If you are looking for the 2021 HMIS Summit, please click here.
Welcome to the 2022 Virtual HMIS Summit, Using Data to Create an Equitable Tomorrow! We want to highlight how the HMIS work that we all do can guide us as we try to achieve a more equitable practice in our homeless response system. This event was held from July 19 to 21.
The Whova event page will remain accessible for several months following the summit. Please feel free to revisit this page while it is still available for access to the sessions and discussions.
List of Sessions
Please visit this folder for any handouts that accompany the sessions (if applicable).
There will be five different "tags" applied to each of the sessions below. These tags correspond to the topic of the session. You may use these tags to quickly see the list of sessions you are most interested in viewing.
One thing to note for the sessions with the Data Warehouse tag is that while the Data Warehouse is a tool that is currently only available in the Michigan implementation, North Carolina users may still opt to attend in order to be more informed about the tool in the case that it becomes available in the North Carolina implementation in the future.
Data Warehouse Introduction tags:
Building a Data Bridge Between the Healthcare and Homeless Response System tags:
p>Using Python Scripts to Better Manage Cases and Automate Tasks tags:
“Thank You For Your Service” – Serving Our Veteran Population tags:
Data Warehouse 2: Core Demographics tags:
An End User's Guide to BusinessObjects tags:
Data Warehouse 3: Project Type Dashboards tags:
Data Quality Plan and Federal Reporting Calendar tags:
WellSky By-Name List Report Demonstration tags:
HMIS: Not a Four Letter Word tags:
Not All HMIS Workflow Look the Same tags:
Data Warehouse 4: Using the Data Warehouse for CQI tags:
Coordinated Entry, By-Name Lists, and the HMIS tags:
Data Warehouse 5: SPMs by Subpopulation tags:
What Does Data Look Like for the Emergency Shelter Program? tags:
Advocacy 101: Making Change Happen tags:
Data Warehouse: Data Collaborative tags: