Prescription Co-pay Reduction Program for Diabetic Employees
12
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Transcript of Prescription Co-pay Reduction Program for Diabetic Employees
Prescription Co-pay Reduction Programfor Diabetic Employees
Kavita V. Nair, Ph.D.,1 Kerri Miller, Pharm.D.,2 Jinhee Park, Ph.D.,3 Richard R. Allen, Ph.D.,4
Joseph J. Saseen, Pharm.D., F.C.C.P., B.C.P.S.,1 and Vinita Biddle, C.E.B.S.5
Abstract
The objective of this study was to examine the impact of reducing the prescription co-pay for diabetesmedications on pharmacy utilization, medication adherence, medical utilization, and expenditures. The co-payreduction involved placing all diabetic drugs and testing supplies on the lowest co-pay tier for one employergroup. The sample comprised members with diabetes who were both continuously enrolled in the 12-month preperiod and the 2 years following co-pay reduction. Measured outcomes included diabetic prescription utiliza-tion, medication adherence, medical utilization, and expenditures. Generalized estimating equations for re-peated measures were used to estimate differences between the pre period and years 1 and 2, while adjusting forage, sex, and comorbidity risk.
Diabetic prescription utilization and medication adherence increased by approximately 3.0% in year 1 anddropped in year 2. The increases were primarily in brand name diabetes medications, which increased byapproximately 5%, while generic use decreased in both years. Decreases in emergency room visits and hospi-talizations were also observed in both years, followed by a decrease in health care expenditures in year 2.Adherent members experienced greater decreases in emergency room visits following the co-pay reductioncompared to nonadherent members.
After the implementation of a co-pay reduction, a modest increase in adherence and use of diabetes medi-cations was observed. There were some compensatory cost savings for the employer from lower medicalexpenditures in year 1. In addition to financial strategies, additional strategies to reinforce medication adherenceare needed to gain and sustain more meaningful increases in prescription utilization. (Population Health Man-agement 2010;13:235–245)
Introduction
One of the health care issues confronting patients
with diabetes is low adherence to medication use,which is an ongoing and complex phenomenon for patientswith any chronic condition. The rates of nonadherence forpatients with diabetes are high and varied from 36% to 93% inretrospective and prospective studies.3 While nonadherencecontinues to be a problem for payers because of its impact ontotal health care costs, the growing cost of pharmaceuticalshas resulted in various cost-sharing benefit designs directedtoward patients. The more traditional pharmacy benefit de-signs include annual caps on total prescription reimburse-
ment (or coverage); coinsurance, or paying a percentage of thecost of drugs; and fixed co-payments, or paying a fixed fee forthe cost of a drug, which may consist of multiple tiers of fixedco-payments and deductibles that represent a thresholdamount patients must pay before prescription drug coveragetakes effect. The premise of these older cost-sharing policieshas been to shift the financial burden of medications to thepatient to unburden the payer from the cost of more expensivemedications and to steer patients toward making more judi-cious choices in their purchase of essential and necessaryprescriptions.
However, the negative impact of these more traditionalcost-sharing benefit designs on medication adherence and
1School of Pharmacy, University of Colorado Denver, Denver, Colorado.2Pharmaceutical Strategies Group Consultants, Research Triangle Park, North Carolina.3GlaxoSmithKline, Raliagh, North Carolina.4Peak Statistical Services, Evergreen, Colorado.5Division of Human Resources for the State of Colorado, Denver, Colorado.This study was funded by a grant from GlaxoSmithKline.
POPULATION HEALTH MANAGEMENTVolume 13, Number 5, 2010ª Mary Ann Liebert, Inc.DOI: 10.1089/pop.2009.0066
235
the resulting additional use of health care resources havebeen well documented.16 Past research has found that in-creasing cost sharing for patients, for vulnerable populationssuch as the elderly and low-income individuals as well asinsured patients, can result in a reduction in adherence toessential medications and increased utilization of medicalservices such as emergency room visits and hospitaliza-tions.17, 18 Notable among this body of research was thework of RAND researchers, who found that for every 10%increase in cost sharing, prescription drug use decreases by2%–6%, depending on the class of drug and the condition ofthe patient.19 For some chronic conditions, such as conges-tive heart failure, lipid disorders, diabetes, and schizophre-nia, increased cost sharing was associated with increased useof other health care services, offsetting any potential costsavings to payers.
Given the overwhelming evidence about the negativeimpact of traditional cost sharing for prescription medica-tions, payers have turned to newer value-based benefit de-signs (VBBD) that are designed to encourage the use ofmedically necessary medications and services, while dis-couraging the use of nonessential medications and services.Academics have defined VBBD as a ‘‘clinically sensitive ap-proach that is explicitly designed to mitigate the adversehealth consequences of high out-of-pocket expenditures.’’20
In their simplest form, the newer VBBDs provide gradu-ated co-pays or coinsurance structures: low or no co-pays/coinsurance for essential medications and necessary medi-cal services and high co-pays or no coverage for nonessen-tial or less essential medications and unnecessary medicalservices.21
Although theoretically VBBDs should apply to all medicalservices, much of the initial focus has been on newer phar-macy benefit designs that either reduce or eliminate co-paysfor chronic disease states.22 Despite the complexities of apharmacy benefit, prescription-based VBBDs are popularbecause employers believe adherence to medications is in-tegral for the management of chronic disease states.23 Inaddition, the ease of implementing a pharmacy benefitchange is also appealing to an employer. In its simplest form,employers merely have to change a pharmacy benefit riderto reflect the lower co-pays and communicate this change toemployees.
