scholarly journals Examining Mental Workload Relating to Digital Health Technologies in Health Care: Protocol for a Systematic Review focusing on Assessment Methods (Preprint)

10.2196/29126 ◽  
2021 ◽  
Author(s):  
Lisanne Kremer ◽  
Myriam Lipprandt ◽  
Rainer Röhrig ◽  
Bernhard Breil
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Mental Workload ◽  
Digital Health ◽  
Assessment Methods ◽  
Health Technologies ◽  
Care Protocol

scholarly journals Examining Mental Workload Relating to Digital Health Technologies in Health Care: Protocol for a Systematic Review Focusing on Assessment Methods (Preprint)

2021 ◽  
Author(s):  
Lisanne Kremer ◽  
Myriam Lipprandt ◽  
Rainer Röhrig ◽  
Bernhard Breil
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Eye Tracking ◽  
Health Care Professionals ◽  
Mental Workload ◽  
Selection Process ◽  
Digital Health ◽  
Research Question ◽  
Health Technologies ◽  
Care Protocol

BACKGROUND The workload in healthcare is steadily increasing - physicians and nurses report stress as well as a very demanding environment with complex and multiple tasks. As a result, mental health issues are on the rise among health care professionals, the proneness to errors in tasks could increase. The digitization of patient care is intended to counteract processes of demographic change, which are partly the cause of higher stress levels. It remains unclear whether the health information systems (HIS) and digital health technologies (DHT) used relieve the professionals or even represent a further burden. The mental construct that describes this burden of technologies is Mental Workload (MWL). Work in the clinic can be viewed as working in safety-critical environments. Particularly in this sensitive setting, the measurement methods of MWL are relevant - mainly due to their strongly differing intrusiveness and sensitivity. The method of eye tracking could provide a useful way to be able to measure MWL directly in the field. OBJECTIVE The systematic review addresses two different, but related objectives. 1. In which manner do DHT contribute to the overall MWL of health care workers: 1.1. Can we observe a direct or indirect effect of DHT on MWL? 1.2. Which aspects or factors of DHT contribute to an increase of MWL? 2. Which methods/ assessments are applied to measure MWL related to HIS/ DHT? 2.1. Which role does eye tracking/ pupillometry play in context of measure? 2.2. Which outcomes are being assessed via eye tracking? METHODS Following the PRISMA statement, we conduct a systematic review. Based on the research question, we define keywords that we then combine in search terms. The review follows the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis and data synthesis. RESULTS As the systematic review is currently ongoing, no results are available yet. The preliminary searches have been completed, the piloting of the study selection process as well as the formal screening against eligibility criteria has started. We are currently analyzing the data and expect to complete the review in spring 2021. CONCLUSIONS We are expecting conclusions after finalizing the review. CLINICALTRIAL PROSPERO registration: CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271&ID=CRD42021233271

Digital health technologies for long term self-management of osteoporosis: a systematic review and meta-analysis (Preprint)

2021 ◽  
Author(s):  
Ghada Alhussein ◽  
Leontios Hadjileontiadis
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Digital Health ◽  
Meta Analysis ◽  
Self Management ◽  
Current Status ◽  
Future Research ◽  
Common Chronic Disease ◽  
Health Technologies ◽  
Management Interventions

BACKGROUND Osteoporosis is the fourth most common chronic disease in the world. Adopting preventative measures and effective self-management interventions help in improving bone health. Mobile health (mHealth) technologies can play a key role in osteoporosis patient care and self- management. OBJECTIVE This study presents a systematic review and meta-analysis of the currently available mHealth applications targeting osteoporosis self-management, aiming to determine the current status, gaps and challenges the future research could address, proposing appropriate recommendations. METHODS In this systematic review and meta-analysis, we searched PubMed, Scopus, EBSCO, Web of Science, and IEEExplore databases between Jan 1, 2010 and May 31, 2021, for all English publications that describe apps dedicated to or being useful for osteoporosis, targeting self-management, nutrition, physical activity, risk assessment, delivered on smartphone devices for young and older adults. In addition, a survey of all osteoporosis-related apps available in iOS and Android app stores as of May 31, 2021 was also conducted. Primary outcomes of interest were the prevention or reduction of unhealthy behaviours or improvement in healthy behaviours of the six behaviours. Outcomes were summarised in a narrative synthesis and combined using random-effects meta-analysis. RESULTS In total, 3906 unique articles were identified. Of these, 32 articles met the inclusion criteria and were reviewed in depth. The 32 studies were comprising 14 235 participants, of whom on average 69.5% were female, with a mean age of 49.8 years (SD 17.8). The app search identified 23 relevant apps for osteoporosis self-management. The meta-analysis revealed that mHealth supported interventions resulted in a significant reduction in pain (Hedge’s g -1.09, 95%CI -1.68 to -0.45) and disability (Hedge’s g -0.77, 95%CI -1.59 to 0.05). The post-treatment effect of the digital intervention was significant for physical function (Hedge’s g 2.54, 95%CI -4.08 to 4.08); yet nonsignificant for wellbeing (Hedge’s g 0.17, 95% CI -1.84 to 2.17), physical activity (Hedges’ g 0.09, 95%CI -0.59 to 0.50), anxiety (Hedge’s g -0.29, 95%CI -6.11 to 5.53), fatigue (Hedge’s g -0.34, 95%CI -5.84 to 5.16), calcium (Hedge’s g -0.05, 95%CI -0.59 to 0.50) and vitamin D (Hedge’s g 0.10, 95% CI -4.05 to 4.26) intake, and trabecular score (Hedge’s g 0.06, 95%CI -1.00 to 1.12). CONCLUSIONS Osteoporosis apps have the potential to support and improve the management of the disease and its symptoms; they also appear to be a valuable tool for patients and health professionals. However, the majority of the apps that are currently available lack clinically validated evidence of their efficacy and they most focus on a limited number of symptoms. A more holistic and personalized approach, within a co-creation design ecosystem, is needed.

