Treatment Selection
for Depression:
The Impact of Caseload
Characteristics
Marisa Elena Domino, Ph.D.
The University of North Carolina
David S. Salkever, Ph.D.
The Johns Hopkins University
We would like to thank the APA for providing data for this project and gratefully
acknowledge support from NIMH.
Context
The tools of managed care are pervasive
in general health as well as behavioral
health
 These tools have been shown to have
externalities at the macro level

2
Price sensitivity and managed care

Pre-managed care:
 Physicians
have little knowledge of and
reaction to price
 Consumers are somewhat price sensitive
 RAND: drug prices matter, but only to
quantity, not to switching
3
Price sensitivity and managed care

managed care:
 May
increase physicians’ response to price
through information or incentives
 This response may spillover to non-managed
care patients
4
Objectives:



to determine the price sensitivity of psychiatrists
when prescribing drugs for their depressed
patients
to determine the impact that various tools of
managed care have on price sensitivity
to investigate the existence of managed care
“spillovers” where psychiatrists with a greater
degree of managed care involvement
demonstrate increased/decreased price
sensitivity to their non-managed care patients
5
Setting: patients with
depression

Why?
 Highly
prevalent
 Wide range in price of treatments
 Little difference in efficacy across all products
6
Dual Agency Model

Insurers want
physicians to chose
treatments that
minimize the
expenses of
treatment

Consumers want
physicians to chose
treatments that
improve their health
and minimize their
out-of-pocket
expenses
7
Theoretical model

Constrained utility maximization
 Physician
maximizes own utility with
arguments: patient utility, income (possibly a
function of treatment), and effort (also a
function of treatment)
 Patient utility a function of health, composite
good, constrained by income
8
Theoretical model

Drug price enters model through agency
relationship with consumers and through
own income
9
Empirical Methods

Nested multinomial logit model on
antidepressant drug choice

Standard errors were adjusted for
clustering on providers
10
Nesting Structure for
Logit Models
No Antidepressant
Drug Prescribed
TCAs
SSRIs
Others
(MAOIs, Heterocyclics)
Choice among
10 TCAs
Choice among
4 SSRIs
Choice among
7 Others
11
Methods




the variable of interest is the price variable
price alone determines price sensitivity
price interacted with patient managed care
variables determines additional influence
on price sensitivity from managed care
price interacted with managed care
caseload variables determines managed
care spillovers
12
Data:
The American Psychiatric
Association Practice Research
Network

The 1997 Study of Psychiatric Patients and
Treatments
linked by provider to:

The 1996 National Survey of Psychiatric
Practice
13
Sample Selection
Persons with a clinical diagnosis of
depression (DSM codes 296.2, 296.3, or
311)
 age 18 or over
 seen on an outpatient basis
 not receiving multiple concurrent
antidepressant therapy

14
Physician and Patient
Characteristics
Variable
Description (n)
Patient Level Characteristics
GAF
Global Assessment of Functioning scale (n=301)
Female
Patient is Female(n=289)
Educ
Years of Education for Patient (n=300)
Age
Age of Patient(n=305)
Inpatyr
Patient has been admitted to a psychiatric facility for the
treatment of a psychiatric disorder in the past 12 months
(n=299)
Subabu
Patient has ever had substance abuse or dependence disorder,
including alcohol or nicotine (n=281)
Primdep
Primary diagnosis of depression (n=305)
Yearstx
Number of years since first treatment (not necessarily for
depression) (n=304)
Provider Level Characteristics (weighted by number of patients in sample)
Doc_age
Age of provider (n=303)
Doc_fem
Provider is female (n=302)
Ppatmon
Number of patients in last month (asked in 1997 patient
survey) (n=301)
Mean/
Percent
Standard
Deviation
49.4
63.3%
14.4
44.9
14.7%
12.0
3.1
13.8
44.4%
77.7%
2.7
49.2
31.5%
137.6
4.0
9.9
93.2
15
Managed Care Variables
Managed Care
Variable
Patient-level description and
percent
Managed Care
Patient belongs to any type of
managed care plan (43.1%; n=295)
Carve-out
Patient belongs to a behavioral
health carve-out plan (12.9%;
n=295)
NA
Managed Care Panels
Discounted Fee-ForService (patients)
Physician is compensated for
treatment provided to this patient at
this visit on a discounted fee-forservice basis (35.1%; n=305)
Provider-level description, mean,
and standard deviation (weighted
by number of patients)
Percentage of patients covered
through a managed care plan (34.4
(27.8); n=294)
Percentage of patients covered
through a behavioral health carveout plan (19.8(23.1); n=294)
Number of Managed Care Panels to
which a Physician belongs
(5.3(6.9); n=280)
Percentage of patients for which fees
are discounted. (40.8(34.4); n=291)
16
Distribution of Treatments
100%
90%
80%
70%
60%
Other
50%
SSRI
40%
TCA
30%
No Antidepressant
20%
10%
0%
All Persons
No
Managed
Care
Managed
Care
17
Explanatory Variable of Interest:
Price

