Vaishali Patel, PharmD, MS

: Bimatoprost 0.01%, a newer ophthalmic formulation, was hypothesized to improve adherence and persistence compared with the original bimatoprost 0.03% formulation.

: A retrospective, observational cohort study was conducted that utilized a pharmacy claims database to examine the adherence to and persistence with prior latanoprost use among patients with glaucoma who were prescribed bimatoprost 0.01% or bimatoprost 0.03% for glaucoma treatment.

: Using pharmacy claims, adherence in 6035 bimatoprost 0.01% patients and 2705 bimatoprost 0.03% patients with prior latanoprost treatment was measured as a proportion of days covered (PDC). Persistence in 7780 bimatoprost 0.01% and 3454 bimatoprost 0.03% latanoprost-experienced patients was measured as the proportion of patients on continuous treatment for up to 12 months.

: Adherence to bimatoprost 0.01% was significantly greater than to bimatoprost 0.03% (mean PDC, 0.74 vs 0.68; P <.001). Persistence with bimatoprost 0.01% (52%) was significantly greater than with bimatoprost 0.03% (46%). Analyses conducted by age group (aged <65 and ≥65 years) yielded similar results.

: In clinical practice, bimatoprost 0.01% demonstrated superior adherence and persistence compared with bimatoprost 0.03% in latanoprost-experienced patients.

Primary open-angle glaucoma treatment focuses on reducing intraocular pressure (IOP), the only known modifiable risk factor linked to glaucoma.

 The goal of treatment is preservation of vision by preventing damage (or further damage) to the visual field and function by lowering IOP to within a target range.

Treatment options include drug therapy (prostaglandin analogs and prostamides [PGAs], alpha-agonists, beta-blockers, carbonic anhydrase inhibitors), laser therapy, and surgery.1,3 Topical PGAs are a class of newer agents that reduce IOP by increasing aqueous fluid drainage.

 FDA-approved agents in this class include bimatoprost (Lumigan; Allergan plc), latanoprost (Xalatan; Pfizer, Inc), tafluprost (Zioptan; Akorn, Inc), and travoprost (Travatan; Alcon, Inc).

Sustained adherence to (complying with daily treatment) and persistence with (remaining on treatment over time) topical PGAs are important for reducing the risk of visual function loss. Adherence to glaucoma treatment is complex and not completely understood, however.

Adverse effects of topical PGAs are thought to contribute to nonadherence.

 Conjunctival hyperemia is the most frequently reported side effect, occurring in approximately 30% of patients, and may result in skipped doses or treatment discontinuation.

In a physician survey of PGA use and adverse effects, respondents estimated that 18% of their patients had reduced adherence to PGA therapy due to hyperemia.

 Complexity of the therapeutic regimen also contributes to nonadherence.

Although PGAs provide the most effective topical therapy

 with once-daily administration, adjunctive therapy may be required, resulting in more complex therapeutic regimens.

 In one study, 28% of patients initiating PGA therapy required adjunctive therapy; however, bimatoprost-treated patients had significantly lower rates of adjunctive therapy use than latanoprost-treated patients (23.2% vs 30.2%; P <.0001).

Bimatoprost is the only PGA with 2 formulations. The newer formulation (0.01%) was designed to provide more efficient drug delivery than the original formulation (0.03%), thereby maintaining efficacy while reducing drug exposure and improving tolerability.

 In a randomized controlled trial, bimatoprost 0.01% had equivalent efficacy to bimatoprost 0.03%.

Treatment-related adverse events were less frequent among those receiving 0.01% (38.4% vs 50.8%; P = .016), with a significantly lower proportion of bimatoprost 0.01%—treated patients experiencing a moderate to severe increase in hyperemia than those treated with bimatoprost 0.03% (8.6% vs 17.6%; P = .023). Adherence has been associated with positive clinical outcomes, and the newer formulation of bimatoprost has the potential to affect adherence by increasing tolerability.

