It’s Complicated: Methods to assess medication

nonadherence and regimen complexity

John Billimek, PhDDepartment of Medicine Grand Rounds | August 12, 2014

Division of General Internal Medicine | Health Policy Research Institute | UC Irvine School of Medicine

Two patients 58 year-old man Type 2 diabetes Middle class,

educated Good overall health

Prescribed

4 medications

58 year-old man Type 2 diabetes Middle class,

educated Good overall health

Prescribed

7 medications

Patient Complexity in Chronic Disease Management

Multiple Chronic Conditions Nationwide (CDC) Among all adults in the US

50% have at least one chronic condition 25% have two or more

Adults over age 65 86% have at least one chronic condition 61% have two or more

Two-thirds of health care spending

Ward 2014 Prev Chronic Dis 2014;11:130389Anderson 2010. Chronic Care: Making the Case for Ongoing Care, RWJ

Complex Patients, Complex Regimens

More Chronic Conditions

More medications

indicated

Over- and under-

prescribing

Worse adherence

More adverse events

Higher costs

Increased hospitalizati

on

Increased readmission

s

Increased mortality

Mansur et al 2012. Am J Geriatr Pharmacother 10;223-229Wilson et al 2014. Ann Pharmacother 48(1);26-32

Medication Nonadherence Over 50% of patients

either Never fill Rx Delay refills Discontinue, and/or Skip doses

Contributes to up to 69% of hospital admissions And $100 billion

Osterweil 2005. NEJM

How much nonadherence is too much?

Varies by condition, treatment and situation

In VA patients with diabetes “Skipping” 20% of doses

+81% mortality risk +58% all-cause admission rate

“Skipping” 50% of doses 12-fold mortality risk

Ho. et al. 2006. Arch Intern Med 166:1836-41 Egede et al. 2011. The Annals of Pharmacotherapy 45: 169 –78

R2D2C2 Study

NIDDK, RWJ, Novo Nordisk funded RCT Disparities in diabetes management Poor, ethnically diverse sample (N=1484) Data collection

Patient questionnaires Chart review Audiorecordings

Study Foci Patient Participation Training Patient Complexity Medication Adherence

Kaplan 2013. J Gen Int Med 28(10): 1340-9

Complex Patients at UCI: Diabetes

75% of R2D2C2 study patients have 2+ additional comorbid conditions 35% have 4+ additional comorbid conditions

87% taking 5 or more different medications 35% are taking 10+ medications

Over 60% report medication nonadherence

Reasons for nonadherence Forgetting Cost, Financial pressures Side effects (currently

experienced) Regimen confusing, complicated Side effects (possible, future

damage) Pharma advertising

Interferes with lifestyle Concerns about alcohol

Concerns about effectiveness, value Experimenting, “N-of-me trials”

DO: (Mixed) Evidence based approaches

Patient

Physician

Pharmacist

NurseProfessio

nal Health

Educators

Community Health Workers

• Multifactorial & Coordinated• Case Management• Education• Patient Engagement

• Tailored & Targeted• One size fits none

DO: The Medical Visit Where treatment

decisions are made

All useful information may not be available

Little time to talk Averages: 15 minutes | 6

topics 5 minutes for main topic 1 minute for each of the rest

Tai-Seale 2007. Health Serv Rsch 42:5 1871-94

Patient

Physician

Pharmacist

NurseProfessio

nal Health

Educators

Community Health Workers

Many patients have problems with adherence

…but few raise problems with the doctor

DO: Coached Care Patient Participation Training

AudioRecord

PatientQuestionnaire

DO: Patient Participation training Coached Care

Raised issue about regimen during visit

Issue was addressed during the visit

0%

10%

20%

30%

40%

50%

60%

70%

39%32%

59%

48%

Standard-ized educa-tion

0%

20%

40%

60%

80%

100%

43%

75%

No issues addressedAt least one issue ad-dressed

% s

how

ing

im

pro

vem

en

t b

y n

ext

vis

it

Raising problems with adherence helps

Patients with A1c>9% at recorded visit

DO: The Medical VisitOrganize

services toCUE UP

topics and info for the medical

visit

Involve the patient to promote FOLLOW-THROUGH

Patient

Physician

Pharmacist

NurseProfessio

nal Health

Educators

Community Health Workers

KNOW: So, who do we help? Two EMR-based approaches to ID

patients

1. Medication Nonadherence Medication Possession Ratio (MPR)

2. Regimen Complexity: Medication Regimen Complexity

Index (MRCI)

Assessing Medication Nonadherence

Don’t we already know who isn’t taking their medications?

0%

20%

40%

60%

80%

25%

61%

Do you take your medications as prescribed? (less than always)

Indicate which (of 9) barriers to adherence you have faced recently (reporting at least one)

% r

ep

ort

ing

non

ad

-h

ere

nce

The way we ask matters

0%

5%

10%

15%

20%

5%6%

11%

14%

% d

iffere

nce

betw

een

n

on

ad

here

nt

vs.

ad-

here

nt

A1c LDL

*

*

Look in the EMR: the Medication Possession Ratio (MPR)

How much nonadherence is too much?

