumatic diseases

Background/Aims The digital healthcare revolution provides the opportunity for clinicians and researchers to collect useful data on a frequent and remote basis. Work ability is impacted by many rheumatic diseases, including the idiopathic inflammatory myopathies (IIMs), however, methods to assess the real-time impacts are limited. This study aims to explore the impact of IIM flares and symptoms upon employment using frequently collected data via a smartphone-based app. Methods The Myositis Physical Activity Device Study recruited a UK-based adult IIM cohort who completed weekly employment and flare questions via a specially designed smartphone-based app throughout a 91 day period in 2019/20. Employment-related questions were assessed every week (see Table 1 for details). Flares were reported via a weekly question. Employment variables were compared between flare and non-flare weeks using descriptive statistics. The relationship between flares and work productivity was assessed using multi-level mixed effects logistic regression modelling, adjusted for age and sex. Results Data on 13 (69% female) employed participants was analysed. A median of 5 flares were reported per patient during the three month period (IQR 3, 9). Summary employment results are displayed in Table 1. Participants reported greater impact of IIM upon employment, lower productivity and fewer hours worked during a flare week, compared to a non-flare week. There was a significant association between flares and detrimental impact upon work productivity (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.03, 1.12, p < 0.01). Flares were also significantly associated with an increased number of work hours missed due to IIM (OR 1.04, 95% CI 1.01, 1.08, p = 0.02) P156 Table 1:- Summary employment parameters compared between flare and non-flare weeksEmployment parameterAnswer formatWhole study period (159 weeks)Flare weeks (60 weeks)Non-flare weeks (99 weeks)p-value*Number of weeks’ work productivity affected by IIM (%)Dichotomous - “yes”, “no”54 (34.0)33 (55.0)21 (21.2)<0.01Mean effect of IIM upon work productivity (SD)Visual analogue scale - “Myositis had no effect on work" (0);“Myositis completely prevented me from working” (100)29.8 (28.8)46.2 (33.3)19.9 (20.0)<0.01Mean number of scheduled work hours per week per participant (SD)Numerical33.2 (15.8)36.9 (19.33)31.0 (13.0)<0.01Mean number of hours worked per week per participant (SD)Numerical23.5 (15.1)18.86 (17.1)26.23 (13.2)<0.01Proportion of hours worked per week per participant / % (SD)Calculated by research team73.7 (38.7)55.9 (43.2)84.7 (31.1)<0.01Mean number of hours of weekly work missed due to IIM per participant (SD)Numerical6.6 (16.6)14.9 (23.4)1.5 (6.6)<0.01Proportion of hours of weekly work missed due to IIM per participant / % (SD)Calculated by research team12.7% (29.5)29.2 (41.1)2.6 (10.0)<0.01SD = standard deviation *Categorical variables were compared using the Chi-squared test and continuous variables compared using the student t-test. Conclusion Our study has demonstrated that IIM flares are significantly associated with detrimental impact upon employment ability. On average, patients lost 15 hours of work a week during a flare compared to less than 2 hours outside a flare. The economic and personal impact of flares highlights the need for research in this area, with the aim of allowing early identification and instigation of treatment and possible need for supported work. Smartphone based remote monitoring of flares and other pertinent variables could enhance digital consultations, which may become more common in the post COVID-19 setting. Disclosure J.C. Williams: None. A.G.S. Oldroyd: None. W.G. Dixon: None. H. Chinoy: None.

Digital Healthcare Revolution: 3D Printing in Pharmaceutical Industry; Applications and Future Perspective

Digital Healthcare Revolution: 3D Printing in Pharmaceutical Industry; Applications and Future Perspective

A Narrative Review of the Patient Journey Through the Lens of Non-communicable Diseases in Low- and Middle-Income Countries.

