{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Montoya ID"],"funding":["NIDA NIH HHS","SAMHSA HHS","Substance Abuse and Mental Health Services Administration"],"pagination":["23"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10988809"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["19(1)"],"pubmed_abstract":["<h4>Background</h4>Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility.<h4>Methods</h4>This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars.<h4>Results</h4>State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost.<h4>Conclusion</h4>We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments."],"journal":["Addiction science & clinical practice"],"pubmed_title":["Cost of start-up activities to implement a community-level opioid overdose reduction intervention in the HEALing Communities Study."],"pmcid":["PMC10988809"],"funding_grant_id":["UM1 DA049415","UM1DA049412","UM1 DA049412","K01 DA051348","UM1 DA049394","UM1DA049394","UM1DA049415","UM1 DA049406","UM1 DA049417","UM1DA049406","UM1DA049417"],"pubmed_authors":["Schackman BR","Amuchi B","Linas BP","McCollister KE","Orme S","Starbird LE","Barocas JA","Aldridge A","Zarkin GA","Castry M","Watson C","Murphy SM","Harlow K","Montoya ID","Speer D","Seiber EE","Ryan D","Bush JL"],"additional_accession":[]},"is_claimable":false,"name":"Cost of start-up activities to implement a community-level opioid overdose reduction intervention in the HEALing Communities Study.","description":"<h4>Background</h4>Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility.<h4>Methods</h4>This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars.<h4>Results</h4>State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost.<h4>Conclusion</h4>We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Apr","modification":"2025-04-18T20:14:12.607Z","creation":"2025-04-07T08:06:42.699Z"},"accession":"S-EPMC10988809","cross_references":{"pubmed":["38566249"],"doi":["10.1186/s13722-024-00454-w"]}}