Does Shared Treatment Decision-Making
Improve Asthma Adherence and Outcomes?
Supported by grants from the National Heart, Lung and Blood Institute
1R01 HL69358 (PI: SWilson) and 1R18 HL67092 (PI: ASBuist)
Only ~50% of patients take asthma
medications at effective doses
Documented problems:
 Under-use of controller medications
 Over-use of relievers & OTC medications
 Poor inhaled medication technique
 Failure to fill/refill prescriptions
 Failure to keep medications available
when and where they are needed
Known contributors to non-adherence

Patient
 Younger age
 Low socioeconomic status
 Lack of education
 Memory problems
 Lack of understanding of the disease

Regimen





Longer duration of treatment
Higher cost
Complexity, more frequent dosing
Properties (bad taste, more side effects, etc.)
Physician-patient relationship




Inadequate monitoring
Failure to explain side effects
Failure to analyze patient’s medication-taking
behaviors
Failure to address the patient’s individual situation and
preferences
Models of Clinician-Patient Interaction

Traditional model:



Interaction is directive;
Clinician makes the treatment decision
Evidence-based management usually follows a
traditional model
Pt
MD

Informed decision-making model:


Clinician provides information to the patient
Patient makes the decision
MD
Pt

Shared decision-making model:



Mutual exchange of information and treatment
preferences between clinician & patient
Both participate in treatment decisions
Each brings unique knowledge to the interaction
MD
Pt
Hypothesis:
Involving patients in treatment decisions should result in:
 Better adherence to treatment
 Better asthma control
 Greater patient satisfaction
Design of the BOAT trial

Three-arm, randomized controlled trial




SDM = shared decision making care management
MBG = guidelines-based traditional care management
UC = usual medical care
Data collection

Baseline and 12-mos. post-randomization
 Questionnaire
 PFT

12-mos. pre and 24 mos. post-randomization (36 mo.)
 Asthma medications dispensed
 All health care utilization
BOAT study hypotheses regarding
adherence and disease outcomes
SDM > MBG
SDM > UC
Study Outcomes
 Primary

 Adherence to asthma
medications
 Asthma-related quality
of life
 Asthma-related health
care utilization
Secondary








Asthma control
Use of reliever medications
Symptom-free days;
Lung function
Satisfaction with asthma care
Preferences, values, &
attitudes towards adherence
Total asthma health care
utilization
Asthma-related health care
costs
Both the SDM & MBG Interventions:


Target patients with poorly controlled,
moderate-severe asthma
Involve 2 in-person sessions, approximately 1
mo. apart, plus 3 follow-up calls at 3 mo.
intervals

Conducted by asthma care managers:





Clinical pharmacists
Nurse practitioners and registered nurses
Physician assistants
Respiratory therapists
Parallel written protocols (scripts) guide both
SDM and MBG clinician-patient interactions


Structured to enable tailoring to the individual patient
Instructional aides and worksheets are included in the
interventionist manual
SDM and MBG Interventions*
Set the Stage
 Establish rapport
 Describe session schedule
 Describe shared decision making approach
Gather patient information
 Asthma symptoms
 Perceptions of control
 Medication use
 Use of alternative therapies
 Environmental triggers
 Patient goals & preferences
Provide information
 Assess understanding of asthma
 Review asthma and how it is treated
 Confirm comprehension
Negotiate (SDM)/Prescribe (MBG)
• Summarize patient goals and priorities
 Review PFTs with patient
 Assess symptom control using objective criteria
 Determine asthma severity per GINA guidelines
 Define medication preferences
 Discuss +/- of each treatment option per patient
goals and preferences
 Negotiate a treatment decision
Wrap Up
 Write Rx
 Give Asthma Action & Management Plan
 Teach proper inhaler use
 Give asthma diary
 Schedule follow-up appointment
* White = MBG and SDM
Gold = SDM only
Inclusion Criteria

Recent ED/hospital visit for asthma and/or
evidence of over-use of rescue medication