Low- and middle-income countries (LMICs) are challenged with a disproportionately high burden of noncommunicable diseases (NCDs) and limited healthcare resources at their disposal to tackle the NCD epidemic. Understanding the patient journey for NCDs from the patients’ perspective can help healthcare systems in these settings evolve their NCD care models to address the unmet needs of patients, enhance patient participation in their management, and progress towards better outcomes and quality of life. This paper aims to provide a theoretical framework outlining common touchpoints along the patient journey for NCDs in LMICs. It further aims to review influencing factors and recommend strategies to improve patient experience, satisfaction, and disease outcomes at each touchpoint. The co-occurrence of major NCDs makes it possible to structure the patient journey for NCDs into five broad touchpoints: awareness, screening, diagnosis, treatment, and adherence, with integration of palliative care along the care continuum pathway. The patients’ perspective must be considered at each touchpoint in order to inform interventions as they experience first-hand the impact of NCDs on their quality of life and physical function and participate substantially in their disease management. Collaboratively designed health communication programs, shared decision-making, use of appropriate risk assessment tools, therapeutic alliances between the patient and provider for treatment planning, self-management tools, and improved access to palliative care are some strategies to help improve the patient journeys in LMICs. Long-term management of NCDs entails substantial self-management by patients, which can be augmented by pharmacists and nurse-led interventions. The digital healthcare revolution has heralded an increase in patient engagement, support of home monitoring of patients, optimized accurate diagnosis, personalized care plans, and facilitated timely intervention. There is an opportunity to integrate digital technology into each touchpoint of the patient journey, while ensuring minimal interruption to patients’ care in the face of global health emergencies.

Health is the Motive and Digital is the Instrument.

The coronavirus crisis has seen an unprecedented response from India and the world. If the viral outbreak has exposed gross inadequacies in the healthcare systems of nations both rich and poor, it has stirred a digital healthcare revolution that has been building since the past decade. We have seen how this new era of digital health evolved over the years since healthcare started getting increasingly unaffordable in the western countries forcing a relook in their strategies to explosion of digital innovations in mobile telephony and applications, internet, wearable devices, artificial intelligence, robotics, big data and genomics. The single biggest trigger for the digital shift has indeed been the COVID-19 pandemic this year, more so in India with astonishing response from the private enterprise and the proactive push from the government so evident. However, the full potential of this digital revolution cannot be realized as long as core structural reforms in public healthcare do not take place along with significant boost in digital infrastructure. The way digital technologies have helped facilitate strategy and response to the global pandemic and with predictions of more zoonotic outbreaks impending in the coming years, it has become imperative for the world to increasingly adopt and integrate digital innovations to make healthcare more accessible, interconnected and affordable.

Digital revolution in healthcare: are stroke patients ready?

The digital revolution is creating opportunities and challenges in the field of medicine and the Digital Hospital could be a benefit for patients, if they are able to use the Internet. Identify the barriers that limit Internet use among stroke patients treated in a public hospital in Santiago. Sociodemographic, clinical and functional variables that could influence the use of the Internet were collected in 107 patients with stroke. Seventy five percent of patients had access to the Internet, but only 29% knew how to use it before their hospitalization. Seventy five percent were older adults, 74% had a low level of education, 78% had an income below the minimum Chilean salary and 56% were discharged with a severe disability (modified Rankin Scale 4 or 5). There was a significant relationship between Internet use and the level of education, income and age. Income levels, age, schooling and stroke related disability limit Internet use in this population.

Discussion Paper: Social accountability for students in a machine learning era

Over the last 30 years, there have been repeated calls to integrate health informatics into undergraduate health professional curricula, in recognition of the integral role computing plays in medicine. The rise of big data sets in health, and the application of advanced computer algorithms to interrogate these, is yet another call for health professionals to receive appropriate training in these technologies. Machine learning (ML) algorithms can learn tasks or make decisions without a requirement for specific behaviours to be pre-programmed. High-impact literature has described ML approaches to clinical problems such as achieving more accurate and timely diagnoses, increasing precision of prognosis and guiding treatment. Despite the promise of ML in healthcare, there are risks of adverse outcomes, unanticipated consequences, misuse and even abuse of ML technologies. For health professionals to advocate for patients and hold those developing ML algorithms in healthcare accountable, they must feel comfortable discussing the fundamental concepts and limitations of ML in healthcare. Healthcare professionals are uniquely positioned to identify problems that could be solved by ML and related technologies. Yet, there is inadequate coverage of ML, or of the wider field of health informatics, in most medical curricula. To create future health professionals who can advocate for positive change and ensure that patients remain at the centre of ML applications in healthcare, we must provide future health professionals with an understanding of how ML will change healthcare delivery and the doctor–patient dynamic, as well as new ethical challenges that arise with the digital healthcare revolution.

