Data Harmonization Challenges
Data harmonization is the process by which fragmented datasets are transformed into standardized formats. In clinical research, it enables effective integration and analysis of data. However, this process is challenging and can slow down research and impact outcomes.
Current Industry Problems
Clinical data is often dispersed across platforms like electronic health records (EHRs), biobanks, and clinical trial repositories. One of the most pressing issues in data harmonization is differences in conventions, terminologies, and data formats between data sources. For instance, a biomarker might be referred to by different names or units in separate datasets or a single dataset might include inconsistent units of measurement (e.g., mg/dL vs. mmol/L) or incomplete metadata. This introduces errors and delays during the harmonization process and prevents meaningful comparisons across studies or institutions. Data silos exacerbate these challenges by restricting access and hindering collaboration across institutions. These silos make it difficult to aggregate data for cross-study analyses, limiting the ability to develop comprehensive insights or patient profiles.
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