scholarly journals Data Sharing of Imaging in an Evolving Health Care World: Report of the ACR Data Sharing Workgroup Part 1: Data Ethics of Privacy, Consent, and Anonymization

2021 ◽  
Author(s):  
Juan Carlos Batlle ◽  
Keith Dreyer ◽  
Bibb Allen ◽  
Tessa Cook ◽  
Christopher J. Roth ◽  
...  
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Data Ethics ◽  
World Report

scholarly journals Data Dentistry: How Data Are Changing Clinical Care and Research

2021 ◽  
pp. 002203452110202
Author(s):  
F. Schwendicke ◽  
J. Krois
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Clinical Care ◽  
Open Data ◽  
User Interaction ◽  
Data Availability ◽  
Related Data ◽  
Data User ◽  
Regulatory Data ◽  
Consumer Data

Data are a key resource for modern societies and expected to improve quality, accessibility, affordability, safety, and equity of health care. Dental care and research are currently transforming into what we term data dentistry, with 3 main applications: 1) medical data analysis uses deep learning, allowing one to master unprecedented amounts of data (language, speech, imagery) and put them to productive use. 2) Data-enriched clinical care integrates data from individual (e.g., demographic, social, clinical and omics data, consumer data), setting (e.g., geospatial, environmental, provider-related data), and systems level (payer or regulatory data to characterize input, throughput, output, and outcomes of health care) to provide a comprehensive and continuous real-time assessment of biologic perturbations, individual behaviors, and context. Such care may contribute to a deeper understanding of health and disease and a more precise, personalized, predictive, and preventive care. 3) Data for research include open research data and data sharing, allowing one to appraise, benchmark, pool, replicate, and reuse data. Concerns and confidence into data-driven applications, stakeholders’ and system’s capabilities, and lack of data standardization and harmonization currently limit the development and implementation of data dentistry. Aspects of bias and data-user interaction require attention. Action items for the dental community circle around increasing data availability, refinement, and usage; demonstrating safety, value, and usefulness of applications; educating the dental workforce and consumers; providing performant and standardized infrastructure and processes; and incentivizing and adopting open data and data sharing.

scholarly journals Evaluation of Privacy Risks of Patients’ Data in China: Case Study

10.2196/13046 ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e13046 ◽  
Author(s):  
Mengchun Gong ◽  
Shuang Wang ◽  
Lezi Wang ◽  
Chao Liu ◽  
Jianyang Wang ◽  
...  
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Data Privacy ◽  
Patient Data ◽  
Chinese Patients ◽  
Biomedical Data ◽  
Safe Harbor ◽  
Patient Privacy ◽  
Privacy Risk ◽  
Privacy Risks

Background Patient privacy is a ubiquitous problem around the world. Many existing studies have demonstrated the potential privacy risks associated with sharing of biomedical data. Owing to the increasing need for data sharing and analysis, health care data privacy is drawing more attention. However, to better protect biomedical data privacy, it is essential to assess the privacy risk in the first place. Objective In China, there is no clear regulation for health systems to deidentify data. It is also not known whether a mechanism such as the Health Insurance Portability and Accountability Act (HIPAA) safe harbor policy will achieve sufficient protection. This study aimed to conduct a pilot study using patient data from Chinese hospitals to understand and quantify the privacy risks of Chinese patients. Methods We used g-distinct analysis to evaluate the reidentification risks with regard to the HIPAA safe harbor approach when applied to Chinese patients’ data. More specifically, we estimated the risks based on the HIPAA safe harbor and limited dataset policies by assuming an attacker has background knowledge of the patient from the public domain. Results The experiments were conducted on 0.83 million patients (with data field of date of birth, gender, and surrogate ZIP codes generated based on home address) across 33 provincial-level administrative divisions in China. Under the Limited Dataset policy, 19.58% (163,262/833,235) of the population could be uniquely identifiable under the g-distinct metric (ie, 1-distinct). In contrast, the Safe Harbor policy is able to significantly reduce privacy risk, where only 0.072% (601/833,235) of individuals are uniquely identifiable, and the majority of the population is 3000 indistinguishable (ie the population is expected to share common attributes with 3000 or less people). Conclusions Through the experiments based on real-world patient data, this work illustrates that the results of g-distinct analysis about Chinese patient privacy risk are similar to those from a previous US study, in which data from different organizations/regions might be vulnerable to different reidentification risks under different policies. This work provides reference to Chinese health care entities for estimating patients’ privacy risk during data sharing, which laid the foundation of privacy risk study about Chinese patients’ data in the future.

scholarly journals Interrelationships Between Patients’ Data Tracking Practices, Data Sharing Practices, and Health Literacy: Onsite Survey Study

10.2196/18937 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e18937
Author(s):  
Yuhan Luo ◽  
Chi Young Oh ◽  
Beth St Jean ◽  
Eun Kyoung Choe
Keyword(s):  
Health Care ◽  
Health Literacy ◽  
Data Sharing ◽  
Health Care Providers ◽  
Clinic Visit ◽  
Survey Study ◽  
Sufficient Information ◽  
Full Potential ◽  
Care Providers ◽  
Data Tracking

