The acquisition and management of healthcare data, within a hospital infrastructure

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The quality of care provided to citizens by professionals and institutions depends on the quality and availability of information. Early commencement of treatment and medication, and the decisions on how to proceed, depend a lot on patients' data in the different modalities available. It is also important to notice that large pools of data help inform health and wellbeing parameters for the largest possible community. To make that possible it is necessary both to have the best hospital practices but also to get consent and collaboration from patients. In order to accomplish such a goal, it is necessary to use practices, which adhere to legal constraints and are transparent while handling data and also to transmit those practices and protocols to professionals and patients. The present document aims to provide a framework envisaging the seamless application of the clinical procedures, following legal guidance and making the process known, secure and trustworthy. It aims to contribute to clinical practice, and clinical research, thereby contributing to big data analysis by ensuring trust and best clinical data handling.

Original languageEnglish
Title of host publicationAdvanced Manufacturing
PublisherAmerican Society of Mechanical Engineers (ASME)
Number of pages6
ISBN (Electronic)9780791884492
DOIs
Publication statusPublished - 16 Feb 2021
EventASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020 - Virtual, Online
Duration: 16 Nov 202019 Nov 2020

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
PublisherAmerican Society of Mechanical Engineers (ASME)
Volume2B-2020

Conference

ConferenceASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020
CityVirtual, Online
Period16/11/2019/11/20

Keywords

  • Anonymization
  • Artificial intelligence
  • Data protection
  • GDPR

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