Joshua N. Liberman, PhD

To quantify the burden of illness of chronic hepatitis C virus (HCV) infection and estimate the impact of interferon-free direct-acting antiviral treatment on healthcare costs in Medicaid.

Medicaid claims data from 2012 for nonelderly adult enrollees with chronic HCV in 16 states were used to estimate

the burden of HCV in Medicaid. Annual measures of health services utilization and cost for patients with HCV were compared with a control group of patients without HCV exactly matched on a robust set of individual characteristics and stratified according to liver disease severity, Medicaid eligibility group, and plan type. Subsequently, HCV burden-of-illness estimates were used in a separate analysis of Medicaid State Drug Utilization Data on interferon-free drug utilization and expenditures to estimate the annual and cumulative impact of these curative medications on national Medicaid costs from 2013 through 2022.

 Annual per-person Medicaid healthcare costs attributed to HCV infection were estimated to range from $10,561 for noncirrhotic disabled adults to $46,263 for nondisabled adults with end-stage liver disease. The costs were due mainly to inpatient hospitalizations and outpatient hospital visits, prescription drug utilization, outpatient physician’s office/clinic visits, and laboratory tests. By 2014, the first full year following the approval of interferon-free treatment, an estimated 12,175 adults with HCV were cured in Medicaid nationwide, each avoiding an estimated $15,907 per year in healthcare costs associated with the disease. As more patients in Medicaid are treated and net savings continue to grow year after year—due to recurring avoidance of health services use and declining drug prices&mdash;total cumulative treatment costs since 2013 are expected to be fully offset by total cumulative healthcare expenditure reductions by the end of 2019. By 2022, the recurrent annual avoidance of healthcare costs will have delivered an estimated $12 billion in total cumulative savings to Medicaid, net of DAA drug expenditures.

 The introduction of interferon-free HCV treatments enables the avoidance of significant healthcare costs previously associated with treating the disease year after year, producing annual cumulative Medicaid savings beginning in 2019. A main finding from this study is that the cost of a complete DAA treatment course, at 2018 estimated net prices, can be expected to be fully offset by healthcare cost savings after only 16 months, on average, on a per-person basis. Given the tremendous value provided by these curative drugs, Medicaid policies aimed toward restricting access to these treatments based on disease severity or other requirements would be shortsighted.

More than 2 million people are currently infected with the hepatitis C virus (HCV) in the United States.

 For many, an HCV infection is an asymptomatic condition that often goes undiagnosed. If untreated, the virus increases an individual’s risk of life-threatening conditions such as cirrhosis, hepatocellular carcinoma, and liver failure.

 As such, HCV imposes substantial costs on society. Patients who are infected with HCV have poorer quality of life and decreased productivity,

 Moreover, healthcare needs increase dramatically as HCV disease progresses.

Until 2011, the primary treatment for chronic HCV infection was a combination of pegylated interferon and ribavirin. With this regimen, about 50% of patients were able to achieve “cure,” defined by a sustained virologic response (SVR)—no measurable virus in the blood&mdash;12 or 24 weeks after the end of treatment.

 The duration of treatment was long (up to 48 weeks) and associated with high discontinuation rates.

 In May 2011, the FDA approved the first agent in a new therapeutic class known as direct-acting antivirals (DAAs). Unlike peginterferon and ribavirin, DAAs interfere with the growth and replication cycles of HCV itself.

 DAAs were initially used in combination with peginterferon and ribavirin; however, since late 2013, interferon-free DAA regimens have been available. Clinical evidence indicates that these interferon-free DAA regimens are well tolerated and effective, achieving SVR in 92% or more of patients, although outcomes vary by genotype, prior treatment, and disease severity.

DAAs were initially more expensive than older treatment options; however, these costs have declined substantially over time with increased competition. Indeed, within a year of the approval of the first interferon-free regimen, additional interferon-free DAAs entered the market, which enabled payers to negotiate large discounts and/or rebates in exchange for favorable formulary placement. Largely because of this increased competition, negotiated supplemental rebates have risen from about 22% off list price in 2014 to as high as 60% in ensuing years.

 Moreover, list prices for DAAs themselves have declined drastically, from nearly $100,000 per treatment course in 2014 to as low as $24,000 per treatment course today.

Despite a reduction in the costs of DAAs, state Medicaid programs have expressed concerns over allowing universal access to these new therapies because of the unique dual challenge of having both the financial constraints of annual public budgets and high numbers of HCV-infected enrollees.

 Consequently, many Medicaid programs have chosen to restrict coverage of DAAs, based on parameters of fibrosis stage (ie, degree of liver damage), abstinence from alcohol and substance use, and prescriber type.

 From an economic efficiency standpoint, the appropriateness of these access restrictions depends not only on the costs of DAAs but also on the benefits derived from their use.

Several economic evaluations of DAAs have been published.

 Moreover, burden-of-illness studies have been conducted on populations of patients with HCV in commercial insurance,

 However, comparable research in Medicaid is scant, with only 1 published study on a single state’s experience.

 The present study estimates the healthcare costs associated with chronic HCV infection in Medicaid using detailed data from 16 states and more than 5 million Medicaid enrollees, paired with actual interferon-free DAA utilization and expenditure data to measure the annual and cumulative impact of these curative medications on Medicaid costs from 2013 through 2022.

