scholarly journals The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare

2019 ◽  
Vol 28 (01) ◽  
pp. 195-202 ◽  
Author(s):  
Marc Cuggia ◽  
Stéphanie Combes
Keyword(s):  
Data Sharing ◽  
Medical Informatics ◽  
Data Privacy ◽  
Data Use ◽  
Health Data ◽  
The European Union ◽  
Global Approach ◽  
Data Governance ◽  
Academic Hospitals ◽  
Access Data

Objective: The diversity and volume of health data have been rapidly increasing in recent years. While such big data hold significant promise for accelerating discovery, data use entails many challenges including the need for adequate computational infrastructure and secure processes for data sharing and access. In Europe, two nationwide projects have been launched recently to support these objectives. This paper compares the French Health Data Hub initiative (HDH) to the German Medical Informatics Initiatives (MII). Method: We analysed the projects according to the following criteria: (i) Global approach and ambitions, (ii) Use cases, (iii) Governance and organization, (iv) Technical aspects and interoperability, and (v) Data privacy access/data governance. Results: The French and German projects share the same objectives but are different in terms of methodologies. The HDH project is based on a top-down approach and focuses on a shared computational infrastructure, providing tools and services to speed projects between data producers and data users. The MII project is based on a bottom-up approach and relies on four consortia including academic hospitals, universities, and private partners. Conclusion: Both projects could benefit from each other. A Franco-German cooperation, extended to other countries of the European Union with similar initiatives, should allow sharing and strengthening efforts in a strategic area where competition from other countries has increased.

scholarly journals Data Governance in the Dairy Industry

Animals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2981
Author(s):  
Roger Cue ◽  
Mark Doornink ◽  
Regi George ◽  
Benjamin Griffiths ◽  
Matthew W. Jorgensen ◽  
...  
Keyword(s):  
Data Sharing ◽  
Data Privacy ◽  
Dairy Farm ◽  
Legal Regulation ◽  
Data Governance ◽  
Codes Of Practice ◽  
The Status ◽  
Data Stewardship ◽  
Data Ecosystem ◽  
Diverse Data

Data governance is a growing concern in the dairy farm industry because of the lack of legal regulation. In this commentary paper, we discuss the status quo of the available legislation and codes, as well as some possible solutions. To our knowledge, there are currently four codes of practice that address agriculture data worldwide, and their objectives are similar: (1) raise awareness of diverse data challenges such as data sharing and data privacy, (2) provide data security, and (3) illustrate the importance of the transparency of terms and conditions of data sharing contracts. However, all these codes are voluntary, which limits their adoption. We propose a Farmers Bill of Rights for the dairy data ecosystem to address some key components around data ownership and transparency in data sharing. Our hope is to start the discussion to create a balanced environment to promote equity within the data economy, encourage proper data stewardship, and to foster trust and harmony between the industry companies and the farmers when it comes to sharing data.

scholarly journals Decentralized Personal Health Records with Interacting Physician Apps and Intelligent Agents on Blockchain and Smart Contract Technologies (Preprint)

2020 ◽  
Author(s):  
Hyeong-Joon ­Kim ◽  
Hye Hyun Kim ◽  
Hosuk Ku ◽  
Kyung Don Yoo ◽  
Suehyun Lee ◽  
...  
Keyword(s):  
Data Sharing ◽  
Intelligent Agents ◽  
Data Privacy ◽  
Data Integrity ◽  
Health Data ◽  
Smart Devices ◽  
Data Element ◽  
Element Level ◽  
Smart Contract ◽  
Transaction Manager