Varies by condition and situation

In VA patients with diabetes “Skipping” 20% of doses

+81% mortality risk +58% all-cause admission rate

“Skipping” 50% of doses 12-fold mortality riskHo. et al. 2006. Arch Intern Med 166:1836-41

Egede et al. 2011. The Annals of Pharmacotherapy 45: 169 –78

Assessing Regimen Complexity

Take two patients taking 7 medications

15 doses 4+ times/day2 modalities

9 doses 2 times/day1 modality

7 meds

S M T W TH F S

Morning

7 (P) 7 (P)

7 (P) 7 (P) 7 (P) 7 (P)

7 (P)

Midday 2 2 2 2 2 2 2

Evening

4 (P) 4 (P)

4 (P) 4 (P) 4 (P) 4 (P)

4 (P)

Night 2 2 2 2 2 2 27 meds

S M T W TH F S

Morning

7 7 7 7 7 7 7

Midday

Evening

2 2 2 2 2 2 2

Night

Look in the EMR: Medication Regimen Complexity Index (MRCI)

One score for each patient

Objective

Actionable

Patient A’s MRCI

score

24

Patient A’s Med List

-------- --- -- ---------- --- -- ---------- --- -- ---------- --- --

-------- --- -- ---------- --- -- ---------- --- --

Flag high-risk patients in a

registry

Available at point of care

MRCI = Total A + Total B + Total Cfor all current prescription medications

Dosage Form Dosing FrequencySpecial Instructions+ +

Medication Regimen Complexity Index (MRCI)A weighted count of currently prescribed medications

A B C

A B C

All polypharmacy is not created equal

Putting it together: Population management of medication issues

MRCI

Patient Reported

Nonadherence

Outcomes

A1c

LDL

ER Visits

Hospital Admissio

ns

Adjust for

Comorbidity

Patient Char

Stage 1: R2D2C2 DatasetHypothesis testing

MRCI

MPR

Outcomes

A1c

LDL

ER Visits

Hospital Admissio

ns

Adjust for

Comorbidity

Patient Char

Stage 2: UCI Diabetes RegistryPredictive modeling

2012 2013

Stage 3: Stakeholder EngagementFrom KNOW to DO

Stage 1 R2D2C2 Dataset: Preliminary Findings

Hospital admission

ER Visit

LDL > 100 mg/dl

A1c > 8%

Medication nonadherence

0.0 0.5 1.0 1.5 2.0 2.5

1.8

1.9

1.1

1.4

1.5

Stage 1 R2D2C2 Dataset: Linking MRCI to outcomes

Higher rates with high MRCI

Odds ratios comparing MRCI above vs. below 17Adult UCI patients with type 2 diabetes (N=998)adjusted for: Age, Sex, Race/ethnicity, Education, Insurance type, Nativity, duration of diabetes and comorbidity (TIBI)*

MRCI

Patient Reported

Nonadherence

Outcomes

A1c

LDL

ER Visits

Hospital Admissio

ns

Adjust for

Comorbidity

Patient Char

Stage 1: R2D2C2 DatasetHypothesis testing

MRCI

MPR

Outcomes

A1c

LDL

ER Visits

Hospital Admissio

ns

Adjust for

Comorbidity

Patient Char

Stage 2: UCI Diabetes RegistryPredictive modeling

2012 2013

Stage 3: Stakeholder EngagementFrom KNOW to DO

MRCI

Patient Reported

Nonadherence

Outcomes

A1c

LDL

ER Visits

Hospital Admissio

ns

Adjust for

Comorbidity

Patient Char

Stage 1: R2D2C2 DatasetHypothesis testing

MRCI

MPR

Outcomes

A1c

LDL

ER Visits

Hospital Admissio

ns

Adjust for

Comorbidity

Patient Char

Stage 2: UCI Diabetes RegistryPredictive modeling

2012 2013

Stage 3: Stakeholder EngagementFrom KNOW to DO

Acknowledgments

Funders DOM Chair’s Award ICTS Pilot Awards program NIDDK

Collaborators Sheldon Greenfield Sherrie Kaplan Dara Sorkin Quyen Ngo-Metzger Shaista Malik Dana Mukamel Lisa Dahm Andrea Hwang UC Irvine Health Informatics &

Research Computing

Patient Advisory Group (La Voz de la Esperanza) Marco Angulo Anabel Arroyo

MRCI/MPR Development team Travis Nesbit Daniel Orlovich

Audiocoding Team Herlinda Guzman Linh Vu Katherine Vu Sophia Nguyen Kimberly Gardner Taylor Gardner Mylon Remley Mei Chang Sana Moosaji Stephanie Torrez Maria Paula Gonzalez Alejandro Avina Jessica Colin Escobar Linda Nguyen

Summary Nonadherence and Complex regimens are

common Problems with regimens are rarely discussed

Regimen complexity Outcomes Independent of comorbid disease burden

EMR-based approaches can identify patients struggling with medication regimen Help direct interventions and resources

Questions?

John Billimek, PhD | jbillime@uci.edu