This study was conducted in 2 separate stages using 2 distinct data sources to estimate Medicaid costs attributable to HCV infection and to Medicaid savings resulting from curative DAA treatment. These sources were Medicaid Analytic eXtract (MAX) files, which were used to quantify the per-patient cost burden of HCV infection, and Medicaid State Drug Utilization Data (SDUD) files, which were used to project the number of Medicaid beneficiaries cured of HCV following the release of interferon-free DAAs and to simulate the expected savings associated with these curative therapies.

MAX files were obtained under a Data Use Agreement from CMS with institutional review board (IRB) approval and oversight (Advarra IRB; Columbia, MD). Created primarily to support research and policy analysis, MAX data include pharmacy and medical claims and encounter records, as well as eligibility information, on all individuals enrolled in Medicaid.

 MAX files for the year 2012 from 16 states—Alabama, California, Connecticut, Florida, Illinois, Indiana, Louisiana, Michigan, New Hampshire, New Mexico, New York, Ohio, Oregon, Pennsylvania, Virginia, and Washington&mdash;were utilized for this study. Participants were aged between 18 and 64 years as of December 31, 2012, with unrestricted Medicaid benefits and without an annual gap in coverage of more than 30 days. After these criteria were imposed, 5,210,249 adult Medicaid recipients remained. Participants were then segmented according to their Medicaid basis of eligibility: either adults who were blind/disabled (hereafter “disabled”) or adults who were other nonblind/disabled (hereafter “nondisabled”). They were further stratified by plan type: either fee-for-service (FFS) or managed care (see 

The SDUD files contain precise information on the counts and reimbursement amounts for all prescriptions dispensed in Medicaid nationwide.

 Specifically, data were obtained on all interferon-free DAA (hereafter just “DAA”) fills from the fourth quarter of 2013 through the second quarter of 2018. Package inserts for each DAA product, which specify recommended dosage amounts and treatment durations by cirrhosis status and treatment naïvety, were used to determine the average number of prescriptions filled per treated patient with HCV infection and were applied to the SDUD to calculate the annual number of patients treated with DAAs. Subsequently, expected DAA-specific SVR rates were used to determine the estimated annual number of patients cured of the virus, accounting for treatment nonadherence. See 

MAX claims and encounter data were analyzed to estimate Medicaid costs attributable to an HCV diagnosis in 2012. Patients with chronic HCV were identified using an algorithm employed by Gordon et al.

 Individuals were required to have at least 1 medical claim with a diagnosis of chronic HCV; at least 2 medical claims on different dates for unspecified HCV or HCV carrier; or 2 or more medical claims at least 6 months apart for unspecified HCV, HCV carrier, or acute HCV. Records for HCV testing were excluded from this case-finding definition to avoid basing HCV status on rule-out procedures. Using these criteria, a total of 72,109 individuals were classified as having chronic HCV during the study period. Patients were then assigned to 1 of 3 liver disease severity cohorts: noncirrhotic, cirrhosis, or end-stage liver disease (ESLD), based on the work of Gordon et al.

Patients with chronic HCV were exact-matched 1:1 to control individuals (those without evidence of HCV) on the following demographic and plan characteristics: basis of eligibility, age, gender, race, ethnicity, state of residence, plan type, any months enrolled in primary care case management, and any months receiving cash maintenance assistance. Individuals were also exact-matched on the presence of diagnoses for asymptomatic HIV or symptomatic HIV/AIDS because these often cooccur with, but are not caused by, HCV infection. Because patients with HCV were exactly matched to patients without HCV, no statistically significant differences in mean values of any of the matching variables were present. Additional details are provided in the 

Five count measures of annual health services utilization (HSU) were constructed from the claims data: inpatient hospitalizations, hospital days, emergency department (ED) visits, physician’s office/clinic visits, and prescription drug fills (adjusted to 30-day equivalents). For individuals enrolled in FFS plans, healthcare cost variables were generated using the amounts paid by Medicaid. Cost measures were not created for managed care plan enrollees because their health services are routinely covered on a capitated basis. In the process of building the MAX files, CMS classifies Medicaid expenditures into 33 specific types of service. For the present analysis, a subset of 14 of these were retained; the remaining 19, which contained little to no spending, were summed to form an “other” category. Costs were aggregated into drug and nondrug subtotals, as well as total healthcare costs. Because HCV prescription drug costs were expected to be a significant part of the burden of illness in 2012, spending on peginterferon and ribavirin—and the proportion of chronic HCV patients treated with this regimen&mdash;was measured and reported separately. The costs associated with the first 2 DAAs on the market (boceprevir and telaprevir), which were used concomitantly with peginterferon and ribavirin in 2012, were itemized.

Differences in mean values for the HSU and cost variables were tested between the chronic HCV and control groups, as well as across liver disease severity cohorts using the nonparametric Kruskal-Wallis equality of populations test.

 All analyses were conducted using Stata/MP version 15.1 (StataCorp LP; College Station, TX).

Impact of DAA Use on Healthcare Costs Simulation

The impact of DAA utilization on overall healthcare costs in Medicaid from 2013 through 2022 was projected by combining the results from the burden-of-illness analysis with DAA costs and utilization data from the SDUD files.

Patients with HCV who were cured of the disease were expected to have HSU similar to that of otherwise comparable individuals without the infection. Specifically, it was assumed that 90% of the estimated average burden of illness would be eliminated by the cure. The remaining 10% of HCV costs would likely be more than sufficient to cover the recommended posttreatment monitoring of some individuals cured of the infection, which may include HCV testing, ultrasound examination, and endoscopy.

 Patients were classified as cured based on DAA product-specific expected SVR rates, assuming a 90% medication adherence rate.

