155 hot topic(s) found with the query "Privacy"
Return of Results in Genomic Research Using Large-Scale or Whole Genome Sequencing: Toward a New Normal
(Posted: Apr 19, 2024 10AM)
From the abstract: "Genome sequencing is increasingly used in research and integrated into clinical care. In the research domain, large-scale analyses, including whole genome sequencing with variant interpretation and curation, virtually guarantee identification of variants that are pathogenic or likely pathogenic and actionable. Multiple guidelines recommend that findings associated with actionable conditions be offered to research participants in order to demonstrate respect for autonomy, reciprocity, and participant interests in health and privacy."
Organizational Factors in Clinical Data Sharing for Artificial Intelligence in Health Care.
Alaa Youssef et al. JAMA Netw Open 2023 12 (12) e2348422
(Posted: Dec 20, 2023 9AM)
From the abstract: "Are organizational factors associated with the motivation of health organizations to share clinical data for artificial intelligence (AI) development? In this qualitative study, 27 leaders from 18 health organizations were interviewed, and a predominant concern among them was data privacy risks. Most stakeholders viewed these as a substantial barrier for public health data sharing due to potential liability and reputational consequences; however, they identified external incentives as key factors for enhancing organizational motivation and fostering both within and across-sector data-sharing collaborations for AI development. The findings of this study suggest that data-sharing policies should be rooted in feasibility and incentivization strategies to promote responsible and equitable AI development in the health care sector. "
Risk perception and intended behavior change after uninformative genetic results for adult-onset hereditary conditions in unselected patients.
Nandana D Rao et al. Eur J Hum Genet 2023 9
(Posted: Sep 27, 2023 8AM)
From the abstract: "Overall, 2761 people received uninformative results and 1352 (49%) completed survey items. Respondents averaged 41 years old, 62% were female, and 56% were Non-Hispanic Asian. Results from the FACToR instrument showed mean (SD) scores of 0.92 (1.34), 7.63 (3.95), 1.65 (2.23), and 0.77 (1.50) for negative emotions, positive emotions, uncertainty, and privacy concerns, respectively, suggesting minimal psychosocial harms from genetic screening. Overall, 12.2% and 9.6% of survey respondents believed that their risk of cancer or heart disease, respectively, had changed after receiving their uninformative genetic screening results. Further, 8.5% of respondents planned to make healthcare changes and 9.1% other behavior changes. "
AI in Public Health
J Pina, ASTHO Blog, August 2023
(Posted: Aug 17, 2023 11AM)
Generative Artificial Intelligence (AI) tools have become increasingly available and accessible in recent years, empowering individuals and organizations to harness the potential of AI and machine learning. These newly available resources have sparked great curiosity within the public health community, and ASTHO members are considering the value of these tools in practice. Through ASTHO’s work in public health data modernization, and broadly in population health innovation, we’ve received many requests to address, recognize, and expound on the value and potential of AI in our field. However, as with any disruptive technology, responsible and ethical use is essential to ensure that these tools are employed in a manner that respects privacy, avoids misinformation, minimizes bias and inequities, and upholds societal well-being.
AI and Medical Education — A 21st-Century Pandora’s Box
A Cooper et al, NEJM, August 3, 2023
(Posted: Aug 02, 2023 6PM)
Many valid concerns have been raised about AI’s effects on medicine, including the propensity for AI to make up information that it then presents as fact (termed a “hallucination”), its implications for patient privacy, and the risk of biases being baked into source data. But we worry that the focus on these immediate challenges obscures many of the broader implications that AI could have for medical education — in particular, the ways in which this technology could affect the thought structures and practice patterns of medical trainees and physicians for generations to come.
Federated Analysis for Privacy-Preserving Data Sharing: A Technical and Legal Primer.
James Casaletto et al. Annu Rev Genomics Hum Genet 2023 5
(Posted: Jul 25, 2023 8AM)
Continued advances in precision medicine rely on the widespread sharing of data that relate human genetic variation to disease. However, data sharing is severely limited by legal, regulatory, and ethical restrictions that safeguard patient privacy. Federated analysis addresses this problem by transferring the code to the data—providing the technical and legal capability to analyze the data within their secure home environment rather than transferring the data to another institution for analysis.
Health Care Privacy Risks of AI Chatbots.
Genevieve P Kanter et al. JAMA 2023 7
(Posted: Jul 07, 2023 9AM)
With the debut of ChatGPT, clinicians and health systems are embracing a brainy, fluent colleague eager to assist with some of the most thankless tasks in medicine. The promise of an artificial intelligence (AI)–powered chatbot that has passed the US Medical Licensing Examination1 and can also—without complaining—prepare structured medical notes from a mélange of clinical facts, identify billing codes, and respond to patient portal messages appears to be an unmitigated boon.
AI Chatbots, Health Privacy, and Challenges to HIPAA Compliance.
Mason Marks et al. JAMA 2023 7
(Posted: Jul 07, 2023 9AM)
We are only beginning to understand the risks, including how chatbots threaten privacy. This Viewpoint examines the privacy concerns raised by medical uses of LLMs. We conclude that chatbots cannot comply with the Health Insurance Portability and Accountability Act (HIPAA) in any meaningful way despite industry assurances. Consequently, novel legal and ethical approaches are warranted, and patients and clinicians should use these products cautiously.
