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Validity of the minimum data set in identifying urinary tract infections in residents of long-term care facilities

Kurt B Stevenson1, James W Moore, Barbara Sleeper

  • 1Qualis Health, Boise, Idaho, USA. kurts@qualishealth.org

Journal of the American Geriatrics Society
|April 17, 2004
PubMed
Abstract

Insights

The Minimum Data Set (MDS) overestimates urinary tract infections (UTIs) in long-term care facilities. Improved UTI definitions for providers using MDS could enhance accuracy for quality measurement.

Area of Science:

  • Gerontology
  • Infectious Diseases
  • Health Informatics

Background:

  • Urinary tract infections (UTIs) are common in long-term care facilities (LTCFs).
  • Accurate detection of UTIs is crucial for quality of care and resident outcomes.
  • The Minimum Data Set (MDS) is used for resident assessment in LTCFs.

Purpose of the Study:

  • To evaluate the validity of the Minimum Data Set (MDS) in identifying urinary tract infections (UTIs) based on evidence-based criteria.
  • To assess the accuracy of MDS for UTI detection in a long-term care setting.

Main Methods:

  • Prospective surveillance of infections in 16 Idaho LTCFs.
  • Data collection included clinical manifestations, microbiology, and treatment for all infections, including UTIs.
  • MDS data on UTI identification was compared against evidence-based criteria.

Main Results:

  • The overall validity of MDS for detecting UTIs was 14% against evidence-based criteria.
  • MDS demonstrated a sensitivity of 57.9% and specificity of 86.5%.
  • Positive predictive value was 13.9%, while negative predictive value was 98.2%.

Conclusions:

  • MDS has potential as a quality measure in LTCFs but significantly overestimates UTI cases.
  • MDS adequately screens out residents without UTIs.
  • Clearer UTI definitions for providers completing MDS are recommended to improve accuracy.

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