1 the impact of patient adherence on physician performance measurement michael b. nichol, ph.d....

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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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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


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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


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Social Support Interventions (practical, emotional, undifferentiated) Large effect sizes seen with social support in well-

designed studies


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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


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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

1 the impact of patient adherence on physician performance measurement michael b. nichol, ph.d....

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