Platform for Managing Medical Data byUsing a Passive Electronic Device.

e-Health is referred to in literature as the usage of Information and Communication Technology (ICT) in the health domain, for administering treatment of patients, research, and health education and monitoring of public health in situ or remotely. Information and Communication Technology (ICT) plays a significant role in society today. Digitalization is changing all areas of human behavior, from social settings to basic needs, like health-related matters. The impact of new technology on improving health and well-being of individuals and populations is unprecedented, creating a phenomenon referred to as digital revolution in healthcare. The purpose of this paper is therefore to present DoctorCloud.net Platform for remote emergency, tactical health, and security support. It is a complete system for direct human support that offers immediate access to medical parameters and data via the Internet cloud.

Digital revolution in healthcare: Potential tool for achieving health equity in Bangladesh

Men’s engagement in women’s sexual and reproductive healthcare as well as responsible parenthood is a demand of time in countries like Bangladesh, where men play a vital role, when it comes to the issue of women’s ability to seek healthcare. Yet, we couldn’t reach a point, where our men are wellequipped with proper healthcare information to assist their partners in a specific health complication and fully participate to take a decision on their health and wellbeing. But, if they can be aware and motivated about the importance of their active involvement in family’s healthcare using ICT tools, they could definitely help their partners to take effective decision in emergency. Ensuring the use of low cost intervention like ICT tools for receiving health information will also help achieving the vision of health equity, by engaging all, regardless of gender or class barriers.Objective: The main objective of this paper is to assist the healthcare professionals and development partners, who are involving with advocacy through e-health awareness programs using ICT tools, to formulate their coordinated next plan of action. By formulating such an action plan, healthcare providers can easily identify the issues that need to be more emphasized, topics that are not covered by anyone yet and prevent duplication of healthcare contents that are already available online. By ensuring e-health for all, we can contribute to implementing our UHC, as part of Sustainable Development Goals (SDG).Materials and Methods: In order to showcase the importance of digital technology in healthcare, we picked up two social media platforms that provide the highest possible healthcare information on adolescence and reproductive health and aim to reduce the rate of maternal mortality and morbidity to the bare minimum. Since the inception of the Facebook page called ‘Dr. Purabi’sHelp Desk https://www.facebook.com/DrPurabisHelpDesk/’ and the YouTube channel ‘Nowsheen Purabi, https://www.youtube.com/user/drpurabihelpdesk’ in November 2012, these online platforms have been delivering video contents, articles on adolescent-maternal-reproductive health, contraception, non-communicable disease prevention, vaccination, nutrition, and mental health.The data we have shown are taken from the analytics/ insights of Facebook page ‘Dr. Purabi’s Help Desk’ and YouTube channel ‘Nowsheen Purabi’. For Facebook page data, we have used the monthly insight report that Facebook provides every page owner. On the other hand, the YouTube data was taken from the channel analytics, which gives a lifetime data to the channel owner.Results: People from reproductive age (18-34 years old) mostly watch the YouTube contents, while same in Facebook Page. 64% men are somehow likely to be active in watching healthcare contents online. Contents are viewed by people from different parts of the world (Bangladesh 88%, India 8%, Saudi Arabia 1%, USA 1%, and Australia 1%). Almost 91% of the viewer uses their mobile phones; 6% use computers and 3% percent use tablets to watch the contents. 94% male and 6% females are engaged in the posts.Conclusion: If we can take necessary steps to engage more people in digital healthcare by lowering the internet price, we will be able to achieve SDG as well as UHC within a short time. We need the coordination of government and private initiatives to bridge the information gap between the healthcare professionals and the patients.International Journal of Human and Health Sciences Vol. 03 No. 04 October’19 Page : 201-206

The placement position optimization of a biosensor array for wearable healthcare systems

