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Measure Last Modified
08-19-2022 10:42 a.m.
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Measure Last Published
08-26-2022 11:49 a.m.
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Status
Active
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Data Source and Calculation
Compare year-to-year homeless population by comparing the results of each succeeding year's annual "point-in-time" survey of the homeless population. The percentage change would be calculated and compared with the results from the preceding year: ((current year count - previous year count)/previous year count) x 100 = percentage change.
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| Enterprise Priorities and Strategies |
| Initiative |
Priority |
Strategy |
| Health and Family |
Children and Families |
Promote strategies that encourage a culture of health through stable housing, access to high-quality health care and proper nutrition. |
| Veterans and Military Families |
Homeless |
Increase affordable housing opportunities and veterans support programs. |
| Service Area Code |
Service Area Name |
| 45801 |
Housing Assistance |
| 45804 |
Homeless Assistance |
| 45805 |
Financial Assistance for Housing Services |
| Name |
Date |
Result |
Note |
| Baseline |
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None |
12.0+ increase in homeless population as determined by a point in time count between 2021 and 2022; significant increase is most likely attributable to COVID-19 pandemic |
| Short Target 2025 |
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None |
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| Long Target 2027 |
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None |
None |
| Year |
Result |
Note |
| 2013 |
9.48 |
Shift to best practices models including Rapid Re-Housing |
| 2014 |
7.93 |
Shift to best practices models including Rapid Re-Housing |
| 2015 |
0.40 |
There was a reduction in funding in the Rapid Re-Housing program for FY 15. The overall number of persons experiencing homelessness in the January 2015 point-in-time count did not decrease significantly from the January 2014 count. Several factors may have contributed to this. At the local level, communities continue to improve their outreach efforts and methodologies for conducting the point-in-time count. As a result, the count in January revealed an increase of 17.5 percent in unsheltered persons. While this is disturbing, it is important that this issue has been identified and can now be addressed. Also, rapid re-housing is the primary tool for getting people out of shelter and into permanent housing quickly. DHCD has encouraged and incentivized this best practice model over the last several years. DHCD lost $500,000 in general fund for rapid re-housing in fiscal year 2015. It is important to note that approximately two percent fewer persons were in shelter which may indicate that people were “moving through the system” and into permanent housing more quickly. That is the desired outcome. The four percent increase in persons in emergency shelter coupled with the 15 percent decrease in persons in transitional housing would seem to support this as well.
While the number of households securing permanent housing and averting homelessness decreased from 2014, it is possible, and perhaps likely, that the 2015 numbers are more accurate. Data collection methods have improved at the local and state levels minimizing duplication. However, without a statewide homeless management information system (HMIS) statewide data collection will continue to be a manual compilation of local and organizational level data leaving many opportunities for human error. |
| 2016 |
10.50 |
This measure is based on a snapshot (point-in-time count) that is partially impacted by weather conditions (e.g., homeless individuals tend to seek shelter during particular weather conditions). The General Assembly restored funding levels that positively impact the number of households assisted during the reporting period. In addition, statewide initiatives have improved overall program implementation and best practice with assisting households to obtain and maintain permanent housing. However, without a statewide homeless management information system (HMIS) statewide data collection will continue to be a manual compilation of local and organizational level data leaving many opportunities for human error. Therefore, DHCD's ability to accurately report the data would be enhanced by a new HMIS system. |
| 2017 |
3.00 |
This measure is based on a snapshot (point-in-time count) that is partially impacted by weather conditions (e.g., homeless individuals tend to seek shelter during inclement weather). System improvements have lowered overall numbers of homeless, but serving those with the highest barriers to obtaining and maintaining permanent housing continues to be a challenge. |
| 2018 |
1.00 |
This measure is based on a snapshot (point-in-time count) that is partially impacted by weather conditions (e.g., homeless individuals tend to seek shelter during inclement weather). System improvements have lowered overall numbers of homeless, but serving those with the highest barriers to obtaining and maintaining permanent housing continues to be a challenge. |
| 2019 |
3.26 |
This measure is based on a snapshot (point-in-time count) that is partially impacted by weather conditions (e.g., homeless individuals tend to seek shelter during inclement weather). System improvements have lowered overall numbers of homeless, but serving those with the highest barriers to obtaining and maintaining permanent housing continues to be a challenge. |
| 2020 |
5.00 |
This measure is based on a snapshot (point-in-time count) that is partially impacted by weather conditions (e.g., homeless individuals tend to seek shelter during inclement weather). System improvements have lowered overall numbers of homeless, but serving those with the highest barriers to obtaining and maintaining permanent housing continues to be a challenge. |
| 2021 |
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| 2022 |
-12.00 |
12.0+ increase in homeless population as determined by a point in time count between 2021 and 2022; significant increase is most likely attributable to COVID-19 pandemic |
| 2023 |
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| Measure ID |
165.0002 |
| Measure Class |
Agency Key |
| Measure Type |
Outcome |
| Year Type |
State FY |
| Preferred Trend |
Increase |
| Frequency |
Annually |
| Statistical Unit |
percentage change in numbers of homele |
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Report Filter
Performance Budgeting System Reports
