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Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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199 hot topic(s) found with the query "Digital health"

The evolution of digital health technologies in cardiovascular disease research
CZ Zwack et al, NPJ Digital Medicine, January 3, 2023 (Posted: Jan-04-2023 6AM)

A recent emergence of research activities in digital technology in cardiovascular rehabilitation (CR), out-of-hospital cardiac arrest (OHCA), and arrythmia research was also demonstrated. Conversely, wearable technologies, activity tracking and electronic medical records research are now past their peak of reported research activity. With increasing amounts of novel technologies becoming available and more patients taking part in remote health care monitoring, further evaluation and research into digital technologies is needed.

DIGItal Health Literacy after COVID-19 Outbreak among Frail and Non-Frail Cardiology Patients: The DIGI-COVID Study
M Vitolo et al, J Per Med, December 31, 2020 (Posted: Dec-31-2022 7AM)

A total of 300 patients were enrolled (36.3% females, median age 75 (66–84)) and stratified according to frailty status as robust (EFS = 5; 70.7%), pre-frail (EFS 6–7; 15.7%), and frail (EFS = 8; 13.7%). Frail and pre-frail patients used digital tools less frequently and accessed the Internet less frequently compared to robust patients. In the logistic regression analysis, frail patients were significantly associated with the non-use of the Internet (adjusted odds ratio 2.58, 95% CI 1.92–5.61) compared to robust and pre-frail patients. Digital health literacy decreased as the level of frailty increased in all the digital domains examined.

Factors associated with long-term use of digital devices in the electronic Framingham Heart Study
CH Pathiravasan et al, NPJ Digital Medicine, December 27, 2022 (Posted: Dec-27-2022 0PM)

Long-term use of digital devices is critical for successful clinical or research use, but digital health studies are challenged by a rapid drop-off in participation. A nested e-cohort (eFHS) is embedded in the Framingham Heart Study and uses three system components: a new smartphone app, a digital blood pressure (BP) cuff, and a smartwatch. This study aims to identify factors associated with the use of individual eFHS system components over 1-year.

Digital health tools to support parents with parent-infant sleep and mental well-being
HL Ball et al, NPJ Digital Medicine, December 21, 2022 (Posted: Dec-21-2022 8AM)

Digital technology has been developed to support parents in the following four ways: (1) providing digital information on infant sleep, (2) offering targeted support for night-time care, (3) managing infant sleep and (4) monitoring infant sleep and safety. Evidence on the effectiveness of these strategies is varied and there are concerns regarding the reliability of information, use of personal data, commercial exploitation of parents, and the effects of replacing caregiver presence with digital technology.

Editorial: Digitalization for precision healthcare
F Cascini et al, Front Public Health, December 2022 (Posted: Dec-21-2022 8AM)

The creation of digital infrastructure and technologies to collect, analyse and connect electronic health and life-science data supports—now more than ever—the growth of precision healthcare. However, the current adoption of digital health tools and infrastructures is geographically variable and often missing an assessment, as shown in a systematic review of the cost-effectiveness of digital interventions. This lacking approach to the digitalisation of the health sector has the effect of wasting resources with no improvement in care.

Digital health technology-specific risks for medical malpractice liability
SP Rowland et al, NPJ Digital Medicine, October 20, 2022 (Posted: Oct-20-2022 6AM)

Medical professionals are increasingly required to use digital technologies as part of care delivery and this may represent a risk for medical error and subsequent malpractice liability. For example, if there is a medical error, should the error be attributed to the clinician or the artificial intelligence-based clinical decision-making system? In this article, we identify and discuss digital health technology-specific risks for malpractice liability and offer practical advice for the mitigation of malpractice risk.

HIV Prevention: Digital Health Interventions to Improve Adherence to HIV Pre-Exposure Prophylaxis
The Community Guide, October 2022 (Posted: Oct-13-2022 6AM)

The Community Preventive Services Task Force (CPSTF) recommends digital health interventions to increase adherence to HIV pre-exposure prophylaxis (PrEP). Systematic review evidence shows interventions improve both daily-use pill taking and retention in PrEP care. This improves health for population groups who are not infected with HIV and engage in behaviors that may increase their chances of getting HIV.

Translational gaps and opportunities for medical wearables in digital health.
Xu Shuai et al. Science translational medicine 2022 10 (666) eabn6036 (Posted: Oct-13-2022 6AM)

Medical grade wearables—noninvasive, on-body sensors operating with clinical accuracy—will play an increasingly central role in medicine by providing continuous, cost-effective measurement and interpretation of physiological data relevant to patient status and disease trajectory, both inside and outside of established health care settings. Here, we review current digital health technologies and highlight critical gaps to clinical translation and adoption.

A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study
CY Cheung et al, The Lancet Digital Health, September 30, 2022 (Posted: Oct-03-2022 6AM)

12?949 retinal photographs from 648 patients with Alzheimer's disease and 3240 people without the disease were used to train, validate, and test the deep learning model. In the internal validation dataset, the deep learning model had 83·6% (SD 2·5) accuracy, 93·2% (SD 2·2) sensitivity, 82·0% (SD 3·1) specificity, and an area under the receiver operating characteristic curve (AUROC) of 0·93 (0·01) for detecting Alzheimer's disease-dementia.

Artificial intelligence for detection of Alzheimer's disease: demonstration of real-world value is required to bridge the translational gap
CR Marshall et al, The Lancet Digital Health, September 30, 2022 (Posted: Oct-03-2022 6AM)

The wide availability of retinal photography could, in principle, support detection of Alzheimer's disease at population level, allowing earlier access to support and treatment. This raises important questions that have yet to be resolved around what constitutes a timely diagnosis of Alzheimer's disease, and how effectively earlier detection improves quality of life, prognosis, and future health-care resource requirements.

Health digital twins as tools for precision medicine: Considerations for computation, implementation, and regulation
KP Venkatesh et al, NPJ Digital Medicine, Sepetmber 22, 2022 (Posted: Sep-23-2022 7AM)

Health digital twins are defined as virtual representations (“digital twin”) of patients (“physical twin”) that are generated from multimodal patient data, population data, and real-time updates on patient and environmental variables. With appropriate use, HDTs can model random perturbations on the digital twin to gain insight into the expected behavior of the physical twin—offering groundbreaking applications in precision medicine, clinical trials, and public health.

