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Health Information Technology and Healthcare Information System01:30

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IBM's Health Analytics and Clinical Decision Support.

M S Kohn1, J Sun, S Knoop

  • 1Martin S. Kohn, MD, MS, FACEP, FACPE, Chief Medical Scientist, Jointly Health, Big Data Analytics for Remote Patient Monitoring, 120 Vantis, #570, Aliso Viejo, CA, 92656, USA,

Yearbook of Medical Informatics
|August 16, 2014
PubMed
Summary
This summary is machine-generated.

Big data and health analytics are crucial for transforming healthcare by improving evidence-based decision-making. These tools offer insights for personalized patient care, though data quality remains a limitation.

Keywords:
Big Dataevidence-supported decision makinghealthcare analyticshealthcare transformation

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Area of Science:

  • Healthcare Informatics
  • Big Data Analytics
  • Clinical Decision Support

Background:

  • Healthcare transformation necessitates improved decision-making through better information utilization.
  • Existing healthcare systems face challenges in managing and analyzing diverse information sources.

Purpose of the Study:

  • To explore the role of big data and health analytics in supporting evidence-based decision-making in healthcare.
  • To examine how IBM's analytic resources contribute to healthcare transformation.

Main Methods:

  • Review of healthcare problems and proposed change strategies.
  • Description of analytic resources designed to address information challenges.
  • Presentation of examples illustrating the application of these resources.

Main Results:

  • Powerful analytic tools leverage big data for personalized, evidence-based clinical decisions.
  • These resources extract relevant information and provide actionable insights for clinicians.
  • Early evidence suggests clinical value, but data quantity and quality pose limitations.

Conclusions:

  • Big data is integral to the future of personalized, evidence-supported healthcare.
  • Effective management and utilization of big data are essential for healthcare transformation.
  • Cognitive computing resources are vital for overcoming big data challenges in healthcare, supporting but not driving transformation.