Interest in VBBDs has mostly grown from the efforts of afew implementations dating back to the 1990s. The City ofAsheville in North Carolina launched one of these earlierforms of prescription-based VBBD in 1997.24 In this program,co-pays for diabetes medications and supplies were waivedfor employees of the City of Asheville if they agreed to becounseled by trained pharmacists every 1–3 months on diet,exercise, medication use, and blood sugar testing, and toundergo foot and eye exams. While prescription costs in-creased for the employer, mean medical costs per memberdecreased between $2705 and $6502 in all 5 years after pro-gram implementation, and 53%–75% of employees had im-proved HbA1C levels. Unlike many VBBDs, however, theAsheville program also included other aspects of pharma-ceutical care, including counseling by pharmacists and casemanagement.
The efforts of Pitney Bowes, a national employer thatprovides various postal services, to implement VBBDs havebeen widely publicized. Between 2002 and 2004, Pitney
Bowes lowered prescription co-pays for brand-name medi-cations used to treat diabetes, asthma, and hypertension to aco-insurance rate of 10%, compared to prior rates of 30% and50%.9 For diabetics, nonadherence to insulin therapy de-creased by two thirds, diabetic testing strip use increased by27%, and the use of fixed combination oral diabetic drugsincreased by 13%.25
More recently, evaluations of a pharmacy-based VBBDhave shown modest results. Chernew and colleagues foundthat when co-pays for generic, preferred, and nonpreferredmedications were decreased by 50%, a 3.8%–6.3% increase inmedication adherence for all drug classes examined wasobserved above and beyond active disease management,which was constant.26
Recently, Nair and colleagues examined the impact ofreduced co-pays on adherence in a 3-tier pharmacy benefitplan for diabetes medications and testing supplies.27 Meanadherence levels increased by 7%–8% in year 1 and fellslightly in year 2 compared with the baseline period. Theresearchers also found that those patients who became ad-herent with their diabetes medications after the introductionof the reduced co-pays had consistently lower health carecosts and utilization compared to those patients who con-tinued to be nonadherent. Although the study was one of thefirst to evaluate the comprehensive impact of VBBDs, thesmall sample size warranted further research to validatewhether improving adherence through lower co-pays has ameasurable impact on use of medical services and expendi-tures for payers. The goal of the present study was to con-tinue this validation with a different employer and a largersample size.
We examined the impact of reducing prescription co-paysfor employees and dependents with diabetes in a largeremployer group over a 2-year period, including the impact ofany resulting increased adherence on the use of medicalservices and expenditures.
Methods
The study design involved a pre-post comparison of acohort of continuously enrolled members at baseline andpost-period years 1 and 2.
Demographic description of the employer group
The program was administered by a state employer with27,881 employees who are enrolled with health benefits. Themean age was 45.9 years, with an average length of service of9.4 years and a mean annual salary of $48,932. Among theemployees, 23.9% were 35–45 years old, 34.2% were 45–55years old, and 20.3% were 55–65 years old. The populationwas 49.1% female; 63.9% were white, 17.4% were Hispanic,and 4.1% were African American.
The primary departments represented in the state-basedemployer group were the Department of Corrections (18.4%of all employees), Department of Human Services (16.4%),Department of Transportation (9.3%), and various highereducation institutions (29% of all employees). With regard toemployment types, 26.2% of all employees were in profes-sional services; 19.8% were in law enforcement and protec-tive services; 16.3% were in labor, trades, and crafts; 14.3%were in administrative support; 10.9% were in health care
236 NAIR ET AL.
services; 6.0% were in physical sciences and engineering; and5.6% were in financial services.
Medical and prescription plan features
The employer offered 4 health plans in 2005, all of whichwere preferred provider organization (PPO) plans. One ofthe plans was not offered in the follow-up years of the studyand therefore was excluded from the analyses. The primaryfeatures of these plans, named PPO A, B, and C, are shown inTable 1. In year 1 of the follow-up period, PPO A and B hadno changes in the medical benefit features, while PPO C hada decrease in the annual deductible from $3500 for individ-uals to $3300 and from $7000 for families to $5000 per year.In year 2, only members in PPO C experienced a decrease inthe annual deductible for individuals, from $3300 to $3000per year. Pharmacy benefits were similar for all plans andconsisted of an annual $100 deductible per individual fol-lowed by co-pays of $10 for tier 1 or generics, $25 for tier 2 orpreferred brands, and $50 for tier 3 nonpreferred brands for a30-day retail supply. Prescription co-pays for mail-orderdrugs were $20 for tier 1 drugs for a 90-day mail-ordersupply, $50 for tier 2 drugs, and $100 for tier 3 drugs fol-lowing a $100 per individual deductible. For PPO B and Cplans, self-administered injectables dispensed through apharmacy were available to individuals at a 30% co-pay,which could not exceed $250 for a 30-day supply or $500 fora 90-day supply. For injectables administered in a physician’soffice or outpatient facility, individuals had to pay 30% of thecost of the medication.