The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field
G Coorey et al, NPJ Digital Medicine, August 26, 2022 (Posted: Aug-26-2022 8AM)

Potential benefits of precision medicine in cardiovascular disease (CVD) include more accurate phenotyping of individual patients with the same condition or presentation, using multiple clinical, imaging, molecular and other variables to guide diagnosis and treatment. An approach to realizing this potential is the digital twin concept, whereby a virtual representation of a patient is constructed and receives real-time updates of a range of data variables in order to predict disease and optimize treatment selection for the real-life patient.

Regulatory considerations to keep pace with innovation in digital health products
J Torous et al, NPJ Digital Medicine, August 19, 2022 (Posted: Aug-19-2022 11AM)

Current regulatory pathways were developed for traditional (hardware) medical devices and offer a useful structure, but the evolution of digital devices requires concomitant innovation in regulatory approaches to maximize the potential benefits of these emerging technologies. A number of specific adaptations could strengthen current regulatory oversight while promoting ongoing innovation.

The diagnostic and triage accuracy of digital and online symptom checker tools: a systematic review
W Wallace et al, NPJ Digital Medicine, August 18, 2022 (Posted: Aug-18-2022 1PM)

Researchers evaluated the accuracy of symptom checkers using a variety of medical conditions, including ophthalmological conditions, inflammatory arthritides and HIV. The diagnostic accuracy of the primary diagnosis was low across included studies (range: 19–37.9%) and varied between individual symptom checkers, despite consistent symptom data input. Triage accuracy (range: 48.8–90.1%) was typically higher than diagnostic accuracy. Overall, the diagnostic and triage accuracy of symptom checkers are variable and of low accuracy.

A framework for digital health equity
S Richardson, NPJ Digital Medicine, August 18, 2022 (Posted: Aug-18-2022 1PM)

We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization of healthcare may widen health disparities if solutions are not developed with these determinants in mind. We examine DDoHs at the individual, interpersonal, community, and societal levels, and discuss the importance of a root cause, multi-level approach.

A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust
N Shutz et al, NPJ Digital Medicine, August 16, 2022 (Posted: Aug-16-2022 10AM)

We introduce and describe a zero-interaction digital exhaust: a set of 1268 digital measures that cover large parts of a person’s activity, behavior and physiology. Making this approach more inclusive of older adults, we base this set entirely on contactless, zero-interaction sensing technologies. Applying the resulting digital exhaust to real-world data, we then demonstrate the possibility to create multiple ageing relevant digital clinical outcome assessments. Paired with modern machine learning, we find these assessments to be surprisingly powerful and often on-par with mobile approaches

The cost-effectiveness of digital health interventions: A systematic review of the literature
A Gentili et al, Front Public Health, August 2022 (Posted: Aug-11-2022 7AM)

The studies were heterogeneous by country (mostly conducted in upper and upper-middle income countries), type of eHealth intervention, method of implementation, and reporting perspectives. The qualitative analysis identified the economic and effectiveness evaluation of six different types of interventions: (1) seventeen studies on new video-monitoring service systems; (2) five studies on text messaging interventions; (3) five studies on web platforms and digital health portals; (4) two studies on telephone support; (5) three studies on new mobile phone-based systems and applications; and (6) three studies on digital technologies and innovations.

The Need for Electronic Health Records to Support Delivery of Behavioral Health Preventive Services.
Huffstetler Alison N et al. JAMA 2022 8 (Posted: Aug-06-2022 8AM)

To accomplish digital health goals, it is essential to adhere to 3 key principles. First, digital health systems need to make it easy for clinicians to deliver national guidelines and quality recommendations. Second, digital health systems need to make information actionable for clinicians and patients. Third, digital health systems need to be easy to use; they should be intuitive for users, easily accessible, and not require complex workflows to enter and retrieve data.

Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies
AE Gonzales et al, The Lancet Digital Health, July 28, 2022 (Posted: Jul-31-2022 7AM)

Accurate assessment of COVID-19 severity in the community is essential for patient care and requires COVID-19-specific risk prediction scores adequately validated in a community setting. We aimed to develop and validate two COVID-19-specific risk prediction scores. Remote COVID-19 Assessment in Primary Care-General Practice score (RECAP-GP; without peripheral oxygen saturation [SpO2]) and RECAP-oxygen saturation score (RECAP-O2; with SpO2). RECAP was a prospective cohort study that used multivariable logistic regression. Data on signs and symptoms (predictors) of disease were collected from community-based patients with suspected COVID-19 via primary care electronic health records and linked with secondary data on hospital admission (outcome) within 28 days of symptom onset.

A Systematic Scoping Review of Digital Health Technologies During COVID-19: A New Normal in Primary Health Care Delivery
C Ndayshimie et al, Research Square, July 19, 2022 (Posted: Jul-20-2022 7AM)

A total of 46 studies were included in the final synthesis: 40 articles; one book; two book chapters; one working paper; and two technical reports. These studies scrutinized various aspects of DHTs, entailing 19 types of DHTs with 20 areas of use that can be compressed into five bigger PHC functions: general PHC service delivery (teleconsultations, e-diagnosis, e-prescription, etc.); behaviour promotion and digital health literacy (e.g., combating vaccine hesitancy); surveillance functions; vaccination and drugs; and enhancing system decision-making for proper follow-up of ongoing PHC interventions during COVID-19.

A systematic review of healthcare provider-targeted mobile applications for non-communicable diseases in low- and middle-income countries
P Geldsetzer et al, NPJ Digital Medicine, July 19, 2022 (Posted: Jul-19-2022 7AM)

Cardiology was the most common clinical domain of the technologies evaluated, with 89 publications. mHealth innovations were predominantly developed using Apple’s iOS operating system. Cost data were provided in only 50 studies, but most technologies for which this information was available cost less than 20 USD. Only 24 innovations targeted the ten NCDs responsible for the greatest number of disability-adjusted life years lost globally. Most publications evaluated products created in high-income countries. Reported mHealth technologies are well-developed, but their implementation in LMICs faces operating system incompatibility and a relative neglect of NCDs causing the greatest disease burden.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study
SK Byeon et al, The Lancet Digital Health, July 11, 2022 (Posted: Jul-14-2022 6AM)

We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites.