The total cost of DAA treatment equaled total annual reimbursements (derived from the SDUD) minus expected rebates. Estimated rebates took into account

the federally mandated Medicaid Drug Rebate,

 any state-negotiated supplemental rebates, and competition from new products, which together produced a range of 23.1% to 59.5%. Total DAA expenditures (net of rebates) were subtracted from total avoided healthcare costs due to curing of HCV infection to yield the net financial impact of DAA use on Medicaid costs, derived annually and cumulatively from 2013 through 2022. Projected costs for the remainder of 2018 through 2022 assumed that DAA prices and utilization rates will not change from the levels exhibited in the first half of 2018. All costs were inflated to 2017 dollars using the Consumer Price Index for Medical Care

Based on the sample selection process, the implied prevalence of diagnosed chronic HCV infection was 1.4% among nonelderly adults in Medicaid. This rate was substantially higher among disabled enrollees (3.0%) relative to the cohort of nondisabled enrollees (0.6%). In comparison with a recent estimate of HCV prevalence in the entire adult US population of 1.0%, the present results reflect a somewhat greater overall proportion of infected individuals in Medicaid.

 Descriptive statistics for all variables employed in the matching process are provided in 

, 71.6% of the disabled cohort and 86.8% of the nondisabled cohort were classified as having noncirrhotic liver disease. Furthermore, disabled patients with chronic HCV had higher percentages of both cirrhosis (8.8% vs 4.8%) and ESLD (19.6% vs 8.4%) than nondisabled patients with chronic HCV. Among both eligibility groups, these percentages varied only slightly between FFS and managed care Medicaid plans.

Regardless of insurance plan type, severity of liver disease, or basis of Medicaid eligibility, individuals with chronic HCV infection had significantly (

<.001) greater use of hospitals, physicians, EDs, and prescription drugs (Tables 

). For example, patients with chronic HCV averaged at least 1 additional hospitalization and 3 to 5 more inpatient hospital days annually compared with Medicaid enrollees without the disease. Although HSU did not radically differ between the noncirrhotic and cirrhotic cohorts, individuals with ESLD had 2 to 3 times more hospitalizations and twice as many ED visits compared with patients with less severe disease (see the 

Higher rates of HSU translated into significantly (

). Mean annual total costs were $53,159 per disabled patient with chronic HCV and $35,280 for their controls without the disease, for a difference of $17,879. Nearly two-thirds of this difference was attributable to inpatient hospitalizations ($11,142). Drug costs were greater by $5370, of which $1849 (34.4%) was for boceprevir and telaprevir and $1237 (23.0%) was for peginterferon and ribavirin, the older treatments supplanted by interferon-free DAAs. Chronic HCV infection was also associated with higher costs for physician visits ($1203), outpatient hospital visits ($1146), laboratory and x-ray services ($810), clinic visits ($589), psychiatric services ($365), and transportation services ($313). Across liver disease severity cohorts, total healthcare costs were similar for patients with noncirrhotic and cirrhotic disease; however, costs were 69.6% higher for those with ESLD.

The nondisabled cohort had lower cost levels than the disabled cohort, but the incremental effect of chronic HCV was comparable in magnitude and significance (

<.001). For example, mean total healthcare costs were $26,788 for patients with chronic HCV versus $9610 for the control group; this difference is $17,178, strikingly similar to the $17,789 estimate derived for the disabled cohort (

). Inpatient services accounted for just over one-third of this amount ($6263). Prescription drug spending was higher by $6658, of which $3177 was for boceprevir and telaprevir and $2265 was for the peginterferon and ribavirin treatment. Moreover, expenditures were greater for psychiatric services ($1242), outpatient hospital visits ($732), clinic visits ($726), laboratory and x-ray services ($697), and physician visits ($437). Total healthcare costs rose dramatically with liver disease severity, the most pronounced increase being for inpatient costs.

Simulated Impact of DAA Use on Healthcare Costs

The results of an analysis of the impact of the use of DAAs on healthcare costs in Medicaid revealed that in 2014, the first complete year following the release of interferon-free DAAs, 12,175 individuals were estimated to have been cured of HCV (see 

). Treatment rates increased over time, such that an estimated 157,519 individuals had been cured by the end of 2018. By the end of 2022, 10 years following the introduction of DAAs, we estimate that HCV will have been eliminated in approximately 331,967 Medicaid enrollees. On average, curing a patient with HCV saves an estimated $15,907 per year in healthcare costs associated with the disease (ie, an HCV burden-of-illness estimate of $17,674 multiplied by the 90% assumed reduction in disease-related spending). Importantly, these spending reductions persist every year post cure. In aggregate, we estimate that the total annual healthcare cost savings associated with alleviated HCV burden were $2.5 billion in 2018 and are expected to reach $5.3 billion in 2022.

