A Multicenter Study of the Epidemiology of Deep Surgical Site Infections in Children With Nonidiopathic Early-Onset Scoliosis Including Associated Pathogens

Can we automate spine fusion surgical site infection data capture?

PURPOSE

Spine fusion surgical site infection (SSI) rate is reported to national quality databases and used as a benchmark for orthopedic departments and hospital systems. However, accurate data require resource-heavy administrative review and even this has shown to vary. We aimed to create a passive electronic medical record (EMR) algorithm to automatically capture spine fusion SSI and compared its accuracy against the administrative chart review and self-reported morbidity and mortality (M&M) rates.

METHODS

We retrospectively reviewed a single institution's spine fusion records for 7 years for all 90-day post-operative SSIs. We used Centers for Disease Control and Prevention (CDC) SSI definition coupled with intention to treat as an infection by orthopedics/infectious disease service as the gold standard. We compared our gold standard to administrative hand-checked SSI data, anonymously reported departmental M&M, and a passive EMR algorithm (ICD-9 or -10 post-operative SSI diagnosis code entered, or all four of: positive culture, antibiotic prescription between 3-90 days post-op, re-operation/re-admission, and a qualifying diagnosis).

RESULTS

Nine hundred and fourteen spine fusions were included, with a 2.8% SSI rate (0.9% superficial and 2.0% deep). Passive EMR algorithm was the most sensitive at 89% (vs 76% administrative review, 73% M&M); all were highly specific at 99-100%. M&M was 100% positively predictive, administrative review 95%, and EMR 79%.

CONCLUSION

Our passive EMR algorithm was more sensitive to pediatric spine fusion 90-day SSI than self-reported M&M and hand-checked administrative chart review. Although EMR may over-report, it can be used by others to narrow the initial sample for review, reduce resource burden involved with administrative spine SSI review, and provide a quality check for M&M self-reporting.

LEVEL OF EVIDENCE

III.

A Clinical Risk Model for Surgical Site Infection Following Pediatric Spine Deformity Surgery

BACKGROUND

Despite tremendous efforts, the incidence of surgical site infection (SSI) following the surgical treatment of pediatric spinal deformity remains a concern. Although previous studies have reported some risk factors for SSI, these studies have been limited by not being able to investigate multiple risk factors at the same time. The aim of the present study was to evaluate a wide range of preoperative and intraoperative factors in predicting SSI and to develop and validate a prediction model that quantifies the risk of SSI for individual pediatric spinal deformity patients.

METHODS

Pediatric patients with spinal deformity who underwent primary, revision, or definitive spinal fusion at 1 of 7 institutions were included. Candidate predictors were known preoperatively and were not modifiable in most cases; these included 31 patient, 12 surgical, and 4 hospital factors. The Centers for Disease Control and Prevention definition of SSI within 90 days of surgery was utilized. Following multiple imputation and multicollinearity testing, predictor selection was conducted with use of logistic regression to develop multiple models. The data set was randomly split into training and testing sets, and fivefold cross-validation was performed to compare discrimination, calibration, and overfitting of each model and to determine the final model. A risk probability calculator and a mobile device application were developed from the model in order to calculate the probability of SSI in individual patients.

RESULTS

A total of 3,092 spinal deformity surgeries were included, in which there were 132 cases of SSI (4.3%). The final model achieved adequate discrimination (area under the receiver operating characteristic curve: 0.76), as well as calibration and no overfitting. Predictors included in the model were nonambulatory status, neuromuscular etiology, pelvic instrumentation, procedure time ≥7 hours, American Society of Anesthesiologists grade >2, revision procedure, hospital spine surgical cases <100/year, abnormal hemoglobin level, and overweight or obese body mass index.

CONCLUSIONS

The risk probability calculator encompassing patient, surgical, and hospital factors developed in the present study predicts the probability of 90-day SSI in pediatric spinal deformity surgery. This validated calculator can be utilized to improve informed consent and shared decision-making and may allow the deployment of additional resources and strategies selectively in high-risk patients.

LEVEL OF EVIDENCE

Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.