دورية أكاديمية
أعرض في EDS

The value of utility payment history in predicting first-time homelessness.

التفاصيل البيبلوغرافية
العنوان: The value of utility payment history in predicting first-time homelessness.
المؤلفون: Middleton CD; Department of Mathematics, Eastern Washington University, Cheney, Washington, United States of America., Boynton K; Avista Utilities, Spokane, Washington, United States of America., Lewis D; Homeless Management Information System, City of Spokane, Spokane, Washington, United States of America., Oster AM; Department of Mathematics, Eastern Washington University, Cheney, Washington, United States of America.
المصدر: PloS one [PLoS One] 2023 Oct 09; Vol. 18 (10), pp. e0292305. Date of Electronic Publication: 2023 Oct 09 (Print Publication: 2023).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science
مواضيع طبية MeSH: Ill-Housed Persons*, Humans ; Social Problems ; Logistic Models
مستخلص: Homelessness is a costly and traumatic condition that affects hundreds of thousands of people each year in the U.S. alone. Most homeless programs focus on assisting people experiencing homelessness, but research has shown that predicting and preventing homelessness can be a more cost-effective solution. Of the few studies focused on predicting homelessness, most focus on people already seeking assistance; however, these methods necessarily cannot identify those not actively seeking assistance. Providing aid before conditions become dire may better prevent homelessness. Few methods exist to predict homelessness on the general population, and these methods use health and criminal history information, much of which may not be available or timely. We hypothesize that recent financial health information based on utility payment history is useful in predicting homelessness. In particular, we demonstrate the value of utility customer billing records to predict homelessness using logistic regression models based on this data. The performance of these models is comparable to other studies, suggesting such an approach could be productionalized due to the ubiquity and timeliness of this type of data. Our results suggest that utility billing records would have value for screening a broad section of the general population to identify those at risk of homelessness.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2023 Middleton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
References: J Adolesc Health. 2009 Dec;45(6):571-8. (PMID: 19931829)
PLoS One. 2020 Aug 20;15(8):e0237905. (PMID: 32817717)
Psychiatr Serv. 1999 May;50(5):667-73. (PMID: 10332904)
Science. 2016 Aug 12;353(6300):694-9. (PMID: 27516600)
Crit Care. 2005 Feb;9(1):112-8. (PMID: 15693993)
Am J Public Health. 2013 Dec;103 Suppl 2:S324-30. (PMID: 24148041)
تواريخ الأحداث: Date Created: 20231009 Date Completed: 20231011 Latest Revision: 20231018
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC10561862
DOI: 10.1371/journal.pone.0292305
PMID: 37812621
قاعدة البيانات: MEDLINE
الوصف
تدمد:1932-6203
DOI:10.1371/journal.pone.0292305