To calculate the net impact of DAA use on healthcare spending in Medicaid, the costs of DAAs themselves were subtracted from the estimated savings in reduced HCV burden. As previously discussed, per-user DAA costs have steadily decreased since 2015 as multiple DAAs have entered the marketplace. For the Medicaid program, total estimated annual postrebate DAA costs peaked in 2015 at $2.1 billion and declined to less than $1 billion in 2018. In the years immediately following the approval of interferon-free DAA regimens (2013-2016), annual DAA costs exceeded annual savings from reduced HCV burden. However, in 2017 and beyond, the annual healthcare cost offsets generated by curing HCV in Medicaid patients eclipsed DAA costs. By 2018, the expected savings in annual healthcare expenditures exceeded the costs of DAAs by $1.5 billion, and this net impact is expected to reach more than $4.3 billion by 2022.

 depicts the cumulative impact of DAAs since their debut in 2013. Although accrued spending on DAAs was higher than the savings from reduced HCV burden between 2013 and 2018, beginning in 2019, Medicaid will have fully recouped all its investment in these HCV cures. The cumulative impact of DAA use in Medicaid due to total healthcare expenditure reductions, net of cumulative DAA costs since 2013, is expected to grow from $1.1 billion at the end of the 2019 to more than $12 billion after 2022—just a decade after the debut of interferon-free DAAs. These financial savings will have been generated through the estimated avoidance of 1.5 million hospitalizations, 2.7 million ED visits, and 16.6 million prescription drug fills. (See the 

The objectives of this study were to estimate the burden of HCV and quantify the impact of DAA use on healthcare costs in Medicaid. Few investigators have evaluated these specific topics using real-world evidence. Medicaid claims and DAA utilization data were employed to address this gap in the extant literature. Annual healthcare costs due to chronic HCV infection were estimated at $17,879 for the disabled cohort and $17,178 for the nondisabled cohort. The burden of illness increased with liver disease severity, from a low of $10,561 for noncirrhotic disabled individuals to a high of $46,263 for nondisabled individuals with ESLD. Among the disabled patients, inpatient hospitalizations accounted for nearly two-thirds of the costs of chronic HCV, yet they accounted for only one-third of the costs among nondisabled patients. Prescription drug costs were also substantially higher for patients with chronic HCV, the majority of which were attributed to older HCV treatment regimens.

In a privately insured cohort, McAdam-Marx et al

 estimated the per-person per-year incremental impact of chronic HCV to be $9681 in 2009 ($12,251 inflated to 2017 dollars).

 This estimate is about 30% lower than the $17,178 and $17,789 figures reported herein. Using the same underlying commercial claims database, Gordon et al

 calculated the average annual total healthcare costs for a patient with HCV to be $24,176 in 2010 ($30,595 in 2017 dollars),

 also about 30% lower than the blended (disabled and nondisabled adults) average of $45,347 derived in the present analysis. Gordon et al also concluded that individuals with HCV and cirrhosis had total healthcare costs that were about 30% greater than those of patients with HCV who were noncirrhotic, and those with ESLD had expenditures that were 2.6 times that of cirrhotic patients.

 Considered alongside these 2 published studies, the current findings suggest that the burden of illness of chronic HCV may be greater among patients with Medicaid compared with those with employer-sponsored or other commercial health insurance.

With both higher per-patient HCV burden and higher HCV prevalence rates, Medicaid program directors should be keenly interested in understanding the financial impact of DAA use. The cure rates offered by highly effective DAAs present the rare opportunity to substantially and permanently reduce overall healthcare costs. Findings from this study indicate that the cost of DAA treatment, at 2018 estimated net prices, can be expected to be fully offset by healthcare cost savings after only 16 months, on average, on a per-person basis. These savings are realized in several ways. First, patients who are cured of HCV require less medical care. The current results demonstrate that individuals who are HCV-free have fewer hospitalizations, ED visits, laboratory tests, and physician encounters. Importantly, these reductions in HSU and costs are not onetime events but instead occur annually for individuals who are HCV-free. Second, prior to the introduction of DAAs, the most common treatment for HCV infection involved interferon, which is associated with significant costs and harmful adverse effects. The morbidity issues and financial expenditures associated with older ineffective regimens can be avoided entirely. Third, costs for patients with HCV who are treated with DAAs are declining over time because of increased competition within the therapeutic class, which has led to estimated rebates as high as 60%.

 This competitive landscape has also resulted in a decline in list prices, which have fallen by more than 70% since the launch of the first interferon-free DAAs.

A key finding of this study is that, since 2017, annual Medicaid healthcare savings for patients cured of HCV have exceeded DAA treatment costs. We estimate annual savings of $1.5 billion resulting from curative treatment; that figure is expected to grow to more than $4.3 billion in 2022. Thus, on a cumulative basis, Medicaid will have fully recouped all its investment in these HCV cures by mid-2019 with cumulative savings of $1.1 billion, growing to more than $12 billion after 2022, just a decade after the debut of interferon-free HCV drugs. Improvements in patient quality of life and enhanced productivity can also be expected to accompany these healthcare cost savings.

This study is not without limitations. First, despite the large sample size, Medicaid claims data used to estimate burden of HCV on all 50 states were not received. Therefore, results might not be generalizable to the entire adult Medicaid population. Second, the control group was constructed by matching on demographic and plan characteristics, as well as on HIV/AIDS status; positive HIV/AIDS status is a high-cost comorbidity that is not caused by, but is otherwise correlated with, HCV infection. The omission of control variables for other conditions could give rise to biased estimates if they are correlated with HCV, but inclusion of them could also lead to bias if they are causally linked to HCV.

 For example, injection drug use—one cause of infection&mdash;may persist post HCV cure. In such cases, the HSU and costs associated with injection drug use would not be averted by DAAs. Without a reliable claims-based algorithm for identifying persons who inject drugs, this potential confounding remains a limitation of the present study. Third, the construction of chronic HCV and liver severity cohorts was based on diagnosis and procedure codes from claims data and encounter records. Although this case-finding definition was highly detailed and had been published previously,

 the possibility for misclassification remains. More recent work by Gordon et al

 demonstrates the limitations of relying on claims data alone to define levels of liver disease severity. It is also worth noting that since HCV infection often goes undiagnosed, the control group may contain individuals who are infected with HCV, which would result in downward-biased burden-of-illness estimates.