Advancement in wearable healthcare technology allows a digital revolution in healthcare that is intended to extend life length and improve life quality. Until now, numerous efforts for wearable device-mediated healthcare systems have been focused on achieving accurate monitoring and robust operation by developing cutting-edge biosensors rather than by optimizing the placement position of well-established biosensors. Much therefore still remains unclear about the optimal position involved in biosensor placement. This leads to the need for systematic optimization of biosensor placement position. Here, the placement positions of 2 biosensor arrays (i.e., ECG-TC array and PPG-TC array) are optimized to achieve high-accuracy measurement and high-robustness operation in monitoring both body temperature and heart rate, which are commonly measured as core vital signs in wearable healthcare systems. The ECG-TC array is composed of an electrocardiography (ECG) sensor (for heart rate measurement) and a thermocouple (TC) sensor (for body temperature measurement) while the PPG-TC array consists of a photoplethysmography (PPG) sensor and a TC sensor. 34 major parts in the human body are scored in terms of monitoring accuracy (MA) and operational robustness (OR), which results in the MA index and OR index. Next, the body part having the maximum value, calculated as the product of two indices, is determined as the optimal placement position. The MA index is calculated from the signal magnitude of each biosensor and the OR index is assessed by quantifying the user accessibility, skin extensibility, and perspiration weight of each body part. Our study shows that the ECG-TC array needs to be placed on armpit, chest, and back thigh and the PPG-TC array on thumb, finger, and ear. This means the optimal placement position of biosensor-based wearable healthcare systems is affected by a combination of different biosensors. The findings of this study are expected to contribute to better understanding of biosensors and lead to further improvement in wearable healthcare devices.

Designing sustainability into the Digital Healthcare Revolution

Designing sustainability into the Digital Healthcare Revolution

Doctor Robot - The digital healthcare revolution (Vol. 22, No. 9, Full Issue)

Asia-Pacific Biotech NewsVol. 22, No. 09 (2018) No AccessDoctor Robot - The digital healthcare revolution (Vol. 22, No. 9, Full Issue)https://doi.org/10.1142/S0219030318001088Cited by:0 Next AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetails Recommended Vol. 22, No. 09 Metrics History PDF download

Cloud based IoT Smart Healthcare System for Remote Patient Monitoring

INTRODUCTION: Covid-19 has exposed the necessitate for the rapid acceptance of increasingly pioneering digital health technologies, especially remote health monitoring. The digital revolution in Healthcare is dynamic ease of use of inexpensive concern solutions, enhancing patient care, reducing complications, improving effectiveness, and authorizing healthcare decision-makers with intelligence insight at the point of care. OBJECTIVES: The primary objective of this work is to depict the need to recognize wearable sensors as a prerequisite for supporting paradigms in monitoring patients in real-time and enabling access information from the cloud. METHODS: Internet of Things (IoT) is the association of substantial objects where information and communication tools connect various embedded devices to the internet for gathering and switching over data. The combinations of embedded devices with cloud servers recommend extensive pertinence of IoT to several areas of human life. This paper has proposed a method through cloud-based IoT healthcare sensors to formulate patient monitoring remotely. In combination with the implementation of various inbuilt capabilities, internet-enabled heterogeneous wearable sensors can be used for the collection of biomedical data to transmit patient data directly to cloud severe systems to monitor health remotely. RESULTS: Smart healthcare monitoring includes channels of communication, embedded internal and external sensors, IoT server, and cloud storage. The health parameters activities are done at various levels of refining named application layer, management layer, network layer and layer of device. Different data sensors have been collected by wireless media from nodes. It is saved as an unstructured dataset in the cloud. For security with username and password, a patient database is created. Authorized individuals have access to the cloud in order to monitor cloud sensor data in data log, analogue log, digital input and digital output. CONCLUSION: Patient physical parameters like heart beat respiration ,high temperature and stress are calculated via sensors and can be progressed by WIFI unit in the cloud. From this healthcare practitioner will analyze medical to have effective medication. For face-to-face consultation between doctors and patients, the video feature can be added in the future work.

Discoveries Interview: Doctor John D. Halamka on the digital healthcare revolution.

Discoveries Interview: Doctor John D. Halamka on the digital healthcare revolution.