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Comparative Study
. 2011 Aug;128(2):323-30.
doi: 10.1542/peds.2010-2064. Epub 2011 Jul 18.

Accuracy of administrative billing codes to detect urinary tract infection hospitalizations

Joel S Tieder  1 , Matthew Hall, Katherine A Auger, Paul D Hain, Karen E Jerardi, Angela L Myers, Suraiya S Rahman, Derek J Williams, Samir S Shah
Affiliations
Comparative Study

Accuracy of administrative billing codes to detect urinary tract infection hospitalizations

Joel S Tieder et al. Pediatrics. 2011 Aug.

Abstract

Background: Hospital billing data are frequently used for quality measures and research, but the accuracy of the use of discharge codes to identify urinary tract infections (UTIs) is unknown.

Objective: To determine the accuracy of International Classification of Diseases, 9th revision (ICD-9) discharge codes to identify children hospitalized with UTIs.

Methods: This multicenter study conducted in 5 children's hospitals included children aged 3 days to 18 years who had been admitted to the hospital, undergone a urinalysis or urine culture, and discharged from the hospital. Data were obtained from the pediatric health information system database and medical record review. With the use of 2 gold-standard methods, the positive predictive value (PPV) was calculated for individual and combined UTI codes and for common UTI identification strategies. PPV was measured for all groupings for which the UTI code was the principal discharge diagnosis.

Results: There were 833 patients in the study. The PPV was 50.3% with the use of the gold standard of laboratory-confirmed UTIs but increased to 85% with provider confirmation. Restriction of the study cohort to patients with a principle diagnosis of UTI improved the PPV for laboratory-confirmed UTI (61.2%) and provider-confirmed UTI (93.2%), as well as the ability to benchmark performance. Other common identification strategies did not markedly affect the PPV.

Conclusions: ICD-9 codes can be used to identify patients with UTIs but are most accurate when UTI is the principal discharge diagnosis. The identification strategies reported in this study can be used to improve the accuracy and applicability of benchmarking measures.

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Figures

FIGURE 1
FIGURE 1
Effect of principal diagnosis on hospital performance according to length of stay. The plot shows each hospital's mean length of stay with 95% CI for urinary tract infection listed as the principal diagnosis (dark circle) or as any diagnosis (open circle).
FIGURE 2
FIGURE 2
Change in hospital rank for individual and combined urinary tract infection discharge diagnosis codes as principal discharge diagnosis according to adjusted median LOS. The reference for comparison was the hospital rank when any of the discharge diagnosis codes were listed as the principal diagnosis. Values were adjusted for age, gender, race, and insurance type. The ICD-9 discharge diagnosis codes were identified as follows: acute pyelonephritis, 590.1; renal and perinephric abscess, 590.2; other pyelonephritis or pyonephrosis, not specified as acute or chronic, 590.8; UTI, site not specified, 599.0; and UTI of the newborn, 771.82.
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References

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