Post on 04-May-2023
10/28/2019
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Association between Medication Adherence and Healthcare Costs among Patients Receiving the Low‐Income Subsidy
Junling Wang, PhD
Professor, Department of Clinical Pharmacy & Translational Science University of Tennessee College of Pharmacy
Presenter Disclosures
(1) The following personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months:
<Junling Wang, PhD>
< This study was sponsored by the Pharmaceutical Research and Manufacturers of America as a grant to Drs. Junling Wang and Kenneth C. Hohmeier.>
Presenter Disclosures
(2) My presentation will include discussion of “off‐label” use of the following:
<Junling Wang, PhD>
<None.>
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Department of Clinical Pharmacy and Translational Science
Co‐Authors
University of Tennessee College of Pharmacy Yanru Qiao, MS
Kenneth C. Hohmeier, PharmDEdward T. Chiyaka, PhD
Pharmaceutical Research & Manufacturers of AmericaSamantha T. Dougherty, PhD
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• Medications are one of the most cost‐effective interventions used to improve healthcare outcomes.
• Medication adherence helps to bring about treatment benefits for medications, reduce complications from chronic diseases, and lower medical costs.
• Medication non‐adherence could mitigate the effectiveness of medication therapy
– 10% of all hospitalizations, and along with other drug‐related morbidity and mortality, costing the healthcare system $100‐$290 billion per year.
Background
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Background
• Adherence rates vary widely across population categories and disease states.
• Factors associated with adherence include:
–Patient socio‐demographics & health beliefs
–Medication‐related factors
–Healthcare system‐related factors
• Patients of lower socioeconomic backgrounds suffer most acutely from barriers that prevent adherence.
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Background
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• Low‐income subsidy (LIS)
– Established by the Medicare Modernization Act, part of Medicare prescription drug benefit (Part D)
– Limited assets and income below 150% of federal poverty level
• In 2018, more than 43 million Medicare beneficiaries were enrolled in Medicare Part D, and 28% received the LIS.
• LIS enrollees
–More likely to be non‐White, and less educated.
– Higher overall prevalence of mental and physical health conditions.
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Background• Among LIS recipients with multiple chronic conditions, the effect of patients being adherent to all recommended medications is not clear.
• Proportion of days covered (PDC) – measures proportion of days a patient is likely to have taken their medication.
• PDC≥80% indicates that the patient is adherent to medication.
• Due to the heterogeneity of medication effects and patient characteristics, such uniform dichotomies may fail to fully capture the optimum classification of patient adherence level.
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Study Objective
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• Explore the effects of medication adherence on healthcare costs among LIS recipients with:
‒ Diabetes
‒ Hypertension
‒ Heart failure
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Methods
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• Retrospective analysis
–Medicare administrative data from 2012‐2013
– Linked to Area Health Resources Files (AHRF)
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Conceptual Framework: Gelberg‐Andersen Behavioral Model for Vulnerable Populations
Groups Variables
Predisposing Factors
Race and ethnicity, age, gender, % non‐white population, % married‐couple families, per capita income, % people in poverty, % various educational achievements, % eligible for Medicaid, % unemployed, % without health insurance
Enabling Factors Metropolitan statistical area, census regions, health professional shortage area
Need Factors Charlson Comorbidity Index, risk adjustment summary score
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Methods
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• Study Population
– ≥ 65 years old
– Alive during the study
– Continuous Parts A/B/D coverage (to eliminate any coverage gap)
– Full or partial LIS
• Patient cohorts
– 3 cohorts of patients with only 1 disease of interest
– 3 cohorts with various combinations of 2 out of 3 diseases
– 1 cohort with all 3 diseases
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Methods
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• Monthly PDC was used to measure patient adherence
• Based on the cutoff points used by Star Ratings to assign levels of stars to health plans.
• Cost categories (monthly costs): Medicare medical costs (Parts A and B) and total Medicare costs (Parts A, B, D).
Patients with 1 chronic disease Patients with 2 or 3 diseases
8 PDC categories: <25%, 25%‐<50%, 50%‐<75%, 75%‐<80%, 80%‐<85%, 85%‐<90%, 90%‐<95%, ≥95%
PDC≥80% for medications for each disease
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Methods
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• Test for differences
– Cost difference between each individual adherence category and lowest adherence category Potential cost savings
– Tukey’s test was used to compare costs across adherence categories following analysis of variance.