18-70 years of age

KFHP member ≥ 1 year

Self-reported, doctor-diagnosed asthma

Currently Rxed asthma medications

Meets obstruction reversibility criterion

One or more asthma control problems
(ATAQ score ≥1)
Exclusion Criteria

Mild intermittent/seasonal asthma

Regular use of oral corticosteroids

Currently receiving asthma care-management

Not able to speak, read, and understand
English

Planning to move out of area within two years
Randomization*
Eligible
Patients
SDM
(N= 204)
MBG
(N= 205)
(N=613)
UC
(N= 204)
* Adaptive randomization algorithm (Pocock, 1983) - ensures better than chance balance
and increases likelihood of better than chance balance on correlated characteristics.
Demographic characteristics*
N=613
Age
Gender
Ethnicity
%
18-34 yrs.
20
35-50 yrs.
42
51-70 yrs.
38
Male
44
Female
56
Hispanic
Asian
Native
Hawaiian/Pacific
Islander
%
Level of
education
80%
Annual
family
income
4
10
8
Black/African
American
16
White/Caucasian
62
38%
< High School Diploma
HS Diploma/GED
16
Technical/Some College
43
4-Year Degree/BA/BS
22
Graduate Degree
17
 $20,000
8
$20,001 - $40,000
21
$40,001 - $60,000
25
$60,001 - $80,000
18
$80,001
24
DK/Refused To Answer
*
2
No significant group differences.
4
Baseline asthma status*
60
Percent
50
40
SDM
MBG
UC
30
20
10
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Symptom Frequency
Nocturnal Symptoms
FEV1 % predicted
* No significant group differences in symptom frequency, nocturnal symptoms,
or FEV1 % predicted at baseline.
De facto medication regimen and
asthma control*
60
Percent
50
40
SDM
30
MBG
20
UC
10
0
t
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nt
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Medication regimen
* No significant group differences at baseline.
Asthma Control
• Did the SDM patients’ medication choices differ
from the MBG care managers’ guidelines-based Rx?
Medication
SDM
N=191
MBG
N=186
Beclomethasone 80
90 (50%)
108 (61%)
Fluticasone 220
78 (43%)
53 (30%)
Other ICS2
13
(7%)
17 (10%)
181 (95%)
178 (96%)
Any ICS
Leukotriene modifier
Theophylline
Any Controller3
pvalue1
0.03
0.67
14 ( 7%)
14
(8%)
0.94
4 ( 2%)
1
(1%)
0.37
181 (97%)
1.00
186 (97%)
1. Chi-square or Fishers exact test.
2. Includes Beclomethasone and Fluticasone at lower strengths, and Budesonide.
3. Includes ICSs, leukotriene modifiers, and theophylline; excludes LABAs and oral
prednisone.
Adherence measure = Continuous Measure of
Medication Acquisition (CMA)

CMA = Number of days’ supply of a medication
dispensed/365 days
 Proportion
of days on which medication was
available for use on Rxed regimen
A commonly used indicator of adherence to
the intended daily regimen

Data from the HMO’s pharmacy database
 ~95% of patients obtain all their medications
from the HMO pharmacy
Cumulative medication acquisition (CMA) values
pre and post randomization, by experimental group
CMA index – Mean (SD)
Baseline Yr.
Any ICS
Any Controller
Follow-up Yr.
Any ICS
Any Controller
UC
MBG
SDM
N
N=203
N=203
N=204
N=610
0.32
(0.32)
0.32
(0.31)
0.33
(0.34)
N=204
N=205
N=204
0.41
(0.47)
0.38
(0.37)
0.40
(0.43)
N=203
N=202
N=204
0.39
(0.37)
0.54
(0.36)
0.62
(0.38)
N=204
N=205
N=204
0.49
(0.52)
0.59
(0.45)
0.69
(0.45)
p-value
0.8986
N=613
0.9490
N=609
SDM vs MBG p=0.0162
SDM vs UC p<0.0001
MBG vs UC p<0.0001
N=613
SDM vs MBG p=0.0095
SDM vs UC p<0.0001
MBG vs UC p=0.0014
Conclusions:
For non-adherent patients with poorly
controlled asthma -
Involving patients in a meaningful
way in treatment decisions does not
result treatment regimens that
conflict with standard guidelines,
assuming patients have a basic
understanding of:
asthma
 their current level of disease control
 the medical rationale for asthma
treatment.

Conclusions:

For non-adherent patients with poorly controlled
asthma, care management that utilizes a
shared clinician-patient approach to selection of
the treatment regimen significantly improves
adherence to asthma controllers over a one
year period when compared with both:



usual medical care, and
traditional, prescriptive care management
Intervention effects did not differ as a function of
ethnic group (Caucasian, Asian and African
American)
Conclusions - continued

Clinical approaches of asthma care managers
can be shaped such that treatment decision
making is shared with the patient in a
meaningful way.


