Published Online: September 19, 2012
Matthew A. Rank, MD; Juliette T. Liesinger, BA; Jeanette Y. Ziegenfuss, PhD; Megan E. Branda, MS; Kaiser G. Lim, MD; Barbara P. Yawn, MD, MSc; James T. Li, MD, PhD; and Nilay D. Shah, PhD
Objectives: To describe how the types of healthcare expenditures for patients with asthma have changed over the past decade.
Study Design: Cross-sectional comparison between individuals from 1996 to 1998 and 2004 to 2006.
Methods: Expenditures among US individuals (aged 5 to 56 years) with asthma were compared using the 1996 to 1998 and the 2004 to 2006 Medical Expenditure Panel Surveys. Direct expenditures (medications, inpatient, outpatient, and emergency services) and changes in productivity (missed school and work days) were compared over this time frame. The adjusted analyses controlled for age, education level, race/ethnicity, gender, poverty, region, metropolitan statistical area, self-reported health, and Charlson Comorbidity Index.
Results: Mean annual per capita healthcare expenditures increased between 1996 to 1998 and 2004 to 2006 ($3802 vs $5322 inflated to 2010 US dollars, P <.0001). Annual medication expenditures doubled from $974 to $2010 per person (P <.0001) and outpatient visit expenditures increased from $861 to $1174 (P <.0001) while hospitalization and emergency department (ED) visit expenditures were similar over the same time period. Missed school and work days decreased between the 2 periods (9.23 days in 1996-1998 vs 6.39 days in 2004-2006, P = .001).
Conclusions: An increase in total direct expenditures in individuals with asthma was largely driven by an increase in spending on medications comparing 2004 to 2006 and 1996 to 1998 data. However, this increase was not offset by lower spending on hospitalization and ED visits.
(Am J Manag Care. 2012;18(9):499-504)
Understanding how the types of healthcare expenditures for patients with asthma have changed over the past decade is helpful for managed care organizations planning programs to care for populations of patients with asthma.
Total healthcare expenditures in individuals with asthma have increased over the past decade.
Expenditure increases in individuals with asthma are driven primarily by increasing medication expenditures.
Increased spending on asthma medications was not offset by decreased emergency department and hospital spending, which both remained stable.
Asthma has a significant economic impact in the United States, accounting for $56 billion in total healthcare costs in 2007.1-3 While asthma is associated with significant spending, the distribution of asthma expenditures has changed over the last 3 decades. In the 1990s, services gradually shifted away from inpatient to outpatient services and medication management in comparison with the previous decade.4,5 In 1987, only 10% of individuals with asthma were considered chronic medication users and hospital services accounted for the largest share of healthcare expenditures associated with asthma.6,7 In the years between 1985 and 1994, total asthma expenditures increased by 54% (direct increased by 20%), inpatient services decreased by 15%, medication increased by 10%, and total expenditure per asthma patient declined by 3%.4 Asthma expenditures since 1994 have been reported,3,8-10 but there have been no evaluations of expenditure distribution for a time period when the management of
asthma changed drastically and medication expenditures for asthma also increased rapidly.11 While recent studies have compared the 1990s with the 2000s (a time period in which asthma medication prescribing changed significantly), these studies did not look into the specific changes in medication-related expenditures.2,8
Several favorable asthma trends emerged from the 1990s to 2000s, including a decreasing asthma mortality rate, a stable asthma exacerbation rate, and what appears to be a stable asthma prevalence rate (although not in all countries).12,13 Many factors, including the dissemination of evidence-based asthma guidelines, may be responsible for these positive trends. The changes in expenditures in individuals with asthma, however, have not been described in sufficient detail for this key time period in asthma management. Specifically, the goal of this study was to determine if asthma medication expenditures have changed over this time period and if expenditures for other services (total, inpatient, emergency department [ED] visits, and missed work/school days) have changed for patients with asthma. We hypothesized that recommendations from the National Asthma Education and Prevention Program (NAEPP) in 1991, with updates in 1997 and 2002, may have impacted the distribution of asthma expenditures such that the spending for asthma medications would have increased while being offset by decreases in hospital and ED spending due to better asthma management. Specifically, we examined differences in expenditures from 2 time periods (1996-1998 and 2004-2006) to gain a better understanding of the changing trends in patients with asthma.