Therefore, the current study was designed to confirm prior published results,

 demonstrating improved adherence to and persistence with bimatoprost 0.01% compared with bimatoprost 0.03% among patients previously treated with branded or generic latanoprost, using a different dataset and more recent years of data.

This retrospective, observational cohort study utilized data from the Longitudinal Rx (LRx) Database from IMS Health, which includes patient-level prescription claims (without diagnoses) for more than 205 million patients. LRx captures approximately 75% of all prescription claims in the United States, is representative of the US population, and includes a wide range of payers. Patient demographic information (age, gender) is available, but prescription plan enrollment dates are not included in this database.

The study period spanned July 1, 2010, through June 30, 2013, including a 6-month enrollment period from January 1, 2012, through June 30, 2012. Patients were required to have ≥1 prescription fill for bimatoprost 0.01% or bimatoprost 0.03% during the enrollment period.

The date of the first fill for either formulation was defined as the index date, and patients were classified into 2 treatment cohorts based on their index formulation. Patient eligibility criteria included: being ≥18 years on the index date; having at least 18 months of continuous pre index pharmacy benefit eligibility, which was proxied by the presence of a pharmacy claim for any medication in each of the 18 months; and having ≥1 prescription fill for latanoprost (branded or generic) within the pre-index period.

PGAs may be commonly used as initial eye drops,1 of which generic latanoprost is likely the most common.

 All patients who met these selection criteria were included in the postindex persistence analysis. Additionally, 12 months of continuous postindex pharmacy benefit eligibility, proxied by the presence of a pharmacy claim for any medication in each of the 12 months, was required for patients included in the adherence and treatment status analyses.

Outcome measures included adherence to and persistence with treatment and monthly treatment status (on or off treatment) in the 12 months following the index prescription. Traditionally, these measures depend on the days’ supply reported on pharmacy claims, but these may be inaccurate for nondiscrete drug formulations.

Therefore, rather than relying on the pharmacist-recorded days’ supply,

 it was calculated for each prescription fill using a drop count method. This method includes a count of the number of drops per bottle and number of drops per dose for the product dispensed:

Days’ supply = [(# of drops)/bottle]/[(# of drops)/dose] x [(# of administrations)/day]

The drop count method was utilized in a prior study,

 and the number of drops per dose was defined per the labeled indication. Bilateral use was assumed for all patients (ie, twice the number of drops per dose).

Adherence to the index bimatoprost treatment (0.01% or 0.03%) was defined as the proportion of days covered (PDC)15 during the 12-month postindex period:

PDC = [Total days with index drug available within 365-day measurement period]/365

The numerator of the PDC calculation for each index drug was the number of days within the postindex period covered by ≥1 prescription for that drug, and the denominator was fixed at 365 days. If patients refilled a prescription prior to completion of the previous fill, the start date for the second prescription was adjusted appropriately to avoid double-counting.

The mean and median PDCs were calculated by treatment cohort and the proportion of patients with PDC values at different adherence levels: a) PDC ≤0.20 (low adherence), b) PDC >0.20 to ≤0.80 (moderate adherence), and c) PDC >0.80 (high adherence). A cross-sectional analysis of patient compliance with the index treatment was also conducted and was defined as the proportion of patients remaining on index therapy at the end of each of the 12 months of follow-up.

Patients were categorized monthly as: a) treatment continuers (ie, with a supply of medication in the prior month and either an index refill or a carry-over of supply into the current month), b) treatment discontinuers (no carry-over supply or index prescription fill in the current month), or c) treatment re-starters (a prescription fill in the current month and no supply of index medication in the prior month).

Treatment continuers and re-starters in a given month were classified as “on treatment” and discontinuers classified as “off treatment.” Persistence with the index bimatoprost (0.01% or 0.03%) treatment was assessed over a period of up to 12 months following the index date.