The Promise of Digital Health: Then, Now, and the Future
A Abernathy et al, National Academy of Medicine discussion paper, June 27, 2022 (Posted: Jun-27-2022 11AM)

Over the past several decades, the development and accelerated advancement of digital technology has prompted change across virtually all aspects of human endeavor. The positive and negative effects of these changes have been and will remain the focus of active speculation, including the implications for human health. Application of mechanical and digital recording and capture of physical status, experiences, and narratives have set the stage for revolutionary progress in individual health and medical management, population-wide health strategies, and integrated real-time generation of new knowledge and insights.

UK National Screening Committee's approach to reviewing evidence on artificial intelligence in breast cancer screening
S Taylor-Phillips et al, The Lancet Digital Health, July, 2022 (Posted: Jun-22-2022 11AM)

When considering cancer detection, AI test sensitivity alone is not sufficiently informative, and additional information on the spectrum of disease detected and interval cancers is crucial to better understand the benefits and harms of screening. Although large retrospective studies might provide useful evidence by directly comparing test accuracy and spectrum of disease detected between different AI systems and by population subgroup, most retrospective studies are biased due to differential verification (ie, the use of different reference standards to verify the target condition among study participants).

Smartphone apps in the COVID-19 pandemic
JA Pandit et al, Nature Biotechnology, June 20,2022 (Posted: Jun-20-2022 6PM)

Smartphone apps, given accessibility in the time of physical distancing, were widely used for tracking, tracing and educating the public about COVID-19. Despite limitations, such as concerns around data privacy, data security, digital health illiteracy and structural inequities, there is ample evidence that apps are beneficial for understanding outbreak epidemiology, individual screening and contact tracing. While there were successes and failures in each category, outbreak epidemiology and individual screening were substantially enhanced by the reach of smartphone apps and accessory wearables.

Watching Parkinson’s disease with wrist-based sensors
JA Diao et al, NPJ Digital Medicine, June 13, 2022 (Posted: Jun-13-2022 7AM)

Parkinson’s disease (PD) lacks sensitive, objective, and reliable measures for disease progression and response. This presents a challenge for clinical trials given the multifaceted and fluctuating nature of PD symptoms. Innovations in digital health and wearable sensors promise to more precisely measure aspects of patient function and well-being. Beyond research trials, digital biomarkers and clinical outcome assessments may someday support clinician-initiated or closed-loop treatment adjustments.

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
JH Thygesen et al, The Lancet Digital Health, June 8, 2022 (Posted: Jun-09-2022 10AM)

Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes).

Key components of successful digital remote monitoring in oncology.
Wells Mary et al. Nature medicine 2022 6 (Posted: Jun-07-2022 8AM)

Although digital interventions are not new to the oncology field, the COVID-19 pandemic has accelerated the wide adoption of technological solutions for remote monitoring4. This has created an urgent need for high-quality evidence to support the implementation of remote monitoring for patients with cancer. In this issue of Nature Medicine, a new study reports the findings of the first randomized controlled trial of a digital remote monitoring intervention (CAPRI) for patients receiving oral anti-cancer therapy.

Digital Health Applications in Oncology: An Opportunity to Seize.
Parikh Ravi B et al. Journal of the National Cancer Institute 2022 5 (Posted: Jun-05-2022 7AM)

This article summarizes the current state of digital health technologies in medical practice and strategies to improve clinical utility and integration. These recommendations, with calls to action for clinicians, health systems, technology innovators, and policymakers, will facilitate efficient yet safe integration of digital health technologies into cancer care.

Multinational landscape of health app policy: toward regulatory consensus on digital health
JA Diao et al, NPJ Digital Medicine, May 11, 2022 (Posted: May-11-2022 7AM)

Due to its enormous capacity for benefit, harm, and cost, health care is among the most tightly regulated industries in the world. But with the rise of smartphones, an explosion of direct-to-consumer mobile health applications has challenged the role of centralized gatekeepers. As interest in health apps continue to climb, national regulatory bodies have turned their attention toward strategies to protect consumers from apps that mine and sell health data, recommend unsafe practices, or simply do not work as advertised.

Wearable fitness tracker use in federally qualified health center patients: strategies to improve the health of all of us using digital health devices
M Holko et al, NPJ Digital Medicine, April 25, 2022 (Posted: Apr-25-2022 7AM)

As the use of connected devices rises, an understanding of how digital health technologies can be used for equitable healthcare across diverse communities is needed. We surveyed 1007 adult patients at six Federally Qualified Health Centers that are a part of the All of Us Consortium regarding wearable fitness trackers. Findings indicate the majority interest in having fitness trackers. Barriers included cost and lack of information, revealing that broad digital health device adoption requires education, investment, and high-touch methods.

The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review
M Mitratza et al, Lancet Digital Health, May 2022 (Posted: Apr-22-2022 1PM)

Of 3196 records identified and screened, 12 articles and 12 study protocols were analysed. Most included articles had a moderate risk of bias, as per the National Institute of Health Quality Assessment Tool for Observational and Cross-Sectional Studies. The accuracy of algorithmic models to detect SARS-CoV-2 infection varied greatly (area under the curve 0·52–0·92). An algorithm's ability to detect presymptomatic infection varied greatly (from 20% to 88% of cases), from 14 days to 1 day before symptom onset. Increased heart rate was most frequently associated with SARS-CoV-2 infection, along with increased skin temperature and respiratory rate. All 12 protocols described prospective studies that had yet to be completed or to publish their results, including two randomised controlled trials. The evidence surrounding wearable devices in the early detection of SARS-CoV-2 infection is still in an early stage.

The medical algorithmic audit
X Liu et al, Lancet Digital Health, April 2022 (Posted: Apr-10-2022 3PM)

We propose a medical algorithmic audit framework that guides the auditor through a process of considering potential algorithmic errors in the context of a clinical task, mapping the components that might contribute to the occurrence of errors, and anticipating their potential consequences. We suggest several approaches for testing algorithmic errors, including exploratory error analysis, subgroup testing, and adversarial testing, and provide examples from our own work and previous studies. The medical algorithmic audit is a tool that can be used to better understand the weaknesses of an artificial intelligence system and put in place mechanisms to mitigate their impact.

Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study
LO Rayner et al, Lancet Digital Health, April 5, 2022 (Posted: Apr-07-2022 10AM)

Digital biomarkers: Convergence of digital health technologies and biomarkers
D Vasudevan et al, NPJ Digital Medicine, March 25, 2022 (Posted: Mar-26-2022 3PM)

Increasing digitization across the healthcare continuum has revolutionized medical research, diagnostics, and therapeutics. This digitization has led to rapid advancements in the development and adoption of Digital Health Technologies (DHT) by the healthcare ecosystem. With the proliferation of DHTs, the term ‘digital biomarker’ has been increasingly used to describe a broad array of measurements. Our objectives are to align the meaning of ‘digital biomarker’ with established biomarker terminology and to highlight opportunities to enable consistency in evidence generation and evaluation, improving the assessment of scientific evidence for future digital biomarkers.

Culturally adapting internet- and mobile-based health promotion interventions might not be worth the effort: a systematic review and meta-analysis
S Balci et al, NPJ Digital Medicine, March 23, 2022 (Posted: Mar-24-2022 8AM)

Out of 9438 records, 13 randomized controlled trials (RCT) investigating culturally adapted health promotion IMI addressing healthy eating, physical activity, alcohol consumption, sexual health behavior, and smoking cessation included. From the included studies 10,747 participants were eligible. Culturally adapted IMI proved to be non-superior over active control conditions in short- (g?=?0.10, [95% CI -0.19 to 0.40]) and long-term (g?=?0.20, [95% CI -0.11 to 0.51]) in promoting health behavior. However, culturally adapted IMI for physical activity (k?=?3, N?=?296) compared to active controls yielded a beneficial effect in long-term (g?=?0.48, [95%CI 0.25 to 0.71]).

Smartphone applications for informal caregivers of chronically ill patients: a scoping review
MG Marguarido et al, NPJ Digital Medicine, March 21, 2022 (Posted: Mar-21-2022 7AM)

36 articles were included, encompassing 26 applications. Of these, smartphone applications were designed for use only by caregivers (n?=?15), with a few applications also intended to be used with patients (n?=?5), healthcare providers (n?=?4), or all three roles (n?=?2). Most applications targeted a single chronic condition (n?=?25), with Alzheimer’s and other dementia being the most common (n?=?18). Only one application was designed for management of multiple chronic conditions. Long-term evaluation methods are needed to continually assess the impact of applications on a range of process and health outcomes, such as usability, caregiver burden, and quality of life.

Health app policy: international comparison of nine countries’ approaches
A Essen et al, NPJ Digital Medicine, March 18, 2022 (Posted: Mar-18-2022 7AM)

We found that most approaches aim for centralized pipelines for health app approvals, although some countries are adding decentralized elements. While the countries studied are taking diverse paths, there is nevertheless broad, international convergence in terms of requirements in the areas of transparency, health content, interoperability, and privacy and security. The sheer number of apps on the market in most countries represents a challenge for clinicians and patients. Our analyses of the relevant policies identified challenges in areas such as reimbursement, safety, and privacy.

Diagnostic accuracy of mercurial versus digital blood pressure measurement devices: a systematic review and meta-analysis
M Muniyandi et al, Scientific Reports, March 1, 2022 (Posted: Mar-02-2022 7AM)

The digital blood pressure monitoring has a moderate level of accuracy and the device can correctly distinguish hypertension with a pooled estimate sensitivity of 65.7% and specificity of 95.9%. After removing one study, which had very low sensitivity and very high specificity, the pooled sensitivity estimate was 79%, and the specificity was 91%. The meta-analysis of DOR suggests that the digital blood pressure monitor had moderate accuracy with a mercury sphygmomanometer. This will provide the clinician and patients with accurate information on blood pressure with which diagnostic and treatment decisions could be made.

Preventing Digital Overdiagnosis.
Capurro Daniel et al. JAMA 2022 1 (Posted: Jan-22-2022 2PM)

The accelerated adoption of digital technologies in people’s lives is creating unique opportunities to leverage routinely collected digital data and machine learning models to diagnose diseases before they become symptomatic. Like traditional tests, digital screening will likely generate cases of overdiagnosis and thereby harm some patients. Digital screening tests (such as detecting mood or sleep disorders from smartphone use patterns) are being developed faster than the ability to assess their value. The additional risks and benefits of these digital tests are not only a function of their accuracy; and it is important that such approaches be validated prospectively.

Digital health tools for the passive monitoring of depression: a systematic review of methods
V de Angel et al, NPJ Digital Medicine, January 10, 2022 (Posted: Jan-11-2022 8AM)

The literature is characterized by small sample sizes, short follow-up duration and great variability in the quality of reporting, limiting the interpretability of pooled results. Bivariate analyses show consistency in statistically significant associations between depression and digital features from sleep, physical activity, location, and phone use data. Machine learning models found the predictive value of aggregated features. Given the pitfalls in the combined literature, these results should be taken purely as a starting point for hypothesis generation.

Management of cardiovascular disease using an mHealth tool: a randomized clinical trial
SH Kang e al, NPJ Digital Medicine, December 3, 2021 (Posted: Dec-05-2021 3PM)

This randomized controlled, single-center, open-label trial tested the impact of a mobile health (mHealth) service tool optimized for ASCVD patient care. Patients with clinical ASCVD were enrolled and randomly assigned to the intervention or control group. Participants in the intervention group were provided with a smartphone application named HEART4U, while a dedicated interface integrated into the electronic healthcare record system was provided to the treating physicians

Sports related concussion: an emerging era in digital sports technology
D Powell et al, NPJ Digital Medicine, December 2, 2021 (Posted: Dec-03-2021 11AM)

We provide insights into sports-related concussion (SRC) clinical assessment methods and the translational utility of digital approaches, with a focus on off-field digital techniques to detect key SRC metrics/biomarkers. We also provide insights and recommendations to the common benefits and challenges facing digital approaches as they aim to transition from novel technologies to an efficient, valid, reliable, and integrated clinical assessment tool for SRC.