Digital Health

2021 ◽  
Author(s):  
Eric D. Perakslis ◽  
Martin Stanley ◽  
Erin Brodwin
Keyword(s):  
Health Care ◽  
Side Effects ◽  
Care Delivery ◽  
Digital Health ◽  
Detailed Examination ◽  
Medical Diagnostics ◽  
Medical Interventions ◽  
Health Technologies ◽  
Solid Models ◽  
Medical Side

Digital health has been touted as a true transformation of health care, but all medical interventions have associated risks that must be understood and quantified. The Internet has brought many advancements, which quickly jumped from our computers into our pockets via powerful and completely connected mobile devices that are now being envisioned as devices for medical diagnostics and care delivery. As health care struggles with cost, inequity, value, and rapid virtualization, solid models of benefit-risk determination, new regulatory approaches for biomedical products, and clear risk-based conversations with all stakeholders are essential. Detailed examination of emerging digital health technologies has revealed 10 categories of digital side effects or “toxicities” that must be understood, prevented when possible, and managed when not. These toxicities include cyberthreat, loss of privacy, cyberchondria and cyber addiction, threats to physical security, charlatanism, overdiagnosis and overtreatment, medical/user error, and the plague of medical misinformation. For digital health to realize its promise, these toxicities must be understood, measured, warned against, and managed as concurrent side effects, in the same fashion as any other medical side effect.

Digital Health Technologies for Remote Monitoring and Management of Inflammatory Bowel Disease: A Systematic Review

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Nghia H. Nguyen ◽  
Ivonne Martinez ◽  
Ashish Atreja ◽  
Amy M. Sitapati ◽  
William J. Sandborn ◽  
...  
Keyword(s):  
Systematic Review ◽  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Remote Monitoring ◽  
Digital Health ◽  
Health Technologies ◽  
Inflammatory Bowel

Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care

2018 ◽  
pp. 1-9 ◽  
Author(s):  
Shivank Garg ◽  
Noelle L. Williams ◽  
Andrew Ip ◽  
Adam P. Dicker
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Health Care ◽  
Data Collection ◽  
Patient Outcomes ◽  
Cancer Care ◽  
Digital Health ◽  
Health Technologies ◽  
Health Care Value

Digital health constitutes a merger of both software and hardware technology with health care delivery and management, and encompasses a number of domains, from wearable devices to artificial intelligence, each associated with widely disparate interaction and data collection models. In this review, we focus on the landscape of the current integration of digital health technology in cancer care by subdividing digital health technologies into the following sections: connected devices, digital patient information collection, telehealth, and digital assistants. In these sections, we give an overview of the potential clinical impact of such technologies as they pertain to key domains, including patient education, patient outcomes, quality of life, and health care value. We performed a search of PubMed ( www.ncbi.nlm.nih.gov/pubmed ) and www.ClinicalTrials.gov for numerous terms related to digital health technologies, including digital health, connected devices, smart devices, wearables, activity trackers, connected sensors, remote monitoring, electronic surveys, electronic patient-reported outcomes, telehealth, telemedicine, artificial intelligence, chatbot, and digital assistants. The terms health care and cancer were appended to the previously mentioned terms to filter results for cancer-specific applications. From these results, studies were included that exemplified use of the various domains of digital health technologies in oncologic care. Digital health encompasses the integration of a vast array of technologies with health care, each associated with varied methods of data collection and information flow. Integration of these technologies into clinical practice has seen applications throughout the spectrum of care, including cancer screening, on-treatment patient management, acute post-treatment follow-up, and survivorship. Implementation of these systems may serve to reduce costs and workflow inefficiencies, as well as to improve overall health care value, patient outcomes, and quality of life.

A systematic review and meta-analysis of digital health technologies effects on psychotic symptoms in adults with psychosis.