Additionally, the projected savings to Medicaid are calculated based on DAA spending and utilization from 2013 to 2018; however, the burden of illness of HCV, used to approximate cost savings following cure, is estimated using 2012 claims data. It is possible that patterns of healthcare spending and utilization have evolved since 2012. Similarly, the distribution of liver disease severity among individuals infected with HCV may be changing over time, particularly since interferon-free DAAs were initially focused on patients with cirrhosis. Finally, although the impact of DAA use was assessed from the perspective of Medicaid, it is possible, or even probable, that much of the healthcare cost savings resulting from DAAs may be enjoyed by other payers—most notably Medicare, because of the aging of the population infected with HCV.

Given the considerable burden of HCV in Medicaid and the tremendous value delivered by DAAs, Medicaid policies that restrict access to them—such as requirements for liver biopsy, advanced disease stage, sobriety, and specialist prescribers&mdash;would seem to be shortsighted. Although many barriers to treatment remain, positive efforts to improve access are under way. A 2017 report on the status of access to DAAs in Medicaid found that many states have decreased restrictions based on severity of liver damage, and fewer states require prescriptions by specialists relative to policies in place in 2014. However, the report also found that more states have implemented sobriety requirements.

 In recognition of the findings presented herein, the elimination of access restrictions on interferon-free DAAs for patients with HCV would not only drive down prevalence of the disease and associated healthcare costs but also produce substantial savings for state Medicaid programs.&ensp;

 Financial support for this work was provided by the Pharmaceutical Research and Manufacturers of America (PhRMA).

 Dr Roebuck is owner of RxEconomics, LLC, a health economics consultancy, which received funding from PhRMA for this study. Dr Liberman reports no potential conflicts of interest.

Concept and design (MCR); Acquisition of data (MCR); Analysis and interpretation of data (MCR, JNL); Drafting of manuscript (MCR, JNL); Critical revision of manuscript for important intellectual content (MCR, JNL); Statistical analysis (MCR); Obtaining funding (MCR); Administrative, technical, or logistical support (MCR); and Supervision (MCR).

M. Christopher Roebuck, PhD, President & CEO; RxEconomics, LLC, 11350 McCormick Rd, EPII Ste 705; Hunt Valley, MD 21031. Email: 

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Articles

Assessing the Burden of Illness of Chronic Hepatitis C and the Impact of Direct-Acting Antiviral Use on Healthcare Costs in Medicaid

 To estimate cost savings associated with ProvenHealth Navigator (PHN), which is an advanced model of patient-centered medical homes (PCMHs) developed by Geisinger Health System, and determine whether those savings increase over time.

A retrospective claims data analysis of 43 primary care clinics that were converted into PHN sites between 2006 and 2010. The study population included Geisinger Health Plan’s Medicare Advantage plan enrollees who were 65 years or older treated in these clinics (26,303 unique members).

Two patient-level multivariate regression models (with and without interaction effects between prescription drug coverage and PHN exposure) with member fixed effects were used to estimate the effect of members’ exposure to PHN on per-member per-month total cost, controlling for member risk, seasonality, yearly trend, and a set of baseline clinic characteristics.

 In both models, a longer period of PHN exposure was signifi cantly associated with a lower total cost. The total cumulative cost savings over the study period was 7.1% (95% confi dence interval [CI] 2.6-11.6) using the model with the prescription drug coverage interaction effects and 4.3% (95% CI 0.4-8.3) using the model without the interaction effects. Corresponding return on investment was 1.7 (95% CI 0.3-3.0) and 1.0 (95% Cl —0.1 to 2.0), respectively.

 Our fi nding suggests that PCMHs can lead to significant and sustainable cost savings over time.

 Geisinger Health Systems has implemented its own version of patient-centered medical homes called ProvenHealth Navigator (PHN) since 2006. Our results demonstrate that the longer the member has been exposed to PHN sites, the lower the cost of care. The return on investment (ROI) has not yet signifi cantly exceeded the break-even point. However, because the magnitude of savings from PHN depends on the length of members’ exposure to PHN, it remains to be seen whether the cumulative ROI can eventually exceed the break-even point.

 Cost savings are achievable by redesigning primary care, but it takes time to reap the benefits.

At this time of national focus on the need to simultaneously improve quality and reduce cost, novel solutions are needed. The fragmented healthcare delivery system further adds to the challenge.

 The key stakeholders—physicians, patients, health insurers, and hospital administrators, as well as the federal government&mdash;now recognize the need for healthcare redesign to increase the quality of care while containing the cost of care.

In particular, reorienting the current healthcare delivery system to one in which greater emphasis is given to more effective primary care is likely to be an important solution to the problem.

Recently, patient-centered medical homes (PCMHs) have gained attention as a way to re-engineer the care-delivery process. In the broadest sense of the term, PCMHs refer to “provision of comprehensive primary care services that facilitates communication and shared decision-making between the patient, his/her primary care providers, other providers, and the patient’s family.”

 There is early but growing evidence that PCMHs have the potential to improve care for individuals, improve health of populations, and slow the growth in costs of healthcare by reviving primary care and bringing the patient and family to the center of the care-delivery system

The ultimate goal of PCMHs is to improve patient outcomes via redesigned primary care. The preventive aspect of primary care enhances the value proposition of PCMHs as a long-term intervention. Such an emphasis on primary care, therefore, implies that PCMHs may have the desirable effect of reducing cost of care. The early experiences of the PCMH demonstrations strongly suggest this.

