Stella Performance Strategy & Analysis Tool June 5 & 6, - - PowerPoint PPT Presentation

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Stella Performance Strategy & Analysis Tool

June 5 & 6, 2019

Stella Performance Webinar Overview

• Future of Homeless Service Data
• Introduction to Stella and the Performance and

Modeling modules

• Stella Performance Module Demonstration
• Accessing Stella P and Key Concepts
• Q & A

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Our Goal

• To end homelessness,

every community needs to be able to implement a systemic response that ensures homelessness is prevented whenever possible or, if it can’t be prevented, it is a rare, brief, and one-time experience.

Future of Homeless Service Data

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The Future of Homeless Service Data

• More strategic
• Advanced tools
• Actionable data

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More Strategic

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Strategic Investment in Capacity

• Bed Coverage
• AHAR submission
• Data Quality
• Loss of HMIS funding
• Staffing to end user

ratio

• HMIS funding to end

user ratio

• HMIS Lead Evaluation
• HMIS Use of a Data

Quality Plan

• HMIS End User

Training

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Strategic Guidance

HUD permits providers to use and disclose or share data without consent for the purposes below as long as your privacy notice clearly articulated the use and disclosure. This can include uses and disclosures for:

• Provision or coordination of

services

• Carrying out administrative

functions

• Payment or reimbursement

functions

• Meeting legal requirements
• Averting a serious threat to

health or safety

• Reporting abuse, neglect or

domestic violence

• Research purposes

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Advanced Tools

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Actionable Data

Stella Strategy & Analysis Tool

Introducing Stella

Stella Performance Module

• Stella P relies on dynamic visuals
• f CoCs’ data to illustrate how

households move through the homeless system, and to highlight

• utcome disparities.
• Does the analytical heavy lifting, so

your CoC can focus on planning and improving your crisis response system.

Stella Modeling Module

• Stella M assists CoCs to explore

how resource investment decisions amplify system capacity to end homelessness.

• Starts with homeless needs and

performance goals, and helps the community transform those needs into a series of resource investment decisions. A strategy and analysis tool that helps CoCs understand how their system is performing and model an optimized system that fully addresses homelessness.

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Stella Performance

• To develop effective performance improvement

strategies you need to understand how your system is performing now

• Producing data visualizations requires significant

investment of resources, not all CoCs have analytic expertise needed to develop and maintain dashboards

• Stella P provides a common visual language about

the main performance measures to support data informed decision making

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From LSA to Stella

Demographics by household type for people experiencing sheltered homelessness, using RRH, and using PSH System Use by household types and population groups

HDX 2.0 Display Stella Performance (Now)

Demographics Length of Time Homeless and in the System Housing Outcomes Returns to Homelessness

CoC-Level HMIS Data

Detailed Downloadable Analysis Tables Stella Modeling (Later)

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Data Informed Decision Making

Performance data helps CoCs evaluate:

• Progress toward the goal of making homelessness rare, brief and one-

time

• Contributions of individual projects to system performance

But data should not be the only factor in CoC decision making about resources and policies. Data should be placed in the context of:

• System design (ex. participants targeted to be served by a project)
• Best practices/research (ex. Housing First, cost effectiveness)

Data informed decision making considers the broader context and plans for system change that are not reflected in data about the current system. This is in contrast to data driven decision making which relies only on data.

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Accessing Stella P & Key Concepts

Accessing Stella

• Set up HDX 2.0 account if needed
• Upload official or local submission LSA dataset to HDX 2.0
• Prepare LSA dataset for Stella P
• See Preparing LSA Files for Stella P Guide for more information
• Choose a LSA dataset on the Stella P page of HDX 2.0

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LSA Files and Stella Performance

• Any LSA file can be prepared for

viewing in Stella P

• See the Preparing LSA Files for

Stella P on the Stella HUD Exchange page https://www.hudexchange.info/ homelessness-assistance/stella/

• Caution should be used in

interpreting system performance from LSA files with outstanding LSA code and data quality issues.

• Users can prepare files for Stella P

to explore the charts and begin planning of how to incorporate Stella P into system planning activities.

• Once the official FY2018 LSA

submission file is available, CoCs may want to remove earlier files from Stella P to prevent sharing of information with unresolved programming or data quality errors.

• Households not people – more important for system planning purposes
• Data from ES/SH, TH, RRH and PSH projects entering data into HMIS
• No SO data (except self-reported time if selected)
• No SSO data
• System level exits – last exit to a destination outside the system during

the report period

• No agency or project level information
• System level performance for all households experiencing

homelessness – not project performance about participants

Stella P Basics

Understanding LSA/Stella P and System Performance

Measures

LSA and System Performance Measure (SPM) reports use different logic:

• LSA universe is households, SPM universe is people served
• Both report time homeless prior to report period: LSA allows for 7

day gap, SPM does not

• LSA looks at returns by household, it will not count returns by

people who were in the original household but now are in a different household. The SPMs look at returns by person, as a result they count all returns. While the measures aren’t exactly the same, improvement shown in the LSA should translate to improvement in the SPMs

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Data Quality and Stella P

• Several types of data quality issues – impact performance in

different ways

• Missing data in client record – impacts specific measures and

filters (data quality insights are about this issue)

• HMIS coverage – missing projects results in incomplete

performance data (ex. missing ES/SH & TH impacts Days Homeless and Returns, missing PH projects impacts Exits and Returns)

• Unknown data – impacts specific measures and filters (ex.

Unknown destination at exit impacts Exits and Returns)

• Resource to improve data quality: CoC Data Quality Brief

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Stella P P Me Meas asures

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Stella P Dashboard

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Homeless

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Exits

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Returns

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Stella Household Types & Population Groups

Household Types Population Groups

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Pathways

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Performance Insights

• Stella P has built in logic to identify data quality issues and

performance that is outside defined performance expectations.

• Users will be able to create their own insights to flag

performance that is not consistent with their expectations for their system.

• Insights can be pulled into an action plan as the first step in

system improvement planning.

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Insights

Stella P Resources

Getting Started

• Introductory Webinar
• Stella P Start Up Guide
• Stella P Prezi
• System Map Video
• Stella Reference Guide

Understanding Performance

• Performance Analysis and

Improvement Webinars

• HUD’s Communities of Practice

Stella Performance HUD Exchange Page: http://www.hudexchange.info/homelessness-assistance/stella/

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QUESTIONS?

Submit questions after the webinar to the HDX AAQ Desk