Flatiron Health, Inc.

Shreyas Lakhtakia

Alexander Rich

Jessie Tseng

Dominique Connolly

Joshua Kraut

James Tyler Martineau

Rebecca Miksad

Breno Neri

Jesse Lee

Pooja Shaw

Andrew Dempsey

Blythe Adamson

Sharon Moon

Maya Najarian

Abigail Orlando

Daniel Obeng

Joseph Brown

A system for classifying patient parameter values may include at least one processor programmed to access first information associated with a plurality of patients, the first information including a plurality of patient parameters associated with the plurality of patients, the first information being accessed electronically via a database; determine a first value associated with a patient parameter of at least one of the plurality of patients; analyze second information associated with at least one patient to determine a second value of the patient parameter; detect, based on analysis of at least the first value and the second value, a potential anomaly in the second value; and cause a graphical user interface of a computing device to display at least one graphical element indicating the potential anomaly.

Systems and methods for analyzing and validating patient information trends

A model-assisted system and method for predicting health care services. In one implementation, a model-assisted system may comprise a least one processor programmed to access a database storing a medical record associated with a patient and analyze the medical record to identify a characteristic of the patient. The processor may determine a patient risk level indicating a likelihood that the patient will require a health care service within a predetermined time period; compare the patient risk level to a predetermined risk threshold; and generate a report indicating a recommended intervention for the patient. The processor may further determine a calibration factor indicating a difference between an average patient risk level and an average actual healthcare service usage for a first group of patients; and determine, based on the calibration factor, a bias relative to a second group of patients.

Clinical risk model

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New York, NY, United States of America

Shreyas Lakhtakia