Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Limitations of electronic databases: a caution.

James E Svenson1, Susan H Pollack, Mary E Fallat

  • 1Section of Emergency Medicine, University of Wisconsin, C7/379 CSC, 600 Highland Avenue, Madison, WI 53792, USA.

The Journal of the Kentucky Medical Association
|April 5, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Workplace violence in trauma centers is a serious problem: an AAST Disaster Committee survey on assaults on trauma teams.

Trauma surgery & acute care open·2026
Same author

Trauma care in Morocco: observations and opportunities from an American Association for the Surgery of Trauma (AAST) delegation visit.

Trauma surgery & acute care open·2026
Same author

Pediatric firearm risk prediction in trauma centers and after discharge: A machine learning analysis.

Journal of pediatric surgery·2026
Same author

Current Status of US Children's Burn Care and Opportunities for Change.

Annals of surgery open : perspectives of surgical history, education, and clinical approaches·2026
Same author

Is Appendiceal Cancer a Risk of Nonoperative Management of Pediatric Uncomplicated Appendicitis?

The Journal of surgical research·2025
Same author

Findings in younger versus older patients with the symptoms of gastroparesis undergoing gastric electrical stimulation.

Journal of pediatric gastroenterology and nutrition·2025
Same journal

Distractive driving or sharks... you be the judge.

The Journal of the Kentucky Medical Association·2010
Same journal

Parental perception of children's weight as a function of ethnicity/race, gender, and age.

The Journal of the Kentucky Medical Association·2010
Same journal

Spurious hypoxemia.

The Journal of the Kentucky Medical Association·2010
Same journal

Funding for a healthy future in Kentucky.

The Journal of the Kentucky Medical Association·2010
Same journal

H1N1.

The Journal of the Kentucky Medical Association·2010
Same journal

The safety and price of guns in Kentucky.

The Journal of the Kentucky Medical Association·2010
See all related articles

Electronic health record data show significant errors. Both voluntary and mandated datasets require validation before use in research or policy decisions to ensure accuracy.

Area of Science:

  • Health Informatics
  • Data Science
  • Public Health

Background:

  • Electronic health records (EHRs) are increasingly used for healthcare research and policy.
  • Data accuracy and completeness are critical for reliable analysis.
  • Two primary sources of EHR data exist: voluntary submissions and mandated reporting.

Purpose of the Study:

  • To evaluate the completeness and accuracy of two distinct electronic health record datasets.
  • To compare voluntarily submitted data with data submitted via mandate.

Main Methods:

  • Compared Kentucky Emergency Medical Services Information System (KEMSIS) data with Uniform Billing Act (UB92) data.
  • Validated electronic data against manually abstracted emergency department (ED) logs and hospital medical records.

Related Experiment Videos

  • Focused on patients admitted to the hospital with specific diagnosis code ranges.

    • Main Results:

    • KEMSIS data captured 84% of ED records, but only 34% were correctly classified as admitted.
    • Only 9% of KEMSIS records accurately reflected the hospital of admission.
    • UB92 data included only 28% of relevant admitted patients, though diagnosis codes were concordant.

    Conclusions:

    • Significant misclassification and omissions exist in both voluntary and mandated electronic health record datasets.
    • Independent validation of electronic health data is essential prior to its use.
    • Ensuring data integrity is crucial for evidence-based healthcare policy and research.