Digital Medicine Technologies Research Articles

Attitude of doctors and patients of the central district hospital to using digital health technologies (based on the results of a medical and sociological study)

Objective: to study the attitude of doctors and patients of the central district hospital to the use of digital medicine technologies. Material and methods. The study was conducted by a questionnaire survey. 43 doctors and 213 patients of the central district hospital were asked to assess the possibilities of digital tools in solving health problems, the degree of use of Internet platforms in the process of doctor-patient interaction, the level of influence of the Internet on patients' adherence to doctor's recommendations. Results. Only 14.0% of doctors and 5.2% of patients believe that digital technologies can help solve the problem of staff shortage. Currently, 65.1 % of doctors and 23.9% of patients use digital technologies in communication in the doctor-patient system. 55.8% of doctors stated the desire of patients to get information about treatment in Internet sources, but 97.7% of patients trust doctors more than recommendations on the Internet. Among the possible ways of using digital technologies in medicine, patients see the design of referrals (61.0%), prescriptions (50.2%), temporary disability sheets, certificates (29.6%). Conclusions. Most representatives of both the medical community and patients do not see digital technologies as a way to radically solve the problems of personnel shortage in rural areas: only 32.6% of doctors and 19.7% of patients consider it possible to increase the availability of medical care through telemedicine, only 23% of patients considered remote consultations to be in demand. First of all, the prospects of digitalization of healthcare, according to patients, are associated with the optimization of the issuance of documents in the provision of medical care.

Progress in COVID research and developments during pandemic.

The pandemic respiratory disease COVID‐19 has spread over the globe within a small span of time. Generally, there are two important points are being highlighted and considered towards the successful diagnosis and treatment process. The first point includes the reduction of the rate of infections and the next one is the decrease of the death rate. The major threat to public health globally progresses due to the absence of effective medication and widely accepted immunization for the COVID‐19. Whereas, understanding of host susceptibility, clinical features, adaptation of COVID‐19 to new environments, asymptomatic infection is difficult and challenging. Therefore, a rapid and an exact determination of pathogenic viruses play an important role in deciding treatments and preventing pandemic to save the people's lives. It is urgent to fix a standardized diagnostic approach for detecting the COVID‐19. Here, this systematic review describes all the current approaches using for screening and diagnosing the COVID‐19 infectious patient. The renaissance in pathogen due to host adaptability and new region, facing creates several obstacles in diagnosis, drug, and vaccine development process. The study shows that adaptation of accurate and affordable diagnostic tools based on candidate biomarkers using sensor and digital medicine technology can deliver effective diagnosis services at the mass level. Better prospects of public health management rely on diagnosis with high specificity and cost‐effective manner along with multidisciplinary research, specific policy, and technology adaptation. The proposed healthcare model with defined road map represents effective prognosis system.

Overcoming Pilotitis in Digital Medicine at the Intersection of Data, Clinical Evidence, and Adoption

Worldwide, digital medicine technologies are being developed at a rapid rate. While these digital medicine technologies offer the potential to transform and revolutionize health care, many are at risk of stalling and remaining in the pilot stage, known as “pilotitis,” thus never reaching true potential. Therefore, overcoming “pilotitis” to increase the uptake of digital medicine technologies is a global concern. To date, several authors have proposed solutions to overcome various barriers owing to the “pilotitis” of digital medicine technologies, such as regulatory frameworks and patients’ data ownership; however, many areas require further consideration. This perspective piece identifies three barriers to the adoption and implementation of digital medicine technologies and proposes approaches for how to overcome them. Addressing such barriers may provide a pathway to success for digital medicine technologies to improve patient outcomes and increase the efficiency of healthcare delivery.

A Matrix Model for Creating Logical Filters of an Electronic Catalog of Prosthetic Modules for Customized Prostheses

Introduction. When synthesizing a prosthesis from ready-made prosthesis units, the prosthetist is faced with the problem of selecting from a large range of components that differ in properties and characteristics. This challenge can be overcome by the creation of a system for processing the patient's biomedical information and its further use as criteria for selecting prosthetic nodes from a global database. For this purpose, an appropriate knowledge base must be incorporated into the system software.Aim. Substantiation of the expediency of presenting the knowledge base about the requirements for the lower limb prosthesis nodes in the form of a matrix model for creating a system of logical filters in the process of selecting nodes from an electronic catalog.Materials and methods. Theoretical research methods were used, including analysis, synthesis and analogy. An expert survey among leading specialists was carried out. To unify the description of the structural and functional state of a disabled person, the terms of the International Classification of Functioning (ICF), Disability and Health were used.Results. At the main stage of filtering, prosthetic modules optimally meeting the patient’s needs are selected using a specialized software application, depending on the patient’s health status and various healthrelated factors. A model of the knowledge base is presented, which describes the logic of selecting prosthetic nodes and their filtering in an electronic catalog.Conclusion. The matrix representation of the knowledge base that contains rules for selecting components of lower limb prostheses, taking into account the patient's condition, is a basis for creating a system of logical filters when searching for prosthetic modules in an electronic catalog for creating customized prostheses. The use of the ICF conceptual language for describing the factors influencing the choice of prosthetic modules is a step towards the formation of a patient’s digital profile, which corresponds to the strategy of transition to digital medicine technologies.

