Data quality is critical for any report being submitted to HUD. Gender, race, and ethnicity are key elements which, according to the HUD Point in Time Data Collection Notice, the numbers reported on the final point in time report submission to HUD must equal the total number of persons experiencing homelessness who were counted. While the new Command Center Demographic Extrapolation Tool, or the HUD Point in Time Count Extrapolation Tool, can be used to produce an estimate, the more complete the data is at the source, the more accurate the final results will be.


Fortunately, even if the dashboard view in the Command Center shows a fair number of people missing these key demographics, there are data clean up steps that can be done even after the count is over. 

Engage the count volunteers in the clean up process:
The "Filter" feature in the Command Center lets you see the results for just a particular count volunteer. This can be used to check completion rates per volunteer in a view format.


If you want to provide a list of records, then you can export the data to Excel and use the following steps:
1. Click "Export to CSV" from the list view under surveys
2. Use filters in Excel to show surveys that are missing information. To do this, click "Sort & Filter" after opening up the data in Excel and click "Filter" from the dropdown. 
3. Use the filters on the User_Name (column E), Gender (column AK), Race (columns AC to AI), and Ethnicity (column AJ) to show just the records missing key information. 
4. Send out these details to the Users who were responsible for the missing data and ask them to help fill in the gaps.


If the HMIS Admin is comfortable with inferring gender based on a person's name, then consider the following:

1. Open the count, click surveys, and then click the "list view" 
2. Click "filters" and under gender select "missing"
3. Click to the right on the header for "client name" and then click "sort descending". This will give you the list of all clients that have a name assigned to them that are missing a gender. 
4. Determine the gender. Sites such as and can be of help on this as both have interfaces that allows a user to submit a first name and be returned the likely gender. 
5. Once the gender is determined, simply select the survey record, click "open" to edit, make the update, and save the record.