Prescription-based VBBD
The program consisted of placing all diabetic drugs andtesting supplies at tier 1 regardless of the brand or genericstatus, so that employees would have access to these drugsand testing supplies for a $10 retail co-pay or a $20 mail-order co-pay after an annual prescription deductible of$100. A letter was sent to all members with diabetes, whowere identified based on either a prescription claim for adiabetic drug or a diagnosis code during the 1-year periodbefore the start of the program, informing them of the re-duced co-pays for brand-name diabetes medications ortesting supplies. No further direct communication aboutthe program was sent to eligible members following theinitial letter. In addition, members had the option of par-ticipating in a diabetes disease management program of-fered by the health plan, which was in place before theintroduction of the prescription-based VBBD. The programwas briefly mentioned in an online newsletter for em-ployees published by the Division of Human Resources, aswell as in bulletins e-mailed to benefit administrators ineach department. Neither of these communications waspromotional in nature.
Sample selection
The sample consisted of members who were continu-ously enrolled with the health plan for all observationperiods. There were 3 observation periods: pre period (orbaseline period): July 1, 2005–June 30, 2006; post periodyear 1: July 1, 2006–June 30, 2007 (referred to as ‘‘year 1’’);post period year 2: July 1, 2007–June 30, 2008 (referred to
as ‘‘year 2’’). Once the continuous enrollment criteria weremet, individuals with diabetes were identified in the preperiod as those who met 1 of the following conditions28: 2outpatient visits with diabetes as the primary or secondaryInternational Classification of Diseases, Ninth Revision (ICD-9)code of 250.xx; 1 emergency room visit with diabetes as theprimary or secondary ICD-9 code; 1 hospitalization withdiabetes as the primary or secondary ICD-9 code; or 2consecutive prescriptions for any diabetes medications.Individuals were excluded who had gestational diabetes,polycystic ovarian syndrome, or chronic renal failure andwho were on dialysis, as well as transplant patients andindividuals with high-cost conditions (eg, cancer, HIV) inthe baseline period.
Pharmacy-based outcome measures
The pharmacy-based measures consisted of annual orannualized measurements per member per year (PMPY) inthe 3 observation periods for: (a) the number of diabetesmedications (any, brand, generic, mail order); (b) the numberof diabetic testing supplies; and (c) medication adherence,defined as the proportion of days covered (PDC) for diabetesmedications (any diabetes medications, oral diabetes medi-cations, or insulin use). Individuals were classified as ad-herent if the PDC was �80% for any diabetes medications,including oral diabetes medications and insulin.29 In-dividuals were classified as adherent or nonadherent in eachperiod separately. Three sets of percent differences weredetermined for all measures: differences between year 1 andthe pre period, year 2 and the pre period, and year 2 and year1, respectively.
Medical utilization–based measures
The medical utilization outcome measures consisted of thenumber of diabetes-related emergency room visits, hospi-talizations, outpatient visits, and laboratory or diagnosticvisits in all 3 observation periods, and the same measures foradherent and nonadherent members in each time period.Percent differences between year 1 and the pre period, year 2and the pre period, and year 2 and year 1 were determinedfor all medical utilization measures for which a diagnosis fordiabetes was present in the primary or secondary ICD-9 di-agnosis position code. In addition, percent differences inmedical utilization of diabetic services between adherent andnonadherent individuals in each time period (baseline, year1, and year 2) were also examined.
Expenditure-based outcome measures
Expenditure-based measures consisted of payer phar-macy expenditures for diabetes medications and testingsupplies, member out-of-pocket costs for diabetes medica-tions and testing supplies (to include co-pays and deduct-ibles), and payer expenditures for diabetic medical servicesfor adherent individuals (those with PDC �80% for anydiabetes medication) and nonadherent individuals (thosewith PDC <80% for any diabetes medication) in each timeperiod separately. In addition, percent differences in all ex-penditure measures between adherent and nonadherent in-dividuals in each time period (baseline, year 1, and year 2)were also examined.
PRESCRIPTION CO-PAY REDUCTION PROGRAM 237
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Covariates
Differences in the outcome measures between each of theobservation periods were adjusted for age, sex, and theRxHCC (prescription drug hierarchical condition category)risk score.30 The RxHCC risk score was developed by theCenters for Medicare and Medicaid Services using a pre-scription drug risk-adjustment model to tailor payments toreflect the health status of plan enrollees. The model usesparticular demographic characteristics and claims informa-tion to predict the following year’s expected costs for anindividual. The RxHCC diagnostic classification groupsmore than 15,000 ICD-9 diagnosis codes into 197 conditionscategories, known as RxCCs, which are then classified intodisease groups.
Statistical analysis
Generalized estimating equations for repeated measureswere used to estimate pairwise differences between the ob-servation periods.31 For count-based variables with <25% ofvalues equal to zero, we assumed a Poisson distribution(numbers of prescriptions, emergency room visits, and hos-pitalizations). For count-based variables with >25% zerovalues, we used a zero-inflated Poisson model (brand orgeneric prescription use, testing supply use, and mail-orderprescription use). Medication adherence was coded as a bi-nary variable (ie, ‘‘yes’’ for adherence of �80% and ‘‘no’’otherwise) and this outcome measure was evaluated usinglogistic regression. Expenditure data were evaluated bycomputing the period-to-period differences within a subject;the differences were approximately normally distributed. Allanalysis was conducted using SAS version 9.1.3 (SAS In-stitute Inc., Cary NC).