BACKGROUND The Health Avatar Platform (HAP) provides a mobile health environment with interconnected patient Avatars, physician apps, and intelligent agents (IoA3) for data privacy and participatory medicine. However, its fully decentralized architecture has come at the expense of decentralized data management and data provenance. OBJECTIVE The introduction of blockchain and smart contract (SC) technologies to the HAP legacy platform with a clinical metadata registry (MDR) remarkably strengthens decentralized health data integrity and immutable transaction traceability at the corresponding data-element level in a privacy-preserving fashion. A crypto-economy ecosystem was built to facilitate secure and traceable exchanges of sensitive health data. METHODS HAP decentralizes patient data in appropriate locations with no central storage, i.e., on patients’ smartphones and on physicians’ smart devices. We implemented an Ethereum-based hash chain for all transactions and SC-based processes to guarantee decentralized data integrity and to generate block data containing transaction metadata on-chain. Parameters of all types of data communications were enumerated and incorporated into three SCs, in this case a health data transaction manager, a transaction status manager, and an API transaction manager. The actual decentralized health data are managed in off-chain manner on their appropriate smart devices and authenticated by hashed metadata on-chain. RESULTS Metadata of each data transaction are captured in a HAP blockchain node by the SCs. We provide workflow diagrams each of the three use cases of data push (from a physician app or an intelligent Agents to a patient Avatar), data pull (requested to a patient Avatar by other entities), and data backup transactions. Each transaction can be finely managed at the corresponding data-element level rather than at the resource or document levels. Hash chained metadata support data element-level verification of the data integrity in subsequent transactions. SCs can incentivize transactions for data sharing and intelligent digital healthcare services. CONCLUSIONS HAP and IoA3 provide a decentralized blockchain ecosystem for health data that enables trusted and finely tuned data sharing and facilitates health value-creating transactions by SCs.

How to Draft Successful Memorandums of Understanding and Data-Sharing Agreements

2019 ◽  
pp. 191-204
Author(s):  
Matthew Penn ◽  
Rachel Hulkower
Keyword(s):  
Public Health ◽  
Health Care ◽  
Health System ◽  
Data Sharing ◽  
Data Use ◽  
Health Data ◽  
Critical Component ◽  
The Public ◽  
Goods And Services ◽  
Public Health Data

This chapter offers tips on crafting data-sharing agreements. Improving and increasing cross-sector collaboration in public health can be facilitated through the use of a memorandum of understanding (MOU). The chapter looks at the benefits of MOUs, and also drawbacks. It provides some case studies of successful MOUs. Cross-sector collaboration is an increasingly critical component of the public health system, the chapter concludes. Community partnerships can involve complex arrangements, with reciprocal promises to exchange goods and services, and MOUs can help organizations negotiate, organize, and maintain those relationships. For partnerships that need health care or public health data to function, a data use agreements (DUA) can provide a mechanism to define the data needed and the parameters around the intended release and use of the data.

scholarly journals Sharing Is Caring—Data Sharing Initiatives in Healthcare

2020 ◽  
Vol 17 (9) ◽  
pp. 3046
Author(s):  
Tim Hulsen
Keyword(s):  
Clinical Trials ◽  
Data Sharing ◽  
Translational Medicine ◽  
Wearable Devices ◽  
Health Data ◽  
Future Developments ◽  
Academic Hospitals ◽  
Data Ownership ◽  
Professional Health ◽  
Valley Of Death

In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these ‘big data’ put together can be utilized to optimize treatments for each unique patient (‘precision medicine’). For this to be possible, it is necessary that hospitals, academia and industry work together to bridge the ‘valley of death’ of translational medicine. However, hospitals and academia often are reluctant to share their data with other parties, even though the patient is actually the owner of his/her own health data. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. There are some publicly available datasets, but these are usually only shared after study (and publication) completion, which means a severe delay of months or even years before others can analyse the data. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here, we show an analysis of the current literature around data sharing, and we discuss five aspects of data sharing in the medical domain: publisher requirements, data ownership, growing support for data sharing, data sharing initiatives and how the use of federated data might be a solution. We also discuss some potential future developments around data sharing, such as medical crowdsourcing and data generalists.

scholarly journals Perceptions of anonymised data use and awareness of the NHS data opt-out amongst patients, carers and healthcare staff

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
C. Atkin ◽  
B. Crosby ◽  
K. Dunn ◽  
G. Price ◽  
E. Marston ◽  
...  
Keyword(s):  
Data Sharing ◽  
Public Awareness ◽  
Data Use ◽  
Academic Research ◽  
Secondary Data ◽  
Data Access ◽  
Health Data ◽  
Healthcare Staff ◽  
Secondary Use ◽  
Opt Out

