VALIDATION OF AN ELECTRONIC ALGORITHM TO IDENTIFY
CANDIDATES FOR COLON SURGICAL SITE INFECTION REVIEW
JA Yegge1, K Gase1, M Hohrein1, H Xu1, R Khoury1, H Babcock2 1BJC HealthCare, St. Louis MO, 2Washington University, St. Louis, MO
In response to an increasing surveillance burden, an electronic algorithm was developed in 2009 to identify surgical site infection (SSI) candidates.
METHOD
RESULTS
The algorithm rules look for readmissions after
a qualifying procedure in addition to cultures,
antibiotic starts and ICD-9 infection codes.
The SSI candidates are sent to an Infection
Preventionist’s work list for review.
Every colon procedure (identified by ICD-9 code) performed between 10/1/2012-12/31/2012 at 10 BJC Healthcare system adult hospitals were included. The electronic medical
records were screened by a single clinical abstractor. Based on the abstracted information a single Infection Preventionist reviewed all procedures identified as potentially
infected to determine infection status using 2012 National Healthcare Safety Network definitions. Specificity, sensitivity, positive and negative predictive values were calculated.
The objective of this study was to
examine the algorithm’s accuracy as a
surveillance method for colon SSIs.
Test
Calculation & Result
Sensitivity
17/(17+1) = 94.45%
Specificity
301/ (301+98) =75.44%
Positive Predictive
Value (PPV)
17/(17+98) = 14.79%
Negative Predictive
Value (NPV)
301/(301+1) = 99.67%
28% 115 Triggered Algorithm
417
Procedures
Identified
72% 302 Did Not Trigger
Algorithm
1
Confirmed Case
(Not Identified by
Trigger)
17
Confirmed
Cases
CONCLUSION
These results confirm that the algorithm is highly effective in rejecting true negatives for further evaluation. It is also highly effective in capturing true positives within the
subset identified for infection investigation. Additional refinement of the algorithm rules is needed to decrease the number of procedures that are flagged for review.
This will decrease the time the Infection Preventionist spends on chart review while not missing any infected cases.
Nothing to Disclose