scholarly journals Sharing Is Caring—Data Sharing Initiatives in Healthcare

Author(s):  
Tim Hulsen

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.

Author(s):  
Tim Hulsen

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.


2019 ◽  
Vol 28 (01) ◽  
pp. 195-202 ◽  
Author(s):  
Marc Cuggia ◽  
Stéphanie Combes

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.


BMJ ◽  
2017 ◽  
pp. j2372 ◽  
Author(s):  
Darren B Taichman ◽  
Peush Sahni ◽  
Anja Pinborg ◽  
Larry Peiperl ◽  
Christine Laine ◽  
...  
Keyword(s):  

Author(s):  
Kelly Bridgham ◽  
Akash Chandawarkar ◽  
Halley Darrach ◽  
Justin M. Sacks

2021 ◽  
Author(s):  
Timothy Coetzee ◽  
Mad Price Ball ◽  
Marc Boutin ◽  
Abby Bronson ◽  
David T Dexter ◽  
...  
Keyword(s):  

UNSTRUCTURED REMOVE


Author(s):  
Jackie Street ◽  
Belinda Fabrianesi ◽  
Rebecca Bosward ◽  
Stacy Carter ◽  
Annette Braunack-Mayer

IntroductionLarge volumes of health data are generated through the interaction of individuals with hospitals, government agencies and health care providers. There is potential in the linkage and sharing of administrative data with private industry to support improved drug and device provision but data sharing is highly contentious. Objectives and ApproachWe conducted a scoping review of quantitative and qualitative studies examining public attitudes towards the sharing of health data, held by government, with private industry for research and development. We searched four data bases, PubMed, Scopus, Cinahl and Web of Science as well as Google Scholar and Google Advanced. The search was confined to English-only publications since January 2014 but was not geographically limited. We thematically coded included papers. ResultsWe screened 6788 articles. Thirty-six studies were included primarily from UK and North America. No Australian studies were identified. Across studies, willingness to share non-identified data was generally high with the participant’s own health provider (84-91%) and academic researchers (64-93%) but fell if the data was to be shared with private industry (14-53%). There was widespread misunderstanding of the benefits of sharing data for health research. Publics expressed concern about a range of issues including data security, misuse of data and use of data to generate profit. Conditions which would increase public confidence in sharing of data included: strict safeguards on data collection and use including secure storage, opt-in or opt-out consent mechanisms, and good communication through trusted agents. Conclusion / ImplicationsWe identified a research gap: Australian views on sharing government health data with private industry. The international experience suggests that public scepticism about data sharing with private industry will need to be addressed by good communication about public benefit of data sharing, a strong program of public engagement and information sharing conducted through trusted entities.


Author(s):  
Katina Michael ◽  
Deniz Gokyer ◽  
Samer Abbas

This chapter presents a set of scenarios involving the GoPro wearable Point of View (PoV) camera. The scenarios are meant to stimulate discussion about acceptable usage contexts with a focus on security and privacy. The chapter provides a wide array of examples of how overt wearable technologies are perceived and how they might/might not be welcomed into society. While the scenario is based at the University of Wollongong campus in Australia, the main implications derived from the fictitious events are useful in drawing out the predicted pros and cons of the technology. The scenarios are interpreted and the main thematic issues are drawn out and discussed. An in depth analysis takes place around the social implications, the moral and ethical problems associated with such technology, and possible future developments with respect to wearable devices.


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