Abstract Background England operates a National Data Opt-Out (NDOO) for the secondary use of confidential health data for research and planning. We hypothesised that public awareness and support for the secondary use of health data and the NDOO would vary by participant demography and healthcare experience. We explored patient/public awareness and perceptions of secondary data use, grouping potential researchers into National Health Service (NHS), academia or commercial. We assessed awareness of the NDOO system amongst patients, carers, healthcare staff and the public. We co-developed recommendations to consider when sharing unconsented health data for research. Methods A patient and public engagement program, co-created and including patient and public workshops, questionnaires and discussion groups regarding anonymised health data use. Results There were 350 participants in total. Central concerns for health data use included unauthorised data re-use, the potential for discrimination and data sharing without patient benefit. 94% of respondents were happy for their data to be used for NHS research, 85% for academic research and 68% by health companies, but less than 50% for non-healthcare companies and opinions varied with demography and participant group. Questionnaires showed that knowledge of the NDOO was low, with 32% of all respondents, 53% of all NHS staff and 29% of all patients aware of the NDOO. Recommendations to guide unconsented secondary health data use included that health data use should benefit patients; data sharing decisions should involve patients/public. That data should remain in close proximity to health services with the principles of data minimisation applied. Further, that there should be transparency in secondary health data use, including publicly available lists of projects, summaries and benefits. Finally, organisations involved in data access decisions should participate in programmes to increase knowledge of the NDOO, to ensure public members were making informed choices about their own data. Conclusion The majority of participants in this study reported that the use of healthcare data for secondary purposes was acceptable when accessed by NHS. Academic and health-focused companies. However, awareness was limited, including of the NDOO. Further development of publicly-agreed recommendations for secondary health data use may improve both awareness and confidence in secondary health data use.

scholarly journals A 21st Century Embarrassment of Riches: The Balance Between Health Data Access, Usage, and Sharing

2018 ◽  
Vol 27 (01) ◽  
pp. 005-006 ◽  
Author(s):  
John Holmes ◽  
Lina Soualmia ◽  
Brigitte Séroussi
Keyword(s):  
Data Sharing ◽  
21St Century ◽  
Data Privacy ◽  
Data Access ◽  
Health Data ◽  
Editorial Team ◽  
Special Topic ◽  
Related Data ◽  
Health Related ◽  
Different Sources

Objectives: To provide an introduction to the 2018 International Medical Informatics Association (IMIA) Yearbook by the editors. Methods: This editorial provides an overview and introduction to the 2018 IMIA Yearbook which special topic is: “Between access and privacy: Challenges in sharing health data”. The special topic editors and section are discussed, and the new section of the 2018 Yearbook, Cancer Informatics, is introduced. Changes in the Yearbook editorial team are also described. Results: With the exponential burgeoning of health-related data, and attendant demands for sharing and using these data, the special topic for 2018 is noteworthy for its timeliness. Data sharing brings responsibility for preservation of data privacy, and for this, patient perspectives are of paramount importance in understanding how patients view their health data and how their privacy should be protected. Conclusion: With the increase in availability of health-related data from many different sources and contexts, there is an urgent need for informaticians to become aware of their role in maintaining the balance between data sharing and privacy.

scholarly journals Open Data: Implications on Privacy in Healthcare Research

2020 ◽  
Author(s):  
David Chen
Keyword(s):  
Data Privacy ◽  
Open Data ◽  
Health Data ◽  
Healthcare Research ◽  
Public Healthcare ◽  
Data Governance ◽  
Healthcare Data ◽  
Private And Public ◽  
Policy Direction ◽  
Healthcare Innovation

The advent of open data in health care has increased healthcare innovation, with the publication of complete datasets aggregated by private and public entities that lead to efficiency through crowdsourcing working code, facilitating research into personalized medicine, and publishing reproducible data pipelines for experimental validation. However, there lacks an internationally recognized definition for health data governance at the scope of individual health data and open source big data, which bring about a discussion about the implications of open data on data privacy. First, healthcare data sourced directly from public healthcare systems: by whom and for what purpose is these data used for within the context of healthcare research. Second, health data from private research: the regulations needed for mutual disclosure. Third, personal user-generated health data: safeguards in a digital era needed to prevent misappropriation and abuse. This paper addresses the opportunities of open data in healthcare research in a digital age without transparent regulation. The consequence of open data on privacy leads to a framework of four safeguards for stakeholders: public education, operational transparency, regulation for accountability, and validation of research ethics. It also pioneers public policy direction for a balanced agenda between privacy and healthcare research.

scholarly journals Public engagement with health data governance: the role of visuality

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Joanna Sleigh ◽  
Effy Vayena
Keyword(s):  
Data Sharing ◽  
Information And Communication Technologies ◽  
Public Engagement ◽  
Public Support ◽  
Personal Data ◽  
Analytical Framework ◽  
Health Data ◽  
Policy Debate ◽  
Data Governance ◽  
Communicative Practices

