Joseph D. Harrison at AMA Journal of Ethics: “Nudges are subtle changes to the design of the environment or the framing of information that can influence our behaviors. There is significant potential to use nudges in health care to improve patient outcomes and transform health care delivery. However, these interventions must be tested and implemented using a systematic approach. In this article, we describe several ways to design nudges for success by focusing on optimizing and fitting them into the clinical workflow, engaging the right stakeholders, and rapid experimentation….(More)”.
How Integrated Data Can Support COVID-19 Crisis and Recovery
Blog by Actionable Intelligence for Social Policy (AISP): “…State and local leaders are called upon to respond to the immediate harms of COVID-19. Yet with a looming recession threatening to undo gains among marginalized groups — particularly the Black middle class — tools to understand and disrupt long-term impacts on economic mobility and well-being are also urgently needed.
Administrative data[3] — the information collected during the course of routine service delivery, program administration, and business operations — provide an essential tool to help policymakers, community leaders, and researchers understand short- and long-term impacts of the pandemic. Several jurisdictions now have the capacity to link administrative data across programs in order to better understand how individuals interact with multiple systems, study longitudinal outcomes, and identify vulnerable subpopulations. As the COVID-19 crisis reveals weaknesses in the U.S. social safety net, states and localities with integrated administrative data infrastructure can use their capacity to identify populations and needs otherwise overlooked. Youth who “age out” of the child welfare system or individuals experiencing chronic homelessness often remain invisible when using traditional methods, aggregate data, or administrative records from a single source.
This blogpost demonstrates how nimble state and local data integration efforts have leveraged their capacity to quickly respond to and understand the impacts of COVID-19, while also reflecting on what can be done to mitigate harm and shift thinking about social welfare and the safety net….(More)”.
Encouraging Participation and Cooperation in Contact Tracing
Lessons from Survey Research by National Academies of Sciences, Engineering, and Medicine: “Contact tracing shares important features with the collection of survey data, as well as the taking of the U.S. Census. This rapid expert consultation suggests proven strategies from survey research that decision makers can use to encourage participation in and cooperation with contact tracing efforts along two fronts: encouraging individuals to respond to outreach from health department officials regarding participation in contact tracing and case investigation, and encouraging those who do participate to share information about people whom they may have exposed to COVID-19.
Encouraging Participation and Cooperation in Contact Tracing is intended to help decision makers in local public health departments and local governments increase participation and cooperation in contact tracing related to COVID-19. This publication focuses on contact tracing methods that involve phone, text, or email interviews with people who have tested positive and with others they may have exposed to the virus…(More)”.
Applying new models of data stewardship to health and care data
Report by the Open Data Institute: “The outbreak of the coronavirus (Covid-19) has amplified and accelerated the need for an effective technology ecosystem that benefits everyone’s health. This report explores models of ‘data stewardship’ (the collection, maintenance and sharing of data) required to enable better evaluation
The pandemic has been accompanied by a marked increase in the use of digital technology, including introduction of remote consultation in general practice, new data flows to support the distribution of food and other essentials, and applications to support digital contact tracing.
This report explores models of ‘data stewardship’ (the collection, maintenance and sharing of data) required to enable better evaluation. It argues everybody involved in technology has a shared responsibility to enable evaluation, whether that means innovators sharing data for evaluation purposes, or healthcare providers being clearer, from the outset, about what data is needed to support effective evaluation.
This report re-envisages the role of evaluators as data stewards, who could use their positions as intermediaries to encourage stakeholders to share data, and help increase access to data for public benefit…(More)”.
Internet Searches for Acute Anxiety During the Early Stages of the COVID-19 Pandemic
Paper by John W. Ayers et al: “There is widespread concern that the coronavirus disease 2019 (COVID-19) pandemic may harm population mental health, chiefly owing to anxiety about the disease and its societal fallout. But traditional population mental health surveillance (eg, telephone surveys, medical records) is time consuming, expensive, and may miss persons who do not participate or seek care. To evaluate the association of COVID-19 with anxiety on a population basis, we examined internet searches indicative of acute anxiety during the early stages of the COVID-19 pandemic.Methods
The analysis relied on nonidentifiable, aggregate, public data and was exempted by the University of California San Diego Human Research Protections Program. Acute anxiety, including colloquially called anxiety attacks or panic attacks, was monitored because of its higher prevalence relative to other mental health problems. It can lead to other mental health problems (including depression), it is triggered by outside stressors, and it is socially contagious. Using Google Trends (https://trends.google.com/trends) we monitored the daily fraction of all internet searches (thereby adjusting the results for any change in total queries) that included the terms anxiety or panic in combination with attack (including panic attack, signs of anxiety attack, anxiety attack symptoms) that originated from the US from January 1, 2004, through May 4, 2020. Raw search counts were inferred using Comscore estimates (comscore.com).