• Multivariate analysis on relationship between adherence and cost
– Linear model with log link and gamma distribution to control for individual and community characteristics.
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Variable Diabetes Hypertension Heart Failure
Number (% of study sample) 49,157 (8.5) 237,856 (40.9) 7,914 (1.4)
Age 76.5 (7.4) 77.8 (8.1) 81.6 (9.0)
Male (number & %) 15,885 (32.3) 63,748 (26.8) 2,547 (32.2)
Race/Ethnicity (number & %)
Non‐Hispanic White 26,989 (54.9) 141,610 (59.5) 5,829 (73.7)
Non‐Hispanic Black 6,689 (13.6) 39,871 (16.8) 886 (11.2)
Hispanic 9,485 (19.3) 31,809 (13.4) 694 (8.8)
% of Non‐White Populationa 27.6 (18.4) 28.72 (17.9) 25.59 (17.8)
% of Married Couple Familiesa 75.2 (7.2) 74.67 (7.2) 75.80 (7.1)
% Eligible for Medicaida 24.1 (9.4) 23.40 (9.0) 23.00 (9.0)
% Unemployed Populationa 8.1 (2.5) 8.0 (2.2) 7.9 (2.2)
% Without Health Insurancea 15.5 (5.2) 15.3 (5.0) 14.9 (4.8)
Sociodemographic characteristics of study cohorts (mean and standard deviation; N=581,145)
a County-level characteristics.
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a County‐level characteristics.
Sociodemographic characteristics of study cohorts (mean and standard
deviation)Variable Diabetes Hypertension Heart Failure
Metropolitan Statistical Area (number & %) 35,494 (72.2) 182,402 (76.7) 5,489 (69.4)
Health Professional Shortage Area (number & %) 45,545 (92.7) 216,745 (91.1) 7,208 (91.1)
Region (number & %)a
Northeast 9,884 (20.1) 47,692 (20.1) 1,608 (20.3)
Midwest 9,566 (19.5) 41,673 (17.5) 1,672 (21.1)
South 17,321 (35.2) 104,738 (44.0) 3,000 (37.9)
West 12,300 (25.0) 43,439 (18.3) 1,625 (20.5)
Other 86 (0.2) 314 (0.1) 9 (0.1)
Charlson Comorbidity Index 2.9 (2.1) 1.7 (1.9) 3.1 (1.9)
Risk Adjustment Summary Score 1.1 (0.7) 1.1 (0.7) 1.7 (0.8)
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Patients with one chronic disease
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3.6%
10.8%
16.2%
5.4%
8.4%
11.5%
17.9%
26.2%
2.7%
7.1%
12.6%
4.9%
7.9%
12.0%
19.6%
33.2%
4.6%
9.3%
14.6%
4.9%
7.3%
11.2%
18.2%
29.8%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
PDC<25% 25%≤PDC<50% 50%≤PDC<75% 75%≤PDC<80% 80%≤PDC<85% 85%≤PDC<90% 90%≤PDC<95% PDC≥95%
Proportion
Proportion of Days Covered (PDC)
Diabetes Hypertension Heart Failure
Although most patients had PDC≥80%, over 25% had PDC<80%
Diabetes Hypertension Heart Failure
36.0% 27.3% 33.5%
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749694 686
622593 583
488a448
876
791831
769733 743
677 670
0
100
200
300
400
500
600
700
800
900
PDC<25% 25%≤PDC<50% 50%≤PDC<75% 75%≤PDC<80% 80%≤PDC<85% 85%≤PDC<90% 90%≤PDC<95% PDC≥95%
Average monthly costs ($)
Proportion of days covered (PDC)
Medicare medical costs Total Medicare costs
a P<0.05 for comparison between a category and its neighbor to the immediate left. Patients with higher adherence had lower costs.
Healthcare costs across adherence categories for patients with diabetes
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0
55 63
127
156a 166a
261a
301a
0
85
45
107
143a 133a
199a 206a
0
50
100
150
200
250
300
PDC<25% 25%≤PDC<50% 50%≤PDC<75% 75%≤PDC<80% 80%≤PDC<85% 85%≤PDC<90% 90%≤PDC<95% PDC≥95%
Average monthly costs ($)
Proportion of days covered (PDC)
Medicare medical costs Total Medicare costs
a P<0.05 for comparison between a category and the lowest adherence category. Total Medicare spending for the most adherent patients was $206 (23.5%) lower than for patients with the lowest adherence.