The imperative for regulatory oversight of large language models (or generative AI) in healthcare
B Mesko et al, NPJ Digital Medicine, July 6, 2023
(Posted: Jul 06, 2023 8AM)
The regulation of generative AI in medicine and healthcare without damaging their exciting and transformative potential is a timely and critical challenge to ensure safety, maintain ethical standards, and protect patient privacy. We argue that regulatory oversight should assure medical professionals and patients can use LLMs without causing harm or compromising their data or privacy. This paper summarizes our practical recommendations for what we can expect from regulators to bring this vision to reality.
Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge.
Zahir Kanjee et al. JAMA 2023 6
(Posted: Jun 19, 2023 1PM)
Generative AI is a promising adjunct to human cognition in diagnosis. The model evaluated in this study, similar to some other modern differential diagnosis generators, is a diagnostic “black box”; future research should investigate potential biases and diagnostic blind spots of generative AI models. Clinicopathologic conferences are best understood as diagnostic puzzles; once privacy and confidentiality concerns are addressed, studies should assess performance with data from real-world patient encounters.
A Review of the Role of Artificial Intelligence in Healthcare
A Al Kuweiti et al, J Per Med, June 5, 2023
(Posted: Jun 05, 2023 8AM)
AI meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs’ belief in enhancing acceptance and boosting significant health consequences. Effective governance is a prerequisite to precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.
Overcoming and mitigating ethical issues raised by artificial intelligence in health and medicine: The search continues
N Liu et al, BMC Blog, December 2022
(Posted: Jan 25, 2023 8AM)
Besides potential bias and inequalities, already well-established as ethical concerns associated with the use of AI in health care, there are also numerous other challenges that may have significant impact on patient care. AI has the potential to impact not only diagnosis but also prevention, treatment, and disease management on systems-scale, thus raising broader questions about its role in public health, for example in anticipating epidemics and providing patient support. AI is data-driven and health care data are often difficult (or even impossible) to anonymise, raising worries about privacy and data protection for patients.
Wastewater-based Disease Surveillance for Public Health Action
National Academies Consensus Report, January 2023
(Posted: Jan 22, 2023 8AM)
The report concludes that wastewater surveillance is and will continue to be a valuable component of infectious disease management. This report presents a vision for a national wastewater surveillance system that would track multiple pathogens simultaneously and pivot quickly to detect emerging pathogens, and it offers recommendations to ensure that the system is flexible, equitable, and economically sustainable for informing public health actions. The report also recommends approaches to address ethical and privacy concerns and develop a more representative wastewater surveillance system. Predictable and sustained federal funding as well as ongoing coordination and collaboration among many partners will be critical to the effectiveness of efforts moving forward.
Managing expectations, rights, and duties in large-scale genomics initiatives: a European comparison.
Horn Ruth et al. European journal of human genetics : EJHG 2022 12
(Posted: Dec 07, 2022 8AM)
This article reports on the findings of an international workshop in 2021. We focus specifically on how collection, storage and sharing of genomic data may pose challenges to established principles and values such as trust, confidentiality, and privacy in countries that have implemented, or are about to implement, large-scale national genomic initiatives. These challenges impact the relationships between patients/citizens and medicine/science, and on each party’s rights and duties towards each other.
Direct-to-consumer genetic testing in the news: a descriptive analysis.
Basch Corey H et al. Journal of community genetics 2022 10
(Posted: Oct 16, 2022 7AM)
Only 10.0% of online news articles mentioned testing confidentiality and privacy protection. Articles that mentioned?>?5 commercial DTC DNA products more often discussed how DTC DNA testing provides personalized information about health and link to family disease risk and other traits (85.7% vs. 61.1%, p?=?0.02), can lead to the location of family members or ancestors (78.6% vs. 55.63%, p?=?0.03), and that the testing results housed in DNA databases can be utilized by law enforcement to track suspects or their relatives.
Knowledge and Attitudes about Privacy and Secondary Data Use among African-Americans Using Direct-to-Consumer Genetic Testing.
Ziegler Emily et al. Public health genomics 2022 9 1-10
(Posted: Sep 29, 2022 8AM)
This study found that African-American consumers of DTC GT had a positive outlook about genetic testing and were open to research and some nonresearch uses, provided that they were able to give informed consent. Participants in this study had little knowledge of company practices regarding secondary uses. Compared to an earlier cohort of European American participants, African-American participants expressed more concerns about medical and law enforcement communities’ use of data and more reference to community engagement.
Diverse Parental Perspectives of the Social and Educational Needs for Expanding Newborn Screening through Genomic Sequencing
GT Timmins et al, Public Health Genomics, September 2022
(Posted: Sep 26, 2022 7AM)
We conducted a semi-structured interview study with English and Spanish speaking mothers who had given birth within the USA in the past 5 years. The interviews explored opinions of expanding NBS, ethical and privacy concerns, and educational and social needs. All participants were interested in some degree of NBS expansion. However, there were differing opinions about the characteristics of conditions that should be included with less consensus for conditions with low penetrance, those without approved treatment, or onset outside of early childhood.