Results
A total of 589 individuals were continuously enrolled forall 3 years and met all the inclusion criteria. Their mean agewas 51 years, 43.3% were female, and the mean risk scorewas 1.09 (Table 2). Sixty-one percent of the sample had hy-pertension, 45% had dyslipidemia, and 17% had depression.
Pharmacy utilization
Pharmacy utilization of diabetic drugs and testing sup-plies is shown in Table 3. There was a mean increase of 3%for any diabetic prescription in year 1 and a decrease of�1.2% in year 2 compared to the pre period. There was a 5%increase in brand-name diabetic prescription use in year 1and a 4.4% increase in year 2, compared to the pre period.Generic prescription use saw a decrease of 4.2% in year 1 and11.5% in year 2, compared to the pre period. Mail-orderprescriptions saw increases of 19.3% in year 1 and 17.4% inyear 2, compared to the pre period. There was a decrease inthe mean number of diabetic testing supplies in year 1(-0.8%) and year 2 (-6.6%), compared to the pre period. Amajority of these differences between years 1 and 2, com-pared to the pre period, were statistically significant(P< 0.05).
Medication adherence
Mean levels of medication adherence increased by 3.2%for any diabetes medication in year 1, but only by 1.3% inyear 2 compared to the pre period (Table 4). Mean levels ofmedication adherence increased from 70.82% to 73.11% inyear 1 and dropped to 71.76% in year 2 for all diabetesmedications. Similar trends in mean levels of medicationadherence were seen for users of oral diabetes medications.However, medication adherence was lower for insulin usersin all years (56.1% in the preperiod, 61.4% in year 1, and62.5% in year 2) compared to those taking oral medications.Insulin users saw an increase of 9.4% in year 1 and a slightincrease in year 2 compared to year 1. Only differences ininsulin adherence were statistically significant.
The percent of adherent individuals increased slightly forany diabetes medications in year 1 compared to the pre pe-riod (48.9% vs. 52.4%). Similar increases were observed formembers using oral diabetes medications (51.2% vs. 53.7%),although the increase was greater for insulin users (22% vs.
Table 2. Sample Demographics (n¼ 589)
Variable Mean (SD)
Age 51 (9.30)Risk score 1.09 (0.27)
n (%)Female 255 (43.3)Members with hypertension 358 (60.8)Members with dyslipidemia 265 (45.0)Members with depression 102 (17.3)
Table 3. Adjusted Percent Differences in Per Member Per Year Pharmacy Utilization for Diabetes
Medications and Testing Supplies in All Three Observation Periods
Mean number % Difference
Sample (n¼ 589) Pre period Year 1 Year 2Pre period
vs. year 1Pre period
vs. year 2Year 2 vs.
year 1
Any diabetic prescriptions1 13.21 13.62 13.06 3.0 �1.2% �4.3Brand-name diabetic prescriptions2 6.53 6.86 6.82 5.0* 4.4* �0.6Generic diabetic prescriptions2 6.12 5.87 5.42 �4.2 �11.5* �7.7Mail-order diabetic prescriptions2 0.99 1.18 1.16 19.3* 17.4* �1.6Diabetes testing supplies2 1.84 1.83 1.72 �0.8 �6.6* �5.8
1Estimates based on a Poisson model.2Estimates based on a zero-inflated Poisson model.*P< 0.05.
PRESCRIPTION CO-PAY REDUCTION PROGRAM 239
30.3%). However, with the exception of insulin, the numberof adherent individuals decreased in year 2 compared to thepre period (any diabetes medication was 48.9% vs. 46.6%and oral diabetes medication 51.2% vs. 46.1%). Only a few ofthe differences in years 1 and 2 compared to the pre periodwere statistically significant.
Medical utilization
Mean diabetes-related medical utilization (Table 5)showed a decrease in diabetes-specific office visits in year 1(-11.9%) and year 2 (-5.0%), compared to the pre period.Emergency room visits saw a statistically significant decreasein year 1 (-30.7%) and year 2 (-36.0%), compared to the preperiod. Hospitalizations showed decreases of �52.8% and�12.8%, respectively, in years 1 and 2, compared to the preperiod. Laboratory and diagnostic visits showed a slightincrease of 2.1% in year 1 and a decrease of �1.4% in year 2,compared to the pre period. Only comparisons for officevisits between the pre period and year 1 and comparisons foremergency room visits between the pre period and year 1and the pre period and year 2 were statistically significant.
Expenditures
There was a 61% increase in payer paid pharmacy ex-penditures PMPY for diabetes medications in year 1 and an85% increase in year 2 compared to the pre period (Table 6).These increases were highest for brand-name diabetes med-ication use (66% in year 1 and 87% in year 2, compared to thepre period). There was no increase in expenditures for ge-neric diabetes medications in year 1, compared to the preperiod, but a 62% increase in year 2, compared to the preperiod, despite a decrease in the use of generic prescriptionsin both years. A majority of differences for pharmacy ex-penditures in years 1 and 2, compared to the pre period,were statistically significant.