Difference in costs between a category and the lowest adherence category for patients with diabetes
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Adherence among patients with diabetes & hypertension
15.3%18.7%
6.7%
59.2%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
PDC<80% for both diabetes& hypertension medication
PDC≥80% for hypertension medication only
PDC≥80% for diabetes medication only
PDC≥80% for both diabetes & hypertension medication
Proportion
About 15% of the patients were not adherent to both diabetes and hypertension medication.
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Healthcare costs across adherence categories (patients with diabetes and hypertension)
aP<0.05 for comparison between a category and its neighbor to the immediate left. Patients adherent to medications for both diseases had lower Medicare medical cost and total costs than those adherent to medications for only one disease.
942
846a792a
624a
1,0701,035 1,005
865a
0
200
400
600
800
1000
1200
PDC<80% for both diabetes &hypertension medication
PDC≥80% for hypertension medication only
PDC≥80% for diabetes medication only
PDC≥80% for both diabetes & hypertension medication
Average M
onthly cost ($)
Medicare medical costs Total Medicare costs
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0
96a
150a
318a
0
3565
205a
0
50
100
150
200
250
300
PDC<80% for both diabetes &hypertension medication
PDC≥80% for hypertension medication only
PDC≥80% for diabetes medication only
PDC≥80% for both diabetes & hypertension medication
Average M
onthly cost ($)
Medicare medical costs Total Medicare costs
a P<0.05 for comparison between a category and the lowest adherence category. Total Medicare spending for the most adherent patients was $205 (19.2%) lower than patients with the lowest adherence.
Difference in costs between a category and the lowest adherence category (patients with diabetes & hypertension)
Department of Clinical Pharmacy and Translational Science
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14.4%
8.4%
23.5%
53.7%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
PDC<80% for medicationsfor all three chronic
conditions
PDC≥80% for any one chronic condition
PDC≥80% for medications for any two chronic
conditions
PDC≥80% for medications for all chronic conditions
Proportion
Almost half of the patients with three diseases were non‐adherent to medication for all three diseases (46.3%).
Adherence to medications for patients with three conditions
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2,136
1,827a
1,601a
1,168a
2,3282,138a
1,859a
1,524a
0
500
1,000
1,500
2,000
2,500
PDC<80% for medicationsfor all three chronic
conditions
PDC≥80% for any one chronic condition
PDC≥80% for medications for any two chronic
conditions
PDC≥80% for medications for all chronic conditions
Average M
onthly cost ($)
Medicare medical costs Total Medicare costs
Healthcare costs across adherence categories
a P<0.05 for comparison between a category and its neighbor to the immediate left. Patients non‐adherent to any medications had total costs 1.5 times that of patients adherent to all medications ($2,328 vs. $1,524; P<0.0001).
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0
309a
535a
968a
0
190a
469a
804a
‐10
90
190
290
390
490
590
690
790
890
990
PDC<80% for medicationsfor all three chronic
conditions
PDC≥80% for any one chronic condition
PDC≥80% for medications for any two chronic
conditions
PDC≥80% for medications for all chronic conditions
Average M
onthly cost ($)
Medicare medical costs Total Medicare costs
a P<0.05 for comparison between a category and the lowest adherence category.
