Accuracy of Electronic Surveillance of Catheter-Associated Urinary Tract Infection at an Academic Medical Center

Objective.

To develop and validate a methodology for electronic surveillance of catheter-associated urinary tract infections (CAUTIs).

Design.

Diagnostic accuracy study.

Setting.

A 425-bed university hospital.

Subjects.

A total of 1,695 unique inpatient encounters from November 2009 through November 2010 with a high clinical suspicion of CAUTI.

Methods.

An algorithm was developed to identify incident CAUTIs from electronic health records (EHRs) on the basis of the Centers for Disease Control and Prevention (CDC) surveillance definition. CAUTIs identified by electronic surveillance were compared with the reference standard of manual surveillance by infection preventionists. To determine diagnostic accuracy, we created 2 × 2 tables, one unadjusted and one adjusted for misclassification using chart review and case adjudication. Unadjusted and adjusted test statistics (percent agreement, sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], and κ) were calculated.

Results.

Electronic surveillance identified 64 CAUTIs compared with manual surveillance, which identified 19 CAUTIs for 97% agreement, 79% sensitivity, 97% sensitivity, 23% PPV, 100% NPV, and κ of .33. Compared with the reference standard adjusted for misclassification, which identified 55 CAUTIs, electronic surveillance had 98% agreement, 80% sensitivity, 99% specificity, 69% PPV, 99% NPV, and κ of .71.

Conclusion.

The electronic surveillance methodology had a high NPV and a low PPV compared with the reference standard, indicating a role of the electronic algorithm in screening data sets to exclude cases. However, the PPV markedly improved compared with the reference standard adjusted for misclassification, suggesting a future role in surveillance with improvements in EHRs.

Infect Control Hosp Epidemiol2014;35(6):685–691

Accuracy of electronic surveillance of catheter-associated urinary tract infection at an academic medical center

OBJECTIVE

To develop and validate a methodology for electronic surveillance of catheter-associated urinary tract infections (CAUTIs).

DESIGN

Diagnostic accuracy study.

SETTING

A 425-bed university hospital.

SUBJECTS

A total of 1,695 unique inpatient encounters from November 2009 through November 2010 with a high clinical suspicion of CAUTI.

METHODS

An algorithm was developed to identify incident CAUTIs from electronic health records (EHRs) on the basis of the Centers for Disease Control and Prevention (CDC) surveillance definition. CAUTIs identified by electronic surveillance were compared with the reference standard of manual surveillance by infection preventionists. To determine diagnostic accuracy, we created 2 × 2 tables, one unadjusted and one adjusted for misclassification using chart review and case adjudication. Unadjusted and adjusted test statistics (percent agreement, sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], and κ) were calculated.

RESULTS

Electronic surveillance identified 64 CAUTIs compared with manual surveillance, which identified 19 CAUTIs for 97% agreement, 79% sensitivity, 97% sensitivity, 23% PPV, 100% NPV, and κ of .33. Compared with the reference standard adjusted for misclassification, which identified 55 CAUTIs, electronic surveillance had 98% agreement, 80% sensitivity, 99% specificity, 69% PPV, 99% NPV, and κ of .71.

CONCLUSION

The electronic surveillance methodology had a high NPV and a low PPV compared with the reference standard, indicating a role of the electronic algorithm in screening data sets to exclude cases. However, the PPV markedly improved compared with the reference standard adjusted for misclassification, suggesting a future role in surveillance with improvements in EHRs.

Cell seeding in porous transplantation devices

Porous laminated discs of 1.35 cm diameter and thickness of 0.5 cm fashioned from biodegradable polymers were used as scaffolds for the transplantation of isolated cell populations. The distribution of cells seeded in these devices via injection was modelled with a system of dyed polymeric microparticles. Optimization of parameters related to device design and surgical injection conditions was carried out to maximize the device volume effectively employed in cell transplantation. The area of distribution on the top surface of each device was determined by image analysis techniques and used as a measure of the spatial distribution of injected particles. For poly(L-lactic acid) devices of porosity of 0.83 and median pore diameter of 166 microns seeded with 6 microns beads under standard injection conditions, the average surface area of distribution was 44.45% (+/- 3.36%). The device pore size was found to be a crucial determinant of particle distribution, whilst particle size in the range of 1-10 microns was not found to be important for the devices tested. Application of these results to the seeding of hepatocyte suspensions was made.