Eva is an open-source project intended for local use by HMIS Administrators in Continuums of Care (CoCs) around the U.S. and its territories. Eva is designed to help you (1) assess the accuracy and completeness of the data within your HMIS, and (2) understand your homeless response system’s flow and performance. Using Eva does not result in reporting or sharing data with HUD and use of Eva is not required by HUD.
Eva is a web-based tool built with R Shiny. This means:
Eva works by uploading a hashed HMIS CSV Export.
Generate a hashed HMIS CSV Export from your local HMIS and store it in a secure location that you can easily find again. It must be a .zip file with 23 csv files in it.
Once you have exported the correct file from your HMIS, you are ready to engage with Eva. Navigate to the 'HMIS CSV Export' tab and follow the instructions there.
Want to explore Eva without uploading? Use Eva's Demo Mode by clicking the toggle at the top.
Welcome to Eva’s Demo Mode. In Demo Mode, you can explore the functionality of Eva with a pre-uploaded HMIS CSV Export file that uses sample HMIS data. When Demo Mode is on, Eva has the same functionality but uses the sample HMIS data to provide examples of possible File Structure Errors, Data Quality Errors, and Warnings. Select any of Eva's pages from the navigation menu to the left to explore the application.
To turn Demo Mode on and off, use the yellow Demo Mode toggle on the top right of the screen. This toggle will be available from every page in Eva. Please note that you can turn Demo Mode off or on at any time, the application will just ask you to confirm your choice.
If you uploaded your own dataset to Eva and then decide to turn on Demo Mode, Eva will (1) clear the application of your HMIS data, ending the session, and (2) replace it with that of the sample dataset. If you wish to see your results again you will need to re-upload your hashed HMIS CSV Export file. To do so, you need to turn off Demo Mode. This will clear the sample HMIS data from the application so you can operate Eva as normal and upload your own HMIS data again.
Trouble-shooting tips:
This project would not exist were it not for the existence of other quality, free and open source products. The following are citations for the products this app relies on.
The foundational code for the app was shared via AGPL license by the Coalition on Homelessness and Housing in Ohio (COHHIO).
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. R programming language.
Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, Tidyverse package.
Chang W, Cheng J, Allaire J, Sievert C, Schloerke B, Xie Y, Allen J, McPherson J, Dipert A, Borges B (2021). _shiny: Web Application Framework for R_. R package version 1.7.1, R Shiny package.
Chang W, Borges Ribeiro B (2021). _shinydashboard: Create Dashboards with 'Shiny'_. R package version 0.7.2, shinydashboard package.
Special thanks to Square Peg Data, the CoCs who provided us with sample datasets to support programming.
To upload your hashed HMIS CSV Export, click the 'Browse' button. Once you find the zip file on your computer, click on it to select it, and click 'Open' to begin the upload. Eva might take a few moments to process your selected file. Eva will first check to determine if the export is hashed. If it is not, Eva will reject the file with an error message, and clear Eva's memory. Eva will continue to do this until you upload a hashed HMIS CSV Export.
After confirming your export is hashed, Eva will review and process the file structure of your upload. The File Structure Analysis assesses the structural components of the uploaded .zip file and determines if it meets Eva’s file structure requirements, such as if the files have all the right names, columns, data types, and allowable values etc.
Once your upload is processed and Eva has finished assessing the file structure integrity of your upload, Eva will provide a pop-up message alerting you of your upload status. You can have either a successful upload or an unsuccessful upload based on the structural integrity of your HMIS CSV export. The key difference between a successful upload and an unsuccessful upload is if the upload has any High Priority File Structure Errors.
While any error identified during the File Structure Analysis represent components in the uploaded HMIS CSV export file that do not meet the most recent HMIS CSV Format Specifications, there are some file structural errors that are more relevant to the functionality of Eva.
If Eva identifies any High Priority File Structure Errors during the File Structure Analysis that prevent Eva from functioning, Eva will reject your upload and stop processing the export. You will thus not be able to assess the data quality of your upload or analyze the system performance of your homeless response system. For both successful and unsuccessful uploads, all identified file structure errors will display in the HMIS CSV File Structure Analysis panel, where you can download the details.
