In France, with some 5.8 million surgical procedures per year, the incidence of SSI is estimated at 1.64%. The economic cost of these infections is considerable, averaging €10,000 per patient, according to an estimate by the Lille University Hospital. On a national scale, this represents an annual cost of around €950 million. SSIs are a major challenge for the healthcare system, leading to prolonged hospital stays, unplanned surgery and increased care costs.
SSIs are a frequent and serious complication of post-operative care. They range from simple skin infections to more serious complications affecting deep tissues or organs. These infections, often due to contamination during or after the operation, despite aseptic precautions, can seriously compromise the patient's recovery. Prevention and early detection are therefore essential to minimize risks and ensure optimal recovery.
Pixacare offers a remote monitoring solution for surgical wounds, with a particular focus on the early detection of surgical site infections (SSI). Our aim is twofold: to reduce morbidity linked to complications, and to avoid unnecessary travel for patients. This is crucial, as any delay in treatment can exacerbate complications.
Follow-up begins at the hospital with Pixacare, immediately after the operation, where the care team takes photos of the scar and fills in a medical questionnaire. Once home, the patient continues to be monitored by the homecare nurse (IDEL), who does the same. The hospital receives regular updates on the patient's file, enabling rapid intervention in the event of complications.
If the wound progresses favorably, the patient continues his or her care at home, without needing to return for a consultation. However, in the event of a complication, there are two possible scenarios. On the one hand, if the IDEL detects an anomaly, he or she immediately alerts the hospital via the Pixacare messaging system. On the other hand, the hospital team may itself detect a complication by examining the photos and questionnaire answers provided by the nurse. In this case, the patient is called in for a consultation.
We plan to integrate a medical decision support system into Pixacare to optimize SSI monitoring.
Our R&D team is working on ScarSpy, an AI specially designed to detect post-operative complications. Winner of the national "i-Lab" competition, this algorithm uses advanced machine learning and image analysis techniques to identify early signs of complications. When a complication is detected, an alert is generated and sent to healthcare professionals, enabling even faster intervention.
As part of this call for tenders, we are offering participating healthcare establishments a partnership to enrich the ScarSpy database.
https://www.iledefrance.ars.sante.fr/sante-numerique-en-chirurgie-2023
https://drees.solidarites-sante.gouv.fr/sites/default/files/2021-01/Fiche