Patients were considered persistent with index treatment as long as they continued to refill their prescription ≤30 days after exhausting their existing days’ supply and nonpersistent (ie, discontinued) if they did not refill within 30 days. The treatment discontinuation date was set at 30 days after the exhaustion of the days’ supply of the last continuous prescription fill because a prior study reported similar persistence results when comparing 15-, 30-, and 60-day allowable refill gaps.

Baseline demographic characteristics, including age at index, gender, and payer type (commercial, Medicare, Medicaid, cash) were used to describe the treatment cohorts (bimatoprost 0.01% and bimatoprost 0.03%). Statistical differences in baseline demographics were evaluated with 

2 tests for proportions and Student’s t tests for means.

Within each cohort, patients were stratified into 2 age groups (aged <65 and ≥65 years) at index. Mean and median PDCs were calculated by treatment cohort (overall and stratified by age). Student’s t tests were used to assess the statistical significance of differences in mean PDC, and Wilcoxon signed rank tests were used to assess differences in median PDC between cohorts.

Mean PDC (adjusted) in the bimatoprost 0.01% cohort was evaluated with a general linear model, with bimatoprost 0.03% used as the reference cohort and patient age, gender, insurance type, and pre-period latanoprost adherence used as covariates. Diagnostic tests of suitability of the linear model (minimum and maximum predicted PDC) to predict the bounded mean value were performed.

Comparisons of the proportions of patients with low, moderate, and high adherence and of patients on treatment (continuers plus re-starters) were conducted using 

2 tests. Adjusted analyses of adherence level (low and high categories) and treatment status (on or off treatment) were performed using logistic regression adjusted with the same covariates as the linear model.

Time to nonpersistence of the index agent was evaluated by Kaplan-Meier survival analysis, including the log-rank test of homogeneity and survival plots. A Cox proportional hazards model was used to compare the covariate-adjusted hazards of nonpersistence between cohorts, with results reported as hazard ratios (HRs) with their 95% confidence intervals (CIs) and associated P values. A P value of ≤.05 was considered statistically significant.

A total of 11,234 patients met the criteria for the persistence analysis; 69.3% of patients had bimatoprost 0.01% as their index agent and 30.7% had bimatoprost 0.03%. A majority of patients (77.8%; n = 8740) met the eligibility requirements for the adherence and treatment status analyses, and the proportions of bimatoprost 0.01% and bimatoprost 0.03% users were nearly identical to those of the persistence analysis (69.1% and 30.9%).

A comparison of baseline demographic and clinical characteristics yielded few significant differences between treatment cohorts in both the adherence and persistence populations (Table 1). There were slightly more females in the bimatoprost 0.01% cohort (P = .0362) in the persistence population.

There were no substantial differences between insurance types and pre-index brand/generic latanoprost use, although the differences present were statistically significant. Higher proportions of commercial and lower proportions of Medicare enrollees in the bimatoprost 0.01% cohort were observed.

In the bimatoprost 0.01% cohort, 34% used brand and generic, 15% used only generic, and 51% used only branded latanoprost, while in the bimatoprost 0.03% cohort, 21% used brand and generic, 19% used only generic, and 60% used only branded latanoprost (P <.001). In the 18-month pre-index period, adherence to latanoprost (branded and generic combined) was significantly higher in the bimatoprost 0.01% cohort than in bimatoprost 0.03% users (mean latanoprost PDC: 0.49 vs 0.43; P <.0001).

In this study of latanoprost-experienced patients, adherence to bimatoprost treatment was significantly greater among bimatoprost 0.01% users than among bimatoprost 0.03% users, overall (mean PDC, 0.74 vs 0.68; adjusted P <.0001; median PDC, 0.88 vs 0.75; P <.0001). Over the 12-month postindex period, the bimatoprost 0.01% cohort had a significantly higher proportion of patients with high adherence and a significantly lower proportion of patients with low adherence compared with the bimatoprost 0.03% cohort (high: 55.2% vs 48.7%, respectively; P <.0001; low: 6.7% vs 10.8%; P <.0001) (Figure 1).