It is essential that you contact your HMIS vendor to resolve all High Priority File Structure Errors identified in the HMIS CSV Export File Structure Analysis, as well as any other structural issues which you feel need to be corrected. Not all structural issues found in this analysis will prevent the data from being accepted for analysis, so they may not require immediate attention. Once your vendor has addressed any High Priority File Structure Errors, you can attempt another upload.
Once you have uploaded a hashed and structurally sound .zip file, you will see a confirmation that your upload was successful, the date range of the files you uploaded, plus the date your Export was downloaded from your HMIS. You will then be able to assess the data quality of your upload and analyze the system performance of your homeless response system.
Users should contact their vendor to resolve high priority errors identified in the HMIS CSV Export File Structure Analysis, as well as any other structural issues which you feel need to be corrected.
To make Eva data quality analysis more useful at the local level, you can adjust the local settings to better analyze your data in a way that is meaningful to your CoC. To edit these, click to expand the relevant box below. If you do not edit them, the Data Quality and Client Counts pages will use the defaults listed. Please note, these local settings do not impact the System Performance Overview page.
These defaults do not imply any HUD recommendations. Please read the description in the Local Settings tab for more information.
This check aims to help communities find Coordinated Entry (CE) Event referrals that may be missing a Result Date or may have been delayed in getting the client to housing. This check is only applied to CE Event referrals which are expected to have an associated Result and Result Date (4.20.2 responses 10-15, 17, 18. Please see the HMIS Data Standards for the complete list of CE Events.)
When a CE Event referral does not have a Result Date at the time the export is uploaded, Eva calculates how many days the referral has been open by looking at the number of days between the Referral Date and the date your upload was exported from your HMIS. Then Eva compares the length of each open referral with the 'Max Days' assumption entered in the input field below. If the referral is open longer than the expected timeframe, it is categorized as an 'Outstanding Referral.' This check is for all projects that have a relevant CE Event referral.
Data quality flags about Outstanding Referrals are categorized as Warnings, indicating that data should be reviewed for accuracy. It does not imply that any data should be changed.
In the field below, specify the maximum number of days a referral can stay open according to the CoC's Coordinated Entry Referral process. The value defaults to 14 days. (These defaults do not imply any HUD recommendations).
This check aims to help communities find enrollments that may be missing an Exit Date. First, the tool calculates the number of days each enrollment has been open (meaning, the number of days between the Entry Date and the date your upload was exported from your HMIS.) Then the check uses one of two methodologies to identify Long Stayers.
For select project types, the check identifies the top % of longest stayers in each project type. For other project types, the check compares the length of each enrollment with assumptions entered about the expected maximum period of assistance envisioned for the project type. For the latter check, users can set the assumptions for each project type. All data quality flags about Long Stayers are categorized as Warnings and is a suggestion to verify that the identified clients are still active in these projects. It does not imply that any data should be changed.
Top 2% longest enrollments are flagged for the following project types:
Top 1% longest enrollments are flagged for the following project types:
Enrollments active longer than the CoC-specified length of assistance targets are flagged for the following project types:
Below, you can specify the expected maximum period of assistance envisioned for the project type, meaning the timeframe after which you would want an organization to confirm the client is still active in the project. You can set these based on your current data or leave them at the defaults (these defaults do not imply any HUD recommendations).
The Data Quality Export Interface provides a centralized location to download all data quality reports generated by Eva, eliminating the need to visit individual pages. Data quality reports available for export include those from the Project Dashboard, Project Descriptor Data, System-level Data Quality, and Organization-level Data Quality pages. These reports help verify the accuracy, completeness, and timeliness of HMIS data entry across projects and organizations. On this page, users can customize their export by selecting the scope (organization-level or system-level), choosing specific reports to download, and applying date filters where applicable.