This required use of a detailed intervention protocol,
training, and ongoing feedback.
Patients evaluate their own vs. the clinician’s
influence on treatment decisions differently
when they experience a shared decision
making approach than when they experience
prescriptive care management
Questions being investigated by
analyses in process
 Does shared decision-making lead to:
 better asthma control?
 better asthma-related quality of life?
 reduced asthma health care utilization?
 increased patient satisfaction?
 Are adherence outcomes mediated by patient
perceptions of their influence on treatment
decisions?
 Are disease outcomes mediated by medication
adherence?
Process outcomes
• How closely did interventionists follow the protocol
• Who made the treatment decisions?
5
Protocol
Adherence
Protocol
Adherence
QC rater
Mean rating
4
Decision Roles
Decision Roles
3
*
p=0.47
Care manager
2
* p<0.001
*
1
0
QC rater
SDM
*
Patients
MBG
Rating scales:
Protocol Adherence 1 = Relevant elements not covered
3 = All elements covered, but some briefly,
incompletely, or inadequately
5 = All topics covered completely, thoroughly,
and accurately
Decision Roles - Treatment decisions were made by:
1 = Care manager alone
2 = Care manager mostly
3 = Patient and care manager equally
4 = Patient mostly
5 = Patient alone
Investigators
Sandra Wilson, PhD, PI (PAMFRI, SUSM)
Sonia Buist, MD, PI (OHSU, CHR)
William Vollmer, PhD (CHR)
Tom Vogt, MD (CHR)
Nancy L. Brown, PhD (PAMFRI, SU)
Philip Lavori, PhD (SUSM)
Margaret Strub, MD (TPMG)
Stephen VanDenEeden, PhD (KRFI/DOR)
Clinical Site Co-investigators
Faith Bocobo, MD (TPMG)
Christine Fukui, MD (TPMG)
Donald German, MD (TPMG)
John Hoehne, MD (TPMG)
Matthew Lau, MD (TPMG)
Myngoc Nguyen, MD (TPMG)
Consultants
Amiram Gafni, PhD
Elizabeth Juniper, PhD
Cynthia Rand, PhD
Sean Sullivan, PhD
Kevin Weiss, MD
(SDM only)
Post-randomization CMA indices for
inhaled corticosteroids, by group1
Overall p<0.00012,3
CMA FOR ICS
1.5
1.0
Mn = 0.62
N = 204
0.5
Mn = 0.54
N = 202
Mn = 0.39
N = 203
0.0
MBG
1.
2.
3.
SDM
GROUP
UC
N=504. Excludes 4 patients with mild persistent asthma for whom no ICS was prescribed.
Overall test of group differences, Wilcoxon/Kruskal Wallis test.
Multiple comparisons: SDM vs. MBG, p=0.02; SDM vs. UC, p<0.0001; MBG vs. UC, p<0.0001.
Post-randomization CMA indices for all
asthma controllers combined, by group1
3
CMA FOR CONTROLLERS
Overall p<0.00012,3
2
Mn = 0.69
N = 204
1
Mn = 0.59
N = 205
Mn = 0.49
N = 204
0
MBG
SDM
UC
GROUP
1.
2.
3.
N = 504. Excludes 4 patients with mild persistent asthma, for whom no controller was prescribed.
Overall test of group differences, Wilcoxon/Kruskal Wallis test.
Multiple comparisons: SDM vs. MBG, p=0.02; SDM vs. UC, p<0.0001; MBG vs. UC, p=0.0023.
Pre-randomization CMA for all controllers,
by ethnicity, within relevant sites
Northern CA & Hawaii
Northern CA & Portland
3
CMA 2 for Controllers
CMA 2 for Controllers
3
2
1
Mn = 0.40
N = 94
Mn = 0.41
N = 344
2
1
Mn = 0.36
N = 59
Mn = 0.47
N = 205
0
0
African American
Asian
White
ETHNICITY
White
Post-randomization CMA for all controllers,
by group, separately for Whites and Asians.
White
2
1
0
Mn=0.66 Mn=0.74
N = 68
N = 68
MBG
SDM
Group
Asian
3
CMA 2 for Controllers
CMA 2 for Controllers
3
Mn=0.52
N = 69
UC
2
1
0
Mn=0.78 Mn=0.87 Mn=0.52
N = 18
N = 19
N = 22
MBG
SDM
Group
Regression model
Group comparison: p-value <=0.0001. Group x Ethnicity interaction: p-value = 0.4478
UC
Post-randomization CMA for all controllers, by group,
separately for Whites and African Americans
White
African American
3
CMA 2 for controllers
CMA 2 for Controllers
3
2
1
0
Mn = 0.63
N = 113
MBG
Mn = 0.74 Mn = 0.53
N = 116
N = 115
SDM
UC
2
1
0
Mn = 0.55
N = 33
MBG
Mn = 0.51 Mn = 0.34
N = 32
N = 29
SDM
Group
UC
Group
Regression model
Group comparison: p-value <=0.0001; Group X Ethnicity interaction: p-value = 0.6993.