A digital mask to safeguard patient privacy
Y Yang et al, Nature Medicine, September 15, 2022
(Posted: Sep 16, 2022 9AM)
We developed a new technology, called the digital mask (DM), which is based on three-dimensional reconstruction and deep-learning algorithms to irreversibly erase identifiable features, while retaining disease-relevant features needed for diagnosis. In a prospective clinical study to evaluate the technology for diagnosis of ocular conditions, we found very high diagnostic consistency between the use of original and reconstructed facial videos (??=?0.845 for strabismus, ptosis and nystagmus.
Potential and Pitfalls of Mobile Mental Health Apps in Traditional Treatment: An Umbrella Review
J koh et al, J Per Med, August 25, 2022
(Posted: Aug 25, 2022 0PM)
A total of 36 reviews published between 2014 and 2022—including systematic reviews, meta-analyses, scoping reviews, and literature reviews—were identified . The majority of results supported the key potential of apps in helping to (1) provide timely support, (2) ease the costs of mental healthcare, (3) combat stigma in help-seeking, and (4) enhance therapeutic outcomes. Our results also identified common themes of apps’ pitfalls (i.e., challenges faced by app users), including (1) user engagement issues, (2) safety issues in emergencies, (3) privacy and confidentiality breaches, and (4) the utilization of non-evidence-based approaches.
Parents’ understanding of genome and exome sequencing for pediatric health conditions: a systematic review
J Gereis et al, EJHG, August 23, 2022
(Posted: Aug 23, 2022 8AM)
We found parents had mixed understanding of the nature of potential secondary findings, and of issues related to data privacy, confidentiality, and usage of sequencing results beyond their child’s clinical care. Genetic counseling consultations improved understanding. Our synthesis indicates that ES/GS can be challenging for families to understand and underscores the importance of equipping healthcare professionals to explore parents’ understanding of ES/GS and the implications of testing for their child.
A blockchain-based framework to support pharmacogenetic data sharing
F Albalwy et all, The PGX journal, July 22, 2022
(Posted: Jul 22, 2022 8AM)
The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue.
How better pandemic and epidemic intelligence will prepare the world for future threats.
Morgan Oliver W et al. Nature medicine 2022 6
(Posted: Jun 30, 2022 7AM)
A new approach to pandemic and epidemic intelligence is needed that includes modern approaches to surveillance and risk assessment, as well as improved trust and cooperation between stakeholders and society. Conducting effective pandemic and epidemic intelligence, however, is not straightforward. Gathering, managing, analyzing and interpreting disparate information from the health sector and beyond is complex, in part because of data fragmentation, difficulties with accessing sources on a continuous basis, licensing, ownership and security restrictions, privacy and re-identification risks, and the inherent complexity of working with a wide range of different data types and formats.
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.
Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening
J Yang et al, NPJ Digital Medicine, June 7, 2022
(Posted: Jun 07, 2022 10AM)
As patient health information is highly regulated due to privacy concerns, most machine learning (ML)-based healthcare studies are unable to test on external patient cohorts, resulting in a gap between locally reported model performance and cross-site generalizability. Different approaches have been introduced for developing models across multiple clinical sites, however less attention has been given to adopting ready-made models in new settings. We introduce three methods to do this—(1) applying a ready-made model “as-is” (2); readjusting the decision threshold on the model’s output using site-specific data and (3); finetuning the model using site-specific data via transfer learning.
Walking the tightrope between data sharing and data protection
Nature Medicine, May 18, 2022
(Posted: May 19, 2022 10AM)
The potential of genomic data to advance human health is enormous, but it can be tapped only if everyone feels safe taking part. Therefore, now is the time for the field to start thinking of how to best deal with emerging and future issues of data security and privacy in genomic research. Although the solution might not be a one-size-fits-all approach, it is key to involve different expertise in the process, probably from diverse backgrounds such as informatics, ethics and law, as well as to include patients and the public in these discussions.
Development of Forecast Models for COVID-19 Hospital Admissions using Mobile Network Data: A Privacy-Preserving Approach
J Taghia et al, Research Square, April 5, 2022
(Posted: Apr 06, 2022 9AM)
The use of mobile network data has come to attention in response to COVID-19 pandemic leveraged on their ability in capturing people social behaviour. Crucially, we show that there are latent features in irreversibly anonymised and aggregated mobile network data that carry useful information in relation to the spread of SARS-CoV-2 virus. We describe development of the forecast models using such features for near-time prediction of COVID-19 hospital admissions.
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.
Stewardship of patient genomic data: A policy statement of the American College of Medical Genetics and Genomics (ACMG)
RG Best et al, Genetics in Medicine, December 16, 2021
(Posted: Dec 17, 2021 6AM)
When ordering genetic tests, clinicians should alert patients of any laboratory policies noted in the laboratory’s consent/requisition form about how patient results and data may be shared in de-identified form for research, giving patients the choice to participate or not. At a minimum, patients must have the opportunity to opt out.
The testing laboratory is the primary steward over the protection of the patient’s interests in controlling the privacy of genetic information.
