DRUG CHARACTERISTICS ASSOCIATED WITH MEDICATION ADHERENCE ACROSS EIGHT DISEASE STATES

Pamala A. Pawloski, PharmD1,2; Richard J Bruzek, PharmD2; Brita Hedblom1; Steve Asche, MA1; Dana Meier, PharmD3; Cheri Rolnick, PhD, MPH11HealthPartners Research Foundation, 2HealthPartners Pharmacy Services, 3Novartis Pharmaceutical Corporation

HMORN Annual Meeting Wednesday, May 2, 2012, Seattle, WA

Background

Medication non-adherence shown to be universally suboptimal and believed to be a key factor in achieving therapeutic goals

Non-adherence represents a multifaceted challenge among patients and providers: leading to poor outcomes, compromised health and serious economic consequences

Determinants of non-adherence previously described as health system, social/economic, therapy-related, condition-related, and patient-related

To date, the impact of drug characteristics on medication adherence has not been studied across multiple disease states

Study Objective

To describe medication adherence by drug characteristics across 8 different disease states:

drug class,

generic utilization,

average out-of-pocket cost/prescription

To identify potential drug-specific factors by disease that may serve as targets for future intervention

Methods

Retrospective analysis of patients with a single diagnosis and oral medication for the following conditions:

•Asthma/COPD •Cancer•Depression •Diabetes •Hypercholesterolemia•Hypertension•Multiple sclerosis (MS) •Osteoporosis

Methods

This study was conducted by HealthPartners Research Foundation

Integrated health system including 3 owned hospitals and 27 owned clinics

15 in-clinic pharmacies and a mail order pharmacy

Serve >750,000 members

Included all patients > 18 years with 1 of 8 medical conditions described above

Methods

Patient records were identified by ICD-9 DM for diagnosis and GPI code for 128 medications of interest through claims occurring between January 1, 2007 and March 31, 2009 • Diagnosis of interest must have occurred

within 24 months of the most recent prescription fill

• A minimum of 2 prescription medication fills for at least a 28-day supply

Methods

Adherence was calculated by the Medication Possession Ratio (MPR) for each patient based on prescription fills within a 12-month window during the study period

Binary adherence (MPR >80%) by drug characteristics within condition were tested with contingency tables and chi-square tests

Methods

Analysis was adjusted for sex, race, age, proportion of adults with high school education, and median income

Logistic regression analysis was conducted to examine predictors of adherence

Patient characteristics for patients with one condition and one medication (n=14,875)

Total

% N=14,875

Female 60.9 Race/ethnicity White African Am. Asian Hispanic Am. Indian Other No answer

82.8 5.6 2.8 1.6 0.5 0.7 6.0

Age 18-49 50-59 60-69 70+

30.4 26.2 20.7 22.7

Proportion of adults in living area with a high school education <88% 88-<93% 93-<96% 96%+ Median=92.7%

25.6 27.1 21.9 25.5

Median income of families in living area

$64,500

Drug characteristics  within condition

Total

N=14,875 Hyperten N=5,440

Depress N=4,349

Hyperlipid N=2,731

Asth/ COPD

N=1,006

Diabetes N=590

Osteo N=521

Cancer N=156

MS N=81

On formulary drug (%)

98.3 98.9 98.2 98.6 97.7 99.3 91.8 96.8 96.3

On generic drug (%)

75.7 91.6 74.6 66.7 22.8 85.6 78.9 41.7 0

Mean member amount paid per 30 days

0-$5 >$5-$12

>$12-$22 >$22-$50

>$50

32.8 39.1 15.2 11.2 1.6

49.0 38.2 7.9 4.5 0.4

22.8 46.4 19.1 10.6 1.2

33.9 38.0 13.8 12.6 1.5

12.7 16.2 24.4 39.6 7.2

17.3 52.4 23.2 6.1 1.0

8.5 31.5 38.2 18.8 3.1

7.1 27.6 27.6 31.4 6.4

8.6 8.6 8.6

45.7 28.4

Binary drug adherence (MPR >80%) by drug characteristics, within condition

* p<.05 **p<.01 ***p<.001 Pearson chi-square. N=20/row min for reporting.

Total

adherent

N=14,875

Hyperten

adherent

N=5,440

Depress

adherent

N=4,349

Hyperlipid

adherent

N=2,731

Asth/

COPD

adherent

N=1,007

Diabetes

adherent

N=590

Osteo

adherent

N=521

Cancer

adherent

N=156

MS

adherent

N=81

Overall (%) 69.7 77.6 62.4 78.3 32.6 59.7 76.6 90.4 84.0

Generic vs. brand (%)