You can specify a date range or a single date for the cohort of clients you want to see in the Project Dasboard Report. Client counts and timeliness metrics seen in the Project Dashboard Report are impacted based on the date selection. All other Data Quality reports will use the full date range of the HMIS CSV Export.
Use this option to review project status or timeliness metrics for a defined period rather than the entire export.
Choose whether to generate reports at the organization level, the system level, or both:
This flexibility allows users to analyze data quality for individual organizations or across the entire system.
Users can select one or more of the following reports:
Selecting All Data Quality Reports will include all available report types in the export.
After setting your export parameters, click the “Download” button to export the chosen reports. Selected reports will be delivered in a .zip file. Depending on the selected export types, the .zip file may contain:
The reports are in Excel format for easy review and analysis. You can send an organization folder to authorized HMIS users at that organization so they can work on correcting their data. Note that protected personal information (PPI), such as Personal ID in combination with other data elements, is contained in the Project Dashboard and Data Quality Reports. Users must follow all applicable HMIS privacy and security policies when storing, transmitting, and disclosing files with client records.
This filter only applies to the Project Dashboard Report. All other DQ reports will use the full date range of the HMIS CSV export. Please see the page instructions for more details.
Please select whether you would like DQ exports by organization-level or system-level (or both).
The Project Dashboard Report provides the number of households/clients who have been served in each project and their enrollment status at the time of CSV Export generation. This report can be used to verify that a project is up to date on their HMIS data entry by comparing counts reported with the number of households/clients that are known to be served in each project. Permanent housing projects can check that the number of households/clients who have not yet moved into housing is correct. The report also contains record entry timeliness metrics that show how long it takes for a project to enter Project Start and Project Exit records into HMIS. Certain project types will also see timeliness metrics for Current Living Situation (CLS) and Bed Night service records.
Select a project from the drop list and adjust the the Date Range for the cohort of clients you want to see reported. The Date Range defaults to the date range covered by the HMIS CSV Export. Users are encouraged to edit the Date Range as desired to see metrics for timeframes within the Export period, such as the number of households/clients who exited during that timeframe with and without a Move-In Date. Note that setting the Start Date to the Export End Date will show the current status for all enrollments for the project. Timeliness metrics only include enrollment data entered within the specified date range. Additionally, while on the Timeliness panel, users can adjust the value in the 'Timeliness: Max Record Entry Days' box to see the percentage of all records entered within a specific number of days for a project.
The Summary tab of the Client Counts panel provides a count of households/clients who have statuses of the following within the selected project:
The Detail tab of the Client Counts panel you will see the Personal ID, Relationship to HoH, Entry Date, Move-In Date, Exit Date, and the Status for each client served by the selected project within the Date Range selected. The rows are ordered by Entry Date (oldest on top), Household ID (not visible), and Personal ID. This enables users to see the oldest enrollments first and groups clients in the same household together. All columns are searchable. For example, to find all enrollments with a Status of 'Active No Move-In Date', you can type 'act' in the Status search bar and the data table will react and filter in that way.
The Record Entry tab of the Timeliness panel provides counts of different record types for a project along with timeliness metrics. Time for Record Entry is calculated by comapring a record's Created Date against the:
To download client count data for all projects in your HMIS CSV Export, click the System-wide download button. The download contains a Current tab limited to just the current date, a Date Range tab limited to the Date Range set, and a Detail tab with clients' PersonalIDs, Entry Date, Move-In Date (if applicable), Exit Date (if applicable), and project status. There are also separate Timeliness tabs for metrics on Project Start, Project Exit, CLS records, and Bed Night service records data entry.
Median Days to Project Start Data Entry
Median Days to Project Exit Data Entry
Once you have successfully uploaded an HMIS CSV Export, you will find a summary of each issue that was flagged in your data regarding your PDDEs. Please download the details by clicking the 'Download' button.
For a description of each issue found, check the Guidance panel.
Use your System-wide Data Quality data to evaluate which organizations may benefit from additional assistance and where extra training may be needed. You can download this data to use for reporting to interested entities about your overall HMIS system data quality.