Studies Focus on Testing Family Members of Cancer Gene Carriers
NCI, November 2021
(Posted: Dec 04, 2021 6AM)
NCI released a funding opportunity to test a “traceback” strategy, where researchers are finding the women who were previously diagnosed with ovarian cancer, communicating with them (or with their family members if they have died), and offering genetic testing. Traceback is a unique approach to genetic testing because the idea is to work backwards and find previously diagnosed cases to test to improve the detection of families at risk. Three grants using different approaches for traceback testing were funded for 4 years; projects are expected to be completed in 2023. The overall goal is to evaluate the best way to communicate sensitive genetic information to ovarian cancer patients and their immediate family members. Challenges associated with privacy laws and ethical concerns, differences in cultural traditions, and medical literacy are taken into account.
Computational tools for genomic data de-identification: facilitating data protection law compliance
A Bernier et al, Nature Comm, November 29, 2021
(Posted: Nov 30, 2021 9AM)
We discuss why computational tools to limit the identifiability of genomic data are a promising avenue for privacy-preservation and legal compliance. Even where these technologies do not eliminate all residual risk of individual identification, the law may still consider such data anonymized.
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)
Functional genomics data: privacy risk assessment and technological mitigation
G Gursoy et al, Nature Rev Genetics, November 2021
(Posted: Nov 18, 2021 6AM)
The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is essential for research advancement but poses notable privacy challenges, some of which are analogous to those that occur when sharing genetic variant data. However, there are also unique privacy challenges that arise from cryptic information leakage during the processing and summarization of functional genomics data from raw reads to derived quantities, such as gene expression values. Here, we review these challenges and present potential solutions for mitigating privacy risks while allowing broad data dissemination and analysis.
Why the United States Needs a National, Coordinated Biobanking System.
Compton Carolyn et al. Annals of internal medicine 2021 11
(Posted: Nov 09, 2021 6AM)
The idea of a national networked biobanking initiative is not new. In 2003, the NCI developed and published a plan for such an entity, a public–private partnership that it called the National Biospecimen Network (NBN). In response to the lack of fit-for-purpose human specimens for proteomic and genomic research in cancer, the NBN aimed “to establish a national, pre-competitive, regulatory compliant and genetic-privacy protected, standardized, inclusive, highest quality network of biological sample(s) banks; supported by and developed via novel financial and other partnerships…that is shared, readily accessible, and searchable using state-of-the-art informatics systems.”
Digital exposure tools: Design for privacy, efficacy, and equity
S Landau, Science, September 10, 2021
(Posted: Sep 12, 2021 5PM)
Use of smartphone-based digital contact- tracing apps has shown promise in responding to the COVID-19 pandemic. But such apps can reveal very personal information; thus, their use raises important societal questions, not just during the current pandemic but as we learn and prepare for other inevitable outbreaks ahead. Can privacy-protective versions of such apps work? Are they efficacious? Because the apps influence who is notified of exposure and who gets tested—and possibly treated—we need to consider the apps in the context of health care equity.
Privacy-first health research with federated learning
A Sadilek et al, NPJ Digital Medicine, September 7, 2021
(Posted: Sep 07, 2021 6AM)
Recent advances in federated learning enable building complex machine-learned models that are trained in a distributed fashion. These techniques facilitate the calculation of research study endpoints such that private data never leaves a given device or healthcare system. We show—on a diverse set of single and multi-site health studies—that federated models can achieve similar accuracy, precision, and generalizability, and lead to the same interpretation as standard centralized statistical models while achieving considerably stronger privacy protections and without significantly raising computational costs.
Making machine learning trustworthy
B Eshete, Science, August 13, 2021
(Posted: Aug 14, 2021 8AM)
Machine learning (ML) has advanced dramatically during the past decade and continues to achieve impressive human-level performance on nontrivial tasks in image, speech, and text recognition. It is increasingly powering many high-stake application domains such as autonomous vehicles, medical image classification, and financial predictions. However, ML must make several advances before it can be deployed with confidence in domains where it directly affects humans at training and operation, in which cases security, privacy, safety, and fairness are all essential considerations.
Genomic Data Science
NIH, July 2021
(Posted: Jul 22, 2021 7AM)
As humans dig deeper into the genome, the analysis and interpretation of the genomic data collected are helping to better understand human health and disease, while also bringing up questions about privacy and ethics.
Mobile health and privacy: cross sectional study.
Tangari Gioacchino et al. BMJ (Clinical research ed.) 2021 6 n1248
(Posted: Jun 20, 2021 7AM)
Users of 20?991 mHealth apps (8074 medical and 12?917 health and fitness found in the Google Play store: in-depth analysis was done on 15?838 apps that did not require a download or subscription fee compared with 8468 baseline non-mHealth apps. We found serious problems with privacy and inconsistent privacy practices in mHealth apps. Clinicians should be aware of these and articulate them to patients when determining the benefits and risks of mHealth apps.
Use of Genomics in Newborn Screening Programs: The Promise and Challenges
CDC September 21 webinar
(Posted: Jun 17, 2021 9AM)
While some have called for newborn screening using whole exome or whole genome sequencing, substantial barriers exist, including cost, privacy, equity in access, and the need for informed consent for sequencing of identifiable individuals. However, these technologies could play a role in testing those who screen positive using initial biochemical screens. Join us as we discuss both current and potential future use of genomics in newborn screening.