AbstractOver the last years, public engagement has become a topic of scholarly and policy debate particularly in biomedicine, a field that increasingly centres around collecting, sharing and analysing personal data. However, the use of big data in biomedicine poses specific challenges related to gaining public support for health data usage in research and clinical settings. The improvement of public engagement practices in health data governance is widely recognised as critical to address this issue. Based on OECD guidance, public engagement serves to enhance transparency and accountability, and enable citizens to actively participate in shaping what affects their lives. For health research initiatives, this provides a way to cultivate cooperation and build public trust. Today, the exact formats of public engagement have evolved to include approaches (such as social media, events and websites) that exploit visualisation mediated by emerging information and communication technologies. Much scholarship acknowledges the advantages of visuality for public engagement, particularly in information-dense and digital contexts. However, little research has examined how health data governance actors utilise visuality to promote clarity, understandability and audience participation. Beyond simply acknowledging the diversity of possible formats, attention must also be paid to visualisations’ rhetorical capacity to convey arguments and ideas and motivate particular audiences in specific situations. This paper seeks to address this gap by analysing both the approaches and methods of argumentation used in two visual public engagement campaigns. Based on Gottweis’ analytical framework of argumentative performativity, this paper explores how two European public engagement facilitators construct contending narratives in efforts to make sense of and grapple with the challenges of health data sharing. Specifically, we analyse how their campaigns employ the three rhetorical elements logos, ethos and pathos, proposed by Gottweis to assess communicative practices, intermediated and embedded in symbolically rich social and cultural contexts. In doing so, we highlight how visual techniques of argumentation seek to bolster engagement but vary with rhetorical purposes, as while one points to health data sharing risks, the other focuses on benefits. Moreover, drawing on digital and visual anthropology, we reflect on how the digitalisation of communicative practices impacts visual power.

A Systematic Review of Privacy Preserving Healthcare Data Sharing on Blockchain

2020 ◽  
pp. 31-37
Author(s):  
Mustafa Tanriverdi ◽  
Keyword(s):  
Data Sharing ◽  
Data Privacy ◽  
Privacy Preserving ◽  
Health Data ◽  
Health Records ◽  
Healthcare Data ◽  
Shared Data ◽  
Quality Of Health Services ◽  
Electronic Health

Sharing the electronic health data helps to increase the accuracy of the diagnoses and to improve the quality of health services. This shared data can also be used in medical research and can reduce medical costs. However, health data are fragmented across decentralized hospitals, this prevents data sharing and puts patients’ privacy at risks. In recent years, blockchain has revealed solutions that make life easier in many areas thanks to its distributed, safe and immutable structure. There are many blockchain-based studies in the literature on providing data privacy and sharing in different areas. In some studies, blockchain has been used with technologies such as cloud computing and cryptology. In the field of healthcare blockchain-based solutions are offered for the management and sharing of Electronic health records. In these solutions, private and consortium blockchain types are generally preferred and Public Key Infrastructure (PKI) and encryption are used for data privacy. Within the scope of this study, blockchain-based studies on the privacy preserving data sharing of health data were examined. In this paper, information about the studies in the literature and potential issues that can be studied in the future were discussed. In addition, information about current blockchain technologies such as smart contracts and PKI is also given.

scholarly journals Sharing Is Caring – Data Sharing Initiatives in Healthcare

2020 ◽  
Author(s):  
Tim Hulsen
Keyword(s):  
Precision Medicine ◽  
Data Sharing ◽  
Citation Rate ◽  
Wearable Devices ◽  
Health Data ◽  
Future Developments ◽  
Academic Hospitals ◽  
Data Ownership ◽  
Professional Health ◽  
Valley Of Death

In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these data combined form ‘big data’ that can be utilized to optimize treatments for each unique patient (‘precision medicine’). To achieve this precision medicine, it is necessary that hospitals, academia and industry work together to bridge the ‘valley of death’ of translational medicine. However, hospitals and academia often have problems with sharing their data, even though the patient is actually the owner of his/her own health data, and the sharing of data is associated with increased citation rate. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. The idea that society benefits the most if the patient’s data are shared as soon as possible so that other researchers can work with it, has not taken root yet. There are some publicly available datasets, but these are usually only shared after studies are finished and/or publications have been written based on the data, which means a severe delay of months or even years before others can use the data for analysis. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here we discuss several aspects of data sharing in the medical domain: publisher requirements, data ownership, support for data sharing, data sharing initiatives and how the use of federated data might be a solution. We also discuss some potential future developments around data sharing.

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