Click the Download button to generate an Excel workbook with the your entire system's Data Quality data. Feel free to modify, add, or remove anything as you see fit. For example, if you are sending this workbook to your CoC management, you may want to remove the tabs that have client-level data on them.
Review the plots below to identify the organizations that you want to examine more closely in the Data Quality > Organization-level tab.
This app categorizes every issue it finds in your data set in terms of its severity.
Regardless of an issue's categorization, users should never edit data that accurately reflects reality.
For each type of issue (High Priority Errors, General Errors, and Warnings) you will find two plots: one plots the counts of issues and one plots the number of issues by organization.
Across all of the organizations in your upload, this plot shows the top 10 issues identified in the data quality scan. This result can help to focus future end-user trainings and bring to light any potential considerations in your federal or local reporting and analysis.
These plots show the top 10 organizations across your system with the highest number of issues identified. You can use these plots to help determine which organizations may need extra assistance in getting their HMIS Errors/Warnings resolved.
To download all of the client and enrollment related issues found in your system, click the Download button. This will give HMIS admins a way of reporting to interested entities, such as your CoC leadership, a broader view of the state of your HMIS data quality.
Below, select the organization whose data quality you would like to check. The data shown will reflect the date range that you used to run your HMIS CSV Export. It will show data quality metrics from all Projects that are associated with that organization.
You can click the Download button to generate an Excel workbook with the selected organization's data quality errors. You can send these to authorized HMIS users at the selected organization so they can work on correcting their data. Feel free to modify, add, or remove anything as you see fit. For example, you may want your users to only address High Priority issues right now. You can easily remove any tabs that may distract your users from that goal. Please note that Overlaps will be shown in the 'Warnings' tab and again in the 'Overlap Detail' tab of the download. This is so your users have enough detail to track down each issue.
Note that protected personal information (PPI), such as Personal ID in combination with other data elements, is contained in the Excel downloads. Users must follow all applicable HMIS privacy and security policies when storing, transmitting, and disclosing files with client records.
This app categorizes every issue it finds in your data set in terms of its severity.
Regardless of an issue's categorization, users should never edit data that accurately reflects reality.
For each type of issue (High Priority Errors, General Errors, and Warnings) you will find two plots: one graphing the number of issues by type, and one graphing the number of issues by project.
Across all the projects within the selected Organization, this plot shows the top 10 issues identified. This can be useful in planning targeted HMIS training efforts.
These plots show the top 10 projects within the selected organization with the highest number of issues identified. You can use this to help determing which projects may need extra assistance in addressing their data quality issues.
To download all of the client and enrollment related issues found in the selected Organization, click the Download button. This will give HMIS admins a way of communicating to an Organization what kinds of HMIS data quality issues they have.
The System Performance Overview page in Eva features three system performance panels, each with their own set of charts: the System Flow Panel, the Client System Status Panel, and the System Demographics Panel. The charts on these panels display system performance data, pulled from your uploaded HMIS CSV export, from all HMIS Continuum projects, excluding homeless prevention projects. Eva uses the last 12 full months of data in the upload, which constitutes the report period. Note that some charts on this page may not display if the uploaded HMIS CSV export has less than 12 full months of data.
The purpose of the system performance charts is to use your HMIS data to (1) evaluate how effective your homeless system is in moving clients through the system and helping them reach permanent housing, and (2) help you understand the demographic composition of all clients served in your homeless system.
Use the Filters Menu to explore system performance trends of clients in your homeless system with specific characteristics. This has two components:
Use the drop-down menus to select the characteristics of the system subpopulation you want to analyze. The default selection is all clients in your homeless system throughout the report period. To see system performance by households, select the "Head of Households only” level of detail. All filters (except one) are single-select, meaning you can only select one category at a time. For the Age filter, you can select multiple age ranges to explore.
