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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Sharing big biomedical data.

Arthur W Toga1, Ivo D Dinov2

  • 1Laboratory of Neuro Imaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of USC, University of Sothern California, 2001 North Soto Street-Room 102, Los Angeles, CA 90033, USA.

Journal of Big Data
|March 2, 2016
PubMed
Summary
This summary is machine-generated.

Developing practical data sharing policies is essential for harnessing the potential of Big Biomedical Data. Addressing technical, social, and financial challenges ensures a sustainable scientific community.

Keywords:
AnalyticsBig dataPolicyPrivacySharing

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Area of Science:

  • Biomedical Informatics
  • Data Science
  • Health Informatics

Background:

  • Big Biomedical Data presents significant opportunities but faces challenges in handling, analysis, and sharing.
  • Existing data practices are hindered by technical, social, regulatory, and institutional barriers.

Purpose of the Study:

  • To propose a framework for practical and sustainable Big Data sharing policies.
  • To integrate sociological, financial, technical, and scientific requirements for a data-dependent scientific community.

Main Methods:

  • Framework development for data sharing policies.
  • Incorporation of multi-faceted requirements (sociological, financial, technical, scientific).

Main Results:

  • Large, heterogeneous datasets can impact biomedical and healthcare studies.
  • Barriers to Big Data utilization include technical, social, regulatory, and institutional factors.

Conclusions:

  • Pragmatic policies promoting data sharing, fusion, and interoperability are crucial.
  • Balancing data security and personal information protection is vital for translational Big Data analytics.