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Assessing public behavioral health services data: a mixed method analysis
BACKGROUND: Measuring behavioral health treatment accessibility requires timely, comprehensive and accurate data collection. Existing public sources of data have inconsistent metrics, delayed times to publication and do not measure all factors related to accessibility. This study seeks to capture th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661157/ https://www.ncbi.nlm.nih.gov/pubmed/33176839 http://dx.doi.org/10.1186/s13011-020-00328-9 |
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author | Vaughn, Sierra X. Maxey, Hannah L. Keen, Alyson Thoele, Kelli Newhouse, Robin |
author_facet | Vaughn, Sierra X. Maxey, Hannah L. Keen, Alyson Thoele, Kelli Newhouse, Robin |
author_sort | Vaughn, Sierra X. |
collection | PubMed |
description | BACKGROUND: Measuring behavioral health treatment accessibility requires timely, comprehensive and accurate data collection. Existing public sources of data have inconsistent metrics, delayed times to publication and do not measure all factors related to accessibility. This study seeks to capture this additional information and determine its importance for informing accessibility and care coordination. METHODS: The 2018 National Survey for Substance Abuse and Treatment Services (N-SSATS) data were used to identify behavioral health facilities in Indiana and gather baseline information. A telephone survey was administered to facilities with questions parallel to the N-SSATS and additional questions regarding capacity and patient intake. Quantitative analysis includes chi-square tests. A standard qualitative analysis was used for theming answers to open-ended questions. RESULTS: About 20% of behavioral health facilities responded to the study survey, and non-response bias was identified by geographic region. Among respondents, statistically significant differences were found in several questions asked in both the study survey and N-SSATS. Data gathered from the additional questions revealed many facilities to have wait times to intake longer than 2 weeks, inconsistency in intake assessment tools used, limited capacity for walk-ins and numerous requirements for engaging in treatment. CONCLUSION: Despite the low response rate to this study survey, results demonstrate that multiple factors not currently captured in public data sources can influence coordination of care. The questions included in this study survey could serve as a framework for routinely gathering these data and can facilitate efforts for successful coordination of care and clinical decision-making. |
format | Online Article Text |
id | pubmed-7661157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76611572020-11-13 Assessing public behavioral health services data: a mixed method analysis Vaughn, Sierra X. Maxey, Hannah L. Keen, Alyson Thoele, Kelli Newhouse, Robin Subst Abuse Treat Prev Policy Research BACKGROUND: Measuring behavioral health treatment accessibility requires timely, comprehensive and accurate data collection. Existing public sources of data have inconsistent metrics, delayed times to publication and do not measure all factors related to accessibility. This study seeks to capture this additional information and determine its importance for informing accessibility and care coordination. METHODS: The 2018 National Survey for Substance Abuse and Treatment Services (N-SSATS) data were used to identify behavioral health facilities in Indiana and gather baseline information. A telephone survey was administered to facilities with questions parallel to the N-SSATS and additional questions regarding capacity and patient intake. Quantitative analysis includes chi-square tests. A standard qualitative analysis was used for theming answers to open-ended questions. RESULTS: About 20% of behavioral health facilities responded to the study survey, and non-response bias was identified by geographic region. Among respondents, statistically significant differences were found in several questions asked in both the study survey and N-SSATS. Data gathered from the additional questions revealed many facilities to have wait times to intake longer than 2 weeks, inconsistency in intake assessment tools used, limited capacity for walk-ins and numerous requirements for engaging in treatment. CONCLUSION: Despite the low response rate to this study survey, results demonstrate that multiple factors not currently captured in public data sources can influence coordination of care. The questions included in this study survey could serve as a framework for routinely gathering these data and can facilitate efforts for successful coordination of care and clinical decision-making. BioMed Central 2020-11-11 /pmc/articles/PMC7661157/ /pubmed/33176839 http://dx.doi.org/10.1186/s13011-020-00328-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Vaughn, Sierra X. Maxey, Hannah L. Keen, Alyson Thoele, Kelli Newhouse, Robin Assessing public behavioral health services data: a mixed method analysis |
title | Assessing public behavioral health services data: a mixed method analysis |
title_full | Assessing public behavioral health services data: a mixed method analysis |
title_fullStr | Assessing public behavioral health services data: a mixed method analysis |
title_full_unstemmed | Assessing public behavioral health services data: a mixed method analysis |
title_short | Assessing public behavioral health services data: a mixed method analysis |
title_sort | assessing public behavioral health services data: a mixed method analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661157/ https://www.ncbi.nlm.nih.gov/pubmed/33176839 http://dx.doi.org/10.1186/s13011-020-00328-9 |
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