Reciprocal Labs Corporation

Christopher Hogg

John David Van Sickle

Mike Lohmeier

Dmitry Stupakov

Gregory F Tracy

Meredith Ann Barrett

John Kalmi

Michael J Tuffli

Ki Hong Han

Leah J Morrell

Charles Clayton Donaldson

Shannon M Hamilton

Robert Austin Lee

Mark William Sehmer

Michael Lohmeier

Jason Grosz

Jeffrey J Alexander

Chase Acton

Nicholas John Hirons

Lucas Karl Dailey

Ian Daniel Alderman

A system and method for providing chronic obstructive pulmonary disease (COPD) exacerbation risk notifications in real time or near-real time is described. Rescue and controller medication events are detected by sensors associated with the patient's medicament device/s, and provide a basis to determine to rescue and controller medication use trends for the patient. This data is analyzed to determine the patient's risk for COPD exacerbation after each event, and is used to send notifications to one or both of the patient and their health care provider.

Pre-emptive chronic obstructive pulmonary disease risk notifications based on medicament device monitoring

A respiratory disease analytics system provides respiratory disease risk reports to a patient, provider, or third-party entity describing a patient's risk of experiencing a medication usage event given data in a geographic region. Regional data, including air pollutant conditions, weather conditions, demographic information, built environment factors, and regional health conditions for a geographic region are accessed from other sources and assigned based on event data recorded during a medicament usage event, as collected by sensors associated with the patient's medicament device/s. The regional data is assigned to medicament usage events occurring within a period of time. The assigned regional data is analyzed to determine an expected number of medication usage events for the geographic region occurring over the period of time.

Evaluation of respiratory disease risk in a geographic region based on medicament device monitoring

This description relates to insight into the asthma management habits of a patient or a plurality of patients. The provided information includes records of rescue medication usage events, records of controller medication events, and overall evaluations of a patients disease management. Users of the application may include both patients who may use the information to monitor their own habits or providers who may use the information to monitor patients or improve a patient's existing medication regimen.

Dynamic graphical user interface for interaction with patient respiratory disease data

This description provides risk notifications for a geographic region to inform patients and effect behavior changes to prevent rescue events and exacerbations from occurring. A risk analysis for a geographic region is based on data gathered from a population of patients who may experience respiratory events within the geographic region. Rescue medication events, environmental conditions relevant to the rescue medication events, and other contextually relevant information are detected by sensors associated with a population of patients' medicament device/s and are collected from other sources, respectively, to provide a basis to determine a risk score. This data is analyzed to determine the severity of the risk of a respiratory event occurring within a geographical region and accordingly sending a notification to patients within that geographical region.

Pre-emptive asthma risk notifications based on medicament device monitoring

Systems and methods for monitoring accurate, real-time medicament device events, performing analytics on that data, and providing notifications are described. In various embodiments, an application server receives controller medication events, analyzes the events, associated event times, and controller medication dosage plans to characterize event times and send notifications for future doses. The controller medication dosage plan may specify a dose time for a planned dose, a narrow time window comprising the dose time, and an expanded time window comprising the narrow time window and longer in duration than the narrow time window, and the events may be characterized based on their time relative to the dose time, the time windows, and other events.

Real time adaptive controller medication dosing

This description provides trigger identification notifications to patients suffering from respiratory diseases based on large amounts of patient data in order to help effect behavior changes in a patient to prevent inhaler rescue usage events from occurring. Rescue medication events, environmental conditions, and other contextually relevant patient information are detected by sensors associated with the patient's medicament devices and are collected from other sources, respectively to provide a basis to determine identify various triggers of rescue inhaler usage events for a patient. Each trigger is analyzed to determine the severity of the patient's reaction to the trigger and is used to send notifications accordingly.

Identification of asthma triggering conditions based on medicament device monitoring for a patient

This description provides asthma risk notifications in advance of predicted rescue usage events in order to help effect behavior changes in a patient to prevent those events from occurring. Rescue medication events, changes in environmental conditions, and other contextually relevant information are detected by sensors associated with the patient's medicament device/s and are collected from other sources, respectively, to provide a basis to determine a patient's risk score. This data is analyzed to determine the severity of the patient's risk for an asthma event and is used to send notifications accordingly.

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San Francisco, CA, United States of America

Christopher Hogg