CoLab Upskills Talent to Extract More Value Out of HHS’ Data
According to a report published by the McKinsey Global Institute, 62% of executives believe they will need to retrain or replace more than a quarter of their workforce between now and 2023 due to advancing automation and digitization. In response to this and the recent White House Executive Order on Maintaining American Leadership in Artificial Intelligence, the HHS Data Science CoLab designed an upskilling program to deliver data science training and function as an internal innovation accelerator. It is a first-of-its-kind, federal, data science upskilling program that brings together participants from a variety of agencies to learn how to write code and blend ideas and insights to improve a host of workflows across the Department.
Over the course of two months, CoLab participants commit sixteen hours per week to apply transferable data science techniques including data wrangling, predictive analytics, visualization, and machine learning to individual Capstone projects, which they ideate prior to entering CoLab. Following the conclusion of CoLab, at Demo Day, participants showcase their hard work, newly developed projects, and skills to a Department-wide audience.
The third round of CoLab was the most competitive selection process to date, due to the vast number of applicants and high quality of Capstone project pitches. We received more applications than ever – over 500 applications for 30 seats – a testament to the innovative and self-driven mindset of many HHS staff. We thank those who applied to CoLab and so thoughtfully pitched ways to improve how data works for the Department.
Demo Day took place on May 21, 2020 in front of a record-sized audience and featured lightning talks by the following CoLab participants:
- Kristi Synold (ACF) – Administration for Native Americans
- Zhong Qi (NIH) – Building O&M Costs – A Machine Learning Prediction
- Claire Yanyan Ji (FDA) – Predicting a Broken Heart
- Ryan Laird (NIH) – Using Unsupervised Machine Learning to Find Clinical Patterns of Autoinflammatory Disease
- S. Janet Kuramoto-Crawford (HRSA) – Using Data to Inform Organ Donation Outreach Efforts
- Sean Klein (ASPE) – Capturing Research Use in Policymaking
- Jason Lin (HRSA) – Identifying Opioid Overdose Death High-Risk Areas Using Supervised Machine Learning Algorithms
- Gregory Pishko (FDA) – Medical Device Issue Highlighter
- Daniel Veltri (NIH) – Leveraging Machine Learning and Clinical Records to Diagnose Patients with Rare Diseases
Dr. Lee Mendoza, Louisiana Department of Health Director of Bureau of Health Informatics, and Dr. Somesh Nigam, Blue Cross Blue Shield of Louisiana Chief Analytics and Data Officer, delivered an eye-opening co-keynote on how a Louisiana public-private partnership is tackling COVID-19 using big data and artificial intelligence (AI).
Will Brady, Chief of Staff to the HHS Deputy Secretary, and Steven Babitch, Head of Artificial Intelligence at the GSA U.S. Technology Transformation Service shared insightful remarks and anecdotes about the value of data-driven decision-making, and fostering continuous learning and growth via upskilling talent within HHS and the federal government.
Currently sponsored in large part by ReImagine HHS, CoLab is one of four program delivery areas within the ReImagine HHS Data Insights Initiative. The initiative is pioneered by HHS and driven from the Office of the CTO to optimize how agencies and offices within HHS share, integrate, analyze, and visualize federated data in alignment with the Federal Data Strategy Action Plan to better inform policymaking and support evidence-based decision-making. Additional program delivery areas include a data sharing platform, operational framework, and use case driven approach.
We thank our partners at the Office of Business Management and Transformation (OBMT), Biomedical Advanced Research and Development Authority (BARDA), and the Office of the Inspector General (OIG) for their tireless support towards making CoLab possible!
The next round of CoLab is tentatively scheduled for late-summer 2020. Stay tuned for an announcement via HHS news!
