Planning for treatment system changes: an overview of different models

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Helsinki seminar, August 2014 Alison Ritter Director, Drug Policy Modelling Program National Drug and Alcohol Research Centre, UNSW Planning for treatment system changes: an overview of different models

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Alison Ritter , Prof. Alison Ritter, National Drug and Alcohol Research Centre (NDARC) at the University of New South Wales, Australia Tehokkaat ja tarveperustaiset päihdepalvelujärjestelmät (Effective and needs-based addiction treatment systems) 26.8.2014, Tieteiden Talo, Helsinki

Transcript of Planning for treatment system changes: an overview of different models

Page 1: Planning for treatment system changes: an overview of different models

Helsinki seminar, August 2014

Alison RitterDirector, Drug Policy Modelling Program National Drug and Alcohol Research Centre, UNSW

Planning for treatment system changes: an overview of different models

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Overview and context

• Planning research we have been undertaking:• Commissioned research for government (Jul 2013 to Jun 2014)• Development of a quantitative needs based planning model

(2009 to 2013)• Literature reviews (2013 to 2014)• Key informants interviews (n=190) with funders and service

providers (Aug to Dec 2013)

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Outline of presentation

1. Defining some concepts2. Quantitative planning3. Other planning methods4. Stakeholder engagement5. Real world considerations

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Planning is difficult and complicated

• “Planning is done haphazardly”• “No application of planning technology, nor pre-defined formulae

for fund distribution”• “Government doesn’t “really” plan”• Decisions “seem to come from nowhere”. (KIs)

But it is seen as important:• “Population modelling would be useful as an indication of funding

needed”• We need to undertake a “whole of sector planning” • “We need better planning”

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Defining central concepts for quantitative planningStrategic planning vs technical planningNeed• Definition = the proportion of people who meet diagnostic criteria for

dependence but who are not in receipt of treatment. Includes people who may be suitable for treatment but do not seek it or request it, those who simply do not want treatment and those who want help via means other than formal treatment

• represented by the numbers of people at a population level, who meet diagnostic criteria for dependence or abuse and who would benefit from treatment but do not access it.

Demand• Definition = the proportion of people who seek treatment but are unable to

access it – that is they want treatment and seek it but for any number of reasons do not receive treatment

• Both unmet need and unmet demand are important estimates in planning for services, but both are tricky…

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IssuesNeed – Issues•Is diagnostic criteria the right thing to use? Does it mean they need treatment? (applicable for medicine but for SUD?). “Many experts have argued that diagnosis alone is not a good proxy for treatment need” (Sareen et al., 2013, p. 1941).•Where does the data come from for diagnostic rate?•Potential for changing population prevalence (eg pharma opioids)•Does not take into account heterogeneity of clients and their needs (ethnicity, gender etc)•Not everyone who “needs’ treatment wants it, or is appropriate for it (over-estimates need)Demand – issues•Measurement problems – current utilisation; intention to seek treatment (self-report); waiting lists (Hoffman, Ford, et al., 2011; Peles et al., 2012; Mojtabai and Crum, 2013; Redko et al., 2006; Kaplan & Johri, 2000; Rotstein and Alter, 2006)•Takes current service system as a “given” – yet dynamics between demand and what is on offer (under-estimates demand)

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Planning: need and demand

• Need to know the number in treatment to get to unmet need or unmet demand.

• How many people are in treatment? How do we know?• Need and demand usually measured as people; current treatment

utilisation usually measured as episodes/separations• Match between need/demand and type of treatment – severity and

level of intervention• Bring need and demand together to form reasonable estimates• Estimate for different types and intensities of treatment

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Planning models (quantitative)

• Social indicator methods – use existing administrative datasets; measures of harms (Beshai, 1984; the Alcohol Epidemiologic Data System, 1982; Gregoire, 2002; Sherman et al., 1996; 1998; McAuliffe and Dunn, 2004)

• Epidemiological methods – use prevalence of disorder rates (Rush & Urbanoski, 2007; Schultz et al. 2003; Mojtabai & Crum, 2013; Kip et al., 2002; Clemens &Ritter, 2008)

• Demand-based methods – use current treatment seeking (Ford and colleagues 1985, 1997; 1983; 1983)

• Combinations of the above – Brian’s work and our work (Rush et al., 2012)

• “Any tool has its limitations” (KI)

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Other things you need to know....

