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Privacy-preserved Syntheic Data in Healthcare

The Role of Data in Healthcare Organizations

Data usage in healthcare organizations is crucial for enabling evidence-based medical decisions, personalized treatments, and medical research. This leads to enhanced patient outcomes, improved operational efficiency, and advancements in medical knowledge and technologies. Synthetic data offers a privacy-preserving alternative by creating realistic and non-sensitive datasets, empowering researchers, clinicians, and data scientists to innovate, validate algorithms, and conduct analyses without compromising patient privacy.

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AI Healthcare Market Value by 2027: $67.4 billion

Insufficient Access to Patient Data: 60% of consumers.

Health Records as Targets: 95% of identity theft cases.

AI in Healthcare IT by 2024: 60% adoption for automation and decision-making.

TESTIMONIALS

Benefits for the healthcare Industry

Hospitals

  • Improve Patient Care: Reduce the time required to access data.
  • Protect Personal Health Information (PHI): Safeguard data from Electronic Health Record Systems (EHR, MHR).
  • Enhance Data Utilization: Boost predictive analytics capabilities.
  • Software Development: Address the lack of realistic data for testing.
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Pharma & Life Sciences

  • Efficient Collaboration: Share data with health systems, payers, and related institutions.
  • Overcome Data Silos: Facilitate data sharing.
  • Clinical Trials: Perform studies to understand drug efficacy on new diseases.
  • Speed Up Analysis: Complete full analyses quickly with less effort.
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Academic Research

  • Accelerate Research: Access data faster and easier.
  • Hypothesis Evaluation: Gain access to more data for research.
  • Precision Healthcare: Generate and share data to support precision healthcare.
  • Feasibility Checks: Evaluate project feasibility before requesting original data access.
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Anonymization techniques destroy data quality, while data accuracy is crucial in health (e.g. for academic research and clinical trials).

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Why health Organizations Consider Synthetic DataData API?

  • Privacy Sensitivity: Health data is highly sensitive with stringent privacy regulations.
  • Innovation: Data is vital for health innovation amidst understaffed and over-pressured conditions.
  • Data Quality: Anonymization techniques often compromise data quality, which is crucial for research and clinical trials.
  • Data Exchange: Collaborative data exchange has enormous potential for health organizations, systems, drug developers, and researchers.
  • Cost Reduction: Analytics driven by data can help healthcare organizations reduce costs.
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