Calculated as the median (of average)
price per prescription by chemical entity
(“drug”) for the first quarter of 1997 from
CMS data on Medicaid Drug Utilization
nationwide
18
Expectations of “Price”

What we want to
happen:
»
“price” picks up true
price effects

What could confound
the results:
»
“price” picks up other
effects which are
correlated with the true
price


side effects
episode costs
19
Model 1:
Any type of Managed Care
Lower Level
Variable
Price (*.01)
Price*Patient MC
Price*Physician MC
(*.01)
Price*Patient MC*
Physician MC (*.01)
Market Age (*.01)
Market Age
Squared (*.0001)
Tricyclic Branch
SSRI Branch
Other Branch
-0.684
(2.054)
-1.088
(2.393)
0.778
(1.554)
2.411
(3.040)
0.495
(0.218)
-0.097
(0.230)
-0.735
(2.282)
-0.014
(0.087)
0.290
(0.815)
-0.498
(1.333)
-0.179
(0.019)
3.753
(0.517)
0.599
(2.693)
0.021
(0.067)
-0.415
(2.284)
0.494
(0.946)
2.505
(2.949)
-0.705
(3.404)
20
Model 1:
Any type of Managed Care
Upper level
coefficients
Intercept
GAF (*.01)
Subabu
Primdep
Yearstx (*.1)
Inpatyr
Age (*.01)
Age2 (*.0001)
Female
Patient Gender
Missing
Education
Ppatmon (*.001)
Doc_fem
Doc_age (*.01)
Doc_age2 (*.0001)
Patient MC *
Physician MC
Patient MC
Physician MC
Inclusive Value
log-Likelihood
Tricyclic Branch
SSRI Branch
Other Branch
-1.082
(0.130)
5.423
(2.277)
0.976
(1.509)
1.086
(1.642)
0.515
(0.925)
0.540
(0.556)
-4.181
(0.339)
9.978
(0.780)
0.554
(0.901)
1.658
(1.295)
-23.661
(2.219)
4.230
(0.710)
0.423
(0.457)
-6.638
(0.235)
-17.506
(0.616)
3.579
(0.570)
-0.499
(0.218)
-2.305
(1.247)
-0.029
(0.040)
-70.625
(0.254)
-0.811
(0.402)
0.148
(0.301)
1.102
(2.258)
-1.166
(1.933)
0.744
(1.052)
-10.150
(1.161)
8.429
(0.873)
0.564
(1.135)
-1.104
(1.090)
-2.706
(0.348)
6.292
(1.148)
1.303
(2.368)
19.340
(1.089)
-21.288
(1.287)
-109.805
(0.425)
-2.943
(0.076)
66.430
(0.539)
-29.659
(0.360)
- 515.49
-139.250
(1.420)
0.973
(0.450)
0.876
(1.590)
1.044
(2.027)
-0.437
(0.738)
0.525
(0.646)
-7.369
(0.709)
7.416
(0.668)
0.327
(0.575)
-1.369
(0.981)
5.012
(0.656)
10.556
(2.064)
1.345
(2.189)
1.872
(0.103)
-6.408
(0.387)
-53.215
(0.909)
-2.980
(0.072)
45.589
(1.425)
24.198
(1.311)
21
Figure 2: Estim ated Price Elasticity of TCAs
With 90% Confidence Interval, based on Results from Model 1
6.000
4.000
2.000
Elasticity
Patient not in Managed Care
Patient in Managed Care
0.000
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
CI-Upper around no MC
CI-Low er around no MC
-2.000
CI-Upper around MC
CI-Low er around MC
-4.000
-6.000
-8.000
Percent of Physician Caseload in Managed Care
22
Figure 3: Estim ated Price Elasticity of SSRIs
With 90% Confidence Interval, Based on Results from Model 1
1.000
0.000
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Estimated Elasticity
-1.000
-2.000
Patient not in Managed Care
Patient in Managed Care
-3.000
CI-Upper no MC
CI-Low er no MC
-4.000
CI-Upper MC
CI-Low er MC
-5.000
-6.000
-7.000
-8.000
Percent of Physician Caseload in Managed Care
23
Figure 4: Estim ated Elasticity of SSRIs
With 90% Confidence Interval, Based on Results from Model 2
2.000
0.000
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Estimated Elasticity
-2.000
Patient not in Carve-out
-4.000
Patient in Carve-out
CI-Upper no CO
-6.000
CI-Low er no CO
CI-Upper CO
-8.000
CI-Low er CO
-10.000
-12.000
-14.000
Percent of Physician Caseload in Carve-outs
24
Conclusions:
Price effects vary strongly among the
three classes of antidepressants
 Psychiatrists do demonstrate price
sensitivity when choosing among
antidepressants
 Price elasticity estimates range from
-0.4 to -4.2

25
Conclusions:
Higher price elasticities for managed care
patients
 Significant evidence of spillovers

 Not
always in the expected direction
 Generally only to other managed care
patients
26