Adherence results were similar when stratified by age groups (<65 and ≥65 years) (not shown). In adjusted analyses (Table 2), patients treated with bimatoprost 0.01% had a 23% higher likelihood of being a high adherer (odds ratio [OR], 1.233; 95% CI, 1.125-1.353; adjusted P <.0001) and a 40% lower likelihood of being a low adherer (OR, 0.602; 95% CI, 0.513-0.707; adjusted P <.0001) compared with patients treated with bimatoprost 0.03%.

The results of the monthly treatment analysis demonstrated that the proportion of patients remaining on index therapy were greater in the bimatoprost 0.01% cohort than in the bimatoprost 0.03% cohort starting at month 3, with 80.4% of bimatoprost 0.03% patients and 83.7% of bimatoprost 0.01% patients remaining on treatment (Figure 2) (adjusted P = .0062).

In each subsequent month, while smaller proportions of patients in each cohort were on treatment, larger reductions were observed in bimatoprost 0.03% patients compared with bimatoprost 0.01% patients. By month 12, 72.5% of bimatoprost 0.01% patients were on treatment compared with 53.6% of bimatoprost 0.03% patients (adjusted P <.0001) (Table 2).

Results from the analysis of persistence indicated that significantly higher proportions of bimatoprost 0.01% patients were persistent with their index therapy, both overall (52.2% vs 45.5%; P <.0001) and within each age group (aged ≥65 years, 52.7% vs 46.2%; P <.0001; aged <65 years, 50.5% vs 43.1%; P = .0009) compared with bimatoprost 0.03% patients.

At any point in time, the bimatoprost 0.01% cohort had a 10% lower probability of nonpersistence compared with the bimatoprost 0.03% cohort, based on the covariate-adjusted analysis (HR, 0.896; 95% CI, 0.848-0.948; adjusted P = .0001) (Table 2).

Kaplan-Meier curves depicting greater persistence for bimatoprost 0.01% compared with bimatoprost 0.03% were statistically significant (log-rank; P <.001) for all ages (Figure 3) and by age group (<65 and ≥65 years) (not shown). The median survival time (ie, time to discontinuation) was 10.9 months for the bimatoprost 0.01% cohort and 9.1 months for the bimatoprost 0.03% cohort.

Articles

A new ophthalmic formulation of bimatoprost was found to improve adherence and persistence compared with the original formulation of bimatoprost.

Adherence and Persistence of Bimatoprost in Prior Latanoprost Users

Prescription drug spending in the United States increased at double-digit rates from 1994 to 2003 compared with single-digit rates for hospital and physician services; this increase fell to 5.8% in 2005, but increased again in 2006, with an average annual growth rate of 8.5%.

 Spending on specialty pharmaceuticals such as biotech injectables grew from 17.5% in 2005 to a projected 25% in 2009.

 Consequently, employers and health plans are adopting benefit design changes that increase cost sharing for patients, in the form of higher deductibles, copayments, and coinsurance rates for drugs and services.

 Payers may influence insurance coverage by shifting injectable and biologic products from the medical benefit to the pharmacy benefit category.

A relationship between higher out-of-pocket (OOP) costs and decreased patient adherence is well documented for lipid-lowering agents, antidiabetic agents, antidepressants, and drugs in general.

 Rates of cost-related medication underuse are greater among patients with lower incomes, higher OOP drug costs, and less generous prescription coverage.

 There is limited research on the effects of benefit design changes from copayment to coinsurance; a recent analysis found that the effect of the benefit change on OOP spending varied by therapeutic class and tier (preferred status) of medications.

Our objectives were to look at trends in OOP spending, the effects of coinsurance requirements on OOP costs, and the existence and amounts of OOP spending limits (caps) in insured patients with rheumatoid arthritis (RA), multiple sclerosis (MS), chronic kidney disease (CKD), and diabetes mellitus (DM).