Digital transformation could increase the burden of treatment on patients
FS Mair et al, BMJ, November 25, 2021 (Posted: Nov-26-2021 10AM)

Digital health has the potential to reduce the burden of treatment for some. The ability to tele-consult (via telephone or video) can reduce the number of visits to health professionals. Attending clinic or hospital appointments is time consuming, can be stressful, and may entail considerable expense and effort. The distance a person must travel, availability and affordability of transportation, building accessibility, and whether the appointment requires the person to negotiate time off work or childcare, can all influence the perceived burden of treatment associated with attending appointments. Reducing these visits through teleconsulting can lessen the burden of treatment for those with busy home or work lives, for those for whom accessing transportation is difficult or expensive, or those with disabilities (visible or invisible). However, teleconsulting via video requires access to fast broadband and wi-fi in the home and assumes that people can use these systems

Bias and privacy in AI's cough-based COVID-19 recognition
HB Espinoza et al, Lancet Digital Health, December 2021 (Posted: Nov-25-2021 9AM)

Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review
SR Knight et al, NPJ Digital Medicine, November 12, 2021 (Posted: Nov-13-2021 6AM)

6969 articles were screened, with 44 articles included. The majority (n?=?34) described small prospective study designs, with a high risk of bias demonstrated. Reporting standards were suboptimal across all domains, particularly in relation to data security, prior patient engagement and cost analysis. Despite the potential of digital health interventions to improve postoperative patient care, current progress is severely restricted by limitations in methodological reporting.

Evaluating the reliability of mobility metrics from aggregated mobile phone data as proxies for SARS-CoV-2 transmission in the USA: a population-based study
N Kishore et al, The Lancet Digital Health, November 2, 2021 (Posted: Nov-03-2021 10AM)

In this population-based study, we collected epidemiological data on COVID-19 cases and deaths, as well as human mobility metrics collated by advertisement technology that was derived from global positioning systems, from 1396 counties across the USA that had at least 100 laboratory-confirmed cases of COVID-19.We show that the reproduction number is most strongly associated with mobility proxies for change in the travel into counties (0·757 [95% CI 0·689 to 0·857]), but this relationship primarily holds for counties in the three most urban categories as defined by the NCHS. This relationship weakens considerably after the initial 15 weeks of the epidemic (0·442 [-0·492 to -0·392]), consistent with the emergence of more complex local policies and behaviors, including masking.

Focusing on Digital Health Equity
CR Lyles et al, JAMA, October 22, 2021 (Posted: Oct-22-2021 1PM)

The pandemic provided examples of troubling barriers to digital health access, such as low uptake of video visits among underserved populations2 and disproportionate barriers to access to online vaccination appointments for communities most affected by the pandemic. These gaps reflect both structural deficiencies within the digital infrastructure in the US as well as a lack of attention to equity within the development and implementation of digital platforms and solutions. Achieving digital health equity entails not only ensuring access to digital infrastructure but also designing digital health solutions with the broad range of end users in mind.

A systematic review of smartphone-based human activity recognition methods for health research
M Strackiewiz et al, NPJ Digital Medicine (Posted: Oct-19-2021 6AM)

We identified 108 articles and described the various approaches used for data acquisition, data preprocessing, feature extraction, and activity classification, identifying the most common practices, and their alternatives. We conclude that smartphones are well-suited for HAR research in the health sciences. For population-level impact, future studies should focus on improving the quality of collected data, address missing data, incorporate more diverse participants and activities, relax requirements about phone placement, provide more complete documentation on study participants, and share the source code of the implemented methods and algorithms.

Blockchain applications in health care for COVID-19 and beyond: a systematic review
WY Ng et al, Lancet Digital Health, October 2021 (Posted: Oct-17-2021 6PM)

The COVID-19 pandemic has had a substantial and global impact on health care, and has greatly accelerated the adoption of digital technology. One of these emerging digital technologies, blockchain, has unique characteristics (eg, immutability, decentralization, and transparency) that can be useful in multiple domains (eg, management of electronic medical records and access rights, and mobile health). We conducted a systematic review of COVID-19-related and non-COVID-19-related applications of blockchain in health care.

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes
A Polhemus et al, NPJ Digital Medicine, October 14, 2021 (Posted: Oct-16-2021 7AM)

Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice.

Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials
M Cucchiniello et al, NPJ Digital Medicine, October 5, 2021 (Posted: Oct-05-2021 6AM)

We identified 69 studies on diabetes (n?=?29), cardiovascular diseases (n?=?13), chronic respiratory diseases (n?=?13), cancer (n?=?10) or their combinations (n?=?4). The apps rarely adopted developmental factors in the design stage, with only around one-third of studies reporting user or healthcare professional engagement. Findings were not significant for the majority of studies across all CD, with most RCTs revealing a high risk of bias.

Cultural adaptation: a framework for addressing an often-overlooked dimension of digital health accessibility
JS Marwaha et al, NPJ Digital Medicine, October 1, 2021 (Posted: Oct-01-2021 6AM)

Relatively little is known about how to make digital health tools accessible to different populations from a cultural standpoint. Alignment with cultural values and communication styles may affect these tools’ ability to diagnose and treat various conditions. In this Editorial, we highlight the findings of recent work to make digital tools for mental health more culturally accessible, and propose ways to advance this area of study.

Mobile health technology for diverse populations: challenges and opportunities
JA Diao et al, NPJ Digital Medicine, September 6, 2021 (Posted: Sep-06-2021 7AM)

Nearly half of US adults have hypertension, and three in four cases are not well-controlled. Due to structural barriers, underserved communities face greater burdens of disease, less consistent management, and worse outcomes. Mobile technology presents an opportunity to reduce financial, geographic, and workforce barriers, but little data currently support its use in populations with digital disparities. A recent article systematically reviews the literature to quantify outcomes for these populations and provide a roadmap toward more inclusive mobile health strategies.

Health Literacy in the Digital Age: Applications to Genomics
Slide presentation, CDC webinar, June 2021 Brand (Posted: Sep-04-2021 8AM)

With the recent COVID-19 pandemic, patients are turning more to online information sources and telehealth services to address their healthcare needs. Digital health literacy plays an increasingly important role in understanding information and in patient-provider communication. This has implications across disease prevention and the healthcare continuum including the field of genetics.

Paying for Digital Health Care - Problems with the Fee-for-Service System.
Adler-Milstein Julia et al. The New England journal of medicine 2021 8 (10) 871-873 (Posted: Sep-02-2021 8AM)

Although billing for more units of (digital) care will increase clinical revenue, such a shift could have substantial negative consequences. Administrative costs will increase because of the increased number of bills submitted and, more important, because of complex billing requirements and related documentation.

Effect of a Mobile App on Prehospital Medication Errors During Simulated Pediatric Resuscitation A Randomized Clinical Trial
JN Siebert et al, JAMA Network Open, August 30, 2021 (Posted: Aug-31-2021 8AM)

In this multicenter, simulation-based, randomized clinical trial including 150 advanced paramedics in 14 emergency medical services centers and 600 drug preparations, the proportion of medication errors committed during sequential preparation of 4 intravenous emergency drugs in prehospital settings was significantly decreased with the use of the app in absolute terms by 66.5%.