Contact Tracing for Covid-19 - A Digital Inoculation against Future Pandemics.
O'Connell James et al. The New England journal of medicine 2021 5
(Posted: May 20, 2021 9AM)
Digital contact tracing is not a perfect intervention, given the risks to privacy, personal data, and false positive or false negative characterization of contact status. However, as in a Swiss cheese model, imperfect interventions can work together to curb epidemics. South Korea’s deployment of digital technology to augment contact tracing was an example of speed trumping perfection.
Privacy practices using genetic data from cell-free DNA aneuploidy screening
CM Parobek et al, Genetics in Medicine, May 19, 2021
(Posted: May 20, 2021 8AM)
Most laboratories allowed for prolonged use and sharing of cfDNA data, demonstrated incomplete adherence to ASHG privacy recommendations, and provided consents written in college-level language. Laboratories should revise their consent forms, and providers should help patients understand these forms.
Ethically utilising COVID-19 host-genomic data
C Gyngell et al, NPJ Genomic Medicine, May 10, 2021
(Posted: May 11, 2021 8AM)
Genetic variants that influence susceptibility to COVID-19 have recently been identified. In this manuscript, we identify and discuss some of the ethical and practical issues raised by these studies. We first outline the ethical case for providing COVID-19 susceptibility testing to healthcare workers, as well as highlighting risks associated with privacy and discrimination. We then argue that the existence of genetically susceptible individuals has implications for the ethical conduct of COVID-19 human challenge trials.
The privacy challenge in the race for digital vaccination certificates
A Rieger et al, Cell (Med), April 28, 2021
(Posted: Apr 29, 2021 7AM)
Data-Driven Surveillance: Effective Collection, Integration, and Interpretation of Data to Support Decision Making.
Dórea Fernanda C et al. Frontiers in veterinary science 2021 8633977
(Posted: Apr 02, 2021 10AM)
An increasing number of new data sources, including many not originally collected for health purposes, are now being used for epidemiological inference and contextualization. Combining evidence from multiple data sources presents significant challenges, but discussions around this subject often confuse issues of data access and privacy, with the actual technical challenges of data integration and interoperability.
Emerging Infectious Diseases — Learning from the Past and Looking to the Future
C. Elias et al, NEJM, March 31, 2021
(Posted: Apr 01, 2021 6AM)
In an era of nearly limitless digital potential, we can harness the tools of the information age to share essential data for detecting new pathogens, accelerating product development, and enhancing pandemic response efforts. Countries should work together to break down barriers to data sharing while taking steps to protect privacy and prevent misuse
Artificial intelligence for good health: a scoping review of the ethics literature.
Murphy Kathleen et al. BMC medical ethics 2021 Feb 22(1) 14
(Posted: Feb 19, 2021 10AM)
The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries.
Privacy protections to encourage use of health-relevant digital data in a learning health system
D McGraw et al, NPJ Digital Medicine, January 4, 2021
(Posted: Jan 04, 2021 2PM)
The authors propose a multi-pronged approach to protecting health-relevant data while promoting and supporting beneficial uses and disclosures to improve health and health care for individuals and populations. Such protections should apply to entities collecting health-relevant data. They also address protections against harms as a critical component of a comprehensive approach to governing health-relevant data.
Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas
A ALeta et al, MEDRXIV, December 17, 2020
(Posted: Dec 18, 2020 0PM)
We integrate real-time, anonymous and privacy-enhanced geolocalized mobility data with census and demographic data in the New York City and Seattle metropolitan areas. We estimate that most infections (80%) are produced by a small number of people (27%), and that about 10% of events can be considered super-spreading events.
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.
Harnessing consumer smartphone and wearable sensors for clinical cancer research
CA Low, NPJ Digital Medicine, October 27, 2020
(Posted: Oct 28, 2020 8AM)
Over the past few years, small studies across a variety of cancer populations support the feasibility and potential clinical value of mobile sensors in oncology. Barriers to implementing mobile sensing in clinical oncology care include the challenges of managing and making sense of continuous sensor data, patient engagement issues, difficulty integrating sensor data into existing electronic health systems and clinical workflows, and ethical and privacy concerns.
FeverIQ - A Privacy-Preserving COVID-19 Symptom Tracker with 3.6 Million Reports
A Rajan et al, MEDRXIV, September 27, 2020
(Posted: Sep 28, 2020 1PM)
The future of digital health with federated learning
N Rieke et al, NPJ Digital Medicine, September 14, 2020
(Posted: Sep 14, 2020 7AM)
Existing medical data is not fully exploited by machine learning (ML) primarily because it sits in data silos and privacy concerns restrict access to this data. However, without access to sufficient data, ML will be prevented from reaching its full potential and, ultimately, from making the transition from research to clinical practice.
Prevalence of Third-Party Tracking on COVID-19–Related Web Pages
MS McCoy et al JAMA, September 8, 2020
(Posted: Sep 08, 2020 11AM)
This study found that 99% of COVID19 related web pages included a third-party data request. Amid debate focused on the privacy implications of COVID-19 contact-tracing apps, The findings suggest that attention should be paid to privacy risks of online information seeking.