Generic

Brand

70.9***

65.9

77.3

81.1

60.6***

67.6

78.8

77.3

18.8***

36.6

59.0

63.5

79.6**

64.5

87.7

92.3

-

84.0

Mean member amount paid per 30 days

0-$5

>$5-$12

>$12-$22

>$22-$50

>$50

72.3***

72.7

64.1

61.5

50.0

78.3***

78.5

70.7

77.3

50.0

55.4***

66.0

60.0

66.4

56.9

82.0***

78.1

77.5

71.3

66.7

30.5

35.0

36.7

30.7

26.4

51.0***

68.3

51.8

42.9

-

52.3***

88.4

77.4

67.5

-

-

92.6

90.7

88.1

-

-

-

81.0

85.0

-

Logistic regression: predicting adherence within condition

Hyperten

% adherent

N=5,078

Depress

% adherent

N=4,025

Hyperlipid

% adherent

N=2,521

Asth/COPD

% adherent

N=916

Diabetes

% adherent

N=521

Osteo

% adherent

N=482

Brand vs. generic

2.82*** (1.86-4.27)

1.61*** (1.34-1.94)

1.56** (1.14-2.13)

3.79*** (2.47-5.81)

3.13** (1.48-6.66)

0.67 (0.37-1.21)

Mean member amount paid per 30 days 0-$5

>$5-$12

>$12-$22

>$22-$50

>$50

Ref 0.92***

(0.79-1.06) 0.53

(0.40-0.69) 0.38

(0.23-0.62) 0.16

(0.06-0.42)

Ref 1.45***

(1.23-1.71) 1.04

(0.85-1.27) 1.14

(0.86-1.51) 0.59

(0.32-1.09)

Ref 0.61***

(0.58-0.78) 0.46

(0.31-0.67) 0.32

(0.21-0.49) 0.22

(0.10-0.47)

Ref 1.52***

0.86-2.68 1.02

0.61-1.7 0.65

0.40-1.08 0.38

0.18-0.80

Ref 2.01***

(1.19-3.41) 0.95

(0.53-1.70) 0.22

(0.08-0.64)

Ref 5.75***

(2.20-15.02) 2.10

(0.88-5.02) 1.24

(0.49-3.08)

C statistic 0.65 0.61 0.69 0.67 0.70 0.74

Odds ratio and 95%CI for odds ratio reported in tableAdjusted for sex, race (white/non-white), age, proportion of adults in living area with high school education, median income of families in the living area. * p<.05 **p<.01 ***p<.001 - p values are associated with entire contrast rather than individual contrasts

Binary drug adherence (MPR >=80%) by drug class, within condition

Condition, Drug class # adherent patients / # patients taking the

medication Unadjusted %

Hypertension*** Calcium channel antagonists Angiotensin II receptor antagonists β-blockers, α/β-blockers Angiotensin converting enzyme inhibitors Antihypertensive combinations (non-diuretic) Antihypertensive combinations (non-diuretic) Diuretics Peripherally acting anti-adrenergic agents

391/477 196/242

1315/1659 777/992 574/734 334/444 574/806

60/86

82.0 81.0 79.3 78.3 78.2 75.2 71.2 69.8

Depression** SNRI1 Tricyclic antidepressants SSRI2 Miscellaneous antidepressants Miscellaneous antianxiety agents Modified cyclic antidepressants

359/506 118/172

1725-2775 323/524

33/63 155/309

71.0 68.6 62.2 61.6 52.4 50.2

Binary drug adherence (MPR >=80%) by drug class, within condition

Condition, Drug class (cont) # adherent patients/ # patients taking the

medication

Unadjusted %

Hyperlipidemia*** HMG-CoA reductase inhibitors Combination antihyperlipidemics Intestinal cholesterol absorption inhibitors Fibric acid derivatives Nicotinic acid derivatives

1841/2311

106/142 67/90

112/165 12/23

79.7 74.7 74.4 67.9 52.2

Asthma/COPD*** Leukotriene modulators Bronchodilators Steroids Adrenergics / combinations Steroid inhalants Nasally administered agents

93/140 34/52 14/37

139/431 23/124 25/223

66.4 65.4 37.8 32.3 18.6 11.2

Binary drug adherence (MPR >=80%) by drug class, within condition

Condition, Drug class (cont) # adherent patients/ # patients taking the

medication

Unadjusted %

Diabetes Thiazolidinediones Sulfonylureas Biguanides Antidiabetic combinations GLP-1 receptor antagonists

41/56

107/180 188/319

8/15 8/20

73.2 59.4 58.9 53.3 40.0

Osteoporosis** Bone density regulators Hormone receptor modulators Calcium

373/478

15/20 11/23

78.0 75.0 47.8

Cancer* Antineoplastic hormonal agents/hormone receptor modulators Antineoplastic agents

117/126

24/30

92.9

80.0

Limitations

Limited population to one diagnosis/medication to identify to evaluate least-confounded population

Small sample size occurred in some cells (across member costs and some disease states)

Generalizability may be limited due to the study population occurring within an integrated health system

Conclusions

Variation in adherence rates by drug class underscores the need to study adherence and outcomes by both disease state and drug class

Future steps include a continuous analysis of adherence to determine changes across the adherence spectrum by disease and drug class

Correlating adherence to clinical outcomes is needed to fully understand the meaning of adherence measures

Questions?

Study Population

MPR

Patient MPR = [(Σ Days Supplied – Days Supply of Last Fill) / (LAST Fill Date – FIRST Fill Date)] * 100

Mean MPR = (Σ Patients’ MPR / Number of patients in the analysis) * 100