Does Shared Treatment Decision-Making Improve Asthma Adherence and Outcomes?

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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)
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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

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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 patients medication-taking
  behaviors
• Failure to address the patients individual
  situation and preferences

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Models of Clinician-Patient Interaction

• Traditional model
• Interaction is directive
• Clinician makes the treatment decision
• Evidence-based management usually follows a
  traditional model
• Informed decision-making model
• Clinician provides information to the patient
• Patient makes the decision

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• 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

• Hypothesis
• Involving patients in treatment decisions should
  result in
• Better adherence to treatment
• Better asthma control
• Greater patient satisfaction

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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

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BOAT study hypotheses regardingadherence and
disease outcomes
SDM gt MBG SDM gt UC
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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

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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

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SDM and MBG Interventions

• Set the Stage
• Establish rapport
• Describe session schedule
• Describe shared decision making approach

• 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

• 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

White MBG and SDM Gold SDM only
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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)

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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

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Randomization
Adaptive randomization algorithm (Pocock, 1983)
- ensures better than chance balance and
increases likelihood of better than chance
balance on correlated characteristics.
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Demographic characteristics
N613 N613
Age 18-34 yrs. 20
Age 35-50 yrs. 42
Age 51-70 yrs. 38
Gender Male 44
Gender Female 56
Ethnicity Hispanic 4
Asian 10
Native Hawaiian/Pacific Islander 8
Black/African American 16
White/Caucasian 62

Level of education lt High School Diploma 2
Level of education HS Diploma/GED 16
Level of education Technical/Some College 43
Level of education 4-Year Degree/BA/BS 22
Level of education Graduate Degree 17
Annual family income ? 20,000 8
Annual family income 20,001 - 40,000 21
Annual family income 40,001 - 60,000 25
Annual family income 60,001 - 80,000 18
Annual family income ?80,001 24
Annual family income DK/Refused To Answer 4
80
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No significant group differences.
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Baseline asthma status
?
Symptom Frequency
Nocturnal Symptoms
FEV1 predicted
No significant group differences in symptom
frequency, nocturnal symptoms, or FEV1
predicted at baseline.
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De facto medication regimen and asthma control
Medication regimen
Asthma Control
No significant group differences at baseline.
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Did the SDM patients medication choices differ
from the MBG care managers guidelines-based Rx?
Medication SDM N191 MBG N186 p-value1
Beclomethasone 80 90 (50) 108 (61)
Fluticasone 220 78 (43) 53 (30) 0.03
Other ICS2 13 (7) 17 (10)
Any ICS 181 (95) 178 (96) 0.67
Leukotriene modifier 14 ( 7) 14 (8) 0.94
Theophylline 4 ( 2) 1 (1) 0.37
Any Controller3 186 (97) 181 (97) 1.00


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.
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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 HMOs pharmacy database
• 95 of patients obtain all their medications
  from the HMO pharmacy

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Cumulative medication acquisition (CMA) values
pre and post randomization, by experimental group
CMA index Mean (SD)
UC MBG SDM N p-value
Baseline Yr. N203 N203 N204 N610
Any ICS 0.32 (0.32) 0.32 (0.31) 0.33 (0.34) 0.8986
Any Controller N204 0.41 (0.47) N205 0.38 (0.37) N204 0.40 (0.43) N613 0.9490
Follow-up Yr. N203 N202 N204 N609
Any ICS 0.39 (0.37) 0.54 (0.36) 0.62 (0.38) SDM vs MBG p0.0162 SDM vs UC plt0.0001 MBG vs UC plt0.0001 SDM vs MBG p0.0162 SDM vs UC plt0.0001 MBG vs UC plt0.0001
Any Controller N204 0.49 (0.52) N205 0.59 (0.45) N204 0.69 (0.45) N613 SDM vs MBG p0.0095 SDM vs UC plt0.0001 MBG vs UC p0.0014 N613 SDM vs MBG p0.0095 SDM vs UC plt0.0001 MBG vs UC p0.0014
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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.

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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)

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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 clinicians
  influence on treatment decisions differently when
  they experience a shared decision making approach
  than when they experience prescriptive care
  management

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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?

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Process outcomes

• How closely did interventionists follow the
  protocol Who made the treatment decisions?

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
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• 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)

Consultants Amiram Gafni, PhD Elizabeth Juniper,
PhD Cynthia Rand, PhD Sean Sullivan, PhD Kevin
Weiss, MD
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)
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(SDM only)
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Post-randomization CMA indices for inhaled
corticosteroids, by group1
Overall plt0.00012,3
Mn 0.62 N 204
Mn 0.54 N 202
Mn 0.39 N 203

1. N504. Excludes 4 patients with mild persistent
   asthma for whom no ICS was prescribed.
2. Overall test of group differences,
   Wilcoxon/Kruskal Wallis test.
3. Multiple comparisons SDM vs. MBG, p0.02 SDM
   vs. UC, plt0.0001 MBG vs. UC, plt0.0001.

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Post-randomization CMA indices for all asthma
controllers combined, by group1
Overall plt0.00012,3
Mn 0.69 N 204
Mn 0.59 N 205
Mn 0.49 N 204

1. N 504. Excludes 4 patients with mild
   persistent asthma, for whom no controller was
   prescribed.
2. Overall test of group differences,
   Wilcoxon/Kruskal Wallis test.
3. Multiple comparisons SDM vs. MBG, p0.02 SDM
   vs. UC, plt0.0001 MBG vs. UC, p0.0023.

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Pre-randomization CMA for all controllers, by
ethnicity, within relevant sites
Northern CA Hawaii
Northern CA Portland
Mn 0.47 N 205
Mn 0.41 N 344
Mn 0.40 N 94
Mn 0.36 N 59
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Post-randomization CMA for all controllers, by
group, separately for Whites and Asians.
White
Asian
Mn0.78 N 18
Mn0.87 N 19
Mn0.52 N 22
Mn0.66 N 68
Mn0.74 N 68
Mn0.52 N 69
Regression model Group comparison p-value
lt0.0001. Group x Ethnicity interaction p-value
0.4478
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Post-randomization CMA for all controllers, by
group, separately for Whites and African Americans
White
African American

Mn 0.55 N 33
Mn 0.51 N 32
Mn 0.34 N 29
Mn 0.63 N 113
Mn 0.74 N 115
Mn 0.53 N 116
Regression model Group comparison p-value
lt0.0001 Group X Ethnicity interaction p-value
0.6993.