Propensity-Matched Cost of Infection Overdiagnosis.

Background: is the leading health care-associated pathogen, but clinicians lack a test that can reliably differentiate colonization from infection. Health care costs attributed to are substantial, but the economic burden associated with false positives is poorly understood.

Methods: A propensity score matching model for cost per hospitalization was developed to estimate the costs of both true infection and false positives. Predictors of positivity used to estimate the propensity score were age, Charlson comorbidity index, white cell count, and creatinine. We used polymerase chain reaction (PCR) cycle threshold to identify and compare 3 groups: (1) true infection, (2) colonization, and (3) negative.

Results: A positive test was associated with $3018 higher unadjusted hospital cost. Among the 3 comparisons made with propensity-matched negative controls (all positives [+$179; = .934], true positives [-$1892; = .100], and colonized positives), only colonization was associated with significantly increased (+$3418; = .012) cost. Differences in lengths of stay (all positives 0 days, = .126; true 0 days, = .919; colonized 1 day, = .019) appeared to underly cost differences.

Conclusions: In the first cost analysis to utilize PCR cycle threshold to differentiate colonization, we found high propensity-matched hospital costs associated with colonized but not true positives. This unexpected finding may be due to misdiagnosis of non- diarrhea or unadjusted factors associated with colonization.