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Exploring the promise of big data for medical error elimination

Objective

Errors in hospitals pose serious threats to human lives and affect total costs. Big data research is fast becoming a tool that not only analyzes patterns but can also provide the predictive likelihood of an event. Big data may be a great opportunity to make data an engine to dramatically decrease error rates in hospital. However, there is very little published research literature that tackles the challenges of using big data in organizations and explores the promise and opportunities for new theories and practices that big data might bring about. The overriding objective of this proposal is to explore the promise of big data for eliminating and managing errors in hospitals. The beneficiary, Prof Eitan Naveh from the Technion – Israel Institute of Technology, is a world leading researcher in the area of errors. The partner organization is Harvard University. The partnership member from Harvard is Prof Sara Singer, a world-class leading Professor of Health Policy and Management at Harvard’s T.H. Chan School of Public Health. Prof Naveh will spend the first year of the research project in Harvard and will be hosted by Prof Singer. During the fellowship, Prof Naveh will obtain training and new knowledge in Harvard’s exciting environment, and specifically in Prof Singer’s new health care High Reliability Learning Lab. Prof Naveh will gain training and new knowledge that refers to new interdisciplinary scientific techniques and transferable skills in big data, and will set a new research agenda for the science of errors in hospitals. The competences Prof Naveh will gain will allow new state-of-the-art research with opportunities to practice and improve health care. Prof Naveh will develop a network to communicate and disseminate the study’s results and to realize its exploration and developments.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF-GF - Global Fellowships

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2015

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Coordinator

TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 177 319,80
Address
SENATE BUILDING TECHNION CITY
32000 Haifa
Israel

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Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 177 319,80

Partners (1)

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