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Operationalizing and selecting outcome measures for the HEALing Communities Study
BACKGROUND: The Helping to End Addiction Long-term(SM) (HEALing) Communities Study (HCS) is a multisite, parallel-group, cluster randomized wait-list controlled trial evaluating the impact of the Communities That HEAL intervention to reduce opioid overdose deaths and associated adverse outcomes. Thi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531340/ https://www.ncbi.nlm.nih.gov/pubmed/33091844 http://dx.doi.org/10.1016/j.drugalcdep.2020.108328 |
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author | Slavova, Svetla LaRochelle, Marc R. Root, Elisabeth D. Feaster, Daniel J. Villani, Jennifer Knott, Charles E. Talbert, Jeffery Mack, Aimee Crane, Dushka Bernson, Dana Booth, Austin Walsh, Sharon L. |
author_facet | Slavova, Svetla LaRochelle, Marc R. Root, Elisabeth D. Feaster, Daniel J. Villani, Jennifer Knott, Charles E. Talbert, Jeffery Mack, Aimee Crane, Dushka Bernson, Dana Booth, Austin Walsh, Sharon L. |
author_sort | Slavova, Svetla |
collection | PubMed |
description | BACKGROUND: The Helping to End Addiction Long-term(SM) (HEALing) Communities Study (HCS) is a multisite, parallel-group, cluster randomized wait-list controlled trial evaluating the impact of the Communities That HEAL intervention to reduce opioid overdose deaths and associated adverse outcomes. This paper presents the approach used to define and align administrative data across the four research sites to measure key study outcomes. METHODS: Priority was given to using administrative data and established data collection infrastructure to ensure reliable, timely, and sustainable measures and to harmonize study outcomes across the HCS sites. RESULTS: The research teams established multiple data use agreements and developed technical specifications for more than 80 study measures. The primary outcome, number of opioid overdose deaths, will be measured from death certificate data. Three secondary outcome measures will support hypothesis testing for specific evidence-based practices known to decrease opioid overdose deaths: (1) number of naloxone units distributed in HCS communities; (2) number of unique HCS residents receiving Food and Drug Administration-approved buprenorphine products for treatment of opioid use disorder; and (3) number of HCS residents with new incidents of high-risk opioid prescribing. CONCLUSIONS: The HCS has already made an impact on existing data capacity in the four states. In addition to providing data needed to measure study outcomes, the HCS will provide methodology and tools to facilitate data-driven responses to the opioid epidemic, and establish a central repository for community-level longitudinal data to help researchers and public health practitioners study and understand different aspects of the Communities That HEAL framework. |
format | Online Article Text |
id | pubmed-7531340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Authors. Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75313402020-10-05 Operationalizing and selecting outcome measures for the HEALing Communities Study Slavova, Svetla LaRochelle, Marc R. Root, Elisabeth D. Feaster, Daniel J. Villani, Jennifer Knott, Charles E. Talbert, Jeffery Mack, Aimee Crane, Dushka Bernson, Dana Booth, Austin Walsh, Sharon L. Drug Alcohol Depend Article BACKGROUND: The Helping to End Addiction Long-term(SM) (HEALing) Communities Study (HCS) is a multisite, parallel-group, cluster randomized wait-list controlled trial evaluating the impact of the Communities That HEAL intervention to reduce opioid overdose deaths and associated adverse outcomes. This paper presents the approach used to define and align administrative data across the four research sites to measure key study outcomes. METHODS: Priority was given to using administrative data and established data collection infrastructure to ensure reliable, timely, and sustainable measures and to harmonize study outcomes across the HCS sites. RESULTS: The research teams established multiple data use agreements and developed technical specifications for more than 80 study measures. The primary outcome, number of opioid overdose deaths, will be measured from death certificate data. Three secondary outcome measures will support hypothesis testing for specific evidence-based practices known to decrease opioid overdose deaths: (1) number of naloxone units distributed in HCS communities; (2) number of unique HCS residents receiving Food and Drug Administration-approved buprenorphine products for treatment of opioid use disorder; and (3) number of HCS residents with new incidents of high-risk opioid prescribing. CONCLUSIONS: The HCS has already made an impact on existing data capacity in the four states. In addition to providing data needed to measure study outcomes, the HCS will provide methodology and tools to facilitate data-driven responses to the opioid epidemic, and establish a central repository for community-level longitudinal data to help researchers and public health practitioners study and understand different aspects of the Communities That HEAL framework. The Authors. Published by Elsevier B.V. 2020-12-01 2020-10-02 /pmc/articles/PMC7531340/ /pubmed/33091844 http://dx.doi.org/10.1016/j.drugalcdep.2020.108328 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Slavova, Svetla LaRochelle, Marc R. Root, Elisabeth D. Feaster, Daniel J. Villani, Jennifer Knott, Charles E. Talbert, Jeffery Mack, Aimee Crane, Dushka Bernson, Dana Booth, Austin Walsh, Sharon L. Operationalizing and selecting outcome measures for the HEALing Communities Study |
title | Operationalizing and selecting outcome measures for the HEALing Communities Study |
title_full | Operationalizing and selecting outcome measures for the HEALing Communities Study |
title_fullStr | Operationalizing and selecting outcome measures for the HEALing Communities Study |
title_full_unstemmed | Operationalizing and selecting outcome measures for the HEALing Communities Study |
title_short | Operationalizing and selecting outcome measures for the HEALing Communities Study |
title_sort | operationalizing and selecting outcome measures for the healing communities study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531340/ https://www.ncbi.nlm.nih.gov/pubmed/33091844 http://dx.doi.org/10.1016/j.drugalcdep.2020.108328 |
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