STUDY DESIGN AND METHODS
This was a cross-sectional study using the Medical Expenditure Panel Survey (MEPS) data from 1996 to 1998 and 2004 to 2006. The MEPS is composed of a collection of large-scale surveys which are gathered into 2 main components: the Household Component and the Insurance Component. For the purposes of our study, only the Household Component, which is administered to both an individual of the selected household and their medical providers, was used. The MEPS Household Component is designed to be nationally representative of the US civilian, noninstitutionalized population and collects information about each respondent’s demographic and socioeconomic characteristics, health status, medical care use, medical care expenditures, and health insurance coverage.14 The MEPS utilizes an overlapping panel design, in which the sample in any given year is followed for a total of 2 calendar years. The survey consists of 5 in-person interviews over 30 months to yield annual use and expenditures for 2 calendar years. Our study utilized the following data files: fullyear consolidated data, medical conditions, prescribed medications, hospital inpatient stays, ED visits, outpatient visits, and office-based medical provider visits. Within the various data files, MEPS collects key healthcare utilization measures for asthma, including ED visits, hospitalizations, outpatient visits, and asthma medication use based on pharmacy dispensing. The MEPS did not collect data on missed work and school days in 1997 to 1998, and therefore, we reported only data from 1996 and 2004 to 2006.
Participants and Definitions
Individuals were identified as having asthma if they had a clinical classification system (CCS) code for asthma (128) as the primary or any secondary diagnosis from the outpatient visits file, office-based medical provider visits file, ED visits file, or hospital inpatient stays file. Individuals aged 5 to 56 years were identified and used for the
primary analysis to limit diagnostic misclassification more common in older and younger age groups. Since an individual could have more than 1 type of insurance coverage throughout the course of a year, a full year measure of insurance coverage was utilized. Insurance groups were defined hierarchically as follows: (1) if an individual ever had Medicaid they were coded as Medicaid; (2) if an individual ever had Medicare they were coded as Medicare; (3) if an individual ever had private insurance (employer-sponsored insurance or direct purchase) they were coded as private; (4) if an individual indicated that they did not have any type of coverage at any point in the entire year, then they were coded as uninsured.
Asthma expenditures considered for this analysis included direct expenditures from inpatient visits, ED visits, outpatient visits, and medications, as well as an estimate of productivity based on missed school and work days. Previous asthma cost studies have suggested that missed work and school represents the largest indirect expenditure associated with asthma.3 Total missed work/school days were calculated by combining the work and school days missed for all individuals with reported values. We estimated the productivity loss into a cost by assuming a US median income of $60,088 (www.census.gov 2009 data) and that missing a day of work would mean a loss of $267 per day. Missed school days were assumed to result in a missed work day for a parent when estimating productivity loss costs. Nonmedical costs such as missed time to attend appointments or cost of transportation to and from appointments were not considered separately. We were also unable to measure decreased productivity while at work or school due to asthma. The costs associated with asthma mortality were also not included in this study. Expenditures were expressed in 2010 US dollars using the gross domestic product deflator. The Mayo Clinic Foundation institutional review board reviewed the study proposal and determined a full review unnecessary as only de-identified data were used.
Three-year averages for 1996 to 1998 and 2004 to 2006 are reported in order to include a large enough sample to produce stable estimates. The only exception was missed work/school days in the earlier time period, for which only 1996 data were available. Demographic data were reported as percent of the population. Differences between the 1996 to 1998 and 2004 to 2006 individuals were analyzed using the Wald χ2 test. All reported summary statistics apply the survey weights as recommended by the Agency for Healthcare Research and Quality (AHRQ) to account for the complex survey design of the MEPS. Generalized linear models were estimated for all the cost models. These models assumed a gamma distribution and log link based on the modified Park test, as suggested by Manning and Mullahy.15 Total missed work/school days were modeled using a negative binomial specification. A sensitivityanalysis was conducted within patients that had missing days for school and for those missing days from work. These findings are reported along with the total days missed. The models controlled for sex, age group (5-17, 18-34, 35-44, 45-56 years), poverty level (below federal poverty level [FPL], 100% to 199% of FPL, 200% to 399% of FPL, 400% or more of FPL), educational attainment (elementary grades 1-8, some high school grades 9-11, high school graduate, some college, college/post graduate), Census region (northeast, midwest, south, west), urban versus rural, self-reported health (excellent, very good, or good vs fair or poor), time (1996-1998 vs 2004-2006), and Charlson Comorbidity Index (insurance variable was highly colinear with poverty and therefore not included). The days-missed model was not adjusted for self-reported health; this is due to a lack of patients that had self-reported health in the earlier time period (1996). In order to isolate the impact of time on the outcomes of interest, we calculated recycled predictions, also known as predictive margins, a method that took into account the complex survey data.16 Recycled predictions were utilized to estimate the outcomes (cost and days missed) by setting first all patients to the time period of 1996 to 1998 and then setting all patients to the time period of 2004 to 2006. The predictions were also compared by time within race. Point estimates were calculated for the 1996 to 1998 and 2004 to 2006 time points with 95% confidence intervals for both along with the P value associated with the time parameter estimate. The statistical analysis was performed using SAS version 9.2 (SAS Institute Inc, Cary, North Carolina) and StataSE version 11 (College Station, Texas).
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