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SESSION MATERIALS
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Session recordings and presentation slides are posted below for most of the sessions in case you were not able to attend a session, or would like to watch it again. |
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A Gold Mining Adventure – |
SCHEDULE
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With an exciting line-up of engaging topics and speakers, you will not want to miss anything! Do you have a busy day, or an upcoming deadline? We get it. That is why the Zoom event is an open-house format with sessions beginning on the hour with 15-minute breaks in between. You can even sit down with us during lunchtime for an informative panel discussion. |
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Click the time to see what session is happening:8:30 | 9:00 | 10:00 | 11:00 | 12:00 | 2:00 | 3:00 |
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Anchor | Session 1 | Session 1 | 8:30- 9:00 | Welcome from CMS Leadership||||||
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Anchor | | Session 2 | Session 2 | 9:00 - 9:45 | A Gold Mining Adventure –
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Join us as we "dig for gold" in sizeable textual data sets to uncover the stakeholder themes and sentiment, with industry-standard accuracy rates. Using a presentation and demo, we will share the challenges we overcame to minimize text interpretation bias by using Natural Language Processing and Machine Learning (ML). Attendees will journey through our data mining process, which maximized model accuracy when identifying themes and associated sentiment. We will compare two thematic/sentiment model visualizations to emphasize the criticality of Human-Centered Design in big data interpretation while highlighting interactive filters to maximize targeted views of subsets of data. |
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: CatchmeMe ifyou canYou Can – How to Fight Fraud, Waste and Abuse using Machine Learning AND Machine TEACHING (by human)PresentersPresenter: Cupid Chan What is this aboutPlenary 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. Who is this for: business users, data scientists and designers Areas of interest: this is the morning plenary session, and we encourage everyone to attend. Session materials: Slides: WUD_Chan.pdf
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How Humans Make AI WorkPresenters: Ian Ian Lowrie and Stephanie Warren What is this aboutPresentation: “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). Who is this forAreas of interest: designers, developers, and product owners Data, Design, Product, Technology Session materials: Slides: WUD_Warren_Lowrie.pdf
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Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare GoalsPresenters: Keith McFarland (moderator) and panelists: Combiz Abdolrahimi Combiz Abdolrahimi, Steve Geller, Harlan Krumholz, MD, SM, Darryl Marshall, and Bin Shao, Ph.D. What is this aboutPanel 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 implementation 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. Who is this for: CMS Leadership, Program leaders, technical team members, CMS contractors, Quality measure specialists, and healthcare professionals Areas of interest: this is a panel discussion, and we encourage everyone to attend Session materials:
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Intermission ActivitiesWatch Satisfy the Cat to learn more about HCD. Have fun with AI with Akinator. 1:15 - 2:00 | BREAK |
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Federated Learning to Collect Mobile Patient-Reported OutcomesPresenters: Dr. Rachele Hendricks-Sturrup and Dr. Sara Jordan What is this aboutPlenary 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. Who is this for: a general audience interested in learning about how to uphold privacy in federated learning architectures to track and monitor patients’ symptoms, preferences, complaints, and/or experiences following a clinical intervention Areas of interest: this is our afternoon plenary session, everyone is encouraged to attend. Session materials: Slides: WUD_Jordan_HendricksSturrup.pdf
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Using Human-Centered Machine-Learning (HCML) to Improve Data Quality & Data Governance ProjectsPresentersPresenter: Edward F. O'Connor What is this aboutPresentation: 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. Who is this for: a general audience interested in ML, business owners of data quality or governance efforts, engineers/developers, and data scientists Areas of interest: Data, Design, Product, Strategy, Technology Session materials: Slides: WUD_OConner.pdf
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ContactIf you have any questions about World Usability Day or to learn more about the HCD CoE, please contact us today. For the HCQIS Community: Visit our HCD Confluence Site -or- For all other visitors, please feel free to email us at: hcd@hcqis.org | ||
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<a href="https://logwork.com/countdown-2s7r" class="countdown-timer" data-style="columns" data-timezone="America/New_York" data-textcolor="#49104d" data-date="2020-11-12 09:00">CCSQ World Usability Day</a> |
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HCD Center of Excellence
CCSQ’s World Usability Day is planned by the HCD Center of Excellence. The HCD CoE is an organization that impacts the way CCSQ delivers policy, products, and services to its customers. Through the provision of education, support, and resources, we promote the continued implementation and use of HCD best practices.