Flatiron Health, Inc.

Jessie Tseng

Lauren Sutton

Angel Leung

Janet Donegan

Rahul Bafna

Dominic Green

Eitan Meir Konigsburg

Raman Choudhry

Victor J Wang

Paul Greenleaf

Anand Kuchibotla

Alexander Rich

Alexander Padmos

Addison Shelley

David Light

Frank Zexi Chen

Dominique Connolly

Yihua Zhao

Neal Meropol

Shreyas Lakhtakia

Barry Leybovich

Jesse Lee

Maneet Kaur

Pooja Shaw

Abigail Orlando

Rebecca Miksad

Nathan Chan

Blythe Adamson

Achin Batra

Trevor Royce

Joshua Kraut

Forrest Xiao

Harvey James Hamrick, Jr

Maya Najarian

Adam Gottesman

Alex Deyle

Filip Frahm

A system for tracking adverse events may include at least one processing device programmed to receive a request from a user to record an adverse event experienced by a patient; receive a search term input by the user; identify, in an adverse event database and based on the search term, at least one database record for an adverse event, wherein the at least one database record includes an adverse event type and at least one characteristic; receive, via an input field, a rating of the at least one characteristic for the patient; generate an adverse event record based on the adverse event type and the rating; and store the adverse event record in an adverse event log.

Systems and methods for tracking patient events

A graphical user interface for displaying an electronic medical record associated with a patient is provided. The graphical user interface may include an area configured to display patient information, which may include at least a name of the patient. The graphical user interface may also include an indicator displayed in association with the name of the patient. The indicator may include information specifying that the patient is potentially eligible for one or more trials, the patient is participating in one or more trials, or the patient has completed one or more trials.

Systems and methods for providing clinical trial status information for patients

Described herein is a graphical intervention test development system. The graphical intervention test development system provides a graphical intervention test development environment that facilitates computer-based design of an intervention test. The graphical intervention test development environment provides a graphical user interface (GUI) and visualizations of various aspects of an intervention test therein. The graphical intervention test development environment further provides a control interface through which a user can manipulate control parameters that affect outcomes of the intervention test.

Graphical intervention test development system

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

Jessie Tseng