Member out-of-pocket expenditures (including deductibleamounts) decreased by 36% for all diabetes medications inyear 1 and by 35% in year 2, compared to the pre-period.Large decreases were seen in member out-of-pocket costs forbrand-name diabetes medications (45% in year 1 and year 2,compared to the pre period). There was a 3% increase inmember out-of-pocket expenditures for generic medicationsin year 1 and a 7% increase in year 2, compared to the pre
Table 4. Adjusted Differences in Mean Adherence Levels and the Number of Adherent Individuals
in All Three Observation Periods
Sample (n¼ 589) nPre
period (%)Year1 (%)
Year2 (%)
% Difference(pre periodvs. year 1)
% Difference(pre periodvs. year 2)
% Difference(year 2
vs. year 1)
Mean adherence levels1
Any diabetes medication 487 70.82 73.11 71.76 3.2 1.3 �1.8Oral diabetes medication 406 72.23 74.06 71.50 2.5 �1.0 �3.4Insulin 132 56.10 61.35 62.46 9.4* 11.3* 1.8
Pre periodvs. year 1odds ratio(P value)
Pre periodvs. year 2odds ratio(P value)
Year 2 vs.year 1
odds ratio(P value)
Number of adherent individuals2
Any diabetes medication 487 48.9 52.4 46.6 1.155 0.911 0.79*Oral diabetes medication 406 51.2 53.7 46.1 1.105 0.812 0.735*Insulin 132 22.0 30.3 33.3 1.570* 1.804* 1.149
1Includes members who took prescriptions in all 3 observation periods.2Includes members whose adherence levels were �80% in each observation period.*P< 0.01.
Table 5. Adjusted Percent Differences in Per Member Per Year Medical Utilization for Diabetic Services
in All Three Observation Periods
Sample (n¼ 589) Pre period Year 1 Year 2
% Difference(pre periodvs. year 1)
% Difference(pre periodvs. year 2)
% Difference(year 2 vs. year 1)
Office visits1 2.14 1.91 2.04 �11.9* �5.0 6.1Emergency room visits2 0.11 0.07 0.07 �30.7* �36.0* �7.7Hospitalizations2 0.02 0.01 0.02 �52.8 �12.8 85.0Laboratory/diagnostic visits1 2.01 2.05 1.98 2.1 �1.4 �3.6
1Estimates based on a Poisson model.2Estimates based on a zero-inflated Poisson model.*P< 0.01; Estimates are rounded up to 2 decimal points. Percent differences reflect differences that include all the decimal values.
240 NAIR ET AL.
period. A majority of differences for member out-of-pocketexpenditures in years 1 and 2, compared to the pre periodwere statistically significant.
With regard to medical utilization, there was an 18% in-crease in total medical expenditures for diabetic services inyear 1 and an 18% decrease in year 2, compared to the preperiod, both of which were statistically significant.
Adherent versus nonadherent individuals
Figure 1 shows the mean number of prescriptions betweenadherent and nonadherent individuals for various categories
of adherence ranging from 0% to 100%. In the lower cate-gories of adherence that included members whose PDCranges were 0%–19%, 20%–39%, and 40%–59%, the numberof prescriptions decreased in years 1 and 2 compared to thepre period. Members whose adherence levels were between60% and 79% and between 80% and 100% had a highernumber of prescriptions in years 1 and 2, compared to thepre period.
The difference in medical utilization for office visits,emergency room visits, hospitalizations, and laboratory ser-vices between adherent and nonadherent individuals in all 3time periods PMPY is shown in Table 7. Office visits and
2.39
7.62
10.05
12.75
20.60
1.04
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9.32
12.79
21.16
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Categories of adherence
Mea
n n
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pre
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s
Pre periodYear 1Year 2
FIG. 1. Per member per year pharmacy utilization for diabetes medications in all three observation periods for differentcategories of adherence.
Table 6. Adjusted Differences in Mean Per Member Per Year Pharmacy, Medical Expenditures,
and Member Out-of-Pocket Prescription Costs in All Three Observation Periods
Sample (n¼ 589)Pre
period Year 1 Year 2
% Difference(pre periodvs. year 1)
% Difference(pre period vs.
year 2)
% Difference(year 2 vs.
year 1)
Health plan pharmacy expenditures**All diabetes medications $667 $1074 $1234 61* 85* 24*Brand-name diabetes medications $615 $1020 $1148 66* 87* 21*All generic medications $53 $53 $85 0 62* 62*
Member out-of-pocket expenditures**All diabetes medications $263 $179 $172 �36* �35* 4Brand-name diabetes medications $193 $106 $106 �45* �45* 0Generic diabetes medications $70 $73 $65 3 7 10*
Health plan medical expenditures for diabetes-specific services**Total $447 $568 $390 18* �18* �31*
Statistical tests are based on the analysis of differences between periods for each subject. *P< 0.05. **Expenditures rounded up to thenearest integer.
PRESCRIPTION CO-PAY REDUCTION PROGRAM 241
laboratory services were generally higher for adherentmembers compared to nonadherent members, with the dif-ferences being greater in year 1 (7.0%) and year 2 (15.5%),compared to the pre period (0.4%). Laboratory use showedlittle difference in the pre period (-0.5%), but was higher by10.5% in year 1 and 26.08% in year 2 for adherent members,compared to nonadherent members. Emergency room visitswere lower for adherent members, compared to nonadherentmembers in all 3 years, with the differences being greater inyear 1 (-30.7%) and year 2 (-36.70), compared to the pre pe-riod (-26.20%). Hospitalizations showed mixed results. Theywere lower by �72.8% in the pre period for adherentmembers, compared to nonadherent members, but higher by21.1% in year 1 and lower by �29.60% in year 2. Only dif-ferences between adherent and nonadherent members inyear 2 were statistically significant.