Psychosis ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 362-373
Author(s):  
Stephen Clarke ◽  
Donncha Hanna ◽  
Ciaran Mulholland ◽  
Ciaran Shannon ◽  
Callum Urquhart
Keyword(s):  
Systematic Review ◽  
Digital Health ◽  
Meta Analysis ◽  
Psychotic Symptoms ◽  
Health Technologies

scholarly journals Barriers to Creating Scalable Business Models for Digital Health Innovation in Public Systems: Qualitative Case Study (Preprint)

2020 ◽  
Author(s):  
Leah Taylor Kelley ◽  
Jamie Fujioka ◽  
Kyle Liang ◽  
Madeline Cooper ◽  
Trevor Jamieson ◽  
...  
Keyword(s):  
Health Care ◽  
Health System ◽  
Health Systems ◽  
Business Models ◽  
Digital Health ◽  
Digital Technologies ◽  
Economic Incentives ◽  
Barriers To Entry ◽  
Health Innovation ◽  
Health Technologies

BACKGROUND Health systems are increasingly looking toward the private sector to provide digital solutions to address health care demands. Innovation in digital health is largely driven by small- and medium-sized enterprises (SMEs), yet these companies experience significant barriers to entry, especially in public health systems. Complex and fragmented care models, alongside a myriad of relevant stakeholders (eg, purchasers, providers, and producers of health care products), make developing value propositions for digital solutions highly challenging. OBJECTIVE This study aims to identify areas for health system improvement to promote the integration of innovative digital health technologies developed by SMEs. METHODS This paper qualitatively analyzes a series of case studies to identify health system barriers faced by SMEs developing digital health technologies in Canada and proposed solutions to encourage a more innovative ecosystem. The Women’s College Hospital Institute for Health System Solutions and Virtual Care established a consultation program for SMEs to help them increase their innovation capacity and take their ideas to market. The consultation involved the SME filling out an onboarding form and review of this information by an expert advisory committee using guided considerations, leading to a recommendation report provided to the SME. This paper reports on the characteristics of 25 SMEs who completed the program and qualitatively analyzed their recommendation reports to identify common barriers to digital health innovation. RESULTS A total of 2 central themes were identified, each with 3 subthemes. First, a common barrier to system integration was the lack of formal evaluation, with SMEs having limited resources and opportunities to conduct such an evaluation. Second, the health system’s current structure does not create incentives for clinicians to use digital technologies, which threatens the sustainability of SMEs’ business models. SMEs faced significant challenges in engaging users and payers from the public system due to perverse economic incentives. Physicians are compensated by in-person visits, which actively works against the goals of many digital health solutions of keeping patients out of clinics and hospitals. CONCLUSIONS There is a significant disconnect between the economic incentives that drive clinical behaviors and the use of digital technologies that would benefit patients’ well-being. To encourage the use of digital health technologies, publicly funded health systems need to dedicate funding for the evaluation of digital solutions and streamlined pathways for clinical integration.

scholarly journals Elements of Trust in Digital Health Systems: Scoping Review (Preprint)

2018 ◽  
Author(s):  
Afua Adjekum ◽  
Alessandro Blasimme ◽  
Effy Vayena
Keyword(s):  
Health Care ◽  
Health Systems ◽  
Scoping Review ◽  
Service Provider ◽  
Digital Health ◽  
Digital Technologies ◽  
Data Access ◽  
Building Blocks ◽  
Sociodemographic Factors ◽  
Health Technologies

BACKGROUND Information and communication technologies have long become prominent components of health systems. Rapid advances in digital technologies and data science over the last few years are predicted to have a vast impact on health care services, configuring a paradigm shift into what is now commonly referred to as digital health. Forecasted to curb rising health costs as well as to improve health system efficiency and safety, digital health success heavily relies on trust from professional end users, administrators, and patients. Yet, what counts as the building blocks of trust in digital health systems has so far remained underexplored. OBJECTIVE The objective of this study was to analyze what relevant stakeholders consider as enablers and impediments of trust in digital health. METHODS We performed a scoping review to map out trust in digital health. To identify relevant digital health studies, we searched 5 electronic databases. Using keywords and Medical Subject Headings, we targeted all relevant studies and set no boundaries for publication year to allow a broad range of studies to be identified. The studies were screened by 2 reviewers after which a predefined data extraction strategy was employed and relevant themes documented. RESULTS Overall, 278 qualitative, quantitative, mixed-methods, and intervention studies in English, published between 1998 and 2017 and conducted in 40 countries were included in this review. Patients and health care professionals were the two most prominent stakeholders of trust in digital health; a third—health administrators—was substantially less prominent. Our analysis identified cross-cutting personal, institutional, and technological elements of trust that broadly cluster into 16 enablers (altruism, fair data access, ease of use, self-efficacy, sociodemographic factors, recommendation by other users, usefulness, customizable design features, interoperability, privacy, initial face-to-face contact, guidelines for standardized use, stakeholder engagement, improved communication, decreased workloads, and service provider reputation) and 10 impediments (excessive costs, limited accessibility, sociodemographic factors, fear of data exploitation, insufficient training, defective technology, poor information quality, inadequate publicity, time-consuming, and service provider reputation) to trust in digital health. CONCLUSIONS Trust in digital health technologies and services depends on the interplay of a complex set of enablers and impediments. This study is a contribution to ongoing efforts to understand what determines trust in digital health according to different stakeholders. Therefore, it offers valuable points of reference for the implementation of innovative digital health services. Building on insights from this study, actionable metrics can be developed to assess the trustworthiness of digital technologies in health care.

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