 In this study, we explicitly explore this possibility by evaluating the effect of ProvenHealth Navigator (PHN), an advanced model of PCMHs developed and implemented by Geisinger Health System (Geisinger), since 2006 on cost of care.

PHN consists of the following 5 core program components: (1) patientcentered primary care, (2) integrated population management, (3) medical “neighborhood”

 (ie, alignment of key community partners, such as home health agencies, skilled nursing facilities, outpatient/ancillary services, hospital facilities, and community pharmacies), (4) comprehensive quality improvement, and (5) value-based reimbursement redesign that includes a quality, outcome-based pay-for-performance program. More detailed descriptions of how the PHN intervention was designed and implemented are published elsewhere.

PHN is designed to move resources further “upstream” in the primary care setting to reduce “downstream” costs from the highest acuity settings. In this system, primary care is considered upstream in the sense that it serves as the starting point in the chain of care delivery. In general, care becomes more expensive as patients move downstream to specialty and inpatient care. Therefore, successful upstream efforts are expected to result in reductions of inpatient care—related costs due to fewer uncontrolled exacerbations of chronic diseases and more effective care transitions that prevent hospital readmissions and unnecessary duplication of services.

A PHN site refers to one of the primary care clinics that has been designated as such by Geisinger and has undergone significant changes in its management and operations in accordance with the PHN practice redesign. PHN was implemented in several phases over the 5-year period from late 2006 through 2010. At its core, the PHN intervention can potentially reduce cost over time while improving quality via:

• Prevention: redesigned primary care using automation to leverage resources and enhance reliability for early detection and interventions prior to exacerbations and complications

• Chronic disease optimization: redesigned primary care using a high-touch, high-technology approach to manage emerging exacerbations and to minimize complications

• Comprehensive care management: health-plan— trained, practice-embedded “concentrated care–RNs” who serve as nurse case managers focused on proactive identification and management of the more medically complex patients

This analysis focuses on individual members’ exposure to PHN by measuring how long a member has been exposed to a PHN site and examining whether a prolonged exposure to PHN is associated with a lower cost of care over time. It is expected that the longer the patient has been exposed to a PHN site, the greater the cost savings.

, a number of primary care clinics in the Geisinger Health Plan (GHP) provider network were selected and converted to PHN sites during each phase of the intervention. As a result, primary care clinics became PHN sites at different times. We exploit this variation in time of PHN conversion to estimate the effect of PHN exposure on total cost. The fi gure also shows the trends in average permember per-month (PMPM) total cost among clinics in each PHN implementation phase. For baseline clinic characteristics in each phase, see 

Our data originated from GHP’s claims database covering the period between January 1, 2006, and December 31, 2010. The unit of observation was member-month (ie, there was a unique record for each member for each month during which the patient was a GHP member). If the member did not have any claims for that month, claim amounts were recorded as $0. Our sample was restricted to GHP’s Medicare Advantage plan members who were at least 65 years of age during the study period (because PHN had focused primarily on the Medicare population during this time) and enrolled in 43 primary care clinics that eventually became PHN sites by the end of 2010 (37 with physicians employed by Geisinger and 6 non- Geisinger primary care practices). About 30% of all patients treated by practices with Geisinger-employed physicians are covered by GHP.

Two measures of PHN exposure were developed: First, a member-level PHN exposure measure was calculated as the number of months a member had been enrolled in a PHN clinic as of a given time. This exposure measure was then broken into 5 categories (0, 1-6 months, 7-12 months, 13-24 months, and >24 months) in order to capture any non-linear relationship between the cost of care and PHN exposure. Second, a clinic-level PHN exposure measure was also calculated as the number of months in which the clinic had been a PHN site as of a given period since its PHN conversion on the phase start date as shown in Figure 1.

The clinic-level PHN exposure variable is intended to capture the degree to which there might have been learning at clinics over time in accordance with PHN’s rapid-cycle innovation principle.

This is in recognition of PHN’s being a dynamic program that has undergone continuous modifi cations over time while maintaining its core components. As such, it is diffi cult to determine exactly at what point the PHN sites transitioned from practice transformation and redesign to fully functioning PHN sites. Nevertheless, we hypothesize that the longer a clinic has been designated a PHN site, the greater its impact on cost of care.

In addition to the member-level and clinic-level PHN exposure variables as described above, the covariates included age and hierarchical condition categories (HCC) risk score to capture each member’s case mix along with year-indicator variables to capture the temporal trend in total cost over time as well as month-indicator variables to capture seasonality. Other covariates included a set of baseline clinic characteristics as of 2005 (ie, percentage of male patients and average patient age in 2005, along with average total cost, HCC score, and number of inpatient admissions and readmissions in 2005). These variables were intended to capture any underlying differences among different clinics which may be correlated with each member’s total cost during the study period.

The main outcome measure was the total cost of care, defined as the total allowed amount (plan payment to providers plus copayments) for a given member in a given month (per-member-per-month [PMPM]) which included payments for inpatient and outpatient facility and professional services, as well as prescription drugs. Less than 2% of the total member- month observations in our sample had 0-value total cost, because capitation payments for certain services, such as behavioral health, were refl ected in the total cost calculations.

Because there are multiple observations for each member, a member fi xed-effects model was used to account for these repeated measures as well as to remove any unobserved and time-invariant member characteristics that could have biased our estimates. In this model, we exploit the within-member variation in the total cost and the PHN exposure variable over time. Thus, each member acts as his or her comparison. In other words, the question that our model seeks to answer may be stated as the following: relative to his or her own cost at 0 PHN exposure, what is each member’s expected total cost at 1 to 6 months, 7 to 12 months, 13 to 24 months, and greater than 24 months, of exposure?