Table 8 shows the difference in payer pharmacy expen-ditures, member out-of-pocket expenditures for medica-tions, and disease-specific medical expenditures betweenadherent and nonadherent individuals in all 3 time periods.Payer pharmacy expenditures services were higher for ad-herent members, compared to nonadherent members in all3 years, with the differences being greater in the pre period(55.57%) and lower in year 1 (47.65%) and year 2 (51.36%).Out-of-pocket expenditures for adherent members werehigher in all 3 periods, compared to the nonadherentmembers, with increases of 49.88% in the pre period,49.82% in year 1, and 52.31% in year 2. Medical expendi-tures were lower for adherent members in all 3 periods,compared to nonadherent members, with the greatest de-creases in the pre period (-78.69%) and year 1 (-45.58%). Amajority of these differences between adherent and non-adherent members for various expenditures were statisti-cally significant.
Discussion
Our study expanded the examination of a prescription-based VBBD design for a more comprehensive set of out-comes than previously included. The present study wasbased on 1 employer group and a sample of employees withdiabetes continuously enrolled for 3 years with reduced co-pays for diabetes medications and testing supplies. Our datarevealed the following key findings.
There were moderate increases in medication utilizationafter the implementation of the program. The increase inadherence levels was modest (less than 5%) following thereduction in co-pays for oral diabetic drugs but higher forinsulin users (9.4%) in year 1.
We offer several explanations for this finding. First, themodest increase we observed in overall adherence levels forall diabetes medications could be due to the high (71%)baseline levels of adherence for this population, which couldreduce the impact of lowering the co-pays. In other words,the population already exhibited higher adherence levels atbaseline and the additional impact of lower co-pays may nothave been able to increase adherence any further. Second, themoderate increases in adherence could be related to themodest reduction in out-of-pocket costs that members ob-served for their diabetes medications. On average, memberssaw a 35% reduction in out-of-pocket costs for their diabetesmedications, which is lower than what has been observed insimilar programs. In other diabetes-related VBBD programs(eg, the MHealthy program for diabetics at the University ofMichigan, the Diabetes Ten City Challenge, the Pitney Bowesmodel) members had either zero co-pays for their diabetesmedications32,33 or faced a 50% reduction in out-of-pocketcosts.25,32 The average co-pay reduction for this populationmay not have been large enough to inspire more significantchanges in adherence and overall utilization of diabetesmedications. Third, the high comorbidity burden of thestudy population (60% with hypertension, 45% with dysli-pidemia, and 17% with depression) may also be a con-founding factor in the results we observed. The complexityof a prescription regimen for members with diabetes who
Table 7. Difference in the Utilization of Key
Medical Services for Adherent Individuals Versus
Nonadherent Individuals in All Three
Observation Periods
NonadherentMembersPMPY
AdherentmembersPMPY % Difference
Office visitsPre period 2.29 2.30 0.40%Year 1 2.03 2.18 7.00%Year 2 2.10 2.49 15.6%*
Emergency room visitsPre period 0.06 0.05 �26.20%Year 1 0.12 0.08 �30.70%Year 2 0.06 0.04 �36.70%*
HospitalizationsPre period 0.05 0.01 �72.80%Year 1 0.02 0.02 0.00%Year 2 0.05 0.03 �29.60%*
Laboratory/diagnosticservices
Pre period 2.11 2.10 �0.50%Year 1 2.08 2.29 10.50%Year 2 1.95 2.45 26.00%*
*P< 0.05; PMPY, per member per year.
Table 8. Difference in the Expenditures
and Member Out-of-Pocket Costs for Adherent
Individuals Versus Nonadherent Individuals
in All Three Observation Periods
NonadherentMembersPMPY
AdherentmembersPMPY % Difference
Health plan pharmacy expendituresPre period $495.00 $1114.00 55.57%*Year 1 $857.00 $1637.00 47.65%*Year 2 $984.00 $2023.00 51.36%*
Member out-of-pocket expendituresPre period $207.00 $413.00 49.88%*Year 1 $138.00 $275.00 49.82%*Year 2 $134.00 $281.00 52.31%*
Medical expendituresPre period $654.00 $366.00 �78.69%*Year 1 $757.00 $520.00 �45.58%*Year 2 $426.00 $417.00 �2.16%
*P< 0.05; PMPY, per member per year.
242 NAIR ET AL.
have multiple comorbidities may partially explain why ourstudy population may have been reluctant to increase theiruptake of diabetes medications, despite the financial incen-tives that were offered. The presence of additional medica-tions and only a 35% reduction in out-of-pocket costs maynot have been sufficient to encourage greater diabetes med-ication use. Finally, our study population was predomi-nantly male (57%) and it is well documented that males withdiabetes and other comorbidities are likely to be less adher-ent to their medications compared to females.34
We also observed that the impact of the co-pay reductionappears to be more pronounced for patients whose adher-ence levels were over 60% at baseline than for patientswho had a lower level of adherence at baseline (PDC <60%).Mail order use also appeared to be substantially impacted,with an approximately 20% increase in utilization, by re-ducing the co-pays in years 1 and 2 compared to the preperiod. Members with diabetes appear to respond better tothe reduction in co-pays for a 90-day supply compared to a30-day supply.