Please note that household type and age group filters use different methods for calculating a client's age. Household type is based on all household members’ ages as of the entry date of their earliest enrollment included in the report period. Age group is determined based on the client’s age as of the entry date of their last enrollment included in the report period. Because of this reporting difference, it is possible for a client that ages from 24 to 25 during the report period to be categorized in the Adult Only 18-24 household type while also being categorized as in the 25-34 age group.
The Race/Ethnicity Methodology Type selection only impacts the Race/Ethnicity filters. To learn more about methodology and demographic categories, please visit the Glossary accessible on Eva's Navigation Menu.
The system performance panels are beneath the Filters Menu. Under each Panel tab are Chart subtabs and an Information subtab. The Information subtab includes a “Chart Overview” section that provides guidance on how to read the charts. Additionally, some panels have an “Interpretation Tips” section that can help you interpret their output.
To support further systems analysis, local reporting, and presentations, Eva includes three System Performance Overview export options. The data in these exports reflect the clients that meet the characteristics of the system subpopulation you selected with the Filters Menu.
To generate an Excel workbook with all client data used for all of the System Performance Overview Charts, click the "Client Level Download" button.
To ensure the privacy and protection of individuals and small population groups, Eva uses varying levels of data suppression. If the total number of clients within a chart is less than 11, the chart will not display. When this happens, you may need to broaden your filter selections or upload a larger dataset to ensure there is enough data to view the chart. Image and Data Downloads are unavailable for charts that are fully suppressed.
The Client Level Download is always available with unsuppressed data, even when the total number of clients across all charts is less than 11.
Use caution when saving and sharing the Excel workbooks. Clients can become more identifiable in the data with smaller numbers, even if the data is in aggregate. Before sharing, feel free to modify, add, or remove anything as you see fit to preserve client anonymity.
The client data in the Client Level Download is easily identifiable as it contains Personal IDs, demographic information, and enrollment dates. We recommend not sharing this Excel workbook with anyone who does not have permission to view client PII.
The System Flow panel shows your homeless system's inflow and outflow during the period, helping you assess the effectiveness of your homeless system. The client universe for this panel is the number of clients identified as active in your system at the start of the report period plus the number of clients that inflowed into your system during the period. The System Flow panel contains a set of three charts: the Summary Chart, the Detail Chart, and the Month-by-Month Chart. The charts are read from left to right.
The Summary and Detail Charts show the total number of clients active in the system at the start and end of the period and whether they are homeless at that time or housed (and still receiving assistance). The Summary Chart shows the inflow and outflow of clients that occurred throughout the period. The Detail Chart breaks down inflow and outflow into several categories.
In the Summary and Detail Charts, the Total Change value is the Outflow value(s) minus Inflow value(s) and is represented by:
Total Change = Inflow value(s) - Outflow value(s)A negative Total Change value means more clients left your system than flowed into your system. A positive Total Change value means more clients flowed into your system than left your system.
The Month-by-Month Chart, which includes a stacked bar chart and a data table, shows Inflow and Outflow counts by month over a 12-month period. The stacked bar chart visually compares, by month, the total count of people that enter the homeless system (Inflow) or are continuingly experiencing homelessness in the system (Active at Start: Homeless) with the total count of people that exited the system (Outflow) or are permanently housed within the system (Active at End: Housed) all within that given month.
Note that a client may be counted more than once in the Month-by-Month Chart. For example, a client who outflows in January and inflows again two months later in March would be counted in both January and March. The actual counts of each category in a given month are listed in a table below the chart, including the Monthly Change value which is represented by:
Monthly Change = Inflow (for a given month) - Outflow (for a given month)A negative Monthly Change value means more clients left your system than flowed into your system during a given month. A positive Monthly Change value means more clients flowed into your system than left your system during a given month. The months that have the most inflow and the most outflow are colored in the table.
The Average Monthly Change, Average Monthly Inflow, and Average Monthly Outflow values have the same underlying calculation represented by:
Average Monthly [Value] = (Month Value 1 + Month Value 2 + ...) / 12A negative Average Monthly Change value means, on average, more clients left your system than flowed into your system each month. A positive Average Monthly Change value means, on average, more clients flowed into your system than left your system each month.
