Koninklijke Philips Corporation N.v.

Andrew G Hoss

Liyi Xu

Raivo Kolde

A method for identifying two or more infections as related or non-related infections based on an estimated genetic relatedness of the two or more infections, comprising: (i) receiving, for each of two or more infected patients, infection-relevant information comprising an antibiotic resistance profile for the patient's infection, a geo-temporal record for the patient, and a caregiver history for the patient; (ii) estimating, using a trained genetic relatedness model, a genetic relatedness of at least two of the two or more infections; (iii) comparing the estimated genetic relatedness between at least two of the two or more infections to a predetermined threshold; (iv) identifying, based on the comparison, the at least two of the two or more infections as a related infection or a non-related infection.

System and method using clinical data to predict genetic relatedness for the efficient management and reduction of healthcare-associated infections

In an epidemiology transmission probability analysis for a medical facility, ray origin points are distributed over a medical facility floor map. Rays are cast from the ray origin points. The cast rays stop upon encountering a physical barrier mapped in the medical facility floor map. An infectious transmission probability map is computed from intersections of the cast rays. At least a portion of the medical facility floor map is displayed on a display, overlaid with the infectious transmission probability map. The distributing, the casting, and the computing are suitably performed by one or more electronic processors.

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Cambridge, MA, United States of America

Andrew G Hoss