Evidence-based drug policy – Evidence-based drug policy – myth or reality?myth or reality?

Alison Ritter, DPMP DirectorAlison Ritter, DPMP DirectorNDARCNDARC

Presentation 6th Feb, 2007, Canberra

Illicit drug policyIllicit drug policy

• Drug policy is complicated

• Multiple perspectives

―Users, families, health professionals, police, politicians, community members

• Strong public opinions

• Significant government spending (*)

• Complicated interventions (*)

Significant government Significant government spendingspending

Total spending: $3.2 billion p.a.

Direct: $1.3 billion (41%)

Indirect/consequences $1.9 billion (59%)

Federal Govt: 30%

State/Territory Govt: 70%

Law enforcement 56%

Australian Governments Illicit Drug-related Spending (2002-03)

Other consequences3%

Health-Related Consequences

5%

Crime-Related Consequences

51% Law enforcement42%

Direct drugs spending

41%

Interdiction14% Prevention

22%

Treatment19%

Harm Reduction2%

Other Policy1%

Government spending Government spending (direct only)(direct only)

Law enforcement $553.9m ($431 to 705)

Interdiction $181.5m ($149 to 351)

Prevention $295.8m ($88 to 534)

Treatment $256.3m ($204 to 279)

Harm reduction $ 26.3m ($19 to 44)

Complicated responsesComplicated responses• Law enforcement, eg:

∙ Legalisation of drugs∙ Crop eradication programs∙ Customs and border control∙ Crackdowns and Raids∙ Police discretion, diversion, drug courts

• Prevention, eg:∙ Mass media campaigns∙ School-based drug education

• Treatment, eg:∙ Detoxification∙ Methadone or buprenorphine maintenance ∙ Therapeutic communities∙ Cognitive behavioural relapse prevention

• Harm reduction, eg:∙ Needle Syringe Programs∙ Peer education for users∙ Non-injecting routes of administration

Evidence-based policy?Evidence-based policy?

• Simple question = what works best?

• Research usually limited on this

• Doesn’t take into account dynamic interactions between sectors

• Doesn’t take into account different outcomes

• Doesn’t take into account policy making processes

Policy making processes - Policy making processes - relationship to evidence?relationship to evidence?

• Uptake of evidence in policy-makingFrustration by researchersPolicy-makers feeling misunderstood

• Problems: ― long (researchers) vs short (policymakers) timeframes; ― ambiguity & lack of certainty in much social science research; ― inaccessibility of research results ― sheer bulk of research materials; ― research career structures and the academic reward systems;― lack of clarity about roles (for example balancing objectivity and

advocacy); ― rapid change in the policy environment; ― problems of governmental capacity; ― clash of cultures; and ― communication failures between researchers and policy makers

• Solutions?― summary reports, bulletins, dot points― personalised briefings― use of mail outs ― respect the limited time of policy makers― be patient ― maintain a reputation of objectivity― think about and prepare ‘good news’ angles to the research― nurture political champions ― develop mutual understanding and respect

• But even with these, not much progress• Solution may lie in understanding the policy-

making processes better

“The policy world is as alien to most researchers as a distant foreign land and most do not even realise it”

Michael Agar, 2002

Models of policy makingModels of policy making

• There is not one model of how policy is made

• Researchers usually assume that the process is linear:

Problem Options Solutions Implementation

• And that it is rational!

So, models of policy So, models of policy making…making…

• Technical/rational model

• Incrementalism model

• Power and pressure groups

• Interactive model

• Garbage can model

• Advocacy coalition framework

• Punctuated equilibrium

• etc

Rational/technical Rational/technical approachapproach

• Conventional image: ID an issue, seek solutions

• Series of steps1. identify problem2. identify causes3. develop options4. analyse options5. select an intervention6. implement and evaluate

• Fundamental, exhaustive, rational, root approach

Rational/technical modelRational/technical model

• Case example: improving pharmacotherapies - buprenorphine

• Implications for researchers―Engage in steps 1-4 (ID problems, causes,

options)―Conduct research that is relevant, timely, credible―Know which problems are on the agenda―Have ready synthesised reports to feed into the

problem, causes or options steps

IncrementalismIncrementalism

• Policy making is not dramatic – rather small incremental shifts

• Successive limited comparisons between existing policies (or alternatives)

• Comparing marginal values

• Better than to attempt (and fail) at big change

Lindblom, C., E. (1959). The science of 'muddling through'. Public Administration Review, 19, 79-88.

Lindblom, C., E. (1979). Still muddling, not yet through. Public Administration Review, 39(26), 517-526.

IncrementalismIncrementalism

• Case example: prevention programs in schools (education/information - competency approach)

• Implications for researchers

―Prepare for long time frame (tobacco 20+yrs)―Tight simple comparative analyses (within

budget) are highly valued.

