Czy zdalne monitorowanie oparte na sztucznej inteligencji może pomóc w lepszym zarządzaniu wizytami awaryjnymi podczas skomplikowanego leczenia nakładkami?
Discussion
This study found a significantly higher number of emergencies in the DM group compared with the control group (51 vs 34). This was due to the fact that DM was able to detect issues early on, which patients can be oblivious to, before they deteriorate and cause the treatment to go offtrack. For example, the most common emergency was noticeable unseats of aligners, with an average of 12.6 per treatment with 84% of patients.
Each time the aligner does not properly fit there is a risk of the treatment not going according to plan, causing a delay and the prospect of additional aligners, which can be frustrating to the doctor and the patient.
These incidents were easily handled remotely with DM; patients were simply sent guidelines on how to use chewies poziomore effectively and wear their aligners for longer. In cases of loss of a button or an attachment, the orthodontist reviewed the pictures and evaluated if these were critical to the tooth movement at that precise moment of the therapy or not, hence triaging these ‘emergencies’.
91% of patients used the chat feature to message the practice directly, with an average of 8.8 messages per patient. Communicating through the app rather than calling the practice every time the patient had a question had a strong impact on reducing the [...]