Prescriber Attitudes, Experiences, and Proclivities Toward Digital Medicine and How They Influence Adoption of Digital Medicine Platforms.

BackgroundPsychiatric prescribers (prescribers) typically assess medication adherence by patient or caregiver self-report. Despite likely clinical benefit of a new digital medicine technology, the role of specific prescriber attitudes, behaviors, and experiences in the likelihood of adoption is unclear.ObjectiveTo identify prescriber characteristics that may affect adoption of the ingestible event marker (IEM) platform.DesignA survey of prescribers treating seriously mentally ill patients was conducted. Factor analysis was performed on 11 items representing prescriber characteristics believed to be related to endorsement of the IEM platform. Four factors were extracted. Regression analysis was used to test the strength of the relationships between the factors and likelihood of adoption of the IEM platform.ResultsA total of 131 prescribers completed the survey. Most (84%) agreed that visits allow enough time to monitor adherence. Factor analysis revealed four underlying dimensions: 1) perspectives on the value of adherence; 2) concerns about measuring adherence; 3) views toward digital health technologies; and 4) views on payer role/reimbursement. Factors 1 and 3 were related to gender, the belief that computerization benefits prescribers, the presence of office support staff, and the belief that new digital medicine (DM) technology will be cost prohibitive. Willingness to adopt the IEM platform was related to gender (p < 0.05) and perspectives on the value of adherence (p < 0.05), with those scoring higher on that measure also being more likely to adopt.ConclusionPsychiatric prescribers are concerned about medication adherence, perceive current monitoring tools to be problematic, and are open to using digital technologies to improve accuracy of adherence assessment. Relationships among prescriber characteristics, beliefs, and experiences should be considered when developing educational materials, particularly when the goal is to encourage adoption and use of the IEM platform.

Digital health care in China and access for older people

Digital health care in China and access for older people

Digital medicine technologies for pre-trip medical examination of drivers

The technologies of automation of pre-trip integrated examination of the drivers’ conditions are considered, which make it possible to significantly improve the quality of control while reducing the time for its passage. A comparative analysis of known analogues is carried out, problems are formulated, the solution of which will increase the diagnostic efficiency of telemedicine examination. The configuration of the developed computer control system and the hardware-software structure of the subject’s control panel are described. The ways of increasing the reliability of user identification are considered. Technical means have been developed for non-contact thermometry and assessment of tremor parameters. Algorithms for assessing the physiological and psychoemotional state of drivers have been implemented.

Digital Medicine in Thyroidology: A New Era of Managing Thyroid Disease.

Digital medicine has the capacity to affect all aspects of medicine, including disease prediction, prevention, diagnosis, treatment, and post-treatment management. In the field of thyroidology, researchers are also investigating potential applications of digital technology for the thyroid disease. Recent studies using artificial intelligence (AI)/machine learning (ML) have reported reasonable performance for the classification of thyroid nodules based on ultrasonographic (US) images. AI/ML-based methods have also shown good diagnostic accuracy for distinguishing between benign and malignant thyroid lesions based on cytopathologic findings. Assistance from AI/ML methods could overcome the limitations of conventional thyroid US and fine-needle aspiration cytology. A web-based database has been developed for thyroid cancer care. In addition to its role as a nationwide registry of thyroid cancer, it is expected to serve as a clinical platform to facilitate better thyroid cancer care and as a research platform providing comprehensive disease-specific big data. Evidence has been found that biosignal monitoring with wearable devices may predict thyroid dysfunction. This real-world thyroid function monitoring could aid in the management and early detection of thyroid dysfunction. In the thyroidology field, research involving the range of digital medicine technologies and their clinical applications is expected to be even more active in the future.

