Understanding Medical Marijuana Laws
Priscillia Hunt, Ph.D.
Jeremy Miles, Ph.D.
Anne Boustead, J.D.
PI- Rosalie Liccardo Pacula, Ph.D.
June 14, 2013
Sponsored by the National Institute on Drug Abuse
(NIDA) R01 DA032693-01
As of Jan 1, 2012, 17 Jurisdictions Had
Medical Necessity Defense Laws
D.C.
Source: Pacula et al. (forthcoming)
Hunt 2 May 2013
And As of Apr. 2013, 10 More States (and Other
Countries) Had Pending Legislation
Pending legislation
D.C.
Source: Marijuana Policy Project
Hunt 3 May 2013
There Is a Lack of Clarity About Numerous
Medical Marijuana Laws (MMLs) in Place
“Our federal marijuana
policy is increasingly out
of step with both the
values of American
citizens and with state
law. The result is a
system of justice that is
schizophrenic and at
times appalling.”
New York Times, 11/12
Hunt 4 May 2013
Many Questions Surround MMLs
and Their Implications
• Are certain laws more effective and efficient to
implement?
• Are the legally feasible MMLs also optimal from a
health and safety point of view?
• Does legalizing medical marijuana (MM) lead to
legalizing marijuana generally?
Hunt 5 May 2013
Many Questions Surround MMLs
and Their Implications
• Are certain laws more effective and efficient to
implement?
• Are the legally feasible MMLs also optimal from a
health and safety point of view?
• Does legalizing medical marijuana (MM) lead to
legalizing marijuana generally?
Answering such questions requires synthesizing numerous
legal provisions into fewer, more manageable groups of laws
Hunt 6 May 2013
Focus of Our Study
• Sought to answer three key research questions:
1. How many MML classes are there?
2. What are the legal provisions distinguishing the classes?
3. How likely are jurisdictions to change classes over time?
• Used unbiased, statistical methodology to:
– Synthesize MMLs
– Better understand what states have been doing and
changes over time
Hunt 7 May 2013
Summary of Key Findings
• Latent Class Analysis (LCA) is useful approach for
better understanding MMLs
• LCA shows that there are 5 distinct classes
– Unacceptable, Research Purposes, Pharmaceutical
Framework, Home Remedy, Mixed Supply
– Classes differ on: patient use, research-only laws,
pharmaceutical laws, supply options
• MMLs used to differ, but now appear to be converging;
generally:
– States adopting MMLs for first time adopted Home Remedy
– States with MMLs already move toward Mixed Supply
• Need to understand why jurisdictions change laws and
whether convergence is good or bad
Hunt 8 May 2013
Today’s Agenda
• How did we approach the study in light of prior
studies?
• What did we find using the approach?
• What conclusions derive from the findings?
Hunt 9 May 2013
MM Classifications Have Been Developed
to Help Organize Information
• Many papers assume 2 classes: Legal, Not legal
• Pacula, Powell, Heaton & Sevigny (forthcoming)
– Use individual legal provisions
• Marijuana Policy Project (2012)
– (1) Have an MML; (2) Removed jail time for small possession;
(3) Both (1) + (2); (4) Limited MM defense; (5) Legal for
recreational use
• Marijuana Policy Project (2011)
– (1) Effective; (2) Workable; (3) Research; (4) Symbolic;
(5) Expired/Repealed; (6) Never had; (7) Non-binding request
Hunt 10 May 2013
Prior Studies Have Two Key Problems
Problem
Characteristics
differentiating
laws are limited
or based on
subjective
assessment
Description
• Basic classification of legal/illegal is
insufficient
• There’s no statistical evidence driving more
complex classifications
• If there are underlying relationships in legal
data, it can’t be drawn out by current
methods
Hunt 11 May 2013
Prior Studies Have Two Key Problems
Problem
Characteristics
differentiating
laws are limited
or based on
subjective
assessment
Description
• Basic classification of legal/illegal is
insufficient
• There’s no statistical evidence driving more
complex classifications
• If there are underlying relationships in legal
data, it can’t be drawn out by current
methods
• Authors of more complex classifications
take annual snap shots—no constant thread
No evaluation of
over time
classifications
• Methods don’t allow us to understand how
over time
and by how much prevalence in legal
classes have changed
Hunt 12 May 2013
We Used Latent Class Analysis to Classify
MMLs Over Time and Across States
• Latent class analysis (LCA) detects statistical
patterns of association in data
• Basic idea of LCA
– Some parameters of hypothesized statistical model differ
across unobserved subgroups (C)
– These subgroups form categories of categorical latent
variable (X)
– Probability of obtaining response pattern y, P(Y = y), is
weighted average of the C class-specific probabilities
P(Y = y|X = x), formally:
𝐶
𝑷 𝒀=𝒚 =
𝑷 𝑋 = 𝑥 𝑷 𝒀 = 𝒚|𝑋 = 𝑥
𝑥=1
Hunt 13 May 2013
We Used Transition Analysis to
Describe Adoption Patterns
• Logistic regression analysis
– Likelihood of transitioning to two specific classes that
permit use and have effective supply channels
• Model specification
– One-period lag dependent variable model
Hunt 14 May 2013
The Methods Were Applied to Legal Database
• Pacula et al. (2013) panel data of jurisdictions’
approval of number of MM legal provisions
• Database built by lawyers, economists, and policy
analysts
• Legal provisions selected reflect economic theory of
what drives access, availability, and
regulation/enforcement
Hunt 15 May 2013
Includes 22 Legal Provisions on Access &
Availability of MM Over 7 General Topics
1. Aspects of process (physician prescription,
reclassification, …)
2. Supply mechanisms covered (dispensary, home
cultivation, …)
3. Affirmative defense (for physician, caregiver, patient)
4. Patient registration (required, recommended)
5. Health conditions explicitly permitted (glaucoma,
HIV/AIDS, …)
6. Type of medical use law (statute, constitutional
amendment)
7. Enactment of medical use law (ballot, legislative)
Hunt 16 May 2013
How We Developed the Legal Database
1. Identified meaningful dimensions of statutes from
policy perspective, review of literature, and our
understanding of issues22 identified
2. Created codebook setting forth specific, replicable,
and verifiable criteria for classifying each statute
along each dimension
–
E.g., in statute, does provision on dispensaries explicitly
state whether dispensaries (or equivalent entity) are
permitted?