We compared search volumes after President Trump declared a national COVID-19 emergency on March 13, 2020, with expected search volumes if COVID-19 had not occurred, thereby taking into account the historical trend and periodicity in the data. Expected volumes were computed using an autoregressive integrated moving average model,4 based on historical trends from January 1, 2004 to March 12, 2020, to predict counterfactual trends for March 13, 2020 to May 9, 2020. The expected volumes with prediction intervals (PIs) and ratio of observed and expected volumes with bootstrap CIs were computed using R statistical software (version 3.5.3, R Foundation). The results were similar if we varied our interruption date plus or minus 1 week….(More)”.
Data Mining on Open Public Transit Data for Transportation Analytics During Pre-COVID-19 Era and COVID-19 Era
Paper by Carson K. Leung et al: “As the urbanization of the world continues and the population of cities rise, the issue of how to effectively move all these people around the city becomes much more important. In order to use the limited space in a city most efficiently, many cities and their residents are increasingly looking towards public transportation as the solution. In this paper, we focus on the public bus system as the primary form of public transit. In particular, we examine open public transit data for the Canadian city of Winnipeg. We mine and conduct transportation analytics on data prior to the coronavirus disease 2019 (COVID-19) situation and during the COVID-19 situation. By discovering how often and when buses were reported to be too full to take on new passengers at bus stops, analysts can get an insight of which routes and destinations are the busiest. This information would help decision makers make appropriate actions (e.g., add extra bus for those busiest routines). This results in a better and more convenient transit system towards a smart city. Moreover, during the COVID-19 era, it leads to additional benefits of contributing to safer buses services and bus waiting experiences while maintaining social distancing…(More)”.
‘Selfies’ could be used to detect heart disease: new research uses artificial intelligence to analyse facial photos
European Society of Cardiology: “Sending a “selfie” to the doctor could be a cheap and simple way of detecting heart disease, according to the authors of a new study published today (Friday) in the European Heart Journal [1].
The study is the first to show that it’s possible to use a deep learning computer algorithm to detect coronary artery disease (CAD) by analysing four photographs of a person’s face.
Although the algorithm needs to be developed further and tested in larger groups of people from different ethnic backgrounds, the researchers say it has the potential to be used as a screening tool that could identify possible heart disease in people in the general population or in high-risk groups, who could be referred for further clinical investigations.
“To our knowledge, this is the first work demonstrating that artificial intelligence can be used to analyse faces to detect heart disease. It is a step towards the development of a deep learning-based tool that could be used to assess the risk of heart disease, either in outpatient clinics or by means of patients taking ‘selfies’ to perform their own screening. This could guide further diagnostic testing or a clinical visit,” said Professor Zhe Zheng, who led the research and is vice director of the National Center for Cardiovascular Diseases and vice president of Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China.
He continued: “Our ultimate goal is to develop a self-reported application for high risk communities to assess heart disease risk in advance of visiting a clinic. This could be a cheap, simple and effective of identifying patients who need further investigation. However, the algorithm requires further refinement and external validation in other populations and ethnicities.”
It is known already that certain facial features are associated with an increased risk of heart disease. These include thinning or grey hair, wrinkles, ear lobe crease, xanthelasmata (small, yellow deposits of cholesterol underneath the skin, usually around the eyelids) and arcus corneae (fat and cholesterol deposits that appear as a hazy white, grey or blue opaque ring in the outer edges of the cornea). However, they are difficult for humans to use successfully to predict and quantify heart disease risk.
Prof. Zheng, Professor Xiang-Yang Ji, who is director of the Brain and Cognition Institute in the Department of Automation at Tsinghua University, Beijing, and other colleagues enrolled 5,796 patients from eight hospitals in China to the study between July 2017 and March 2019. The patients were undergoing imaging procedures to investigate their blood vessels, such as coronary angiography or coronary computed tomography angiography (CCTA). They were divided randomly into training (5,216 patients, 90%) or validation (580, 10%) groups.
Trained research nurses took four facial photos with digital cameras: one frontal, two profiles and one view of the top of the head. They also interviewed the patients to collect data on socioeconomic status, lifestyle and medical history. Radiologists reviewed the patients’ angiograms and assessed the degree of heart disease depending on how many blood vessels were narrowed by 50% or more (≥ 50% stenosis), and their location. This information was used to create, train and validate the deep learning algorithm….(More)”.
