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A perspective on harmonizing diabetes management datasets.

Miriam K Wolff1, Sam Royston2, Anders L Fougner3

  • 1Norwegian University of Science and Technology, Department of ICT and Natural Sciences, Larsgårdsvegen 2, 6009 Ålesund, Norway.

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|March 19, 2025
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Summary
This summary is machine-generated.

Standardizing diabetes management datasets improves research consistency and data sharing. This study proposes guidelines for a unified tabular format to harmonize heterogeneous data from various health devices.

Keywords:
Blood glucose predictionData harmonizationPhysiological modellingPredictive modellingSensor data integrationStandardizationTime series forecasting

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Area of Science:

  • Biomedical Informatics
  • Health Data Science
  • Diabetes Research

Background:

  • Diabetes management research utilizes diverse data from sensors and devices, leading to heterogeneous formats.
  • Inconsistent data formats and sharing practices hinder reproducibility and cross-study comparisons in diabetes research.

Purpose of the Study:

  • To explore current data-sharing practices in diabetes management research.
  • To propose guidelines for harmonizing heterogeneous datasets using a unified, time-aligned tabular format.
  • To address challenges in achieving data harmonization for improved research outcomes.

Main Methods:

  • Review of current data-sharing practices in diabetes management.
  • Development of guidelines for a unified time-aligned tabular data format.
  • Application and validation of proposed guidelines on three established diabetes datasets.

Main Results:

  • Identified significant inconsistencies in diabetes dataset formats and data-sharing practices.
  • Demonstrated the feasibility of harmonizing diverse datasets using the proposed unified tabular format.
  • Highlighted key challenges encountered during the data harmonization process.

Conclusions:

  • Standardized data-sharing formats are crucial for advancing diabetes management research.
  • Adoption of a unified time-aligned tabular format can enhance data consistency and facilitate dataset consolidation.
  • The research community is urged to develop and implement detailed recommendations for standardized data-sharing practices.