Health Policy and Privacy Challenges Associated With Digital Technology
D Grande et al, JAMA Network Open, August 9, 2020
(Posted: Aug 11, 2020 7AM)
Five key characteristics were associated with health privacy policy challenges: invisibility (people are unaware of how their data are tracked), inaccuracy (data in the digital health footprint can be inaccurate), immortality (data have no expiration date and are aggregated over time), marketability and identifiability.
Regulatory, safety, and privacy concerns of home monitoring technologies during COVID-19
S Gerke et al, Nature Medicine, August 7, 2020
(Posted: Aug 10, 2020 8AM)
There has been increasing interest in the use of home monitoring technologies during the COVID-19 pandemic to decrease interpersonal contacts. This Perspective explores how these technologies raise major concerns pertaining to safety and privacy. We make recommendations for needed interventions to ensure safety and review best practices.
Build trust in digital health
Nature Medicine editorial, August 7, 2020
(Posted: Aug 10, 2020 8AM)
The rapid rollout of digital health approaches in the ongoing global COVID-19 pandemic has neglected to prioritize data privacy and is a missed opportunity for building users’ trust in these technologies for future outbreaks and quotidian healthcare.
Decentralized Blockchain for Privacy-Preserving Large-Scale Contact Tracing
W Lv et al, ARXIV, July 2, 2020
(Posted: Jul 04, 2020 8AM)
Privacy challenges and research opportunities for genomic data sharing
L Bonomi et al, Nature Genetics, June 29, 2020
(Posted: Jun 30, 2020 9AM)
In this work, we provide an overview of major privacy threats identified by the research community and examine the privacy challenges in the context of emerging direct-to-consumer genetic-testing applications. We additionally present general privacy-protection techniques for genomic data sharing and their potential applications.
Can phone apps slow the spread of the coronavirus?
K Servick, Science, June 19, 2020
(Posted: Jun 19, 2020 9AM)
Epidemiological models suggest apps can change a pandemic's course. Ensuring that an app detects risky contacts without overwhelming users with false alarms is one challenge; getting enough people to download an app is another. Health officials weigh competing apps and prepare pitches to privacy-conscious citizens considering how to put an app to the test.
The need for privacy with public digital contact tracing during the COVID-19 pandemic
Y Bengio et al, Lancet Digital Health, June 2, 2020
(Posted: Jun 03, 2020 7AM)
Despite their potential advantages, most of the applications in use or under consideration have an impact on individual privacy that democratic societies would normally consider to be unacceptably high. In a free and democratic society, there are major concerns regarding privacy.
The interface of genomic information with the electronic health record: a points to consider statement of the American College of Medical Genetics and Genomics (ACMG)
TA Grebe et al, Genetics in Medicine, June 1, 2020
(Posted: Jun 01, 2020 10AM)
This document discusses types of genomic information in the EHR, mechanisms of placement, data entry, usage, patient/provider access, results disclosure, portability, and privacy. It highlights patient, family, and societal benefits; discuss areas of concern, identifying where modifications are needed; and make recommendations for optimization.
Ethical guidelines for COVID-19 tracing apps-Protect privacy, equality and fairness in digital contact tracing with these key questions.
J Morley et al, Nature, News May 28, 2020
(Posted: May 30, 2020 7AM)
Here we set out 16 questions to assess whether — and to what extent — a contact-tracing app is ethically justifiable. These questions could assist governments, public-health agencies and providers to develop ethical apps — they have already informed developments in France, Italy and the UK. They will also help watchdogs and others to scrutinize such technologies.
CoVista: A Unified View on Privacy Sensitive Mobile Contact Tracing Effort
D Culler et al, ARXIV, May 27, 2020
(Posted: May 28, 2020 8AM)
Digital Smartphone Tracking for COVID-19- Public Health and Civil Liberties in Tension
IG Cohen et al, JAMA, may 27, 2020
(Posted: May 27, 2020 0PM)
This Viewpoint compares manual and digital strategies for coronavirus disease 2019 (COVID-19) contact tracing, describes how countries in Asia and Europe have used smartphone tracking, and discusses privacy and discrimination concerns and strategies for balancing public health and civil liberties in the US.
Use of apps in the COVID-19 response and the loss of privacy protection
T Sharma et al, Nature Medicine, May 26, 2020
(Posted: May 26, 2020 1PM)
Mobile apps provide a convenient source of tracking and data collection to fight against the spread of COVID-19. We report our analysis of 50 COVID-19-related apps, including their use and their access to personally identifiable information, to ensure that the right to privacy and civil liberties are protected.
A Scramble for Virus Apps That Do No Harm- Dozens of tracking apps for smartphones are being used or developed to help contain the coronavirus pandemic. But there are worries about privacy and hastily written software.
JV DeVries et al, New York Times, April 29, 2020
(Posted: May 04, 2020 7AM)
Show evidence that apps for COVID-19 contact-tracing are secure and effective
Nature editorial, April 29, 2020
(Posted: Apr 30, 2020 9AM)
Key questions need answers: One serious concern is accuracy. If incorrect information has been sent to a large group of contacts, it will have caused unnecessary alarm. An equally important concern is privacy. It is becoming easier to identify individuals from anonymized data sets.