The Month-by-Month Chart also has three Flow Type Filters for viewing monthly "First-Time Homeless" and "Inactive" client counts.
This section provides general tips on how to interpret the chart. Depending on the data you uploaded, some of the items below may not apply.
| Scenario | What You See | What It Means |
|---|---|---|
| Less than 36 months of data are uploaded | In the Detail chart, "Inflow Unspecified" displays instead of "First-Time Homeless.” | The "First-Time Homeless” category refers to someone who has not been served in the system within the 24 months prior to their entry. Therefore, it is not possible to assess if people are newly homeless or returners/re-engagers without a 36-month dataset. Thus, because of the shorter timeframe of your export, the number of returners/re-engagers may be an undercount. |
| Less than 12 months of data are uploaded | In the Detail chart, "Inflow Unspecified" displays instead of "First-Time Homeless.” | The "First-Time Homeless” category refers to someone who has not been served in the system within the 24 months prior to their entry. Therefore, it will be difficult to draw conclusions about whether changes in inflow/outflow are meaningful. For instance, change in inflow/outflow over a 4-month period may reflect expected seasonal shifts instead of a difference in system performance. For a fuller and more complete picture of your system, please use a file that has at least 36 months of data. |
| Total Inflow is greater than total Outflow | In the Summary chart, the bar for Inflow is larger than the bar for Outflow. The Total Change value is a positive number, representing an increase. | This means there were more clients that came into your system than left your system during the reporting period. Compare with results from prior years to see if more clients are coming into the system than in prior years, or if the change is because fewer clients are exiting. Use the Detail Chart to explore if a majority of the clients flowing in were first-time homeless, returning to homelessness after previously exiting to a permanent destination, or re-engaging with the system after previously exiting to a non-permanent destination. |
| Total Outflow is greater than total Inflow | In the Summary chart, the bar for Outflow is larger than the bar for Inflow. The Total Change value is a negative number, representing a reduction. | This means there were more clients that left your system than came into your system during the reporting period. |
| The largest Outflow category is "Non-Permanent Destination” | In the Detail chart, the bar for "Non-Permanent Destination” is larger than the bar for "Permanent Destination” and the bar for "Inactive.” | This means most clients leaving your system are exiting to temporary or unknown destinations. Check your completion rate for exit destination to see if any corrections to unknown destinations are possible. To inform strategies for improving performance, filter to look at results for more specific groups, to see if there are differences in the rate of exits to temporary destinations. |
| The largest Outflow category "Inactive” | In the Detail chart, the bar for "Inactive” is larger than the bar for "Permanent Destination” and the bar for "Non-Permanent Destination.” | This means many ended the report period with (1) an open enrollment in an Emergency Shelter – Night-by-Night project that has not had a bed night recorded within the last 15 days of the report period, (2) an open enrollment in Street Outreach, Day Shelter, Supportive Services, and Other project type enrollments without a Current Living Situation (CLS) record within the last 60 days of the report period, or (3) an open enrollment in Coordinated Entry without a CLS record within the last 90 days of the report period. |
The Client System Status Chart shows the end-of-year housing status of the clients that were active in your homeless response system at the start of the period. This chart helps you identify the proportion of clients that ended the period as (1) homeless or (2) housed or in permanent housing. The client universe for this chart is the number of clients active in your system at the start of the report period. This chart does not include clients that inflowed into your system after the start of the report period.
The left-hand bar labeled "Period Start” in the chart shows the status of clients active/enrolled in your system at the start of the period; clients are identified as either "Homeless” or "Housed.” The right-hand bar labeled "Period End” in the chart shows the status of these clients at the end of the period. Clients are categorized into five system statuses at the end of the period: "Exited, Non-Permanent,” "Enrolled, Homeless,” "Inactive,” "Exited, Permanent,” and "Enrolled, Housed.”
In the area of the figure between the two bars, the Client System Status Chart depicts the change of these clients from their status at the start of the period to their status at the end of the period through visible linkages that connect the two bars. The width of each linkage represents the proportion of clients that make up that linkage. Meaning, the thicker the linkage, the larger proportion of clients it represents.