Moreover, because members’ total costs vary depending on whether they have prescription drug coverage or not, a binary indicator variable for prescription drug coverage status during each month was also included as a covariate. Because of the fixed effects model used in this analysis, our estimate of the drug coverage effect relied on variation in the prescription drug coverage variable due to the change in each member’s drug coverage status over time. About 32% of the members picked up the drug coverage and dropped it at some point, or vice versa.

We hypothesized that the effect of PHN on total cost may differ depending on whether a member has prescription drug coverage in each period (ie, an interaction effect between prescription coverage and PHN exposure). For instance, a case manager might fi nd out whether his or her members have drug coverage or not, and if they have coverage, the case manager might encourage them to become more adherent to their drug therapy and therefore incur greater total cost. As such, we estimated 2 models: one with and another without the interaction effects. These 2 models might yield different estimates of total cost savings attributable to PHN, because in the model with interaction effects, the estimates depend both on the level of each member’s PHN exposure and the proportion of members who have drug coverage in each period. In the model without the interaction effects, the estimates depend only on the PHN exposure level.

Using the parameter estimates obtained from the fi xedeffects model, we calculated the expected total cost if none of the members had any PHN exposure (ie, member as well as clinic-level PHN exposure of 0 months) and compared them against the total costs given the actual levels of PHN exposure for each member in each given period (ie, the “observed” cost). This allowed us to estimate the effect of the PHN exposure on cost in terms of percent savings (see eAppendices A and B for the full regression model parameter estimates). The mean percent savings and the standard errors used to construct the 95% confi dence intervals (CIs) were obtained via bootstrap method with 200 replications.

As a sensitivity check, we also obtained a number of alternative estimates using different sample defi nitions. In particular, we obtained estimates with a restricted sample consisting of only those who did not switch their primary care clinics during the study period (about 80% of the full sample size). This allowed us to control for any clustering effects due to similarities among members enrolled in same clinics

 by including member-clinic fi xed effects in our regression model. The resulting estimates (available upon request) were similar to the reported estimates shown below.

, the fi nal sample consisted of 26,303 members over the 5-year period, corresponding to 1,053,445 member-month observations in 43 primary care clinics that were designated as PHN sites at different points in time between 2006 and 2010. The median age of the members was 76 years, and 42% were male. Slightly less than half of the member-month observations fell in the 0 member-level PHN exposure category; about 12% fell in the highest category of greater than 24 months of PHN exposure. Table 1 also indicates that greater PHN exposure is associated with higher total cost and age, as well as greater proportion of membermonths with prescription coverage. This suggests that the effect of PHN exposure on total cost is confounded by member age and presence of prescription drug coverage benefit.

On average, GHP members in our sample maintained their membership for about 40 months out of the maximum possible 60 months, suggesting a stable enrollment pattern. About 20% of the members in our sample switched from a non-PHN site to a PHN site during our study period, while only about 1% switched from a PHN site to a non-PHN site.

 shows the regression coeffi cients and their corresponding 95% CIs for the key covariates in the 2 models (with and without the interaction effects between drug coverage and PHN exposure). In both models, the coeffi cients on the PHN exposure variables are consistently negative and get increasingly larger as the length of exposure increases, suggesting that longer PHN exposure is consistently associated with lower total cost. However, in contrast, the coeffi cient estimates on the interaction terms between drug coverage and PHN exposure are consistently positive, suggesting that there is a significant interaction between them.

shows the estimated percent savings and the corresponding bootstrapped 95% CIs as obtained from the regression model parameter estimates shown in Table 2. Table 3 clearly supports the hypothesis that a longer exposure to PHN is associated with lower total cost and therefore greater savings, regardless of whether the interaction effects were included in the model. The largest and statistically most signifi cant percent saving was achieved in the highest category of PHN exposure (>24 months) in both models.

ProvenHealth Navigator, Geisinger's version of advanced patient-centered medical homes, is associated with significant savings in total cost of care over time.

Reducing Long-Term Cost by Transforming Primary Care: Evidence From Geisinger's Medical Home Model

 To compare adherence rates under voluntary and mandatory mail benefit designs.

 Adherence rates in the first year of therapy were compared between voluntary and mandatory mail cohorts composed of individuals who initiated statin, angiotensin-converting enzyme (ACE) inhibitor, angiotensin receptor blocker (ARB), platelet aggregation inhibitor, metformin, glitazone, or sulfonylurea therapy at a retail pharmacy between January 1 and March 31, 2009. Initiators in mandatory mail plans were matched on therapeutic class, age, sex, prospective risk, and cost of initial prescription with those in voluntary mail plans. Logistic regression models of optimal adherence were constructed to adjust for measured confounders.

 Persistence rates were similar through the first 60 days of therapy. The mandatory mail cohort had a notable drop in persistence by day 90 (63.3% vs 56.3%, P <.001), with a more pronounced drop among those without previous mail-service pharmacy use (50.5%). Median medication possession ratio (49.2% vs 57.4%) and optimal adherence (33.6% vs 36.1) were also lower. In the multivariable models, mandatory mail participants were less likely to achieve optimal adherence overall (odds ratio [OR] 0.70; 95% confidence interval [CI] 0.67-0.74) and in the metformin (OR 0.55), sulfonylurea (OR 0.72), ACE inhibitor (OR 0.74), ARB (OR 0.69), and statin (OR 0.69) classes. Participants with no prior use of mail-service pharmacy had significantly lower odds of achieving optimal adherence in all therapeutic classes.