The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data
JL Kephart et al, Lancet Digital Health, August 26, 2021 (Posted: Aug-27-2021 6AM)

In this longitudinal ecological study, we compiled aggregated mobile phone location data, daily confirmed COVID-19 cases, and features of urban and social environments to analyze population mobility and COVID-19 incidence at the subcity level among cities with more than 100?000 inhabitants in Argentina, Brazil, Colombia, Guatemala, and Mexico. Reduced population movement within a subcity area is associated with a subsequent decrease in COVID-19 incidence among residents of that subcity area.

Cultural adaptation of internet- and mobile-based interventions for mental disorders: a systematic review
K Spanhel et al, NPJ Digital Medicine, August 25, 2021 (Posted: Aug-26-2021 7AM)

Providing accessible and effective healthcare solutions for people living in low- and middle-income countries, migrants, and indigenous people is central to reduce the global mental health treatment gap. Internet- and mobile-based interventions (IMI) are considered scalable psychological interventions to reduce the burden of mental disorders and are culturally adapted for implementation in these target groups.

The potential use of digital health technologies in the African context: a systematic review of evidence from Ethiopia
T Manyazewal et al, NPJ Digital Medicine, August 17, 2021 (Posted: Aug-17-2021 7AM)

Digital health: how to govern during a never-ending data tsunami
DS Muntz, NPJ Digital Medicine, August 10, 2021 (Posted: Aug-10-2021 3PM)

Good data governance requires principles1 to help guide people who produce and consume data. The three primary activities of a good data governance process are communication, coordination, and most importantly, collaboration. These 3Cs are force multipliers. Harnessing the power of a tsunami requires strong principles-based governance.

Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study
LS Canas et al, Lancet Digital Health, July 29, 2021 (Posted: Jul-30-2021 6AM)

In this large-scale, prospective, epidemiological surveillance study, we used prospective, observational, longitudinal, self-reported data from participants in the UK on 19 symptoms over 3 days after symptoms onset and COVID-19 PCR test results extracted from the COVID-19 Symptom Study mobile phone app.Our results suggest that a hierarchical Gaussian process model is effective in predicting SARS-CoV-2 infection when earlier symptoms are considered. This study represents a novel effort to identify and refer individuals for COVID-19 testing, enabling a more efficient allocation of medical resources during crucial stages of a pandemic.

Power to the people
Editorial, Lancet Digital Health, July 2021 (Posted: Jul-29-2021 8AM)

Artificial intelligence (AI) for health is a rapidly evolving field, with many potential benefits and risks, but governing bodies are struggling to keep pace. This lag is further fuelled by a lack of comprehensive international guidance on how to ensure AI for health complies with ethical norms and human rights standards. To address this gap, WHO has published guidance on the ethics and governance of AI for health.

Anosmia, ageusia, and other COVID-19-like symptoms in association with a positive SARS-CoV-2 test, across six national digital surveillance platforms: an observational study
CH Sudre et al, Lancet Digital Health, July 2021 (Posted: Jul-27-2021 11AM)

Despite differences in syndromic surveillance methods, access to and timing of SARS-CoV-2 testing, and disease prevalence, anosmia or ageusia were consistently the strongest predictors of COVID-19 infection across all platforms over time. The odds of a positive COVID-19 test was nearly 17 times higher among individuals with anosmia or ageusia than those without these symptoms. Fever and respiratory symptoms (shortness of breath and cough) also ranked highly in their association with test positivity. This large, collaborative analysis showed that anosmia–ageusia, fever, shortness of breath, and cough are suitable empirical signals of ongoing COVID-19 transmission.

Bridging the Digital Divide in Healthcare to Improve Access to Care
ASTHO, July 2021 (Posted: Jul-24-2021 7AM)

The Federal Communications Commission reports that 19 million Americans still lack access to highspeed internet. As telehealth becomes more accessible due to increased federal funding investments and lifted policy restrictions catalyzed by the COVID-19 pandemic, the disparities in access to technology used for telehealth (i.e., smartphones, laptops) and high-speed broadband remain. This digital divide in healthcare remains a challenge, creating a growing a division between communities who have access to digital health technologies and efficient broadband resources versus those who experience limited access due to socioeconomic, geographic, and financial barriers.

Mobile health strategies for blood pressure self-management in urban populations with digital barriers: systematic review and meta-analyses
EC Khoong et al, NPJ Digital Medicine, July 22, 2021 (Posted: Jul-23-2021 7AM)

Mobile health (mHealth) technologies improve hypertension outcomes, but it is unknown if this benefit applies to all populations. This review aimed to describe the impact of mHealth interventions on blood pressure outcomes in populations with disparities in digital health use.

The new platforms of health care
ER Dorsey, NPJ Digital Health (Posted: Jul-16-2021 7AM)

Mobile app validation: a digital health scorecard approach
R Sedhom et al, NPJ Digital Medicine, July 14, 2021 (Posted: Jul-16-2021 7AM)

We investigated the pragmatic application of a previously described framework for digital health validation, the Digital Health Scorecard, in a cohort of 22 popular mobile health oncology apps. The apps evaluated using this framework performed poorly, scoring 49.4% across all evaluation criteria as a group.

The powers and perils of using digital data to understand human behaviour
Nature Editorial, July 2021 (Posted: Jul-05-2021 11AM)

During the course of the coronavirus pandemic alone, researchers have been able to access millions of mobile-phone records to study how people’s movement changed during the pandemic and the impact of those changes on how SARS-CoV-2 spread. They have been able to access anonymized credit-card purchase histories to study how people are spending money during the pandemic — information which is then used to understand how COVID-19 is affecting various sectors of the economy.

Race representation matters in cancer care
Lancet Digital Health, June 2021 (Posted: Jun-26-2021 7AM)

Without reporting how representative existing datasets are, we cannot understand if potentially lifesaving technologies for cancer screening and diagnosis are built for use by everyone. In response, the National Institutes of Health launched the All of Us initiative in 2015 with ambitious goals to collect genomic data from one million people, with a focus on recruiting minority ethnic volunteers. However, there continues to be a paucity of data from non-White populations, widening the gap between those who already benefit and those who do not.

