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Related Experiment Videos

Data quality after restructuring a national medical registry

M Gissler1, J Teperi, E Hemminki

  • 1National Research and Development Centre for Welfare and Health (STAKES), Department of Public Health, University of Helsinki.

Scandinavian Journal of Social Medicine
|March 1, 1995
PubMed
Summary

Data validity in the Finnish Medical Birth Registry improved after form changes in 1990. Most variables showed good validity, though diagnoses and procedures need further refinement for better accuracy.

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Area of Science:

  • Public Health
  • Medical Informatics
  • Epidemiology

Background:

  • The Finnish Medical Birth Registry (FMBR) is a crucial source for public health research.
  • Ensuring the accuracy of registry data is vital for reliable epidemiological studies.
  • Changes to data collection forms can impact data quality.

Purpose of the Study:

  • To assess the validity of the 1991 Finnish Medical Birth Registry data.
  • To evaluate the impact of the 1990 data collection form modifications on data accuracy.
  • To identify areas for improvement in the FMBR data collection process.

Main Methods:

  • A sample of 865 births from a five-day period in 49 hospitals was selected.
  • Data from medical records were compared against FMBR register information.

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  • Validity was assessed for 33 variables, including continuous scales and check-box formats.

    • Main Results:

    • Good or satisfactory validity was achieved for 32 out of 33 variables with continuous scales.
    • Satisfactory validity was found for 10 out of 45 variables using a check-box format for diagnoses and procedures.
    • Improvements in validity were noted for variables converted to the check-box format compared to a 1987 study.

    Conclusions:

    • The 1991 FMBR data demonstrates good overall validity, particularly for continuously scaled variables.
    • Further improvements are needed for diagnoses and procedures recorded in check-box format.
    • Minor modifications to data collection forms can significantly influence data validity.