Olga Redondo-González M.D., M.P.H. José María Tenías M.D., Ph.D. Ángel Arias B.Sc., M.Sc. Alfredo J. Lucendo M.D., Ph.D., F.E.B.G.H.
Objective: To conduct an updated assessment of the validity and reliability of administrative coded data (ACD) in identifying hospitalacquired infections (HAIs).
Methods: We systematically searched three libraries for studies on ACD detecting HAIs compared to manual chart review. Metaanalyses were conducted for prosthetic and nonprosthetic surgical site infections (SSIs), Clostridium difficile infections (CDIs), ventilatorassociated pneumonias/events (VAPs/VAEs) and nonVAPs/VAEs, catheterassociated urinary tract infections (CAUTIs), and central venous catheterrelated bloodstream infections (CLABSIs). A randomeffects metaregression model was constructed.
Results: Of 1,906 references found, we retrieved 38 documents, of which 33 provided metaanalyzable data (N = 567,826 patients). ACD identified HAI incidence with high specificity (≥93 percent), prosthetic SSIs with high sensitivity (95 percent), and both CDIs and nonprosthetic SSIs with moderate sensitivity (65 percent). ACD exhibited substantial agreement with traditional surveillance methods for CDI (κ = 0.70) and provided strong diagnostic odds ratios (DORs) for the identification of CDIs (DOR = 772.07) and SSIs (DOR = 78.20). ACD performance in identifying nosocomial pneumonia depended on the ICD coding system (DORICD10/ICD9CM = 0.05; p = .036). Algorithmic coding improved ACD's sensitivity for SSIs up to 22 percent. Overall, high heterogeneity was observed, without significant publication bias.
Conclusions: Administrative coded data may not be sufficiently accurate or reliable for the majority of HAIs. Still, subgrouping and algorithmic coding as tools for improving ACD validity deserve further investigation, specifically for prosthetic SSIs. Analyzing a potential lower discriminative ability of ICD10 coding system is also a pending issue.