HMIS Data Quality Report Cards

The data quality dashboard is posted quarterly, and includes Data Completeness, Data Accuracy and Data Timeliness. Review the Data Quality Plan to review all components of data quality, and the Data Quality page for data quality resources.

Data Quality Dashboard

• 2024

• • Quarter Two 2024 (4/1/24 – 6/30/24)
  • Quarter One 2024 (1/1/24 – 3/31/24)

• 2023
  • Quarter One 2023 (1/1/23 – 3/31/23)
  • Quarter Two 2023 (4/1/23 – 6/30/23)
  • Quarter Three 2023 (7/1/23 – 9/30/23)
  • Quarter Four 2023 (10/1/23 – 12/31/23)
• 2022
  • Quarter One 2022 (1/1/22 – 3/31/22)
  • Quarter Two 2022 (4/1/22 – 6/30/22)
  • Quarter Three 2022 (7/1/22 – 9/30/22)
  • Quarter Four 2022 (10/1/22-12/31/22)
• 2021
  • Quarter One 2021 (1/1/21 – 3/31/21)
  • Quarter Two 2021 (4/1/21 – 6/30/21)
  • Quarter Three 2021 (7/1/21 – 9/30/21)
  • Quarter Four 2021 (10/1/21 – 12/31/21)

• 2020
  • Quarter One 2020 (1/1/20 – 3/31/20)
  • Quarter Two 2020 (4/1/20 – 6/30/20)
  • Quarter Three 2020 (7/1/20 – 9/30/20)
  • Quarter Four 2020 (10/1/20 – 12/31/20)
• 2019
  • Quarter Three 2019 (7/1/19 – 9/30/19)
  • Quarter Four 2019 (10/1/19 – 12/31/19)

Data Completeness

Data Completeness refers to the degree to which all required data is known, valid and documented in HMIS. A data element is considered to have a valid response when it is in accordance with the HUD Data Standards, and it is different than Client Doesn’t Know, Client Refused, and Data Not Collected. No Exit Interview Completed is also not considered a valid response for the Destination field.

The Average Data Completeness Score is a unique indicator of data completeness for each project. It is calculated by dividing the total valid responses that the project has across all the universal data elements, by the total clients that need an answer to each UDE.

Reference the UDE DQ Corrections Reference Guide for information on what is considered a data quality error for each universal data element. Reference the PSDE DQ Corrections Reference Guide for information on what is considered a data quality error for each program specific data element.

The table below shows the Data Completeness thresholds for each project type:

Project Type	Universal Data Elements	Program Specific Data Elements – Entry	Program Specific Data Elements – Exit
Coordinated Entry	95%	N/A	N/A
Emergency Shelter	98%	96%	65%
Homeless Prevention	98%	96%	95%
PH – Housing Only	98%	96%	95%
PH – Permanent Supportive Housing	98%	96%	95%
PH – Rapid Re-Housing	98%	96%	95%
Services Only	95%	90%	50%
Street Outreach	95%	90%	50%
Transitional Housing	98%	96%	95%

Data Accuracy

Data accuracy refers to the degree to which data entered in HMIS represents the real information on the clients that are served in the projects contributing data to the system. Data Accuracy issues include responses that are not valid for each data element according to the HUD Data Standards, as well as responses that present data incongruences.

Data Timeliness

Data Timeliness refers to the degree to which the data is collected in HMIS and available when it is needed. The Data Timeliness tab of the DQ Dashboard shows the average number of days taken to enter Project Starts, Project Exits, and Service Provided into HMIS for each project.