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Transcript of 1 The Impact of Patient Adherence on Physician Performance Measurement Michael B. Nichol, Ph.D....
![Page 1: 1 The Impact of Patient Adherence on Physician Performance Measurement Michael B. Nichol, Ph.D. Pharmaceutical Economics and Policy University of Southern.](https://reader035.fdocuments.us/reader035/viewer/2022070400/56649f115503460f94c234a1/html5/thumbnails/1.jpg)
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The Impact of Patient Adherence on Physician Performance Measurement
Michael B. Nichol, Ph.D.Pharmaceutical Economics and Policy
University of Southern California
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The nature of the problem: Why do adherence and persistence impact P4P?
The problem metric: How do we measure adherence and persistence?
The population: Who adheres or persists? Solving the problem: What can we do to improve our
performance, especially for P4P?
Presentation Objectives
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Definitions
Why are we going to use compliance and adherence interchangeably?
Compliance = whether patients follow the instructions of their doctor Dichotomous measure
Adherence = whether patients endorse the instructions of their doctor Dichotomous measure
Persistence = how long they follow the advice (whether they modify it over time) dichotomous or continuous
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Motivation for Compliance Studies
General recognition that non-compliance is a problem Ultimate goal is to improve health outcome by targeting
some patients on modifiable factors to improve compliance
Different parties in health care have different perspectives and interest (e.g., clinicians, patients, and payers)
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Evidence that Non-Compliance is a Problem: Medication Event Monitoring System (MEMS)
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Administrative Data on Drug Reimbursement
Good snapshot of acquisition in relationship to other mediations
Affordable Reliability can be ascertained Insight into dosing intervals
Many confounders Selection bias Dependent on
provider of data Retrospective
Features Limitations
Information about patient’s medication acquisition and procurement behavior using pharmaceutical benefit manager (PBM) reimbursement data
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Advantages of Administrative Claims-based Analyses
Objective (no recall bias) Real-world (not controlled) Relatively cheap to obtain Large sample Multiple outcomes Cost analysis Pattern recognition
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Measuring the Complexityof Non-Compliance
Drug A
Drug B
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An Example of Non-Compliance: Statins
Benner et al. JAMA 2002;288:455-461.
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Days Covered for Statins and CCBs
0
10
20
30
40
50
60
70
80
90
100
1 31 61 91 121 151 181 211 241 271 301 331 361
Day
Pro
po
rtio
n o
f p
ati
en
t in
co
ho
rt (
%)
Statin onlyStatin+CCB*CCB onlyCCB+Statin*Statin&CCB
Source: Unpublished data
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Medication Possession Ratio for Statins/CCBs Figure 1. Average 180-Day MPR by Index Year
30
40
50
60
70
80
1995 1996 1997 1998 1999 2000 2001
Index Year
Av
era
ge
180
-Da
y M
PR
(%
)
CCB only
Statin only
Statin+CCB
Statin*+CCB
CCB+Statin
CCB*+Statin
* MPR is for the newly initiated (not current)medication in the combinationtherapy.
Source: Unpublished data
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Patterns of Non-Compliance
15-20% of first scripts never filled
Of those filled, 20-35% never fill a second
Persistence declines slowly after 6 months
Patients who discontinue rarely restart, at least within a two year window for many chronic problems
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Why Do We Care?
Lack of efficacy from recommended treatment Increased mortality and morbidity Increased costs Inability to meet P4P goals
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($174)
($637)
$281
($591)($800)
($600)
($400)
($200)
$0
$200
$400
$600
Type of Service
Ambulatory Hospital Drugs Total Costs
Health Care Costs Associated with Discontinuation: Hypertension
Source: McCombs JS, Nichol MB, Newman C and Sclar DA: The costs of interrupting antihypertensive drug therapy in a Medicaid population. Medical Care, 32(3): 214-226, 1994.
N=6,430
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($922)
($157)
$515
($753)
($1,400)
($900)
($400)
$100
$600
Type of Service
Ambulatory Hospital Drugs Total Costs
N=1,240
Health Care Costs Associated with Discontinuation: Major Depressive Disorder
Source: McCombs JS, Nichol MB, Stimmel GL. The role of SSRI antidepressants for treating depressed patients in the California Medicaid (Medi-Cal) program. Value in Health, 2(4): 269-280, 1999.
