Fresenius Medical Care Holdings, Inc.

Thomas C Blanchard

Len Usvyat

Franklin W Maddux

Peter Kotanko

Dugan W Maddux

Yuedong Wang

Dinesh K Chatoth

Caitlin Kelly Monaghan

Brian C Ellison

Judith E Moran

Sheetal Chaudhuri

Joanna L Willetts

Wendy Millette

Melissa C Herman

Brian Ellison

Judith Moran

Teresa A Nash-Hampton

Joanna Willetts

Exemplary systems and methods for estimating progression of chronic kidney disease in a patient and applying clinical interventions may include determining historic values of at least one patient parameter that varies as a function of the progression of the chronic kidney disease over time, and computationally estimating a trend corresponding to the historic values. Based on the trend, at least one marker may be automatically provided that identifies a clinical intervention and a time in the future when the clinical intervention is expected to be needed. Based on the at least one marker, clinical preparations may be executed at a time prior to the administration of the intervention in order to improve at least one of a) timeliness of the execution of the intervention and b) effectiveness of the intervention.

Systems and methods for treating and estimating progression of chronic kidney disease

Systems and methods for generating anonymized acoustic fingerprints. For a predetermined time interval, raw audio data associated with an environment can be captured and processed. Based on the captured raw audio data, a plurality of discrete data elements can be generated.

Systems and methods for generating anonymized acoustic fingerprints

A method and system for determining a patient's risk of developing an infection is disclosed. In one embodiment, the system and method includes extracting patient data from one or more databases corresponding to a pool of patients receiving treatment; using one or more predictive models with the extracted patient data to generate, for each of the patients in the pool of patients, a respective patient risk score for developing an infection within a selected time period; generating a report including at least a portion of the identified subset of the pool of patients and their respective patient risk scores; and transmitting the report to one or more health care facilities, the one or more health care facilities further identifying one or more patients from the portion of the identified subset of the pool of patients for interventional treatment, consultation, training, or combinations thereof.

Systems and methods for identifying risk of infection in dialysis patients

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Somerville, MA, United States of America

Thomas C Blanchard