Implementing a Semi-Automated Method for Surgical Site Infections Monitoring in a Limited Setting: The SPICMI Method in Martinique University Hospital

<jats:p>Surgical Site Infections (SSIs) are a key target for Healthcare-Associated Infections surveillance. In France, the SPICMI program monitors SSI using hospital medico-administrative and microbiological data. At Martinique University Hospital (MUH) surveillance remains time-consuming manual due to limited data integration. This study implemented a semi-automated SSI detection method at MUH using the SPICMI protocol to identify SSIs suspected cases. The new algorithm detected 85 high and 36 moderate suspicion cases. Manual review confirmed 27 high and 3 moderate cases, improving SSI monitoring and aligning local practices with national surveillance standards.</jats:p>