 Mandatory mail appears to cause some members to discontinue therapy prematurely, particularly those without previous mailservice pharmacy experience.

	Pharmacy benefit designs that mandate mail pharmacy use interfere with prescription drug access that could be particularly important for individuals with chronic conditions.

		By restricting pharmacy choice and access, mandatory mail appears to cause some members to discontinue therapy prematurely.

		When members choose to discontinue rather than switch pharmacy channels, the unintended consequence is a reduction in medication adherence and the potential for increased medical expenses.

		Individuals without previous use of mail-service pharmacy are particularly sensitive to this plan design and are an important population to target for interventions to support adherence.

	A critical challenge in designing pharmacy benefits is to find the optimal balance between access to essential medications and cost management.

Employers seek pharmacy benefit designs that maximize access to effective medications and support appropriate adherence to those medications, with the intent of reducing health service use and promoting health and productivity. However, as pharmacy expenditures have risen, cost management has received increased attention. In addition to escalating use of incentivized formularies and higher copayments,

employers increasingly offer a mailservice option as a mechanism to reduce costs. In 2010, nearly 96% of all employers offered mail pharmacy services to their employees.

	The majority of plan sponsors offer “voluntary mail”: a pharmacy benefit that allows prescriptions to be dispensed from either retail or mail-service pharmacy but that discounts out-of-pocket costs to encourage mail-service pharmacy use. In contrast, nearly 19% of employers implement “mandatory mail,” a design that requires use of mail-service pharmacy for maintenance medications by ending benefit coverage for retail-dispensed prescriptions after a predetermined limit is reached. By requiring mail-service pharmacy use for all chronic medications, plan sponsors can expect additional cost savings,

 but they limit access to retail pharmacies, a channel through which the vast majority of prescriptions are dispensed.

	Little is known about how voluntary and mandatory mail benefit designs affect adherence to essential medications. Plan sponsors should be aware of the trade-offs in adherence that may be related to limiting pharmacy choice or other barriers to drug access imposed by mandating a specific pharmacy channel. This trade-off can be analogous to the choice that payers must make when assigning copayments to medications: cost savings through elevated copayments can come at the expense of nonadherence to essential medications.

 Accordingly, we compared voluntary and mandatory mail pharmacy benefit designs with respect to their impact on medication adherence. Payers can use this information to appropriately balance cost management with beneficiary medication adherence when designing pharmacy benefits.

	We conducted a matched retrospective cohort study of medication adherence among initiators in their first year of therapy. The sampling frame was employersponsored pharmacy insurance plans that offered either mandatory (n = 85) or voluntary (n = 240) mail pharmacy benefits managed by CVS Caremark between July 1, 2008, and March 31, 2010. Within this sampling frame, we identified potential study subjects among members who were enrolled in a pharmacy insurance plan with a mandatory mail benefit (mandatory mail participants) or a plan with a voluntary mail benefit (voluntary mail participants). In addition, eligible study participants met the following criteria: (1) valid demographics (age, sex, zip code); (2) valid Pharmacy Risk Group score; (3) a paid retail 30-day pharmacy claim (index prescription) between January 1 and March 31, 2009, for a prescription drug in 1 of the following therapeutic classes: HMG CoA reductase inhibitors (statins), angiotensin receptor blockers (ARBs), angiotensin-converting enzyme (ACE) inhibitors, platelet aggregation inhibitors (PAIs), sulfonylureas, metformin, or glitazones; (4) no previous paid pharmacy claim for a drug in the same class within the previous 6 months; and (5) continuous eligibility for pharmacy benefits for the 6 months before and 12 months subsequent to the index prescription.

	Mandatory mail participants who met these qualifications were individually matched (1:1 match without replacement) to voluntary mail participants on the following criteria: age (±5 years); sex; index therapeutic class; out-of-pocket cost for the index prescription (±$0.20 per day of supply); and Pharmacy Risk Group category. Therapeutic class definitions were derived from Medi-Span’s Generic Product Identifier. The Pharmacy Risk Group score uses a proprietary algorithm based on pharmacy claims to provide an estimate of each individual’s predicted healthcare costs; this score can be used to adjust for risk in the absence of medical utilization data. The Pharmacy Risk Group score was derived from claims filled prior to the index prescription date. The final analytical sample was limited to the mandatory and voluntary mail participants successfully matched.

	Medication adherence was measured for each therapeutic class separately using the following metrics: medication possession ratio (MPR) and persistence. The MPR was defined as the total days of supply divided by 365 days (the follow-up period), and an MPR greater than or equal to 80% signified optimal adherence. Beginning with the index prescription, we catalogued each prescription filled during the follow-up period and aligned them chronologically. Using the days of supply associated with each prescription, we determined the expected availability of drug therapy on a given day. For example, if the index prescription had a 30-day supply and the refill was dispensed on the 32nd day after the index fill date, day 31 would be designated as a day without available drug therapy. Days with available drug therapy were deemed as persistent days, and we calculated the proportion of patients persistent on each day during the follow-up period. Daily persistence was then graphed in 5-day increments and stratified by baseline mail pharmacy use. For all calculations, days of supply from early refills were counted from the beginning of the date of exhaustion of the previous prescription, and the days of supply that extended beyond the follow-up period were truncated.

Pharmacy benefit designs that mandate mail pharmacy use interfere with prescription drug access, particularly for individuals without previous mail pharmacy experience.

Joshua N. Liberman, PhD

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