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Eval Rev ; 39(5): 480-500, 2015 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-26468235

RESUMO

INTRODUCTION: Homelessness is a public health problem, and persons experiencing homelessness are a vulnerable population. Estimates of the number of persons experiencing homelessness inform funding allocations and services planning and directly determine the ability of a community to intervene effectively in homelessness. The point-in-time (PIT) count presents a logistical problem in large urban areas, particularly those covering a vast geographical area. MATERIALS AND METHODS: Working together, academia, local government, and community organizations improved the methodology for the count. Specific enhancements include use of incident command system (ICS), increased number of staging areas/teams, specialized outreach and Special Weapons and Tactics teams, and day-after surveying to collect demographic information. RESULTS: This collaboration and enhanced methodology resulted in a more accurate estimate of the number of persons experiencing homelessness and allowed comparison of findings for 4 years. While initial results showed an increase due to improved counting, the number of persons experiencing homelessness counted for the subsequent years showed significant decrease during the same time period as a "housing first" campaign was implemented. The collaboration also built capacity in each sector: The health department used ICS as a training opportunity; the academics enhanced their community health efforts; the service sector was taught and implemented more rigorous quantitative methods; and the community was exposed to public health as a pragmatic and effective discipline. PRACTICAL IMPLICATIONS: Improvements made to increase the reliability of the PIT count can be adapted for use in other jurisdictions, leading to improved counts and better evaluation of progress in ending homelessness.


Assuntos
Censos , Pessoas Mal Alojadas/estatística & dados numéricos , Projetos de Pesquisa , Fortalecimento Institucional/métodos , Comportamento Cooperativo , Interpretação Estatística de Dados , Humanos , Relações Interinstitucionais , Texas , Fatores de Tempo , População Urbana/estatística & dados numéricos
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