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Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
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Updated: Jun 4, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Data completeness can be optimized in clinical databases.

Peer Wille-Jørgensen1

  • 1Department of Surgery K, Bispebjerg Hospital, Faculty of Health Sciences, University of Copenhagen, Denmark. pwil0002@bbh.regionh.dk

Danish Medical Bulletin
|February 9, 2011
PubMed
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Data completeness in colorectal cancer reporting is crucial. Meticulous data control and comparison with national registries can minimize missing patient data in databases.

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Area of Science:

  • Oncology
  • Public Health
  • Health Informatics

Background:

  • Reporting colorectal cancer cases to national databases is essential for public health surveillance.
  • Data completeness in cancer registries is vital for accurate epidemiological analysis and treatment planning.

Purpose of the Study:

  • To analyze the incidence and causes of incomplete colorectal cancer data reporting from a hospital department to a national registry.
  • To identify specific error types and contributing factors to data incompleteness.

Main Methods:

  • Monthly error lists comparing the departmental database with the National Patient Registry were generated.
  • A detailed analysis of newly identified errors was conducted after a system revision in May 2009.
  • The nature and root causes of data discrepancies were investigated.

Main Results:

  • Out of 1,530 colorectal cancer patients, 60 (3.9%) were missing from the departmental database.
  • Erroneous diagnosis registration in the National Patient Registry by the department was the primary cause of missing data.
  • Clerical errors within the department also contributed significantly to data incompleteness.

Conclusions:

  • Minimizing missing patient data requires rigorous data control and cross-validation with national registries.
  • Addressing erroneous registration and clerical errors at the departmental level is key to improving data accuracy.
  • Systematic data quality checks are essential for maintaining comprehensive cancer registry information.