Dataset Information

Development of a Needs-Based Planning Model to Estimate Required Capacity of a Substance Use Treatment System.

ABSTRACT: OBJECTIVE:Substance use services and supports have traditionally been funded without the benefit of a comprehensive, quantitative planning model closely aligned with population needs. This article describes the methodology used to develop and refine key features of such a model, gives an overview of the resulting Canadian prototype, and offers examples and lessons learned in pilot work. METHOD:The need for treatment was defined according to five categories of problem severity derived from national survey data and anticipated levels of help-seeking estimated from a narrative synthesis of international literature. A pan-Canadian Delphi procedure was used to allocate this help-seeking population across an agreed-upon set of treatment service categories, which included three levels each of withdrawal management, community, and residential treatment services. Projections of need and required service capacity for Canadian health planning regions were derived using synthetic estimation by age and gender. The model and gap analyses were piloted in nine regions. RESULTS:National distribution of need was estimated as Tier 1: 80.7%; Tier 2: 10.4%; Tier 3: 6.1%; Tier 4: 2.6%; and Tier 5: 0.2%. Pilot work of the full estimation protocol, including gap analysis, showed the results triangulated with other indicators of need and were useful for local planning. CONCLUSIONS:Lessons learned from pilot testing were identified, including challenges with the model itself and those associated with its implementation. The process of estimation developed in this Canadian prototype, and the specifics of the model itself, can be adapted to other jurisdictions and contexts.

SUBMITTER: Rush B

PROVIDER: S-EPMC6377026 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Development of a Needs-Based Planning Model to Estimate Required Capacity of a Substance Use Treatment System.

Rush Brian B Tremblay Joël J Brown David D

Journal of studies on alcohol and drugs. Supplement 20190101 18

<h4>Objective</h4>Substance use services and supports have traditionally been funded without the benefit of a comprehensive, quantitative planning model closely aligned with population needs. This article describes the methodology used to develop and refine key features of such a model, gives an overview of the resulting Canadian prototype, and offers examples and lessons learned in pilot work.<h4>Method</h4>The need for treatment was defined according to five categories of problem severity deri ...[more]

PMID: 30681949

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Project description:BackgroundTimely knowledge mobilization has become increasingly critical during the COVID-19 pandemic and complicated by the need to establish or maintain lines of communication between researchers and decision-makers virtually. Our recent pan-Canadian research study on the mental health and substance use health (MHSUH) workforce during the pandemic identified key policy barriers impacting this essential workforce. To bridge the evidence-policy gap in addressing these barriers, we held a facilitated virtual policy dialogue. This paper discusses the insights generated at this virtual policy dialogue and highlights how this integrated knowledge mobilization strategy can help drive evidence-based policy in an increasingly digital world.MethodsWe held a 3-hour virtual policy dialogue with 46 stakeholders and policy decision-makers as the final phase in our year-long mixed-methods research study. The event was part of our integrated knowledge mobilization strategy and was designed to generate stakeholder-driven policy implications and priority actions based on our research findings. The data collected from the virtual policy dialogue included transcripts from the small-group breakout rooms and main sessions, reflective field notes and the final report from the external facilitator. Coded data were thematically analysed to inform our understanding of the prioritization of the policy implications and action items.ResultsFacilitated virtual policy dialogues generate rich qualitative insights that guide community-informed knowledge mobilization strategies and promote evidence-informed policy. Our policy dialogue identified actionable policy recommendations with equity as a cross-cutting theme. Adapting policy dialogues to virtual formats and including technology-assisted facilitation can offer advantages for equitable stakeholder participation, allow for deeper analysis and help build consensus regarding evidence-based policy priorities.ConclusionsOur facilitated virtual policy dialogue was a key knowledge mobilization strategy for our research on the capacity of the Canadian MHSUH workforce to respond to the COVID-19 pandemic. Our policy dialogue allowed us to engage a diverse group of MHSUH workforce stakeholders in a meaningful action-oriented way, provided an avenue to get feedback on our research findings, and generated prioritized action items that incorporated the knowledge and experience of these MHSUH workforce stakeholders.

Dataset Information

Development of a Needs-Based Planning Model to Estimate Required Capacity of a Substance Use Treatment System.

Publications

Development of a Needs-Based Planning Model to Estimate Required Capacity of a Substance Use Treatment System.

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