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Related Concept Videos

Data Collection I01:30

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Source-oriented records, or SOR, are medical record-keeping organized by the data source. The SOR system was first developed in the mid-1900s to organize the growing patient data in hospitals and other healthcare facilities.
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Data Collection III01:05

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Agreement between veterinary patient data collected from different sources.

Natalie J Robinson1, Marnie L Brennan1, Malcolm Cobb2

  • 1Centre for Evidence-based Veterinary Medicine, School of Veterinary Medicine and Science, The University of Nottingham, Sutton Bonington Campus, Loughborough, UK.

Veterinary Journal (London, England : 1997)
|May 20, 2015
PubMed
Summary

The accuracy of electronic medical records (EMR) in veterinary practices was assessed by comparing EMR data with owner and observer records. Most signalment data showed strong agreement, vital for reliable practice-based research.

Keywords:
Electronic medical recordElectronic patient recordPractice-based researchVeterinary consultationsVeterinary informatics

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Area of Science:

  • Veterinary medicine
  • Data science in healthcare
  • Clinical informatics

Background:

  • Accurate electronic medical records (EMR) are crucial for advancing practice-based research in veterinary medicine.
  • Signalment data (breed, age, sex, neuter status) is fundamental for clinical studies.
  • The reliability of EMR data in veterinary settings requires validation.

Purpose of the Study:

  • To evaluate the agreement between signalment data recorded in veterinary EMR and data obtained from direct observation and owner reports.
  • To identify potential discrepancies in signalment data collection within veterinary practices.
  • To inform researchers about the reliability of EMR data for practice-based studies.

Main Methods:

  • Direct observation of small animal consultations across eight veterinary practices.
  • Systematic recording of signalment data (breed, age, sex, neuter status) from EMR, owners, and direct observation.
  • Statistical comparison of agreement between data sources for each signalment variable.

Main Results:

  • "Almost perfect" or "strong" agreement was found in 18 out of 28 comparisons between EMR data and other sources.
  • Variations in agreement levels were observed across different animal species.
  • The study highlights areas of high fidelity and potential inconsistencies in EMR data collection.

Conclusions:

  • EMR data for signalment in small animal veterinary practices demonstrates substantial accuracy, particularly for certain variables.
  • Researchers can be cautiously optimistic about using EMR data for practice-based research, acknowledging species-specific variations.
  • Further investigation into the accuracy of other EMR data types is warranted to fully understand its research utility.