Cellphone tracking could help stem the spread of coronavirus. Is privacy the price?
Science, March 22, 2020
(Posted: Mar 22, 2020 3PM)
At its simplest, digital contact tracing might work like this: Phones log their own locations; when the owner of a phone tests positive for COVID-19, a record of their recent movements is shared with health officials; owners of any other phones that recently came close to that phone get notified of their risk of infection and are advised to self-isolate.
Consumer Genomic Testing in 2020
WG Feero et al, JAMA, March 19, 202-0
(Posted: Mar 20, 2020 9AM)
This Viewpoint discusses gaps between the growth of direct-to-consumer genomic testing and knowledge about how best to use the information, highlighting the absence of diversity in genetic databases, the scarcity of accompanying genetic counseling, and data security and privacy concerns.
Patient acceptance of genetic testing for familial hypercholesterolemia in the CASCADE FH Registry.
Gidding Samuel S et al. Journal of clinical lipidology 2020 Feb
(Posted: Mar 11, 2020 9AM)
Barriers to genetic testing and subsequent family cascade screening for familial hypercholesterolemia (FH) include cost, patient and provider awareness, privacy and discrimination concerns, need for a physician order, underutilization of genetic counselors, and family concerns about the implications of genetic testing for care.
Ethical and Legal Aspects of Ambient Intelligence in Hospitals.
Gerke Sara et al. JAMA 2020 Jan
(Posted: Jan 26, 2020 7AM)
As computer vision–driven ambient intelligence accelerates toward a future when its capabilities will most likely be widely adopted in hospitals, it also raises new ethical and legal questions. We focus on 3 specific concerns: (1) privacy and reidentification risk, (2) consent, and (3) liability.
Your Fitbit could help health officials predict flu outbreaks in real-time
A Kim, CNN, January 2020
(Posted: Jan 24, 2020 8AM)
Researchers reviewed de-identified data from users wearing Fitbits -- the company's privacy policy allows for the potential use of de-identified user data for research, and found that they were able to do real-time flu prediction at the state level. This is the first time heart rate trackers and sleep data have been used to predict infectious disease in real time.
Attacks on genetic privacy via uploads to genealogical databases
MD Edge et al, elife, January 7, 2020
(Posted: Jan 10, 2020 8AM)
Direct-to-consumer genetics services are increasingly popular, with tens of millions of customers. Several genealogy services allow users to upload genetic data to search for relatives, identified as people with genomes that share identical by state regions. We describe methods by which an adversary can learn database genotypes by uploading multiple datasets.
Genealogy: The challenges of maintaining genetic privacy
S Carmi, elife, January 7. 2020
(Posted: Jan 10, 2020 8AM)
Navigating 2020 and beyond
Nature Genetics editorial, January 7, 2020
(Posted: Jan 08, 2020 8AM)
As we usher in a new year of a new decade and ponder what the future will bring for the genetics field, we wish to reflect on some specific areas related to diversity, privacy and genome editing that require attention and vigilance from the community.
Why Are You Publicly Sharing Your Child’s DNA Information? By uploading their children’s genetic information on public websites, parents are forever exposing their personal health data.
N Bala, NY Times, January 2, 2020
(Posted: Jan 03, 2020 9AM)
When parents test their children’s DNA before they are old enough to truly consent, those children lose their right not to know certain information. This is significant because of the right to privacy: “the individual interest in avoiding disclosure of personal matters,” and “the interest in independence in making certain kinds of important decisions.”
How Can Law Support Development of Genomics and Precision Medicine to Advance Health Equity and Reduce Disparities?
Wolf Susan M et al. Ethnicity & disease 2019 29(Suppl 3) 623-628
(Posted: Jan 02, 2020 10AM)
Legal barriers limit use of precision medicine to advance health equity. Problems include inadequate privacy and anti-discrimination protections for research participants, lack of health coverage and funding for follow-up care, failure to use law to ensure access to genomic medicine, and practices by research sponsors that tolerate and entrench disparities.
How Can Law Support Development of Genomics and Precision Medicine to Advance Health Equity and Reduce Disparities?
SM Wolfe et al, Ethnicity and Disease, suppl 2019
(Posted: Dec 16, 2019 7AM)
Multiple legal barriers limit broad inclusion in genomic research and the development of precision medicine to advance health equity. Problems include inadequate privacy and anti-discrimination protections for research participants, lack of health coverage, failure to use law to ensure access, and practices by research sponsors that entrench disparities.
The promise and peril of AI
The Economist, October 10, 2019
(Posted: Oct 13, 2019 1PM)
AI, the technique of using data and algorithms to make decisions as well as (or better) than humans—is on track to become a mainstream technology, on a par with electricity or computing. But in order to flourish it needs to overcome several challenges. From privacy and market concentration, to safety and explainability.
Exploring the Current Landscape of Consumer Genomics - A Workshop
NASEM workshop, October 29, 2019
(Posted: Sep 30, 2019 9AM)
The Roundtable on Genomics and Precision Health will host a public workshop on October 29, 2019 to explore the current landscape of consumer genomics and implications for how genetic test information is used or may be used in research and clinical care. Discussions include topics such as health literacy and engagement, knowledge gaps and data privacy concerns.