The increase in prescription utilization and adherenceobserved in year 1 of the co-pay reduction program de-creased or reverted to baseline levels in year 2, raisingquestions about the long-term sustainability of lowering co-pays as an effective method to improve adherence rates.However, despite these modest increases, total health carecosts decreased by �18% in year 2. Whether these decreasesin total health care costs can be attributed to lower utilizationof medical services as a result of the co-pay reduction isunclear at this time. It is also possible that regression to themean effects may offer an explanation of why we observed adecrease in utilization, adherence, and total health care costsin year 2 of the post period, compared to year 1. We discussthe potential impact of this effect in greater detail in thelimitations section.
The use of brand-name diabetes medications increasedfollowing the reduction in co-pays, while generic use wasreduced. Out-of-pocket costs for brand-name diabetes med-ications were reduced by �45% for patients. The increase inbrand-name medication use in both years 1 and 2 followingthe co-pay reduction may have been due to the transition bypatients who were treated with generics despite their unmetneeds. It may also have been spurred in part by the intro-duction of newer agents/formulation to the market in 2006and 2007. Another reason for the increases in brand-namemedication use may be due to a ‘‘moral hazard,’’ as patientsdid not bear the same financial burden for brand-namemedications as before the co-pay reduction.35 However, de-termining which of these was the driving force behindthe increased brand name use was beyond the scope of thecurrent study.
Although adherent members had approximately 50%higher prescription use as a result of a 100%–125% decreasein member out-of-pocket expenditures, they had 30%–36%fewer emergency room visits and higher rates of office visitsand laboratory services compared to nonadherent membersin both follow-up time periods, although the differenceswere not statistically significant in year 1. Adherent membersexperienced notably lower medical expenditures in the preperiod and year 1. Our findings corroborate previous re-search that showed that adherent individuals are less ex-pensive for payers and that VBBDs aimed at increasing the
number of adherent individuals will decrease total healthcare expenditures for payers.36 However, it is possible thatthe differences we observed in medical utilization betweenadherent and nonadherent individuals may be a result ofinherent differences between adherent and nonadherentmembers rather than the result of a prescription co-pay re-duction. In other words, adherent individuals are more likelyto manage their diabetes better than nonadherent individu-als, and thereby incur fewer medical services and health careexpenditures than nonadherent individuals. These differ-ences may exist irrespective of the presence of a lower co-payfor diabetes medications.
What lessons were learned from this endeavor? First, therewere modest increases in adherence after the simple co-payreduction. However, the observed impact was not sustain-able in the long term. It is important to note that the pre-scription-based VBBD design we measured was a ‘‘no frills’’approach, with the primary change to diabetes managementbeing the co-pay reduction for tier 2 and tier 3 diabetesmedications. The program was communicated to the mem-bers via a 1-time mailing only. Additional value-based effortsto reinforce the impact of financial incentives with behaviormodification methods and integration with disease man-agement programs are likely needed to yield a more mean-ingful and sustainable change in adherence.
Second, payers need to be encouraged to think differentlyabout return on investment for a prescription-based VBBD.Payers may expect to offset the increased pharmacy costsincurred as a result of lower co-pays with savings on medicalcosts. Our findings show that individuals who are adherentwith their diabetes medications had fewer emergency roomvisits, consumed 50% more diabetes medications, and usedmore office visits and laboratory/diagnostic services after aco-pay reduction was introduced. Therefore, payers must beencouraged to think of return on investment in alternativeterms (eg, fewer sick days taken by employees and improvedwork efficiency) and to find ways to encourage members toimprove their adherence to chronic medications. By gettingmore members to achieve adherence levels of �80%, payersmay realize savings in medical costs over time.
Finally, the employer paid a substantial amount of moneyfor this program. Its prescription costs increased by 62% inyear 1 and by 108% in year 2 compared to the pre period.While a �18% reduction in medical costs for diabetic serviceswas observed in year 2, it was not enough to offset the in-creased pharmacy costs borne by the payer and cannot bedefinitely attributed to the reduction in prescription co-pays.Because the baseline adherence for diabetes medications forthis population was high, it is possible that a more targetedapproach may provide a better return-on-investment forpayers. This can be further supported by the fact that thepatients with a lower level of adherence were less likely to beimpacted by the program. Focusing a co-pay reduction onhigh-risk diabetics or those with multiple comorbid condi-tions may prove to be a greater incentive for these members,thereby increasing the impact of this type of VBBD.
Limitations
Our study had several limitations. First, there was nocontrol group. This would have allowed us to differentiatethe effects of the co-pay reduction from any underlying
PRESCRIPTION CO-PAY REDUCTION PROGRAM 243
trends in prescription use and medication utilization. Wetried to identify a comparison group from the health plan’sother employer groups that had a similar 3-tier pharmacybenefit, type of industry, age, sex, and risk score distribution.However, these efforts did not yield an appropriate com-parison group.
