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The Anchor Community Initiative Resource Hub is a collection of resources, tools and case studies to help you use data to end youth and young adult homelessness in your community.

Data Quality Assurance: Timeliness and Accuracy Policy Examples and Guidance

Elisha Pritchett
By Name List, Data for Improvement

THIS PAGE PROVIDES RESOURCES AND GUIDANCE AROUND BY-NAME LIST SCORECARD QUESTIONS 11A-11B:

11a) Does your community have policies and protocols in place for keeping your by-name list up to date and accurate, including timelines for data submission from providers and ongoing quality assurance protocol? 

11b) Do you implement policies and procedures to ensure that data collection takes place in a complete and consistent way across all access points to your system?

A Timeliness and Accuracy Policy (Data Quality Assurance) is one of four BNL policies and procedures required to say yes to question 11a:


Data Quality Assurance: Outline how you (will) continuously ensure that your by-name list is accurate and current, including timelines for provider data submission and ongoing quality assurance protocol

The validity and effectiveness of your community’s monthly, system-level data and By-Name List depends on the timeliness and accuracy at data entry level. To ensure that your By-Name List contains all necessary data elements and is being tracked as close to real time as possible, your community needs to implement a Timeliness and Accuracy Policy (Data Quality Assurance Plan).

What to include when drafting your Timeliness and Accuracy (Data Quality Assurance) Policy:

  • Purpose: Why is it important? How does it impact the quality of your By-Name List?

  • Roles and Responsibilities: Who is responsible for data quality oversight?

  • Protocol: How will you maintain data quality?

  • Timelines: When does data need to be submitted each month? What are the timeliness standards for HMIS projects? Any exceptions?

  • Accuracy: What are the standard definitions across projects? E.g. Exit Destinations

  • Completeness: What Universal Data Elements need to be tracked? What is the demographic data collection standard?

  • Ongoing Assurance: What is the frequency of review?

Example Policies and Plans:

Data Entry Timeframes Example

Chicago HMIS Data Quality Plan

Maricopa HMIS Data Quality Plan

Alaska HMIS Timeliness and Accuracy Standard Plan

Related Resources:

Inactivity Policy Examples and Guidance

Non-Consenting Policy Examples and Guidance

BNL Policies and Procedures Guidance and Examples

Key System Changes for Sexual Orientation Data Collection (Scorecard Question 13)

Pierce County Data Deep Dive

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