3. Used legal analysts to record classifications using
relevant legal documents (e.g., public law version
of MM statutes)
Hunt 17 May 2013
List of Legal Provisions:
Form and Formation of Law
Theme
Form and
Formation
of Law
Variable
Description
Law type for
medical use
• Law was statutorily enacted
• Law was created by constitutional
amendment
Enactment type
for medical use
• Law was passed by legislature
• Law was passed by voter-initiated ballot
Therapeutic
research
• Statute only allows for MM to be used in
research setting or in clinical trial, not by
patients not participating in medical
research
Reclassification
• Law explicitly contains provision
reclassifying MM
Hunt 18 May 2013
List of Legal Provisions:
Legal Protection
Theme
Variable
Physician affirm
Legal
Protection
Patient affirm
Caregiver affirm
Patient protect
Description
• Law explicitly allows physicians to use
affirmative defense if face charges because
they recommend (prescription,
authorization) MM to patient
• Law allows medical use as any type of
affirmative defense to at least one type of
marijuana crime under any situation
• Law allows medical use as any type of
affirmative defense to at least one type of
marijuana crime under any situation
• Some form of legal protection for patients
who obtain MM upon
recommendation/authorization of physician
Hunt 19 May 2013
List of Legal Provisions:
Health Conditions
Theme
Variable
Description
<condition>
• Law explicitly states MM can be used to treat <condition>
(e.g., if law lists <condition> as allowable medical
condition)
• Conditions explicitly considered are glaucoma, cancer,
HIV/AIDS; not pain is brought out as another variable
definition because of less objective measurement
Pain 1, 2, & 3
• Pain 1: MM can be used if patient has disease that causes
pain (e.g.,: “a chronic or debilitating disease or treatment
for such diseases, which produces severe pain
• Pain 2: MM can be used to treat pain, without requiring
pain to be caused by medical condition (e.g., definition of
debilitating medical condition that includes intractable
pain
• Pain 3: MM can be used provided physician determines it
is medically justified (e.g., statute that allows MM to be
used “in treatment of any other illness for which
marijuana provides relief
Health
Conditions
Hunt 20 May 2013
List of Legal Provisions:
Process
Theme
Process
Variable
Patient
registry
Description
• Law explicitly requires patient participation in
system or does not provide for any legal protection
for patients who do not participate in the registry
system
Hunt 21 May 2013
List of Legal Provisions:
Providers
Theme
Variable
Description
• Law explicitly states insurers are not liable
for claims associated with MM
Health insurance
Providers
Pharmacy
provide
Physician
prescribe
• Law explicitly contains provision allowing
patients to obtain MM from phamacist
• Law explicitly indicates physician can
“prescribe” MM
Hunt 22 May 2013
List of Legal Provisions:
Supply Mechanisms
Theme
Supply
Mechanisms
Variable
Description
NIDA supply
• Law explicitly allows patients to obtain MM from
NIDA
Home supply
• Law either: (1) includes explicit statement allowing
for home cultivation; (2) defines medical use to
include cultivation; or (3) includes particular
number of plants in describing use
Dispensary
supply
• Law explicitly states dispensaries (or equivalent
organizations) are permitted
Law enforce
supply
• Law explicitly allows patients to obtain MM from
law enforcement sources
Most appropriate
supply
Non-addressed
supply
• Law explicitly states patients are allowed to obtain
marijuana for medical use by means most
appropriate
• Law does not include any discussion of how MM
users are able to obtain marijuana for medical use
Hunt 23 May 2013
Key Summary of the Legal Database
• State legal statutes or amendments only (not health
agency regulations, for example)
• 50 states and District of Columbia (51 jurisdictions)
• 1990–2012: Laws made legally effective by January
1st of the year
• Unit of analysis: jurisdiction-years (N = 1,176)
• All legal variables are categorical
Hunt 24 May 2013
A View of the Legal Database
Hunt 25 May 2013
Today’s Agenda
• How did we approach the study in light of prior
studies?
