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J Stud Alcohol Drugs Suppl. 2019 Jan;Sup 18:51-63.

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

Author information

1
Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.
2
Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada.
3
Pathways Research, Winnipeg, Manitoba, Canada.

Abstract

in English, French, Spanish

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.

PMID:
30681949
PMCID:
PMC6377026
[Available on 2020-01-01]

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