Difference in costs between a category and the lowest adherence category
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Medical Costs Total Costs
Ratio 95% Confidence Interval Ratio 95% Confidence Interval
Patients with Diabetes
25%≤PDC<50% 1.02 0.91 – 1.15 1.04 0.94 – 1.14
50%≤PDC<75% 1.02 0.91 – 1.15 1.06 0.97 – 1.17
75%≤PDC<80% 0.95 0.83 – 1.09 1.02 0.91 – 1.14
80%≤PDC<85% 0.98 0.86 – 1.11 1.05 0.95 – 1.16
85%≤PDC<90% 0.98 0.87 – 1.11 1.07 0.97 – 1.18
90%≤PDC<95% 0.80 0.71 – 0.90 0.95 0.86 – 1.04
PDC≥95% 0.75 0.61 – 0.84 0.96 0.88 – 1.05
Patients with Heart Failure
25%≤PDC<50% 0.87 0.71 – 1.07 0.89 0.74 – 1.07
50%≤PDC<75% 0.73 0.60 – 0.89 0.76 0.64 – 0.91
80%≤PDC<85% 0.69 0.55 – 0.85 0.75 0.62 – 0.91
85%≤PDC<90% 0.58 0.47 – 0.71 0.65 0.54 – 0.78
90%≤PDC<95% 0.50 0.41 – 0.600.57 0.49 – 0.68
PDC≥95% 0.43 0.36 – 0.510.52 0.45 – 0.62
Effects of medication adherence on healthcare costs among Medicare beneficiaries in adjusted analysis
(PDC<25% as reference)
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Medical Costs Total Costs
Ratio 95% Confidence Interval Ratio 95% Confidence
Interval
Patients with Diabetes and Hypertension
PDC<80% for Medications for Both Diseases ‐ ‐ ‐ ‐
PDC≥80% for Hypertension Medications Only 0.93 0.90 – 0.96 1.01 0.98 – 1.03
PDC≥80% for Diabetes Medications Only 0.91 0.87 – 0.95 1.01 0.97 – 1.05
PDC≥80% for Medications for Both Diseases 0.77 0.75 – 0.79 0.92 0.90 – 0.94
Patients with Diabetes, Hypertension and Heart Failure
PDC<80% for All Medications ‐ ‐ ‐ ‐
PDC≥80% for Medications for One Disease 0.88 0.82 – 0.95 0.95 0.89 – 1.01
PDC≥80% for Medications for Two Diseases 0.83 0.79 – 0.88 0.88 0.83 – 0.92
PDC≥80% for All Three Diseases 0.67 0.64 – 0.71 0.78 0.75 – 0.82
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Effects of medication adherence on healthcare costs among Medicare beneficiaries based on adjusted regression model
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Results
• Most adherent patients with diabetes & heart failure had 25% & 57%, respectively, lower Medicare medical costs compared with the lowest adherent patients.
• Patients adherent to medications for both diseases had total Medicare costs 23% lower than those adherent to medications for neither disease.
• Medicare medical costs for patients adherent to medications for all three diseases were 33% lower compared to patients non‐adherent to medications for any of the three diseases.
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Study Limitations
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• Additional sociodemographic/clinical information not available.
• Medication adherence may be over‐ or underestimated using claims.
• One cannot draw causal conclusions regarding the relationship between adherence and cost savings because this is an observational study.
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Conclusion
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• A large portion of the LIS population are not adherent to prescribed medications.
• Higher adherence is associated with significant economic benefits.
• Cost savings can be achieved with even moderate increase in adherence.
• “Super‐adherent” patients (PDC≥95%) may incur the highest cost savings.
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Conclusion
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• Prime areas for future research:
–New initiatives to target incremental improvements from patient’s adherence baseline.
– Roles of other interventions in improving medication adherence among the LIS population, particularly among those with multiple chronic conditions.
– The causal relationship between adherence and healthcare costs.
• Strategies to improve adherence in this population are promising for controlling healthcare costs.
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Acknowledgements
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• This study was supported by Pharmaceutical Research & Manufacturers of America.
• We would like to acknowledge the assistance from Jenny Lee, Laura Meyer, Jason Zeng, Michael Tran, Anoop Pravin Kotian, David Q. Brannon II, Damien Stevenson, and Lorraine Todor, all PharmD students at the University of Tennessee College of Pharmacy.
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References
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• Congressional Budget Office. Offsetting effects of prescription drug use on Medicare’s spending for medical services. Available at: https://www.cbo.gov/publication/43741.
• Goldman L, Epstein AM. Improving adherence ‐money isn't the only thing. N Engl J Med 2011;365:2131‐3.
• Research Data Assistance Center. Data File Search. Available at: http://www.resdac.org/cms‐data.
• Health Resources and Services Administration (HRSA). Area Health Resources Files. Available at: https://data.hrsa.gov/topics/health‐workforce/ahrf.
• Gelberg L, Andersen RM, Leake BD. The behavioral model for vulnerable populations: application to medical care use and outcomes for homeless people. Health Serv Res 2000;34(6):1273‐302.
• Pharmacy Quality Alliance (PQA). Available at: https://www.pqaalliance.org/.
• Centers for Medicare & Medicaid Services. Part C and D Performance Data. Available at: https://www.cms.gov/medicare/prescription‐drug‐coverage/prescriptiondrugcovgenin/performancedata.html.