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Efficacy/Goal Relationship
Efficacy
Go
al A
ttai
nm
en
t
100%
100%
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Efficacy/Goal/Adherence Relationship
Efficacy
Go
al A
tta
inm
en
t
100%
100%
10% Efficacy reduction
30% Adherence reduction
Plus
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Impact on P4P Goals:LDL <= 130
Simulation of impact on P4P LDL goal Data source is the IHA 2007 P4P reporting for
LDL <= 130 84.3% of the cardiovascular population were
screened Assumes that all patients screened are treated Assumes that treatment is 100% efficacious
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Impact on P4P Goals:LDL <= 130
Source: Table computed from 2007 P4P results provided at iha.org
Proportion adherent to Rx
All screened treated, Proportion meeting goal
90% screened treated, Proportion meeting goal
baseline 59.6%
(70% “adherent”)
59.6%
(78% “adherent”)
80% Rx adherent 67.4% 60.7%
90% Rx adherent 75.9% 68.3%
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Theory of Compliance Behavior
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G e ne r al i ze d C o nc e pt o f C o m pl i anc e
C o m plia n ce
L a te n t C o n s tru c t
I n div idu a lL e v e l
I n te rpe rs o n a lL e v e l
C o m m u n ityL e v e l
Fa m i l y a n d S o c i a l S u p p o r t ( r e f e r e n tp o w e r )
P a tien t-P h y s icia n R ela tio n s (ex p ert p o w er)
In s u r a n c e ( c o p a y )
C u l t u r a l n o r m S o c i a l S t a n d a r d
P o l i c y ( r e s o u r c e , c a r e a c c e s s )
S e l f - e f f i c a c y
D i s e a s e S t a t u s
B e l i e f s
S a t i s f a c t i o n
U n i d e n t i f i e d
L o c u s o f c o n tr o l
M u ltip le C a u s e s(c u rre n t o r re c e n t)
P e r s o n a l i t y ( f o r g e t fu l n e s s ,r e s p o n s i ve n e s s )
M e dica t io n( tre a tm e n t )
L e v e l
Ea s e o f t a k i n g , d o s i n g f r e q u e n c y , t a s t e ,B r a n d l o y a l ty , S i d e e f f e c t s
F a c to r le v e l
T a rge t of c om plia nc e -prom oting in te rve ntion
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Causes of Non-Compliance
Multiple causes with multiple levels Many factors may not be observable to researchers
(many latent variables) Each causal level can be targeted to improve compliance
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What Can We Do About Non-Adherence:Targeting for Compliance
Who is non-compliant? Why are they non-compliant? How can we change their behavior? When can we change their behavior?
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Demographic Associations with Adherence
Few studies show clear correlations with adherence among characteristics like age, gender, education, and socio-economic status
Correlation between patient education level and adherence is positive, but only for medications to treat chronic disease
DiMatteo MR. Variations in patients’ adherence to medical recommendations, Medical Care: 42:200-209, 2004
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Selected Disease Condition Adherence Rates
Mean Rate
0
10
20
30
40
50
60
70
80
90
100
HIV (N=8) Cancer (N=65) CVD (N=129) Infectious disease(N=34)
Diabetes (N=23)
Mea
n R
ate
DiMatteo MR. Variations in patients’ adherence to medical recommendations, Medical Care: 42:200-209, 2004
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Reasons for Non-Compliance
I just forget (54.9%)
Other (3.6%)
Don’t like being dependent on drugs (7.3%)
Don’t like being told what to do (0.6%)
Too expensive (1.8%)
If I don’t take them, supply will last longer (1.3%)
Side effects (6.4%)
Don’t think drugs are working (3.4%)
Hate taking drugs (7.1%)
Don’t think its always necessary (13.7%)
Cheng JW, et al. Pharmacotherapy. 2001;21:828-841.
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What Works? A Review of Reviews
Review of 38 meta-analytic reviews of adherence interventions
Technical Interventions (simplifying medication regimen; electronic monitoring) Less frequent dosing = improved adherence Single dose/day better than multiple doses/day Electronic device improvements attributed to
reduction in doses
Van Dulmen S, et al. Patient adherence to medical treatment: A review of reviews, BMC Health Services Research, 7:55, 2007
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What Works? A Review of Reviews
Behavioral Interventions (memory aids, monitoring by calendars, support or rewards) Financial rewards improved adherence in 10/11
studies Mail and telephone reminders can improve adherence
Van Dulmen S, et al. Patient adherence to medical treatment: A review of reviews, BMC Health Services Research, 7:55, 2007
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What Works? A Review of Reviews
Educational Interventions (teaching/providing knowledge, including personal, group, audio-visual, home visits) Effects can be important in the short term, but decay
over time (> 4 weeks) When tested against dosing simplification,
educational interventions less robust Collaborative care (systematic inclusion of multiple
providers) superior to education alone intervention
Van Dulmen S, et al. Patient adherence to medical treatment: A review of reviews, BMC Health Services Research, 7:55, 2007
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What Works? A Review of Reviews
Social Support Interventions (practical, emotional, undifferentiated) Large effect sizes seen with social support in well-
designed studies
Van Dulmen S, et al. Patient adherence to medical treatment: A review of reviews, BMC Health Services Research, 7:55, 2007
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What Works? A Review of Reviews
Complex or Multi-faceted Interventions (combine multiple approaches) Less than half resulted in improved adherence, and
only a third better treatment outcomes Successful interventions very resource intensive Even the most effective did not yield large effect sizes Variability in intervention and study design
compromises assessment
Van Dulmen S, et al. Patient adherence to medical treatment: A review of reviews, BMC Health Services Research, 7:55, 2007
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Intervention Effects:Largest to Smallest
Reduced drug dose frequency Financial rewards Prompting devices Adherence-enhancing packaging Telephone calls Personal counseling Home visits Reminder letters Written education material
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Pitfalls to Avoid
Starting with the intervention “concept” Doing too little Intervening too late Preaching to the choir Not from a trusted source Measurement via self-report Broad intervention population
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Recommendations for Improving Adherence to Chronic Medications
Low hanging fruit Quick follow-up by medical staff after initial
prescription (not automated calls) Only apply sampling for cost reasons Get the discontinuers back!
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Recommendations for Improving Adherence to Chronic Medications
Medium term Screen for depression Build IT capacity to support clinical staff
Long term Targeted populations Medical Home Social support
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Conclusions
Non-compliance remains an on-going and significant problem in health care
The factors associated with non-compliance are now being investigated
Literature reviews indicate that largest effect sizes will be produced by complex or multi-faceted interventions
Multiple longitudinal interventions may be required to obtain positive results
Non-compliance can significantly affect attainment of P4P goals