‘It’s hard to know what’s trustworthy’: A new research effort aims to vet digital health data from wearables
K Palmer, Stat News, June 22, 2021 (Posted: Jun-23-2021 8AM)

Digital health: balancing innovation and cybersecurity
Lancet Respiratory Medicine editorial, June 16, 2021 (Posted: Jun-17-2021 9AM)

Digital health is an area of medicine that has seen huge acceleration and investment globally over the past decade—even more so during the COVID-19 pandemic, when reliance on digital and telehealth has been essential. With this growth in digital health, however, comes concern surrounding the use of digital patient data and the associated risks of cybersecurity breaches.

Big data, artificial intelligence, and the opioid crisis
Lancet Digital Health editorial, June 1, 2021 (Posted: May-26-2021 6AM)

Big data and artificial intelligence can help to target preventive measures (eg, addressing comorbidities and socioeconomic inequalities) to reduce future risks of opioid misuse. Community-level modelling can forecast the number of fatal overdoses that could be avoided through wider availability of key treatments. But model explainability and integration of individual-level factors— clinical and social—are crucial to remove barriers and ensure prevention and treatment efforts are accessible to all.

Glucose monitors revolutionized diabetes care. Now digital health startups want to bring them to the masses
K Palmer, Stat News, April 15, 2021 (Posted: Apr-16-2021 6AM)

The flood of startups belies their belief in the opportunity for glucose monitoring to improve health, especially in the U.S., where the burden of metabolic disease is especially high. Each targets a slightly different subset of users while steering clear of any medical claims.

Digital Health Passes in the Age of COVID-19- Are “Vaccine Passports” Lawful and Ethical?
LO Gostin et al, JAMA, April 7, 2021 (Posted: Apr-07-2021 11AM)

Digital health passes could become an important vehicle for a rapid return to commerce, recreation, and travel. To ensure their success, they must be scientifically well grounded and the least restrictive alternative. Above all, DHPs must be administered equitably, ensuring that everyone has a fair chance to return to a normal life.

Digital health interventions in palliative care: a systematic meta-review
AM Finucane, et al, NPJ Digital Medicine, April 2021 (Posted: Apr-07-2021 6AM)

This meta-review revealed 21 relevant systematic reviews, encompassing 332 publications. Interventions delivered via videoconferencing (17%), electronic healthcare records (16%) and phone (13%) were most frequently described in studies within reviews. DHIs were typically used in palliative care for education (20%), symptom management (15%), decision-making (13%), information provision or management (13%) and communication (9%).

Applications of Digital Tools for Precision Public Health in the COVID-19 Era: Where Are We?
M Khoury et al, CDC Blog, March 29, 2021 Brand (Posted: Mar-31-2021 8AM)

Two scoping reviews provide valuable insights into the current limitations of digital health technologies in public health. Significant challenges remain in adoption, scale-up, and integration into healthcare systems and public health programs. Other considerations include equity issues in deployment of such technologies among disproportionately affected groups.

The digital scribe in clinical practice: a scoping review and research agenda
MM van Buchem et al, NPJ Digital Medicine, March 26, 2021 (Posted: Mar-27-2021 7AM)

The number of clinician burnouts is increasing and has been linked to a high administrative burden. Automatic speech recognition (ASR) and natural language processing (NLP) techniques may address this issue by creating the possibility of automating clinical documentation with a “digital scribe”. We reviewed the current status of the digital scribe in development towards clinical practice and present a scope for future research.

Utility of a virtual counselor (VICKY) to collect family health histories among vulnerable patient populations: A randomized controlled trial.
Wang Catharine et al. Patient education and counseling 2021 (Posted: Mar-26-2021 9AM)

A virtual counselor overcomes many of the literacy-related barriers to using traditional digital tools and highlights an approach that may be important to consider when collecting health histories from vulnerable populations. The usability of digital health history tools will have important implications for the quality of the data collected and its downstream clinical utility.

Ushering in safe, effective, secure, and ethical medicine in the digital era
WJ Gordon et al, NPJ Digital Medicine, March 25, 2021 (Posted: Mar-26-2021 8AM)

From clinical trials to care delivery, advanced, digitally enabled technologies and analytics offer new approaches to how we think about medicine, health, and biology. The Covid-19 pandemic has accelerated this conversation, and forced a roadmap, once measured in years or decades, to unfold over days, weeks, and months.

Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study
Z Zhao et al, Lancet Digital Health, March 24, 2021 (Posted: Mar-25-2021 6AM)

In patients with COVID-19, artificial intelligence based on chest x-rays had better prognostic performance than clinical data or radiologist-derived severity scores. Using artificial intelligence, chest x-rays can augment clinical data in predicting the risk of progression to critical illness in patients with COVID-19.

Health Literacy in the Digital Age: Applications to Genomics
CDC Webinar, June 10, 2021 Brand (Posted: Mar-20-2021 11AM)

With the recent COVID-19 pandemic, patients are turning more to online information sources and telehealth services to address their healthcare needs. Digital health literacy plays an increasingly important role in understanding information and in patient-provider communication. This has implications across disease prevention and the healthcare continuum including the field of genetics. Register today to attend our June 10, 2021 webinar.

Applications of digital health for public health responses to COVID-19: a systematic scoping review of artificial intelligence, telehealth and related technologies
DV Gunasekeran et al, NPJ Digital Medicine, February 26, 2021 (Posted: Feb-27-2021 7AM)

Although a large quantity of reports investigated applications of artificial intelligence (AI) (44.9%, n?=?111/247) and big data analytics (36.0%, n?=?89/247), weaknesses in study design limit generalizability and translation, highlighting the need for more pragmatic real-world investigations.

Challenging racism in the use of health data
HE Knight et al, Lancet Digital Health, February 4, 2021 (Posted: Feb-06-2021 7AM)

The authors examine how structural inequalities, biases, and racism in society are easily encoded in datasets and in the application of data science, and how this practice can reinforce existing social injustices and health inequalities.

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database
C Lee et al, Lancet Digital Health ,February 3, 2021 (Posted: Feb-05-2021 7AM)

A novel machine learning-based approach produced a prognostic model, Survival Quilts, with discrimination for 10-year prostate cancer-specific mortality similar to the top-ranked prognostic models, using only standard clinicopathological variables. Additional data will likely improve model performance and accuracy for personalized prognostics.

Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.
Muehlematter Urs J et al. The Lancet. Digital health 2021 Jan (Posted: Jan-26-2021 9AM)

There has been a surge of interest in artificial intelligence and machine learning (AI/ML)-based medical devices. We searched governmental and non-governmental databases to identify 222 devices approved in the USA and 240 devices in Europe. The number of approved AI/ML-based devices has increased substantially since 2015, with many being approved for use in radiology. Of the 124 AI/ML-based devices commonly approved in the USA and Europe, 80 were first approved in Europe.

Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter
TK MacKey et al. Lancet Digital Health, Feb 2021 (Posted: Jan-26-2021 8AM)

Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis
UJ Muehlmatter et al, Lancet Digital Health, January 18, 2021 (Posted: Jan-19-2021 8AM)

We searched governmental and non-governmental databases to identify 222 devices approved in the USA and 240 devices in Europe. The number of approved AI/ML-based devices has increased substantially since 2015, with many being approved for use in radiology. However, few were qualified as high-risk devices.

Public Health Impact of Digital Health: Reinventing the Wheel
MJ Khoury et al, CDC Blog, January 15, 2021 Brand (Posted: Jan-16-2021 3PM)

As digital health technologies become standardized and interoperable, and as evidence of utility develops, health care and public health will become more efficient and effective, ushering the new era of precision medicine. At the same time, potential risks and harms must be addressed. Until then, digital health adoption will be a challenge to its widespread use. Just like genomic tests, there are no shortcuts on the long road to evidence-based digital health.

Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use
J Levy et al, NPJ Digital Medicine, January 4, 2021 (Posted: Jan-04-2021 3PM)

The goal of this study was to identify and validate digital oximetry biomarkers (OBMs) for creating a reference toolbox for continuous oximetry time series analysis. We review the sleep medicine literature to identify clinically relevant OBMs. We implement these biomarkers and demonstrate their clinical value within the context of obstructive sleep apnea diagnosis.

Artificial intelligence bridges the complexity of intractable medical problems
B McCall, Lancet Digital Health, January 2021 (Posted: Dec-30-2020 3PM)

Nestled within a web of interactions between genes and environment, the sheer enormity of data on the factors that drive these complex medical problems is insurmountable using conventional methods of analysis alone. However, as artificial intelligence (AI) becomes an ever more powerful tool, so it promises to help us understand both causal risk factors and predict outcomes that can change the course and burden of these diseases.

Digital Health—The Need to Assess Benefits, Risks, and Value
E Perakslis et al, JAMA, December 28, 2020 (Posted: Dec-28-2020 11AM)

Digital health includes personal wearable devices and internal devices as well as sensors in people, homes, cars, and communities. Digital health can help identify health risks and assist with diagnosis, treatment, and monitoring of health. Digital health has potential to improve health management, but the current state of technology development and deployment requires a “buyer beware” cautionary note.

Advancing digital health: FDA innovation during COVID-19
K Kadakia et al, NPJ Digital Medicine, December 2020 (Posted: Dec-21-2020 7AM)

The U.S. Food and Drug Administration (FDA) has issued a number of temporary policies to support digital health innovation during the pandemic, such as guidance documents to expand the use of digital therapeutics for psychiatric disorders and medical devices for remote patient monitoring.

Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test
AAS Soltan et al, Lancet Digital Health, December 11, 2020 (Posted: Dec-14-2020 9AM)

This was the largest laboratory artificial intelligence study on COVID-19 to date, training with clinical data from more than 115?000 patients presenting to hospital, and the first to integrate laboratory blood tests with point-of-care measurements of blood gases and vital signs.

2021: research and medical trends in a post-pandemic world
M May, Nature Medicine, December 7, 2020 (Posted: Dec-10-2020 11AM)

Goodbye 2020: Research and medical trends in a post-pandemic world include a new normal, open repositories, leaps ahead for immunology, more digital health and better preparedness.

Why Healthcare Won’t Go Back to the Way It Was
E Li, the Atlantic, November 2020 (Posted: Dec-01-2020 8AM)

Before COVID-19, people’s adoption of digital health services had stalled. But as the pandemic circled the globe, virtual healthcare services became a necessity for millions of people as efforts to slow transmission of the coronavirus sharply limited face-to-face visits with doctors and care professionals.

Predicting the risk of developing diabetic retinopathy using deep learning
A Bora et al, Lancet Digital Health, November 26, 2020 (Posted: Nov-27-2020 2PM)

We created and validated a deep-learning system to predict the development of diabetic retinopathy in patients with diabetes who had had teleretinal diabetic retinopathy screening in a primary care setting. Deep-learning systems predicted diabetic retinopathy development using color fundus photographs, and the systems were independent of and more informative than available risk factors. Such a tool might help to optimize screening intervals to improve vision-related outcomes.

Push Button Population Health: The SMART/HL7 FHIR Bulk Data Access Application Programming Interface
K Mandl et al, NPJ Digital Medicine, November 19, 2020 (Posted: Nov-20-2020 9AM)

The Office of the National Coordinator of Health Information Technology (ONC) published a rule—21st Century Cures Act Interoperability, Information Blocking, and the ONC Health IT Certification Program—regulating the API requirement along with protections against information blocking. The rule specifies the SMART/HL7 FHIR Bulk Data Access API, which enables access to patient-level data across a patient population, supporting use cases in healthcare, research, and public health.

Digital Health Technologies and the Drug Development Life Cycle
The National Academies, November 2020 (Posted: Nov-18-2020 10AM)

As part of continued work on this topic, the National Academies hosted a virtual public workshop, titled “The Role of Digital Health Technologies in Drug Development.” The workshop provided a venue for stakeholders to discuss challenges and opportunities in using DHTs to improve the probability of success in drug R&D.

What's next for COVID-19 apps? Governance and oversight
A Blasimme et al, Science, November 13, 2020 (Posted: Nov-13-2020 9AM)

Digital health technologies are a promising tool to address COVID-19. But deploying these systems is fraught with challenges, and most national DCT apps have not yet had the expected rate of uptake. This can be attributed to uncertainties regarding general awareness of apps, privacy risks, actual effectiveness of DCT, as well as public attitudes toward a potentially pervasive form of digital surveillance. DCT thus appears to face a typical social control dilemma.


Disclaimer: Articles listed in Hot Topics of the Day are selected by the CDC Office of Genomics and Precision Public Health to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.