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Volume 36, Issue 3, Pages 155-164 (April 2008)


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Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care–associated infections

Kurt B. Stevenson, MD, MPHabCorresponding Author Informationemail address, Yosef Khan, MBBS, MPHab, Jeanne Dickman, MT, CICa, Terri Gillenwater, RN, BSNc, Pat Kulich, RN, CICa, Carol Myers, RN, BSN, CICa, David Taylor, PhDa, Jennifer Santangelo, BAd, Jennifer Lundy, BS, MHAd, David Jarjoura, PhDe, Xiaobai Li, PhDe, Janice Shook, BSb, Julie E. Mangino, MDab

Background

ICD-9-CM coding alone has been proposed as a method of surveillance for health care-associated infections (HAIs). The accuracy of this method, however, relative to accepted infection control criteria is not known.

Methods

Retrospective analysis of patients at an academic medical center in 2005 who underwent surgical procedures or who were at risk for catheter-associated bloodstream infections or ventilator-associated pneumonia was performed. Patients previously identified with HAIs by Centers for Disease Control and Prevention's National Healthcare Safety Network surveillance methods were compared with those of the same risk group identified by secondary infection ICD-9-CM codes. Discordant cases identified by only coding were all rereviewed and adjusted prior to final analysis. When coding and surveillance were both negative, a sample of patients was used to estimate the proportion of false negatives in this group.

Results

The positive predictive values (PPVs) ranged from 0.14 to 0.51 with an aggregate of 0.23, even after adjustment for additional cases detected on subsequent medical record review. The negative predictive values (NPVs) ranged from 0.91 to 1.00, with an aggregate of 0.96. The estimates of the true variance of PPVs and NPVs across surgical procedures were small (0.0129, standard error, 0.009; 0.000145, standard error, 0.00019, respectively) and could be mostly explained by variation in prevalence of surgical site infections.

Conclusion

Administrative coding alone appears to be a poor tool to be used as an infection control surveillance method. Its proposed use for routine HAI surveillance, public reporting of HAIs, interfacility comparisons, and nonpayment for performance should be seriously questioned.

a Department of Clinical Epidemiology, Ohio State University Medical Center, Columbus, OH

b Division of Infectious Diseases, College of Medicine, Columbus, OH

c Department of Quality and Operations, Ohio State University Medical Center, Columbus, OH

d OSUMC Information Warehouse, Ohio State University Medical Center, Columbus, OH

e Center for Biostatistics, The Ohio State University, Columbus, OH

Corresponding Author InformationAddress correspondence to Kurt B. Stevenson, MD, MPH, Associate Professor of Medicine, Division of Infectious Diseases, Department of Internal Medicine, The Ohio State University College of Medicine, N1147 Doan Hall, 410 West 10th Avenue, Columbus, OH 43210.

 Financial disclosures: None.

 Supported by the Research Foundation of the Association for Professionals in Infection Control and Epidemiology (APIC Research Foundation).

PII: S0196-6553(08)00087-4

doi:10.1016/j.ajic.2008.01.004


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