Background Although the use of patient-generated data (PGD) in the optimization of patient care shows great promise, little is known about whether patients who track their PGD necessarily share the data with their clinicians. Meanwhile, health literacy—an important construct that captures an individual’s ability to manage their health and to engage with their health care providers—has often been neglected in prior studies focused on PGD tracking and sharing. To leverage the full potential of PGD, it is necessary to bridge the gap between patients’ data tracking and data sharing practices by first understanding the interrelationships between these practices and the factors contributing to these practices. Objective This study aims to systematically examine the interrelationships between PGD tracking practices, data sharing practices, and health literacy among individual patients. Methods We surveyed 109 patients at the time they met with a clinician at a university health center, unlike prior research that often examined patients’ retrospective experience after some time had passed since their clinic visit. The survey consisted of 39 questions asking patients about their PGD tracking and sharing practices based on their current clinical encounter. The survey also contained questions related to the participants’ health literacy. All the participants completed the survey on a tablet device. The onsite survey study enabled us to collect ecologically valid data based on patients’ immediate experiences situated within their clinic visit. Results We found no evidence that tracking PGD was related to self-reports of having sufficient information to manage one’s health; however, the number of data types participants tracked positively related to their self-assessed ability to actively engage with health care providers. Participants’ data tracking practices and their health literacy did not relate to their data sharing practices; however, their ability to engage with health care providers positively related to their willingness to share their data with clinicians in the future. Participants reported several benefits of, and barriers to, sharing their PGD with clinicians. Conclusions Although tracking PGD could help patients better engage with health care providers, it may not provide patients with sufficient information to manage their health. The gaps between tracking and sharing PGD with health care providers call for efforts to inform patients of how their data relate to their health and to facilitate efficient clinician-patient communication. To realize the full potential of PGD and to promote individuals’ health literacy, empowering patients to effectively track and share their PGD is important—both technologies and health care providers can play important roles.

Patient Experiences, Trust, and Preferences for Health Data Sharing

2021 ◽  
Author(s):  
Rochelle D. Jones ◽  
Chris Krenz ◽  
Kent A. Griffith ◽  
Rebecca Spence ◽  
Angela R. Bradbury ◽  
...  
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Health Care System ◽  
Lived Experiences ◽  
Care Delivery ◽  
Group Discussion ◽  
Final Analysis ◽  
Secondary Use ◽  
The Impact ◽  
Care System

PURPOSE: Scholars have examined patients' attitudes toward secondary use of routinely collected clinical data for research and quality improvement. Evidence suggests that trust in health care organizations and physicians is critical. Less is known about experiences that shape trust and how they influence data sharing preferences. MATERIALS AND METHODS: To explore learning health care system (LHS) ethics, democratic deliberations were hosted from June 2017 to May 2018. A total of 217 patients with cancer participated in facilitated group discussion. Transcripts were coded independently. Finalized codes were organized into themes using interpretive description and thematic analysis. Two previous analyses reported on patient preferences for consent and data use; this final analysis focuses on the influence of personal lived experiences of the health care system, including interactions with providers and insurers, on trust and preferences for data sharing. RESULTS: Qualitative analysis identified four domains of patients' lived experiences raised in the context of the policy discussions: (1) the quality of care received, (2) the impact of health care costs, (3) the transparency and communication displayed by a provider or an insurer to the patient, and (4) the extent to which care coordination was hindered or facilitated by the interchange between a provider and an insurer. Patients discussed their trust in health care decision makers and their opinions about LHS data sharing. CONCLUSION: Additional resources, infrastructure, regulations, and practice innovations are needed to improve patients' experiences with and trust in the health care system. Those who seek to build LHSs may also need to consider improvement in other aspects of care delivery.

scholarly journals Changing the Rules of the Game: How Do We Measure Success in Social Media?

2017 ◽  
Vol 30 (04) ◽  
pp. 259-263 ◽  
Author(s):  
Aisling Hogan ◽  
Desmond Winter
Keyword(s):  
Health Care ◽  
Social Media ◽  
Open Access ◽  
Knowledge Acquisition ◽  
Data Sharing ◽  
Professional Life ◽  
Online Media ◽  
Global Level ◽  
The Real ◽  
Rules Of The Game

AbstractOurs will be the generation proud to say we shifted the sands of educational deserts by open access and proliferation, seeding of data sharing, and watering grassroots research in resource-compromised environments. Universal “social” media is defining features of modern professional life that provide powerful modes of knowledge acquisition/sharing to that end. Altmetric and other measurements stratify academic communications according to this alternate, online media presence (not academic penetrance). Are they meaningless, self-absorbed integers, or reliable yardsticks of scientific and educational prowess? Far beyond this trite, patronizing question from the minds of outdated, terrified technophobes, the real impact of “social” media is not narcissistic solipsism. Instant dissemination of contemporary surgical controversies on a truly global level drives improved (or at least reflective) health care for all. While a numerical assignment of value according to views, “likes,” impressions, or “retweets” may seem meaningless to cynical, established academics, the impetus for universal improvement is self-evident. Electronic data and opinion sharing may not balance the inequity between low- and high-income countries, but it keeps it in perspective. The best way to shift desert sands is to blow on them constantly.

