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Alliance chain-based simulation on a new clinical research data pricing model.

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A new data pricing model quantifies medical data value in multicenter clinical research. This model addresses challenges in evaluating data contributions, offering a quantitative approach for fair data valuation.

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Area of Science:

  • Health Economics
  • Data Science
  • Clinical Research Informatics

Background:

  • Multicenter clinical research presents challenges in quantitatively assessing each center's data contribution.
  • Existing data pricing models inadequately address the specific needs of clinical research scenarios.
  • A robust mechanism is required to accurately measure the value of medical data in research settings.

Purpose of the Study:

  • To develop and validate a quantitative data pricing model for multicenter clinical research.
  • To establish a framework for evaluating the value of medical data contributions from different research centers.
  • To address the limitations of current models in the context of clinical data sharing and collaboration.

Main Methods:

  • Analysis of diverse data sources including rare disease lists, electronic medical records (EMR) structures, and provincial healthcare regulations.
  • Expert consultation with nine senior professionals in clinical research, data governance, and health economics.
  • Identification and weighting of seven key data attributes, followed by quantization using proposed algorithms.
  • Development of distinct data value models for chronic and other diseases based on data timeliness sensitivity.
  • Construction of a simulation system utilizing blockchain and federated learning to validate the pricing model.

Main Results:

  • A comprehensive clinical data pricing model was proposed.
  • Simulation involving three research centers and 50 million real clinical data entries demonstrated the model's effectiveness.
  • The model successfully computed the quantitative value of medical data.

Conclusions:

  • The proposed data pricing model effectively enables quantitative evaluation of medical data value in multicenter clinical research simulations.
  • The model shows promise for real-world application and future refinement in clinical research settings.