This study used commercial insurance claims from the MarketScan databases from Thomson Reuters to capture expenditures for inpatient and outpatient procedures and prescription drugs from self-insured employer health plans. Data from 110 employers included healthcare claims of employees and dependents, early retirees, COBRA  beneficiaries, and Medicare-eligible retirees with employer-sponsored Medicare Supplemental plans. Details regarding coinsurance and OOP limits were captured from each plan’s Summary Plan Description booklet. Complete benefit details were available for 376 plans from 2002-2005, which covered approximately half of the patients in our study. Out-of-pocket expenditure data are presented for all patients to understand spending in as broad a population as possible. Differences between patients whose plans provided benefit details versus patients whose plans did not provide benefit details were unknown.

Patients diagnosed with any of 4 chronic diseases were selected: RA, MS, CKD without diabetes or cancer, and DM without CKD. At least 1 inpatient or 2 outpatient 

International Classification of Diseases, Ninth Revision, Clinical Modification

 codes were required for diagnosis (see the 

 for codes). A prevalence approach was used whereby patients were included in the year they were first diagnosed and in subsequent years. Patients exited the study when they were no longer eligible for insurance. A comparison group of “all utilizers” included patients who had at least 1 outpatient, inpatient, or drug claim during the years that they were eligible for insurance or during prior years in the study period.

Annual OOP expenditures were tabulated, including copayments, coinsurance payments, and deductibles as captured on insurance claims. Expenditures in each calendar year were annualized as follows: Annualized OOP = (total expenditures over the year/number of months eligible for insurance during the year) × 12. The following insurance plan characteristics were assigned to patients’ claims:

• Patient was required to pay medical coinsurance when using network providers.

• Patient was required to pay pharmacy coinsurance for prescription drugs from network pharmacies.

• Benefit plan had a total annual cap on OOP medical expenses and/or prescription drug costs.

The OOP expenditures for patients with in-network coinsurance requirements were compared with those of patients without such requirements. When years 2002-2005 were combined, the expenditures were expressed in 2005 dollars. The escalation factor used was the percent difference in the average per-patient value of annualized insurance claims for all utilizers between the target year and 2005. Values were escalated 30.86%, 21.03%, and 6.66% in 2002, 2003, and 2004, respectively.

Approximately 8.3 million members in the commercial claims database had at least 1 medical claim during the study period (all utilizers). Patients with any of the 4 chronic diseases were on average 6 to 10 years older than the all-utilizers group. The MS and RA patient groups were approximately 75% female, while other groups were more evenly split by sex (

Median annual OOP expenses increased each year. Patients with MS had the highest median OOP costs, rising from $832 in 2002 to $1042 in 2005 (a relative increase of 25%). By 2005, median annual OOP spending was also approaching $1000 for RA patients (another 25% increase). The all-utilizers group paid less than half the amount spent by any of the chronic disease groups, or slightly more than $300 in 2004 and 2005 (

). The 90th percentile in MS exceeded $3000 in 2004 and 2005, and patients in the top spending category with any of the 4 chronic diseases faced spending of at least $2400 in 2005.

Compared with relative growth in the Consumer Price Index for all medical care, each study group faced a greater relative increase in median OOP spending from 2002 to 2005. The OOP spending of CKD patients increased 60%, OOP spending of DM patients increased 23%, and OOP spending of all utilizers increased more than 34%. During this time, the medical care Consumer Price Index increased only 13%. 

 Patients spent similar amounts on outpatient care and prescription drugs: MS and DM patients had slightly higher drug versus outpatient care spending, while CKD, RA, and all utilizers had higher outpatient care versus drug spending (data not shown). Patients in all disease groups spent considerably less on inpatient care. Mean OOP spending by type of expense tended to increase over the 4-year study period for all disease groups, though between 2004 and 2005 the increase was not as great for prescription drugs, and even decreased for MS and RA patients. Mean inpatient OOP spending decreased slightly from 2004 to 2005 for all disease groups except all utilizers.