Coronavirus (COVID-19) – Is Blockchain a True Savior in This Pandemic Crisis
Paper by Ajay Chawla and Sandra Ro: “The COVID-19 pandemic has impacted virtually all businesses, but the effect has not been stable yet. While the current disruption may present challenges to the blockchain industry in the short term, it will also unlock new opportunities in the mid and longer-term. By providing help in the COVID-19 crisis and recovery, blockchain can play a pivotal role in accelerating post-crisis digital transformation initiatives and solving those problems highlighted in the current system.
Of course, no one could have foreseen the unprecedented upheaval caused by the novel coronavirus (COVID-19) pandemic which has almost disrupted and dislocated economies and ecosystems across the planet but COVID-19 has brought supply chains to their knees.
Nevertheless, there are some bright spots where blockchain is used to combat the effects of COVID-19 and aid in the recovery process. These innovative use cases can demonstrate the benefits of blockchain to a wider audience.
Organizations including the World Health Organisation (WHO), Oracle, Microsoft, IBM, among other tech companies, government agencies, and international bodies are all working together to develop the blockchain-based platforms and solutions.
Blockchain technology is anchored by its ability to enable decentralized sharing of verified, trusted, and secure information among individuals or organizations. Furthermore, it can be paired with critical security and cryptography to protect the privacy of the users and individuals contributing data while still providing provenance and trust in the shared data.
By providing help in the COVID-19 crisis and recovery, blockchain can play a pivotal role in accelerating post-crisis digital transformation initiatives and solving those problems highlighted in the current system.
However, at the present moment, blockchain is not the panacea of all the problems. While the promise and potential of blockchain are undoubtedly transformative, it is still in the nascence of its evolution.
Keeping a tab on this technology and our capacities is the right direction we can head towards….(More)”.
Health Data Privacy under the GDPR: Big Data Challenges and Regulatory Responses
Book edited by Maria Tzanou: “The growth of data collecting goods and services, such as ehealth and mhealth apps, smart watches, mobile fitness and dieting apps, electronic skin and ingestible tech, combined with recent technological developments such as increased capacity of data storage, artificial intelligence and smart algorithms have spawned a big data revolution that has reshaped how we understand and approach health data. Recently the COVID-19 pandemic has foregrounded a variety of data privacy issues. The collection, storage, sharing and analysis of health- related data raises major legal and ethical questions relating to privacy, data protection, profiling, discrimination, surveillance, personal autonomy and dignity.
This book examines health privacy questions in light of the GDPR and the EU’s general data privacy legal framework. The GDPR is a complex and evolving body of law that aims to deal with several technological and societal health data privacy problems, while safeguarding public health interests and addressing its internal gaps and uncertainties. The book answers a diverse range of questions including: What role can the GDPR play in regulating health surveillance and big (health) data analytics? Can it catch up with the Internet age developments? Are the solutions to the challenges posed by big health data to be found in the law? Does the GDPR provide adequate tools and mechanisms to ensure public health objectives and the effective protection of privacy? How does the GDPR deal with data that concern children’s health and academic research?
By analysing a number of diverse questions concerning big health data under the GDPR from various different perspectives, this book will appeal to those interested in privacy, data protection, big data, health sciences, information technology, the GDPR, EU and human rights law….(More)”.
COVID Data Failures Create Pressure for Public Health System Overhaul
Kaiser Health News: “After terrorists slammed a plane into the Pentagon on 9/11, ambulances rushed scores of the injured to community hospitals, but only three of the patients were taken to specialized trauma wards. The reason: The hospitals and ambulances had no real-time information-sharing system.
Nineteen years later, there is still no national data network that enables the health system to respond effectively to disasters and disease outbreaks. Many doctors and nurses must fill out paper forms on COVID-19 cases and available beds and fax them to public health agencies, causing critical delays in care and hampering the effort to track and block the spread of the coronavirus.
There are signs the COVID-19 pandemic has created momentum to modernize the nation’s creaky, fragmented public health data system, in which nearly 3,000 local, state and federal health departments set their own reporting rules and vary greatly in their ability to send and receive data electronically.
Sutter Health and UC Davis Health, along with nearly 30 other provider organizations around the country, recently launched a collaborative effort to speed and improve the sharing of clinical data on individual COVID cases with public health departments.
But even that platform, which contains information about patients’ diagnoses and response to treatments, doesn’t yet include data on the availability of hospital beds, intensive care units or supplies needed for a seamless pandemic response.
The federal government spent nearly $40 billion over the past decade to equip hospitals and physicians’ offices with electronic health record systems for improving treatment of individual patients. But no comparable effort has emerged to build an effective system for quickly moving information on infectious disease from providers to public health agencies.
In March, Congress approved $500 million over 10 years to modernize the public health data infrastructure. But the amount falls far short of what’s needed to update data systems and train staff at local and state health departments, said Brian Dixon, director of public health informatics at the Regenstrief Institute in Indianapolis….(More)”.