Events
Webinar: Improving Public Comment Review with Automation, Machine Learning, and Advanced Analytics—RTI SmartReview
Date
October 14, 2021 11:00am - 12:00pm
US/Eastern
Each year, federal agencies are required to obtain input on potential policy changes during a public comment review period. Timely identification of relevant comments is critical to maximize time for the government to review, consider, and respond to comments. How do you identify relevant comments in a timely manner to inform critical policy changes?
RTI resolved this issue by developing a data science tool and workflow—RTI SmartReview—that enables federal agencies to quickly prioritize, review, and respond to public comments. RTI SmartReview uses an automated data pipeline, natural language processing, and machine learning to select relevant comments and integrate organized comment data into dashboards quickly, accurately, and automatically.
During the SmartReview webinar, attendees learned about:
- applying advanced analytical methods to solve rulemaking problems and automate routine manual tasks;
- how RTI SmartReview assessed more than 30,000 public comments for the Medicare Shared Savings Program and identified relevant comments for consideration within two days of the comment period closing;
- the importance of human-centered design in effectively solving problems and identifying successful methods; and
- the benefits of software applications like RTI SmartReview for public comment review.
Meet the Moderator
Cindy D'Annunzio
Cindy D'Annunzio is a Strategic Account Executive at RTI International, supporting the strategy and growth behind RTI's projects with the Centers for Medicare & Medicaid Services (CMS). As a Managing Director, Ms. D'Annunzio is responsible for building partnerships, understanding consumers' needs, and bridging the right solutions for those challenges.
Meet the Presenters
Kim Danforth, ScD
Kim Danforth is a Senior Research Public Health Analyst at RTI International whose work focuses on cancer and outpatient safety. Dr. Danforth recently helped develop an algorithm using coded data and natural language processing to identify lung nodules. Her current work includes filling a critical gap in cancer registry data by extracting bladder cancer recurrence and progression from free-text notes.
Robert Chew
Robert Chew is a Senior Research Data Scientist and Program Manager at RTI International. Mr. Chew leverages his expertise in machine learning, data visualization, software development, and computational social science to help federal agencies solve complex data problems. He has successfully integrated data science into projects across health care, criminal justice, public health, and the environment. Mr. Chew was recently named a Bureau of Labor Statistics Senior Research Fellow.
Anna Godwin
Anna Godwin is a Research Data Scientist at RTI International. Ms. Godwin actively collaborates with subject matter experts to develop data science solutions with the end user in mind. She has experience in data analysis, model development, data visualization, and model deployments, which she has applied across a variety of industries, including health care, software products, insurance, and banking.
Ian Thomas
Ian Thomas is a Senior Software Developer at RTI International. With 20 years of professional experience in internet and data technology, Mr. Thomas has worked as a data engineer and reporting analyst where he developed large-scale data pipelines for collecting and analyzing incoming data from millions of users, utilizing the information to build interactive dashboards. As an advocate for user-centered design and agile development practices, he believes in an iterative approach to project design and development.
Interested in learning how RTI SmartReview can help you analyze public comments? Fill out the below form to let us know how we can collaborate.