Second, related to our inability to find a control group,pre-post designs can be affected by regression to the mean,which impacts the validity of results. Regression to the meanrefers to the phenomenon in which, without the influence ofan intervention (ie, the co-pay reductions), diabetic memberswith high costs and utilization in the baseline year will tendto use fewer services and thereby have lower expenditures inthe following year (ie, year 1 of post period).37 The conversemay also occur when members with diabetes who use fewerservices in the baseline year may use more services and incurgreater costs in year 1 of the post period. In both instances,costs and use of services could be moving closer to the mean.The use of a control group avoids this phenomenon as twosimilar groups chosen at the same baseline should havesimilar outcomes because they are expected to ‘‘regress’’ in asimilar fashion. In pre-post designs, choosing a longerbaseline period (ie, 2 years or more) could mitigate theseeffects to some extent. A longer time period allows the nat-ural movement of individuals across the range of measure-ment for each outcome measure, allowing a greaterprobability of reaching the mean prior to the start of the postperiod. Our study design used only 1 year for the baselineperiod and, therefore, it is possible that some of the resultswe observed, in particular the reduction in utilization, ad-herence, and total health care costs in year 2, may be influ-enced by regression to the mean.
Our results showed a larger increase in adherence for in-sulin users (9.4%) compared to those members who take oraldiabetes medications. However, our measure of adherencefor insulin use may not be the most reflective of its actualuse. Insulin is dispensed as individual vials or as pens withmultiple doses. The dosing of insulin (from once a day up to4 times a day) can vary for each individual. Because dosinginformation is not present in pharmacy claims data, ourmeasure of the length of time a member had insulin may notaccurately reflect ‘‘adherence’’ with insulin therapy per se.Therefore, the results we observed for insulin users shouldbe interpreted with caution.
Despite the availability of diabetic testing supplies atlower co-pays, our results showed a decrease in the use ofthese agents in both years 1 and 2. The mean number oftesting supplies was less than 2.0 in all time periods, whichcould indicate that members were not buying their testingsupplies through their pharmacy benefit insurance but ratherfrom other sources. We could not confirm these behaviorsand hence were not able to accurately measure the impact ofreducing co-pays on the use of diabetic testing supplies.
A few external factors may have influenced our results.The presence of a disease management program for thesemembers and the $4 prescription programs initiated byWalmart began in September 200638 and may have impactedthe adherence levels we observed in this population, as theprogram included many generic oral diabetes medications.We did not have data on whether members in our samplechose to purchase diabetes medications directly from Wal-mart or other pharmacies for $4 rather than through their
health plan, thereby resulting in lower observed adherencelevels in the health plan data used for this study. We also didnot have information about how many members in ourstudy sample chose to participate in the disease manage-ment program provided by the employer. The presence ofboth these programs may have influenced our results. Asthe popularity of the $4 prescription programs continues, theimpact of this source of prescription medications must beconsidered when making any assessments of a prescription-based VBBD.
We observed small sample sizes for the utilization ofemergency room visits and hospitalizations, which are notcommon medical events (ie, most members do not experi-ence such events). Therefore, changes in emergency roomvisits and hospitalizations should be interpreted with cau-tion as the mean number of annual visits per member wassmall (<0.1) in all years.
We were not able to compare changes in diabetes pre-scription use by tier status in the pharmacy claims. Theidentifiers for tier status (tiers 1–3) were not available in theclaims, and cross-references using the formulary and brand/generic indicator was not conclusive. Thus, we were unable toexamine whether members purchased more expensive brand-name medications that were placed in the highest tier (ie, tier3) before the co-pay reduction was introduced, which couldimply the possibility of moral hazard behavior after the pro-gram was implemented. Similarly, as 30% of our sample haddiagnosis codes for both Type 1 and Type 2 diabetes, theresulting sample sizes after all inclusion criteria were met didnot permit a comparison of these two forms of diabetes.
Finally, the ultimate impact of a prescription-based VBBDfor diabetes is on clinical outcomes. Although we were notable to collect data on clinical markers such as HbA1c levels,examining these outcomes for improvements in mean levelsof HbA1c markers and the number of individuals whoseHbA1c levels improved after the co-pay reductions formedications could provide greater evidence of the positiveimpact of a VBBD.
Conclusions
Implementing reduced co-pays for diabetes medicationsresulted in modest increases in prescription utilization andmedication adherence. The use of brand-name medicationsincreased, while generic use decreased after the introductionof the program. Despite these modest changes in pharmacyutilization, decreases in high-cost medical services such asemergency room visits and hospitalizations were observed.Members who were adherent with their diabetes medica-tions had fewer emergency room visits, consumed 50%more diabetes medications, and used more office visits andlaboratory/diagnostic services after the co-pay reductionwas introduced. Payers may see more gains in long-termmedical savings by supplementing financial incentives withadditional behavior modification methods to see a greaterand more sustainable impact on medication adherence.
Author Disclosure Statement
Drs. Nair, Miller, Park, Allen, Saseen, and Ms. Biddle haveno institutional or commercial affiliations that might pose aconflict of interest.
244 NAIR ET AL.
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Address correspondence to:Kavita V. Nair, Ph.D.
School of ParhmacyUniversity of Colorado Denver
12631 17th Avenue, Box C-238 L-15PO Box 6511
Denver, CO 80045
E-mail: [email protected]
PRESCRIPTION CO-PAY REDUCTION PROGRAM 245
