Expanded Mental Health
Benefits and Outpatient
Depression Treatment Intensity
Anthony T. Lo Sasso
University of Illinois at Chicago
Richard C. Lindrooth
Medical University of South Carolina
Ithai Z. Lurie
John S. Lyons
Northwestern University
Research supported by NIMH grant R01MH62114
Goal of the Research
To study how a mental health benefit
expansion affected outpatient depression
treatment utilization
Particular emphasis will be placed on
examining how the benefit change
affected the “dose” of outpatient psychotherapy received by patients
Initiation → OP visits → sufficient # of OP
visits
Setting & Benefit Design
Large Fortune 50 electronics manufacturing
company
Between 1995 and 1996, the company initiated
a new approach in health benefits for mental
health with three components:
– reduced copayments for mental health treatment
– the creation of a network of select mental health
providers
– de-stigmatize the treatment of mental disorders
Details on the Benefit Change
Selective contracting with mental health
providers
High cost sharing & utilization limits for out-ofnetwork care
No limits are placed on in-network mental
health services
Coinsurance rates on inpatient care were
changed from 80% to 90%,
80% coinsurance for outpatient services was
replaced with a flat $10 copayment
Data
Claims and enrollment data from intervention
company for years 1995-1998
– for all persons with a mental health diagnosis or
procedure code suggestive of mental health
treatment
– Data only for continuously enrolled members of
the company’s self-insured health insurance plan
Comparison group comprised of random
sample of employed persons from Medstat
Marketscan database, 1995-1998
Methods
We compare outpatient treatment in the
intervention group to the comparison group over
time:
– Outpatient treatment initiation for depression
– Outpatient treatment visits
– An indicator variable for more than 8 visits for
psychotherapy
Basic model:
OP Visits = α + βPost + γIntervention +
δPost×Treatment + θX + ε
Methods II
By restricting the regression to the withinprovider type impact, we can isolate the
impact of the copayment reduction &
destigmatization:
OP Visits = α' + β'Post + γ'Treatment +
δ'Post×Treatment + λ1 Non-MD Specialist
+ λ2 MD-Specialist + θ'X + ε
Where δ' represents the remaining effect
of the benefit change controlling for the
effect of provider choice
Methods III
Using estimates of the elasticity of
demand for mental health treatment from
published studies, we can decompose δ'
into the expected impact of the cost
sharing reduction and destigmatization
Descriptive Statistics of Depression
Treatment Initiation and Utilization
Intervention Group
Control Group
Initiation
%
OP
visits
% > 8 Initiation
visits
%
OP
visits
%>8
visits
1995
2.2
5.6
28.7
2.5
5.6
21.7
1996
2.6
7.5
41.0
2.3
6.0
25.2
1997
2.7
6.8
38.0
2.0
5.8
27.4
1998
2.7
6.8
37.3
2.1
6.3
26.9
Regression Results, Basic
Specification
Treatment×
Post (δ)
Initiation
(Logit-OR)
OP Visits
(OLS)
8 or More
Visits
(Logit-OR)
1.33**
1.25**
1.25
N=310,882 for Initiation regression, n=7,560 for other regressions
* Indicates 0.01<p<0.05, ** indicates p<0.01
Descriptive Statistics of Specialist
Use & Percentage > 8 Visits
1995
1996
1997
1998
Intervention Group
Comparison Group
Generalist
Non-MD
specialist
MD
Specialist
Generalist
Non-MD
specialist
MD
Specialist
511
385
143
157
226
171
22.5%
35.8%
31.5%
22.9%
21.2%
21.1%
530
765
150
135
198
132
31.1%
46.9%
46.5%
18.5%
27.3%
28.8%
609
771
124
150
270
142
36.3%
39.4%
37.9%
16.0%
34.1%
26.8%
647
775
83
118
274
117
34.9%
39.0%
39.8%
7.6%
37.2%
22.2%
Regression Results, WithinProvider Type
Treatment×
Post (δ')
OP Visits
(OLS)
8 or More Visits
(Logit-OR)
1.03**
1.22
N=7,560
* Indicates 0.01<p<0.05, ** indicates p<0.01
Summary of Findings
Our prior work has shown that the selective
contracting network was not defined restrictively
enough to increase distance to providers, but
the emphasis on specialist access (particularly
non-MD) had a significant impact on utilization:
1.25-1.03 = +0.23 visits
Based on the RAND HIE elasticity of -0.17, we
calculate the predicted effect of the copayment
reduction to +0.42 visits
The remainder then is attributed to destigmatization: +0.6 visits
Under Different Assumptions…
If instead we use a higher elasticity
measure from the literature, -0.32, the
predicted impact of the copayment
reduction is +0.79 visits
Under this assumption, we are left with a
de-stigmatization effect of +0.23 visits
Discussion
Our empirical results suggest that the
combination of benefit changes instituted
by the company was successful in not only
encouraging more employees to enter
depression treatment, but also in enabling
more patients to stay in treatment longer
increasing the likelihood that they receive
the appropriate minimum adequate “dose”
of 8 outpatient psychotherapy visits
Discussion II
Our results suggest that each aspect of
the benefit change—promotion of innetwork specialty providers, reducing
copayments, and a company-wide effort to
reduce the stigma associated with mental
health treatment—played an important
part in increasing the number of outpatient
visits per episode of treatment conditional
upon treatment initiation for depression
Conclusion
Starting treatment is not what matters in
behavioral healthcare
Engaging in a successful episode of care
is a far more relevant indicator
The results point to the potentially
important role that corporate benefit
designers and planners can play in
improving access to mental health care for
employees