Approximately 60% (range 59%-64%) of patients with benefit design data had in-network medical or pharmacy coinsurance requirements (Table 1). Most of these patients had in-network medical coinsurance (range 55%-61%); innetwork pharmacy coinsurance was less common (range 12%-15%). The most common pharmacy benefit design was a 2- or 3-tiered copayment system. Pharmacy copayments in the vast majority of plans were less than $20 per prescription, with the exception of mail-order brand copayments, which tended to be higher.

More than 80% of patients with in-network medical coinsurance had an OOP cap; only 24% to 29% of patients with pharmacy coinsurance had an OOP cap. The proportions of patients with coinsurance and with OOP caps were similar across all patient groups, though the requirement for coinsurance was slightly more common among patients with chronic diseases compared with all utilizers.

Over the 4-year study period, the percentage of all utilizers with a medical or pharmacy coinsurance requirement increased (

). The largest increase occurred between 2004 and 2005, reflecting an increase in the proportion with medical coinsurance as well as a large increase in the proportion with pharmacy coinsurance, which was uncommon until 2005.

 Out-of-Pocket Spending by Coinsurance Status

Median annual OOP spending was generally more than twice as much for patients with in-network coinsurance versus no coinsurance; in the all-utilizers group, the difference was 3-fold ($493 vs $163) (

). MS and CKD patients at the 90th percentile of spending and with coinsurance spent more than $4000 per year.

In 2005, half of the patients with RA, MS, and CKD were in a plan that capped OOP medical expenditures. The mean cap was $1574 (

); 70% had a cap of less than $2000. Relatively few patients, between 7% and 10% of patients with caps, had liability greater than $4000 for their OOP medical expenses.

In contrast to medical benefits, fewer patients (~30%) had caps on pharmacy benefits. Moreover, the mean cap on pharmacy benefits for patients with RA, MS, or CKD was $2587, which was considerably higher than the medical benefit cap. Very few patients (2%-4%) had the lowest caps of less than $1000. About 35% to 40% had pharmacy caps greater than $4000: all utilizers, 35%; DM, 42%; and RA/MS/CKD, 36% (data not shown).

Our results show that median annual OOP expenditures for patients with chronic diseases such as RA, MS, CKD, and DM were approximately $1000 in 2005 (about $80 or less per month), an amount that could be considered reasonable for most employer-insured patients. The presumption that most patients have reasonable OOP responsibilities is  supported by the findings of a 2005 survey of 3600 pharmacy benefit plan members, in which only 2% of respondents reported that they could not afford their medication.

 In an analysis of Blue Cross Blue Shield pharmacy claims, member cost sharing for MS self-injectable drugs was moderate but increasing

; the median OOP cost per claim increased from $20 in 2004 to $30 in 2007.

In willingness-to-pay (WTP) studies of patients with DM or RA, mean monthly WTP estimates were similar to our median estimate of $80 or less.

 In 2 non-US studies, DM patients were willing to pay $89 and $86 per month, on average, above the cost of standard insulin therapy for special insulins

 Mean valuation of hypothetical cures for RA ranged from Can $1190 annually ($77 monthly)

 Dutch women with osteoporosis were prepared to pay 195 euros ($287) per 10% reduction in fracture risk and 338 euros ($497) total for a hypothetical treatment, although the time frame was not reported.

 Taken together, the WTP data suggest that patients are willing to pay approximately $100 per month for treatment of a serious chronic disease, which is greater than the monthly median OOP costs in our study.

There was a trend toward increasing OOP costs from 2002 to 2005. Some patients bore a large annual cost burden; for instance, patients with MS in the top 10th percentile of OOP spending paid more than $3200 ($266 per month) in 2004 and 2005. In this top decile of spending, OOP costs were well over $2000 ($166 per month) for all 4 chronic diseases studied and greater than WTP estimates in the literature. The proportion of all patients with a coinsurance requirement increased from 54% in 2002 to 86% in 2005. Patient OOP spending could become substantial for the average patient and formidable for patients in the higher spending brackets if these trends continue.

