Abstract
Manual surveillance of surgical site infections (SSIs) after total hip or knee arthroplasty is time-consuming and prone to error. Semiautomated surveillance based on routine care data extracted from electronic health records can retrospectively identify deep SSIs and substantially reduce workload while maintaining 100% sensitivity.
| Original language | English |
|---|---|
| Pages (from-to) | 732-735 |
| Number of pages | 4 |
| Journal | Infection control and hospital epidemiology |
| Volume | 38 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2017 |
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