Socio-demographic characteristics (as these drive need/demand)•Socio-demographic data, age, sex, education, occupational status, socioeconomic status, Aboriginal status, CALD, income distribution, poverty, etc (Eagar et al., 2001)Geography (where matters)•Geographical information about where people with needs reside, service locations (Russell et al., 2013);Effectiveness of treatment •Systematic reviews of the evidence for treatment effectiveness and cost-effectiveness, randomised and controlled studies, other types of research studies, health systems research, clinical guidelines, treatment models (Robinson, 1999)Current service system (over and above current utilisation)•Information on services, what exists, location, specification of activities etc (Harris et al., 2012; Whiteford, Eagar, et al., 2013; Green, 2007)•Budget and resources data: current resource allocation, costing of staffing (Robinson, 1999; Whiteford, Harris, et al., 2013)•“We don’t know what programs are delivering” (KI)

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Other methods and data

• Surveys, focus groups, consultative groups and in-depth interviews of stakeholders, document analysis, continuing consultation (Best et al., 2005; Fuller and Edwards, 2004; Sutton et al., 2011; Weiner et al., 2011)

• Various potential dialogue methods: nominal group technique, Delphi expert panel and so on (Eagar et al. 2001; McDonald et al., 2009)

• Consensus forecasting; scenario planning (Eagar et al., 2001)

• Information on client and potential clients’ views on services, accessibility, affordability, needs and levels of satisfaction, barriers to treatment (Best et al., 2005; Digiusto and Treloar, 2007; Eagar et al., 2001; Mitton et al., 2009; Treloar et al., 2010).

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Engagement of stakeholders

• “…powerful stakeholder interests are likely to undermine effective planning if there are no mechanisms in place that allow for consensus building” (Fazekas et al., 2010, p. 9)

• Stakeholders:– Funders (government, philanthropy, other?)– SA service providers– Allied service providers (eg housing, employment and so on)– Researchers– Clients (existing and potential new clients)– Community members

• “Effective planning requires transparency on all sides” (KI)

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Real world considerations

• Who is doing the SA treatment planning?– Government? Funders? (municipalities; regions?)– Which funders? Together or separately?– Service providers?

• What level is the SA treatment planning?– “Scale” for planning – what is a meaningful ‘unit’ (100,000

people?)– Matching the planning ‘unit’ to the decision-making– Local, regional, state, federal/national– “If priorities are set centrally (and are specific), this may

conflict with local needs” (KI)

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Real world considerations (2)

• Good planning should provide the platform for purchasing decisions– How is planning connected to funding decisions? – how tightly

are they bound together?– Level of sophistication required of planning models versus the

pragmatics of treatment funding…– “The risk is that it [planning] takes the politics out of funding

AOD treatment and it is actually the politics that give AOD treatment the best option for getting funded” (KI)

• Relationship between AOD, MH and other social welfare services?– Plan together? Plan separately? Does it matter?

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Is it worth it?

• Comprehensive approach to planning;– Multiple methods, costly and time intensive– Engagement of stakeholders– Significant data demands

• Does it inform purchasing? (is it used?)• Marrying local, with regional, state and national needs?• Balancing specificity with flexibility• Ensuring innovation is not stifled

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Thank-you

Professor Alison RitterDrug Policy Modelling Program, DirectorNational Drug and Alcohol Research CentreUNSW, Sydney, NSW, 2052, AustraliaE: [email protected] T: + 61 (2) 9385 0236DPMP Website: http://www.dpmp.unsw.edu.au

Funding:This work was funded by the Commonwealth Department of Health and

Ageing. Prof Alison Ritter is funded by an NHMRC Senior Research Fellowship.

There are no conflicts of interest.

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Spare slides

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Summary of purchasing mechanismsWays in which providers are chosen

1. Competitive (open, targeted, preferred provider panel)2. Historical / negotiated3. Accredited providers4. Third party / outsourcing

Ways in which services are paid for5. Block grant6. Fee-for-service7. Payment for activity 8. Payment for outcome9. Capitation

Ways in which price is managed10. Fixed price 11. Negotiated price