““Garbage can” modelGarbage can” model

• Three independent streams:―Problems―Politics―Policy processes/solutions, alternatives

• Sloshing around, waiting to be matched up

• Policy window opens: task = to match problems and solutions

Kingdon, T. (2003) Agendas, Alternatives and Public Policies. (2nd Ed). NY: Longman

““Garbage can” modelGarbage can” model1. PROBLEMSAgenda setting

oIndicators and monitoringoFocusing eventsoSymbolsoBudgets

InterpretationProblem recognition (“should do something”)

oNeed a solution/alternativeRise and fade

2. POLITICSAgenda settingInfluenced by:

oNational moodoOrganised political forcesoGovernmental phenomena

Consensus building through bargaining

3. POLICY PROCESSESAlternatives Policy communityIdeas as an evolutionary processes (mutation & recombination)Criteria for success of an alternative (technical feasibility; values congruence; constraints manageable; public and political acceptability)Softening up (years)Emerging consensus (diffusion & tipping point)

Coupling of 1 + 2 + 3Policy entrepreneurs: join problem, solution and politics

POLICY

WINDOW

Small/short and scarce.

Predictable orUnpredictable

“Problem” window (1)“Politics” window (2)

Kingdon, T. (2003) Agendas, Alternatives and Public Policies. (2nd Ed) NY: Longman

““Garbage can” modelGarbage can” model

• Case example: NCADA: problem = IDU and/or AIDS; politics = Hawke; policy processes/solutions = various (academics, drug treatment community, gay community).

• Implications for researchers―“Policy processes” component – key role in

presenting alternatives (and data on problems)―Look for when policy windows open―Match up problems and solutions creatively (don’t

pair too early)

Power & pressure Power & pressure groupsgroups

• Three forces that determine policy:―Ideology (philosophy, values)―Interests (primarily self-interests)―Information (multiple sources…)

• The distribution of power determines whose I-I-I will be dominant.

Weiss, C. H. (1983). Ideology, interests and information: the basis of policy positions. In D. Callahan & B. Jennings (Eds.), Ethics, Social Sciences and Policy Analysis. NY: Plenum Press.

Power & pressure Power & pressure groupsgroups

• Case example: Diversion initiative―Different constructions of the problem.

Different Ideology, Interests and Information.

• Implications for researchers

―“Information” component―Be aware of all “information” types and

influences―Strategic dissemination: mailouts, briefings etc.

Advocacy Coalition Advocacy Coalition FrameworkFramework

• Policy subsystem = interaction of diverse actors interested in same policy area.

• Illicit drugs as a policy subsystem. • Within each policy subsystem, advocacy coalitions

form (because diversity of views across the whole subsystem). Usually 2-4 AC’s.

• AC’s include: policy analysts, academics, journalists, advocates etc.

• Policy change occurs when AC’s are in conflict and one AC rises to ‘power’ – specifies the agenda, and the policies

Sabatier, P. A. (1988). An advocacy coalition framework of policy change and the role of policy-oriented learning therein. Policy Sciences, 21, 129-168.

Advocacy Coalition Advocacy Coalition FrameworkFramework

• Case example: Supervised Injecting Centre (Van Beek, 2004)― Players = local community, A&D service providers, local

chamber of commerce, the churches, non-govt expert bodies, parliamentary processes, media, advocates.

• Implications for researchers―Know the AC’s that exist―Provide briefings etc for significant players―Stakeholder engagement in the research from

the start―Use advocacy strategies

SummarySummary

• Different models apply at different times

• Models overlap – they describe/focus on different components of the same processes

• No one way to ensure uptake of evidence

Don’t despair..Don’t despair..

• Role of evidence – in above models have mainly been looking at research as “instrumental” to a direct policy decision.― Knowledge-driven (new science) ― Problem-solving (to answer a policy question)

• But other ways in which research evidence is used:― Interactive (iteration among multiple players)― Political (to support a position; “ammunition”)― Tactical (to delay, deflect criticism, show responsibility) ― Enlightenment (new ideas permeate over time, “backdrop of

ideas”) *

Where to from here?Where to from here?

DPMP aims to

• develop the evidence-base for policy;

• develop, implementing and evaluating dynamic policy-relevant models of drug issues; and

• study policy-making processes in Australia

Challenges

• Further work on models and what they mean for drug policy

• Comparisons of policy options

• Policy analysis rather than descriptive research

• Improving the evidence AND the intersection between researchers and decision-makers

AcknowledgementsAcknowledgements

This work forms part of the Drug Policy Modelling Program (DPMP). Funded by:

―Colonial Foundation Trust ―NHMRC Career Development Award

Thanks to:

• The DSS study group (at the ANU, led by Prof Bammer)

• RegNet, the ANU

Further informationFurther information

Assoc Prof Alison RitterDrug Policy Modelling Program, DirectorNational Drug and Alcohol Research CentreUNSW, Sydney, NSW, 2052, AustraliaE: alison.ritter@unsw.edu.auT: + 61 (2) 9385 0236

DPMP Monographs:

http://notes.med.unsw.edu.au/ndarcweb.nsf

Research – current – Drug Policy Modelling Program