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System and Method of Identifying Contagion Exposure through Social Interactions Analysis

IP.com Disclosure Number: IPCOM000248673D
Publication Date: 2016-Dec-24
Document File: 5 page(s) / 173K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a method and system to determine the related incidental medical conditions of people from a patient’s/user's connections and interactions. The proposed method and system mine the user's social media and other interactions with friends, scores and ranks those with similar symptoms based on defined attributes, and then present the results to the physician in a user interface (UI).

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System and Method of Identifying Contagion Exposure through Social Interactions Analysis

Users of social media have a tendency to post a lot of information about themselves and interactions with others that can be medically relevant. People are often exposed to contagions while in contact with other individuals who are carriers. Users of various social media platforms frequently provide details of these interactions can be mined for medical data analysis.

When a patient presents at an emergency room/hospital or doctor’s office with a particular set of symptoms, it would be beneficial to understand if the patient was potentially exposed to any contagions in their recent interactions. For example, if a patient reports a medical condition, the physician could research the list of other patients who had presented with similar and are connected to the current patient through social media. Social media interaction can indicate physical interactions that might have spread an illness.

A method is needed that enables a physician to identify the contagions to which a patient has been potentially exposed. This would help limit the number of potential diagnoses for a patient.

The novel contribution is a method and system to determine the related incidental medical conditions of people from a patient’s/user's connections and interactions. The proposed method and system mine the user's social media and other interactions with friends, scores and ranks those with similar symptoms based on defined attributes, and then present the results to the physician in a user interface (UI).

The system comprises the following core elements: · Access to the patient’s electronic medical record (EMR), as well as other

patients’ records in the system/hospital · Access to a social media footprint of the patient, as well as that of other patients

in the system/hospital · A medical analytics system capable of understanding the signs and symptoms

(i.e., Indicators) or various conditions/illnesses · An interaction analysis engine capable of mapping a patient’s interactions both

virtually through social media and physically with other patients

Social posts can be extrapolated to electronic medical records of patient's record, associated family members, and people who are geographically colocated.

A cognitive medical system can have an understanding of the signs and symptoms associated with various medical conditions. It can also be aware of which conditions are contagious and under which circumstances.

Figure 1: Basic components and process flow

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For example, the system has the following data about Tuberculosis (TB): · TB is contagious when the disease is active · TB can take two to twelve weeks to show a positive test result and can take a

year or more to develop the active disease · Only patients with active TB can spread the disease to others · Active TB of the lungs has (but is not limited to) the following symptoms:

-Loss of appetite -Coughing -Chest pain - Pain when brea...