This section provides general tips on how to interpret the chart. Depending on the data you uploaded, some of the items below may not apply.
| Scenario | What You See | What It Means |
|---|---|---|
| The sum of "Enrolled, Housed” and "Exited, Permanent” is greater than the sum of the remaining categories at Period End | The bars for "Enrolled, Housed” and "Exited, Permanent” combined look larger than the bars for the remaining categories in the chart. | This means the majority of clients who were active in your system at the start of the report period exited to or retained permanent housing by the end of the report period. |
| The sum of "Enrolled, Homeless” and "Exited, Non-Permanent” is greater than the sum of the remaining categories at Period End | The bars for "Enrolled, Homeless” and "Exited, Non-Permanent” combined look larger than the bars for the remaining categories in the chart. | This means the majority of clients who were active in your system at the start of the report period either exited to homeless, temporary, or unknown destinations or remained homeless by the end of the report period. Check your completion rate for exit destination to see if any corrections to unknown destinations are possible. |
| Clients who were active in the system at Period Start are inactive at Period End | The category "Inactive” is display in the chart at Period End. | This means some clients ended the report period with (1) an open enrollment in an Emergency Shelter – Night-by-Night project that has not had a bed night recorded within the last 15 days of the report period, (2) an open enrollment in Street Outreach, Day Shelter, Supportive Services, and Other project type enrollments without a Current Living Situation (CLS) record within the last 60 days of the report period, or (3) an open enrollment in Coordinated Entry without a CLS record within the last 90 days of the report period. |
For a simple count of totals within a demographic category, select only one category. To see the intersection of two demographic categories, select both categories to create a crosstab chart. To change your crosstab selection, uncheck at least one of your previous selections before selecting new categories. Note that you can only select one Race/Ethnicity category to display in the chart at a time.
The System Demographics Chart shows the demographic make-up of your homeless system and highlights important trends among various demographic groups. The client universe for this chart is the number of clients identified as active in your system at the start of the report period plus the number of clients that inflowed into your system.
Under the chart tab are five demographic categories you can choose from: Age, All Races/Ethnicities, a second race/ethnicity option, and Veteran Status. Please note, the second race/ethnicity option differs for each Race/Ethnicity Methodology Type selection you made earlier on the Filter Menu.
For a simple count of totals within a demographic category, select only one category. To see the intersection of two demographic categories, select both categories to create a crosstab chart. To change your crosstab selection, uncheck at least one of your previous selections before selecting a new category. Please note that you can only select one race/ethnicity category to display in the chart at a time.
Each cell in the chart is a unique combination of demographic characteristics. For example, if you selected Age and Race/Ethnicity, a unique demographic combination would be "25 to 34” and "Black alone.” Any cell with a count is shaded. The darker the color in a cell, the greater the value of that cell.
Please note that household type and age group filters use different methods for calculating a client's age. Household type is based on all household members’ ages as of the entry date of their earliest enrollment included in the report period. Age group is determined based on the client’s age as of the entry date of their last enrollment included in the report period. Because of this reporting difference, it is possible for a client that ages from 24 to 25 during the report period to be categorized in the Adult Only 18-24 household type while also being categorized as in the 25-34 age group.
Additional levels of data suppression apply to the System Demographics Chart.
All suppressed values are represented by *** in the chart.
Please note that while data can be suppressed in the System Demographics chart in Eva and in its image download, the data in the chart’s data download will not be suppressed. Be careful how you save and share the data download, which is an Excel export. With smaller numbers, clients can become more identifiable in the data. Before you share the Excel export, feel free to modify, add, or remove anything as you see fit to preserve client anonymity.
This glossary provides definitions for the terms used throughout Eva's System Performance Overview page. You can review definitions of the terms by their focus, including:
You can also search for a specific term using the search bar.
This tab will list the most recent technical updates and changes to Eva. For more in-depth information on current and past issues, please go to GitHub.