• What did we find using the approach?
• What conclusions derive from the findings?
Hunt 26 May 2013
Model-of-Fit Statistics and Conceptual
Investigation Indicate a 5-Class Solution
Number of
Latent Classes
3
4
5
11211.9 11693.3
10712.0 11355.6
9950.5 10756.2
6
9520.9 10488.8
7
9362.0
AIC
BIC
10492.0
Only 1 jurisdiction in a class, split on
“Physicians can prescribe”
Hunt 27 May 2013
What Are the Results of Having Provisions in
Place, Conditional on Class Membership?
Latent Class
Unaccept- Research
Pharma
Assigned Label
able
Purposes Framework
Proportion of jurisdiction–years
0.53
0.23 Latent Class
0.12
Conditional probability of a Yes Unacceptabl
response Research
Pharmaceutic
Assigned Label
1. Physician can prescribe
2.
Proportion of jurisdiction–years
Conditional probability ofmay
a Yes response
Patient/caregiver
obtain
recommendation
Physician can prescribe
3. Reclassification
Patient/caregiver may obtain
recommendation
4. Researchers
may obtain for
Health insurers explicitly not liable
therapeutic
Reclassification research
Researchers may obtain for therapeutic
5. Home
cultivation
research
6. State authorized supply
e
0.00
0.53
Purposes
0.08 al Framework
0.23
0.12
0.00
0.00
Home Remedy
0.61
0.00
0.00
Aspects of Process
0.08
0.00
0.03
0.61
0.19
0.31
0.10
0.17
0.92
0.17
0.00
0.92
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.31
0.00
0.70
0.00
0.00
0.76
0.18
0.42
0.00
0.00
0.920.00
0.00
0.00
0.00
1.00
0.42
0.79
0.00
0.14
0.00
0.00
0.42
0.00
0.00
0.01
1.00
0.25
0.92
1.00
Mixed
Supply
0.10
Mixed Supply
0.19
1.00
0.36
0.36
Home
Remedy
0.03
…
31. Passed via ballot initiative
Item-response probabilities greater than 0.5 shown in bold to facilitate interpretation.
Hunt 28 May 2013
LCA Results Allow Us to Present Provisions
Distinguishing Classes
Hunt 29 May 2013
We Can Also Consider the Distribution of
MML Classes Over Time
Proportion of Jurisdictions
0.7
0.65
0.6
Unacceptable
0.5
0.39
0.4
0.29
0.3
Research Purposes Only
0.24
0.18
Pharmaceutical Framework
0.1
12
2012
10
2010
2009
08
2008
2007
06
2006
04
2004
2003
Year
02
2002
00
2001
0.04
2000
1999
98
1998
1997
96
1996
1995
94
1994
92
1993
Mixed Supply
1992
1991
90
1990
0.0
0.00
0.00
0.10
Home Remedy
2005
0.12
2011
0.2
Hunt 30 May 2013
Logistical Regression Results Show the
Transitioning from One Class to Another
Marginal effect on probability of
membership to class:
Home Remedy
Mixed Supply
Class at time t-1 (Unacceptable omitted)
Research Purposes
.
0.006
Pharmaceutical
0.001
0.005
Home Remedy
0.851***
0.133**
Mixed Supply
0.004
0.980***
Observations
R2
866
0.64
1,122
0.78
*** p<0.01, ** p<0.05, * p<0.10.
Marginal effects of discrete change from Unacceptable class.
Hunt 31 May 2013
Today’s Agenda
• How did we approach the study in light of prior
studies?
• What did we find using the approach?
• What conclusions derive from the findings?
Hunt 32 May 2013
Medical Marijuana Laws Don’t Look Like This . . .
D.C.
Source: Pacula et al. (forthcoming)
Hunt 33 May 2013
. . . They Look Like This
Unacceptable
Research Only
Pharmaceutical
Home Remedy
Mixed Supply
D.C.
Jurisdictions’ Classes (as of 01/01/2012)
Hunt 34 May 2013
Conclusions
• Medical marijuana laws are not homogenous
– Previous literature mainly considers 2 classes: Legal, Not
Legal
– We find 5 distinct classes that differ on: patient use,
research-only laws, pharmaceutical laws, supply options
• Laws used to differ, but now appear to be converging
– Generally, states adopting MMLs for first time adopted
Home Remedy
– Generally, states with MMLs already move toward Mixed
Supply
Hunt 35 May 2013
Next Steps
• Try to better understand why jurisdictions change laws
– Political-economy?
• Laws appear to be converging: is that good or bad?
– Associated health and safety outcomes
– Productivity and other economic outcomes
Hunt 36 May 2013
Thank You !!!