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: [email protected]: + 61 (2) 9385 0236
DPMP Monographs:
http://notes.med.unsw.edu.au/ndarcweb.nsf
Research – current – Drug Policy Modelling Program