Poster Title

Using Cloud Computing to Assess Healthcare Professionals

Presenter Information

Parker KainFollow

Grade Level at Time of Presentation

Junior

Institution

Northern Kentucky University

KY House District #

4

KY Senate District #

4

Department

Department of Computer Science

Abstract

Introduction:

Traditionally, the assessment of healthcare professionals relies on surveillance data, which is both intensive in terms of human labor, and difficult to collect.

Purpose:

In this research, we pushed to develop a method to rank and compare physicians based on social media analytics.

Objectives or Hypothesis:

Rather than forcing patients to rate healthcare professionals after hospital visits, this research pushes to develop a method to rank and compare physicians based on social media analytics. Twitter continues to grow as a Social Media platform, and with it the field of data analytics pushes to analyze and connect this data into meaningful patterns. Traditionally one of the barriers to this type of analyze is the lack of computing resources to process the continuously coming data and handle the large scale analysis. Therefore, in this research, we used cloud computing such as Amazon Web Services to address this issue.

Results:

Python was leveraged using the TweePy library to pull tweets and twitter account information from Cincinnati area twitter users, and natural language processing was used on these account details to determine if the users were healthcare professionals using natural language processing libraries like NLTK. Network analysis was performed on a single confirmed professional to find additional potential physician accounts until a suitable base was gathered. This information was then pushed to Amazon Web Services for cloud storage, where it then could be analyzed further using a python server. From here, more Natural Language Processing was done to determine the defining features of a successful physician, and whether or not social media data has a correlation with other healthcare ranking sites.

Conclusion:

Based on this research, we have found that social media paired with cloud computing can used to analyze physician performance. Cloud computing environment like Amazon AWS can support social media analysis.

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Using Cloud Computing to Assess Healthcare Professionals

Introduction:

Traditionally, the assessment of healthcare professionals relies on surveillance data, which is both intensive in terms of human labor, and difficult to collect.

Purpose:

In this research, we pushed to develop a method to rank and compare physicians based on social media analytics.

Objectives or Hypothesis:

Rather than forcing patients to rate healthcare professionals after hospital visits, this research pushes to develop a method to rank and compare physicians based on social media analytics. Twitter continues to grow as a Social Media platform, and with it the field of data analytics pushes to analyze and connect this data into meaningful patterns. Traditionally one of the barriers to this type of analyze is the lack of computing resources to process the continuously coming data and handle the large scale analysis. Therefore, in this research, we used cloud computing such as Amazon Web Services to address this issue.

Results:

Python was leveraged using the TweePy library to pull tweets and twitter account information from Cincinnati area twitter users, and natural language processing was used on these account details to determine if the users were healthcare professionals using natural language processing libraries like NLTK. Network analysis was performed on a single confirmed professional to find additional potential physician accounts until a suitable base was gathered. This information was then pushed to Amazon Web Services for cloud storage, where it then could be analyzed further using a python server. From here, more Natural Language Processing was done to determine the defining features of a successful physician, and whether or not social media data has a correlation with other healthcare ranking sites.

Conclusion:

Based on this research, we have found that social media paired with cloud computing can used to analyze physician performance. Cloud computing environment like Amazon AWS can support social media analysis.