HYPERTENSION MANAGEMENT IN CANADIAN INDIGENOUS COMMUNITIES AND LOWER AND MIDDLE INCOME COUNTRIES, RESULTS OF THE CANADIAN ARM OF THE DREAMGLOBAL STUDY

The DreamGlobal study incorporates innovations in digital medicine technology with text messaging and the use of cell phones, as well as task shifting of blood pressure measurement to the Community and transmission of the measures to the patient's health care provider. In this pragmatic RCT study participants received culturally competent text message to improve their engagement in hypertension management over a one year period. Blood pressure was measured with an automated device linked by BlueTooth to a smartphone and central server. Blood pressure was measured by trained non-medical health workers every three months. The readings in the first two months were compared to the readings in the last two months of the study. Participants had uncontrolled hypertension and lived on one of six participating First Nations reserves in Ontario, Québec, or New Brunswick. Participants received Hypertension Canada Clinical Practice Guidelines based SMS text messages twice weekly, randomized to receive either passive (health behaviours change only) or active (including also treatment information). Health literacy about the SMS messages was assessed at study end. Over 120 subjects were part of the blood pressure lowering cohort. Baseline blood pressure was 143/85 mmHg and fell to 136/81 mmHg over the course of the study. There was a greater blood pressure fall in the active than in the passive SMS groups (7.5/4.7 mmHg vs 6.5/2.7 mmHg p < 0.01 for DBP). Health literacy scores for the active SMS group were higher than in the passive SMS group. Achieving guidelines based management of non-communicable chronic diseases is more challenging in remote, resource poor environments. SMS messages can help to improve health literacy and are shown to be associated with improved blood pressure lowering in people with uncontrolled hypertension. Task shifting of blood pressure measurement including non-medical health workers supported by a secure system to bring the results to the health record and to the patient, supported by informative SMS messages leads to lower blood pressure. Canadian Institutes of Health Research (CIHR)

"What Goes Around Comes Around": Lessons Learned from Economic Evaluations of Personalized Medicine Applied to Digital Medicine.

The growth of "big data" and the emphasis on patient-centered health care have led to the increasing use of two key technologies: personalized medicine and digital medicine. For these technologies to move into mainstream health care and be reimbursed by insurers, it will be essential to have evidence that their benefits provide reasonable value relative to their costs. These technologies, however, have complex characteristics that present challenges to the assessment of their economic value. Previous studies have identified the challenges for personalized medicine and thus this work informs the more nascent topic of digital medicine. To examine the methodological challenges and future opportunities for assessing the economic value of digital medicine, using personalized medicine as a comparison. We focused specifically on digital biomarker technologies and multigene tests. We identified similarities in these technologies that can present challenges to economic evaluation: multiple results, results with different types of utilities, secondary findings, downstream impact (including on family members), and interactive effects. Using a structured review, we found that there are few economic evaluations of digital biomarker technologies, with limited results. We conclude that more evidence on the effectiveness of digital medicine will be needed but that the experiences with personalized medicine can inform what data will be needed and how such analyses can be conducted. Our study points out the critical need for typologies and terminology for digital medicine technologies that would enable them to be classified in ways that will facilitate research on their effectiveness and value.

A framework for smartphone-enabled, patient-generated health data analysis.

Background: Digital medicine and smartphone-enabled health technologies provide a novel source of human health and human biology data. However, in part due to its intricacies, few methods have been established to analyze and interpret data in this domain. We previously conducted a six-month interventional trial examining the efficacy of a comprehensive smartphone-based health monitoring program for individuals with chronic disease. This included 38 individuals with hypertension who recorded 6,290 blood pressure readings over the trial.Methods: In the present study, we provide a hypothesis testing framework for unstructured time series data, typical of patient-generated mobile device data. We used a mixed model approach for unequally spaced repeated measures using autoregressive and generalized autoregressive models, and applied this to the blood pressure data generated in this trial.Results: We were able to detect, roughly, a 2 mmHg decrease in both systolic and diastolic blood pressure over the course of the trial despite considerable intra- and inter-individual variation. Furthermore, by supplementing this finding by using a sequential analysis approach, we observed this result over three months prior to the official study end—highlighting the effectiveness of leveraging the digital nature of this data source to form timely conclusions.Conclusions: Health data generated through the use of smartphones and other mobile devices allow individuals the opportunity to make informed health decisions, and provide researchers the opportunity to address innovative health and biology questions. The hypothesis testing framework we present can be applied in future studies utilizing digital medicine technology or implemented in the technology itself to support the quantified self.

A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors.

Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers–some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program–making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group.

Telemedicine and digital management in repair and regeneration after nerve injury and in nervous system diseases.

Telemedicine and digital management in repair and regeneration after nerve injury and in nervous system diseases.