scholarly journals Accelerating Health Data Sharing: A Solution Based on the Internet of Things and Distributed Ledger Technologies (Preprint)

2019 ◽  
Author(s):  
Xiaochen Zheng ◽  
Shengjing Sun ◽  
Raghava Rao Mukkamala ◽  
Ravi Vatrapu ◽  
Joaquín Ordieres-Meré
Keyword(s):  
Health Care ◽  
Internet Of Things ◽  
Data Sharing ◽  
Data Access ◽  
Health Data ◽  
Security And Privacy ◽  
Access Management ◽  
Related Data ◽  
Distributed Ledger ◽  
Health Related

BACKGROUND Huge amounts of health-related data are generated every moment with the rapid development of Internet of Things (IoT) and wearable technologies. These big health data contain great value and can bring benefit to all stakeholders in the health care ecosystem. Currently, most of these data are siloed and fragmented in different health care systems or public and private databases. It prevents the fulfillment of intelligent health care inspired by these big data. Security and privacy concerns and the lack of ensured authenticity trails of data bring even more obstacles to health data sharing. With a decentralized and consensus-driven nature, distributed ledger technologies (DLTs) provide reliable solutions such as blockchain, Ethereum, and IOTA Tangle to facilitate the health care data sharing. OBJECTIVE This study aimed to develop a health-related data sharing system by integrating IoT and DLT to enable secure, fee-less, tamper-resistant, highly-scalable, and granularly-controllable health data exchange, as well as build a prototype and conduct experiments to verify the feasibility of the proposed solution. METHODS The health-related data are generated by 2 types of IoT devices: wearable devices and stationary air quality sensors. The data sharing mechanism is enabled by IOTA’s distributed ledger, the Tangle, which is a directed acyclic graph. Masked Authenticated Messaging (MAM) is adopted to facilitate data communications among different parties. Merkle Hash Tree is used for data encryption and verification. RESULTS A prototype system was built according to the proposed solution. It uses a smartwatch and multiple air sensors as the sensing layer; a smartphone and a single-board computer (Raspberry Pi) as the gateway; and a local server for data publishing. The prototype was applied to the remote diagnosis of tremor disease. The results proved that the solution could enable costless data integrity and flexible access management during data sharing. CONCLUSIONS DLT integrated with IoT technologies could greatly improve the health-related data sharing. The proposed solution based on IOTA Tangle and MAM could overcome many challenges faced by other traditional blockchain-based solutions in terms of cost, efficiency, scalability, and flexibility in data access management. This study also showed the possibility of fully decentralized health data sharing by replacing the local server with edge computing devices.

scholarly journals Using Blockchain Technology to Mitigate Challenges in Service Access for the Homeless and Data Exchange Between Providers: Qualitative Study

10.2196/16887 ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. e16887
Author(s):  
Anjum Khurshid ◽  
Vivian Rajeswaren ◽  
Steven Andrews
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Data Exchange ◽  
Service Providers ◽  
Health Sector ◽  
Real Life ◽  
Homeless Population ◽  
Sensitive Information ◽  
Service Access ◽  
Blockchain Technology

Background In the homeless population, barriers to housing and supportive services include a lack of control or access to data. Disparate data formats and storage across multiple organizations hinder up-to-date intersystem access to records and a unified view of an individual’s health and documentation history. The utility of blockchain to solve interoperability in health care is supported in recent literature, but the technology has yet to be tested in real-life conditions encompassing the complex regulatory standards in the health sector. Objective This study aimed to test the feasibility and performance of a blockchain system in a homeless community to securely store and share data across a system of providers in the health care ecosystem. Methods We performed a series of platform demonstrations and open-ended qualitative feedback interviews to determine the key needs and barriers to user and stakeholder adoption. Account creation and data transactions promoting organizational efficiency and improved health outcomes in this population were tested with homeless users and service providers. Results Persons experiencing homelessness and care organizations could successfully create accounts, grant and revoke data sharing permissions, and transmit documents across a distributed network of providers. However, there were issues regarding the security of shared data, user experience and adoption, and organizational preparedness for service providers as end users. We tested a set of assumptions related to these problems within the project time frame and contractual obligations with an existing blockchain-based platform. Conclusions Blockchain technology provides decentralized data sharing, validation, immutability, traceability, and integration. These core features enable a secure system for the management and distribution of sensitive information. This study presents a concrete evaluation of the effectiveness of blockchain through an existing platform while revealing limitations from the perspectives of user adoption, cost-effectiveness, scalability, and regulatory frameworks.

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