Keeping patient phenotypes and genotypes private while seeking disease diagnoses
KA Jagadeesh et al, BioRXIV, August 24, 2019
(Posted: Aug 26, 2019 9AM)
In this work, the authors develop secure protocols to maintain patient privacy while computing meaningful operations over both genotypic and phenotypic data for two real scenarios: COHORT DISCOVERY and GENE PRIORITIZATION.
Why home DNA tests might not be as private as you think
C Fox, World Economic Forum, August 9, 2019
(Posted: Aug 19, 2019 8AM)
Big Data, Big Tech, and Protecting Patient Privacy
IG Cohen et al, JAMA, August 9, 2019
(Posted: Aug 10, 2019 9AM)
The market for patient data has never been more active. Technology companies, from startups to giants, are eager to access electronic health record (EHR) data to build the next generation of health-focused products. Medical artificial intelligence (AI) is particularly data-hungry.
Time to discuss consent in digital-data studies
Nature editorial, July 31, 2019
(Posted: Aug 01, 2019 8AM)
Anonymized data sets are growing and it is becoming easier to identify individuals. Research-consent procedures must be updated to protect people's privacy and confidentiality.
Estimating the success of re-identifications in incomplete datasets using generative models
Luc Rocher, et al. Nature Communications 10, Article number: 3069 (2019)
(Posted: Jul 25, 2019 10AM)
This modeling study finds that 99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes. The study suggests that even heavily sampled anonymized datasets are unlikely to satisfy the modern standards for anonymization.
Your Data Were Anonymized? These Scientists Can Still Identify You
G Kolata, NY Times, July 23, 2019
(Posted: Jul 24, 2019 8AM)
Computer scientists have developed an algorithm that can pick out almost any American in databases supposedly stripped of personal information. One possible solution is to control access. Those who want to use sensitive data ? medical records, for example ? would have to access them in a secure room.
How Your Genetic Data Could Be Shared Without Your Consent
E Matloff, Forbes, July 18, 2019
(Posted: Jul 22, 2019 8AM)
Imagine getting an email from a private company informing you that they have info about your genetic carrier status.
Without the involvement of a genetic counselor, discussion of sharing genetic test results w family is falling by wayside
DNA Test Service Exposed Thousands of Client Records Online
N Grant, Bloomberg News, July 9, 2019
(Posted: Jul 11, 2019 8AM)
Emerging technologies towards enhancing privacy in genomic data sharing
B Berger et al, Genome Biology, July 2, 2019
(Posted: Jul 05, 2019 9AM)
As the scale of genomic and health-related data explodes and our understanding of these data matures, the privacy of the individuals behind the data is increasingly at stake. Traditional approaches to protect privacy have fundamental limitations. The authors discuss emerging privacy-enhancing technologies that can enable broader data sharing and collaboration in genomics research.
Walking the tightrope of artificial intelligence guidelines in clinical practice
Lancet Digital Health editorial, July 2019
(Posted: Jun 29, 2019 5PM)
Artificial Intelligence approaches in medical practice needs to be lawful, ethical, and robust. According to the EU guidelines for trustworthy AI, there are seven key requirements for ethical AI: human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination, and fairness; societal and environmental wellbeing; and accountability
Cases in Precision Medicine: Concerns About Privacy and Discrimination After Genomic Sequencing.
Stiles Deborah et al. Annals of internal medicine 2019 May
(Posted: May 08, 2019 9AM)
Direct-to-Consumer Genetic Testing and Potential Loopholes in Protecting Consumer Privacy and Nondiscrimination
RM Hendircks-Sturrup et al, JAMA< April 18, 2019
(Posted: Apr 19, 2019 8AM)
Your genome could help medical research. It could also be a privacy nightmare
CBC, March 24, 2019
(Posted: Mar 24, 2019 9AM)
Privacy in Direct-to-Consumer Genetic Testing
JY Park et al, Clin Chem, March 2019
(Posted: Mar 04, 2019 8AM)
Privacy in the age of medical big data
WN Price, Nature Medicine, January 7. 2019
(Posted: Jan 07, 2019 2PM)
Feasibility of Reidentifying Individuals in Large National Physical Activity Data Sets From Which Protected Health Information Has Been Removed With Use of Machine Learning
L Na et al, Network Open, December 2012, 2018
(Posted: Dec 24, 2018 10AM)
Protecting trust in medical genetics in the new era of forensics
C Curtis, Genetics in Medicine, December 18, 2018
(Posted: Dec 18, 2018 1PM)
What specific protections apply to health-related, genetic, or biometric data?
Global Alliance for Genetics and Health, December 5, 2018
(Posted: Dec 09, 2018 4PM)
Is it time for a universal genetic forensic database?
JW Hazel et al, Science, November 22, 2018
(Posted: Nov 23, 2018 0PM)
A systematic literature review of individuals' perspectives on privacy and genetic information in the United States.
Clayton Ellen W et al. PloS one 2018 (10) e0204417
(Posted: Nov 01, 2018 8AM)