Our findings are comparable to the results presented in a 2007 Government Accountability Office report on employer- sponsored benefits.27 The analysis of Kaiser Family Foundation data noted that among workers enrolled in preferred provider organizations requiring cost sharing, the copayment amounts and coinsurance rates increased from 2004 to 2006. While the share of covered workers paying lower coinsurance rates fell by 12% between 2004 and 2006, 12% more workers paid higher coinsurance rates. In a 2005 survey of large private-sector employers, 34% reported that they had increased retiree coinsurance or copayments and 19% had increased OOP spending limits in the previous year.

A troubling consequence of high OOP costs is decreased persistence with medications, as documented in several studies,

 including a recent systematic review by Goldman et al.

 Our own work using MarketScan claims data for RA patients noted that increases in OOP costs significantly decreased persistence with medications.

A week of therapy was lost with each $5.50 increase in weekly OOP, or an increase of 2.2 percentage points in the patient’s share of cost for anti-tumor necrosis factor (anti-TNF) therapy. Patients who paid more than $50 per week for anti-TNF drugs were more likely to discontinue therapy than patients who paid less. Poor medication adherence is associated with adverse health outcomes in vulnerable populations and greater healthcare costs in chronically ill patients.

 Evidence linking cost sharing to decreased use of medical services is not limited to prescription drugs; a recent study found that members of a high-deductible health plan may have substituted fecal occult blood testing for colonoscopy and other noncovered colon cancer screening exams.

 Mammography rates were significantly lower in cost-sharing Medicare managed care plans compared with plans with full coverage.

Most patients had an OOP medical cap that averaged $1500 to $1750 annually, protecting patients in the highest spending brackets. However, if coinsurance payments on higher-priced pharmaceuticals increase, a corresponding growth of caps may occur. On the other hand, the amount of the OOP pharmacy cap was so high that it may not protect most patients from burdensome pharmacy expenses; in our study, in 2005 more than one-third of patients would only reach their annual OOP pharmacy cap after spending $4000.

Price and access controls may not be in the best interests of patients or society. The economic value of “good health” has a positive and statistically significant effect on labor productivity: a 1-year improvement in a population’s life expectancy has been found to lead to a 4% increase in output.

 Changes in medical technology for treatment of conditions such as myocardial infarction, low-birthweight babies, cancer, and depression have resulted in increased spending, but the associated additional years of life have an economic value that exceeds these costs.

 In the area of HIV/AIDS, Philipson and Jena argue that while the aggregate value of increased survival due to HIV/AIDS drugs is equal to nearly $1.4 trillion, only 5% of the social surplus was appropriated by innovators, with 95% going to consumers.

Our study had some limitations. Benefit plan information was not available for all patients. Biases of indeterminate nature and degree may have existed, based on which insurance plans provided benefit data. Thus, the 2 parts of the study (total OOP expenses and OOP expenses by type of insurance) are not directly comparable. Additionally, socioeconomic data were not available; comparing OOP expenses with income would have provided a more complete picture of the relative burden of OOP healthcare costs. The study data were  not current, in part due to the normal time lag involved with acquiring claims data. While the actual amounts of copayments and coinsurance are likely to have evolved, the potential impact of cost sharing on use of health services is less time dependent. Awareness of OOP costs is particularly important during an economic downturn, when patients may be more likely to discontinue needed medications due to financial constraints.

The results of this analysis of the MarketScan database from January 2002 to December 2005 suggest that most patients with commercial insurance and serious chronic  conditions have reasonable annual OOP spending. Mean OOP prescription drug spending for RA and MS patients decreased slightly during 2004-2005. However, a minority of patients were liable for nearly $3000 in OOP expenses per year, and more than one-third of patients’ OOP pharmacy caps may not be sufficient to shield against high costs. The potential impact of OOP spending on consumers should be considered when making benefit design changes.

A small proportion of patients with chronic conditions have very high healthcare expenditures, and a trend was observed toward increasing coinsurance requirements.