Leveraging Stella P to Enhance Homeless Services Systems: An Introduction to Charlotte-Mecklenburg’s LSA Data Analysis

Stella is an analysis and strategy tool developed by the Department of Housing and Urban Development (HUD) to support Continuums of Care (CoCs) in understanding the performance of their homeless services system. The Stella Performance Module (Stella P) visualizes homeless system performance using a CoC’s Longitudinal System Analysis (LSA) data so that the community can develop and monitor system performance improvement strategies. This blog is the first in a series of blogs that will examine Charlotte-Mecklenburg’s most recent LSA data using the Stella P Module.

This blog provides an overview of the LSA and Stella P, highlights the System Performance Map, and explains how this tool can be used to develop system performance improvement strategy in Charlotte-Mecklenburg.

LONGITUDINAL SYSTEMS ANALYSIS

The Longitudinal Systems Analysis (LSA) report is generated from a Continuum of Care’s (CoC) Homelessness Management Information System (HMIS) and is submitted annually to the U.S. Department of Housing and Urban Development (HUD). This system level report provides HUD and CoCs with vital insights into how individuals and households experiencing homelessness that are served by HMIS participating agencies engage with their system of care during the federal fiscal year. It helps CoCs evaluate their progress in addressing homelessness by providing insights into trends, patterns, and outcomes for households experiencing homelessness. The LSA assesses various factors such as housing stability, exits to permanent housing, returns to homelessness, and demographic characteristics. This data-driven approach aids in understanding the effectiveness of interventions and informs decision-making to improve homeless service systems.

LONGITUDINAL SYSTEMS ANALYSIS VS. SYSTEM PERFORMANCE MEASURES

The Longitudinal System Analysis (LSA) and System Performance Measures (SPMs) are both tools used by Continuums of Care (CoCs) to evaluate and improve their homeless service systems, but they serve different purposes, focus on different aspects of the system, and while they measure similar outcomes, there are key differences in how the measures are calculated.

LSA

• Household level analysis focused on tracking and analyzing data over time within a CoC. Households are the unit of analysis because  system planning is typically focused on meeting household level needs.
• Includes data from emergency shelter, safe haven, transitional housing, rapid rehousing, and permanent supportive housing project types.
• Provides insights into trends, patterns, and outcomes for households experiencing homelessness.
• Facilitates the assessment of housing stability, exits to permanent housing, returns to homelessness, and demographic characteristics.
• The LSA’s goal is to understand the effectiveness of interventions and identify areas for improvement within the homeless service system.

SPMs

• Person level standardized metrics used to assess the overall performance of homeless service systems.
• Measures include emergency shelter, safe haven, transitional housing, street outreach, rapid rehousing, permanent supportive housing, and other permanent housing project types.
• Includes metrics regarding the number of people experiencing homelessness, length of time spent homeless, exits to permanent housing, and returns to homelessness.
• Used for benchmarking and comparing the performance of different CoCs or tracking progress towards specific goals, such as reducing homelessness or increasing housing stability.
• Provides valuable insights into system-level performance but may not capture the nuances and longitudinal trends that LSA can reveal.

The LSA focuses on analyzing data trends and outcomes over time within a specific CoC, while SPMs are standardized metrics used to evaluate the overall performance of homeless service systems and compare them across different geographic areas. It is important to note that neither the LSA nor SPMs include Coordinated Entry data.

STELLA P

Stella P is used to visualize a CoC’s Longitudinal System Analysis (LSA) data. It consists of five sections:  Dashboard, Days Homeless, Exits, Returns, and Demographics.

Dashboard: Provides an overview of the number of households and people served and a performance overview; trends over the past 3 years; and a system performance map.

Days Homeless, Exits, Returns: Reviews system level performance for number of days homeless, permanent housing exits from the homeless system, and returns to homelessness after exits to a permanent destination. Each measure can be examined by pathway (combination of projects types a household uses when moving through the homelessness system), population group, and race and ethnicity.

Demographics: Provides an overview of demographic characteristics for households and individuals served by household type and project type and a comparison of demographic characteristics by project type.

Future blogs will take a deeper on the various components of Stella P. This blog focuses on the system performance map.

SYSTEM PERFORMANCE MAP

Households within the homeless system utilize various project types during their experience of homelessness. The combinations of project types that people utilize as they move through the system are known as pathways. Stella P provides pathway specific averages for cumulative days homeless, exits to permanent housing, and returns to homelessness. The system map visualizes the performance of main project types within the homeless system performance across the 3 performance measures: days homeless, exits, and returns and can be used to drill down on the performance of key pathways.

Looking at the overall system map, we are able to see each type of intervention, the percentages of households who used those interventions, how households moved through the system, and what their outcomes were based on their pathway through the system.

HOW TO READ THE MAP

Purple: displays days enrolled in ES, TH, SH, or RRH or PSH (without move in date)

Gray dotted line: point of housing line or when on average households become permanently housed

Gray boxes: represent time housed in RRH or PSH

Green lines: exits to permanent destinations

Green box: total system exits to permanent destinations

Red line: Returns to the homeless system

Each line is part of one or more pathways.

The percentage and the thickness of the lines show the proportion of the households that use each type of project.

CHARLOTTE-MECKLENBURG SYSTEM PERFORMANCE MAP

The Charlotte-Mecklenburg System Performance Map shows that on average households served by the homeless services system during the HUD fiscal year were homeless 197 days. Forty percent of households exited the system to a permanent destination and 8% returned to homelessness within 6 months of exit to a permanent destination. Of those who returned to homelessness within 6 months, the average number of days to return was 125 days.

The pathway that served the largest number of households was the sheltered pathway; 74% of all households used emergency shelter or safe haven. There were 2,643 households that used emergency shelter or safe haven alone or in conjunction with other project types. Households with emergency shelter or safe haven in their pathway to exit averaged of 183 days in shelter. Seventy-five percent of households only used the shelter pathway while in the homeless services system. Seventeen percent used shelter in combination with rapid rehousing, 4% used shelter in combination with permanent supportive housing, and 4% used shelter in combination with transitional housing. For those who used the shelter pathway only, 33% exited to permanent destinations. The map can also be limited to examine the shelter + RRH pathway which shows 64% of households who use this pathway exit to a permanent destination after spending on average 346 days in RRH and the shelter + TH pathway which indicates 48% of households which use this pathway exit to a permanent destination.

Since the shelter only pathway is used by the highest number of households, has a lower rate of exits to permanent destinations than the overall system, and a higher rate of returns, focusing on increasing permanent exits and decreasing returns for this pathway would have the greatest impact on the overall system in Charlotte-Mecklenburg.