HMIS Data Quality Quarter 2 2017
The links below rank each project’s average data quality score for the three different types of data elements our users collect data for: Universal Data Elements, Program Specific Data Elements at Entry, and Program Specific Data Elements at Exit.
The Average Data Quality Scores are calculated by averaging the percentage of enrollments that have a response for each of the data elements in each of the data element type. A data element is considered to have a valid response when its answer is in accordance with the HUD Data Standards, and it’s different than ‘Client doesn’t know’, ‘Client refused’ and ‘Data not collected.
We recommend that you work on making your average data quality percentages the best they can be, as these percentages may be used in future NOFA rankings for CoC-funded projects. If you have any questions about your average data quality, please contact the HMIS Helpdesk.