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CCSQ D&A HOME | Communications Calls | Community of Practice | QNET Analytics Distro List | Archive
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The CCSQ Data & Analytics Data Camp is a multi-session, multi-day event focused on educating the CCSQ Data & Analytics user community. During this special event, technical experts and special guests present during multiple one-hour sessions, each ending with a question and answer session. This Data Camp is an opportunity for the user community to come and learn more about SAS Viya, CDR, and the future of CAP.
Upcoming Data Camp - November 17th and 18th
12:30- 1:00pm EDT | Welcome from CMS Leadership
1:00 - 1:55pm EDT | CCSQ Data & Analytics Environment Overview
Presenter: Mr. Peter Grivas
Presentation: Wondering about the SAS Viya environment and how it all works together? We'll provide an overview of technical details on SAS Viya, Hive, and AWS and how they all work together.
Invitation:
1:55 - 2:00pm EDT | BREAK
2:00 - 2:55pm EDT | CDR Data Overview
Presenter: Mr. Curtis Smith and Mr. Manpreet Khural
Presentation: The relationships between the key data sources in DR will be covered here. This presentation will cover how claims data works with provider & beneficiary data and how these sources relate to other CCSQ dat sources like iQIES, HQR, and EQRS.
Invitation:
2:55 - 3:00pm EDT | BREAK
3:00 - 3:55pm EDT | Visual Analytics Overview
Presenters: Mr. Lee Herman
Presentation: SAS Visual Analytics provides a complete platform for analytics visualization. Interactive, self-service BI and reporting capabilities are combined with out-of-the-box advanced analytics so everyone can discover insights from any size and type of data, including text.
Invitation:
3:55 - 4:00pm EDT | BREAK
4:00 - 4:55 | Hive SQL In-Depth
Presenters: Pete Grivas, Junwen Wang, Yevgeiny Elbert, Sri Akula, and Shirish Tatikonda
Panel Discussion: Take a deeper dive into execution plans, how the Hive works behind the scenes with partitions, and why explicit SQL is recommended over implicit SQL.
Invitation: this is a panel discussion, and we encourage everyone to attend
4:55 | End of Day One
8:30- 9:00 | Welcome from CMS Leadership
9:00 - 9:45 | A Gold Mining Adventure – Using Natural Language Processing and Machine Learning to find Gold in Unstructured Data
Presenter: Chris Schilstra
Presentation: Join us to "dig for gold" in sizeable textual data sets to uncover stakeholder themes and sentiment, with industry-standard accuracy rates. We will compare two thematic/sentiment model visualizations with a presentation and demo and explore the importance of incorporating Human-Centered Design (HCD) with Artificial Intelligence (AI).
Areas of interest: Data, Design, Policy, Technology
9:45 - 10:00 | BREAK
10:00 - 10:45: Catch Me if You Can – How to Fight Fraud, Waste and Abuse using Machine Learning AND Machine TEACHING (by human)
Presenter: Cupid Chan
Plenary Session: Machine Learning (ML) is often the focus of an Artificial Intelligence (AI) discussion, but Machine TEACHING is just as important. This session will intersect a technical conversation with a real business context: Fraud, Waste, and Abuse.
Areas of interest: this is the morning plenary session, and we encourage everyone to attend.
10:45 - 11:00 | BREAK
11:00 - 11:30 | How Humans Make AI Work
Presenters: Ian Lowrie and Stephanie Warren
Presentation: “Artificially intelligent” systems rely on complex combinations of humans and machines to produce the desired user experiences, posing challenges for service design and ultimately affecting overall user trust and user experience. This session will explore systems like chatbots and provide practical guidance for UX professionals working with or curious about Artificial Intelligence (AI).
Areas of interest: Data, Design, Product, Technology
11:30 - 12:00 | BREAK
12:00 - 1:15 | Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals
Presenters: Keith McFarland (moderator) and panelists: Combiz Abdolrahimi, Steve Geller, Harlan Krumholz, MD, Darryl Marshall and Bin Shao, Ph.D.
Panel Discussion: Machine Learning (ML) can support patient care improvement while managing costs, but there are risks involved. Join us for a panel discussion on how a ML approach can be implemented without compromising reliability, trustworthiness, and safety. The panel of professionals will share their knowledge in areas including Human-Centered Design (HCD), Health Privacy, Data, and more.
Areas of interest: this is a panel discussion, and we encourage everyone to attend
1:15 - 2:00 | BREAK
2:00 - 2:45 | Federated Learning to Collect Mobile Patient-Reported Outcomes
Presenters: Dr. Rachele Hendricks-Sturrup and Dr. Sara Jordan
Plenary Session: Health data requires unique privacy and governance protections, and patient-reported outcomes measures (PROs/PROMs) data is no exception. We will discuss what it takes to ensure patient privacy in federated learning architectures.
Areas of interest: this is our afternoon plenary session, everyone is encouraged to attend
2:45 - 3:00 | BREAK
3:00- 3:45 | Using Human-Centered Machine-Learning (HCML) to Improve Data Quality & Data Governance Projects
Presenter: Edward F. O'Connor
Presentation: Are you interested in understanding the components of a real-world and complex Machine Learning (ML) project? Join us as we walk through the implementation process of combining Human-Centered Design (HCD) techniques into a ML project.
Areas of interest: Data, Design, Product, Strategy, Technology
3:45 - 4:00 | Closing Remarks
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