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Asthma Expenditures in the United States Comparing 2004 to 2006 and 1996 to 1998

The American Journal of Managed CareSeptember 2012
Volume 18
Issue 9

Increased expenditures in US asthma are driven by increased medication spending that are not offset by decreases in emergency department and hospital spending.


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.


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.


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).


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 Sample

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.

Statistical Analysis

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).


Table 1

Figure 1

A total of 2396 individuals were included in the 1996 to 1998 and 2004 to 2006 groups (N = 918 and N = 1478, respectively) for all analyses except those addressing missed work/school days. Demographic data are summarized in , and are notable for differences in age and insurance status when comparing the 1996 to 1998 and 2004 to 2006 groups. The total direct annual expenditures (adjusted for sex, age group, poverty level, educational attainment, Census region, self-reported health, and Charlson Comorbidity Index) in individuals with asthma were $3802 in 1996 to 1998 and $5322 in 2004 to 2006, resulting in a statistically significant increase of $1521 per year, P <.0001 (direct expenditures summarized in ). Differences in total direct expenditures were different by race/ethnicity over time (increases of $1566 in white, $1320 in black/African American [P = 0.08], and $1202 [P = .005] in Hispanic individuals in 2004 to 2006 compared with 1996 to 1998, using the white total expenditure as the comparison value). There were no significant differences in expenditures for inpatient ($1730 vs $1340) and emergency services ($162 vs $216) between 1996 to 1998 and 2004 to 2006, respectively. Outpatient expenditures in individuals with asthma increased significantly in 2004 to 2006 compared with 1996 to 1998 ($1174 vs $861, P <.0001).

Figure 2


Medication expenditures more than doubled between 1996 to 1998 and 2004 to 2006 ($974 vs $2010, P <.0001). This increase in medication expenditures was seen across race/ethnicity groups ($1078 for white, $876 for black/African American, and $801 for Hispanic individuals). Changes in asthma medications are presented in to provide some additional detail regarding the shift in asthma medication dispensing comparing 1996 to 1998 and 2004 to 2006. Key differences include significant increases over time for controller medications (3.67 controller medications dispensed compared with 2.14, P <.0001) in general, and specifically for inhaled corticosteroid plus long-acting beta-agonist (1.52 vs 0, P <.0001) and leukotriene modifiers (1.35 vs 0.27, P <.0001). The describes which asthma medications qualified for which asthma medication category.

Table 2

Productivity loss in individuals with asthma was assessed in the MEPS by measuring missed work/school days. For total work/school days missed, there were 1497 patients who had a value for either a missed day of work or school, 746 patients had values for work days missed, and 909 had values for school days missed. Total missed work/school days decreased by 2.8 days (P = .001), from 9.2 in 2004 to 2006 to 6.4 in 1996 (), representing an estimated $748 in lost wages. This significant decrease in missed work and school days was consistent by race/ethnicity (2.6 days less in white, 4.0 less in black/African American [P = .006], and 3.3 less in Hispanic individuals [P = .108], with white individuals’ missed work and school days as the comparison value). The sensitivity analysis showed similar results within work days missed and school days missed (Table 2).

We performed an additional sensitivity analysis by including all individuals with asthma of all ages and found similar results. Total direct expenditures in this analysis were $4239 in 1996 to 1998 and $5807 in 2004 to 2006. Outpatient expenditures and asthma medication expenditures were similar ($939 and $1325 for outpatient, $996 and $2049 for medication, in 1996 to 1998 and 2004 to 2006). Productivity loss for individuals with asthma of all ages was also similar to the age-restricted analysis (7.95 total missed days in 1996 compared with 5.90 in 2004 to 2006).


The data from this nationally representative study of individuals with asthma in 1996 to 1998 and 2004 to 2006 extends our understanding of expenditure trends in individuals with asthma; we found increased total direct expenditures, increased medication expenditures, increased outpatient visit expenditures, stable hospital and ED expenditures, and decreased missed work/school days. These findings appear to be a continuation of the asthma trends described for 1985 to 1994 which also noted increasing medication expenditures and a general shift of costs to outpatient management.4 The findings from this study are unique compared with other recent asthma expenditure analyses2,8,10 in that we have included data about changes in types of asthma medications and studied the expenditures over longer time periods. The changes in asthma medication expenditures likely reflect national asthma guidelines emphasizing use of asthma controller medications; however, it is somewhat surprising that inpatient and ED expenditures have not decreased in accordance with increased spending on asthma controller medications. It is an encouraging trend, however, that individuals with asthma are missing fewer days of school and work in 2004 to 2006 compared with 1996 to 1998.

A recent report describes an increase in adherence to asthma medication guideline recommendations over a similar time period (1997-1998 and 2004-2005), but was unable to detect any difference in the 2 time periods for asthma exacerbations.17 These findings suggest that asthma medications may not be properly targeted in the sample population (ie, over- or undertreatment with asthma controller medications). The findings from our expenditure analysis over the same time period would be consistent with increased spending on asthma medications without any impact on spending for ED or hospitalizations. Another recent report has described the costs attributable to asthma.10 The total costs were slightly higher in this report compared with ours, likely due to inclusion of older individuals, and found the leading categories of asthma spending were for asthma medications, hospitalizations, and home healthcare. Data from our findings extend these results by demonstrating that asthma medication expenditures is the only category that is significantly increasing (of the 3 leading categories identified by Sullivan and colleagues).10

Are the expenditure patterns we have observed for asthma when comparing 2004 to 2006 with 1996 to 1998 unique to asthma, or are they a reflection of the general medical expenditure trends? AHRQ reports unadjusted total direct expenditures per capita each year with expenditure categories reported separately, as well as missed work/school days.14 Total unadjusted direct medical expenditures in 1996 to 1998 ($2389, $2424, and $2444) appeared nearly 40% lower than those reported in 2004 to 2006 ($3879, $4082, and $4078).14 Unadjusted medication expenditures in the general MEPS population were $374, $429, and $461 in 1996 to 1998 versus $1037, $1140, and $1191 in 2004 to 2006.14 Inpatient expenditures in the general MEPS population were reported only for those with an expense and therefore are not helpful in comparing with our sample that included individuals regardless of an inpatient expense having been reported. The mean number of missed work days was 12.3 in 1997, 11.3 in 2001, and 10.0 in 2007, suggesting an average decrease over 10 years of 2 missed work days.14 Although the values of the AHRQ MEPS data are unadjusted (and need to be interpreted cautiously), comparisons of general MEPS expenditure data suggest that expenditures in asthma are similar to general trends observed in all individuals in the MEPS.

There are several limitations in this asthma expenditure analysis. First, the trends are derived from the US population due to the MEPS sample frame, but may have similar lessons for those countries with similar asthma patient populations and treatment patterns. Second, we reported total expenditures in individuals with asthma rather than asthma-specific incremental expenditures due to concerns about the validity of methods to assign and determine asthma-specific incremental costs. Risk for misclassification and error in disease-specific attribution supports our decision to measure total expenditures and adjust for key confounders, rather than attempt a calculation for asthma- specific expenditures.18 Reporting total expenditures with adjustment may make comparison with other asthma expenditure studies more difficult. Finally, missed work and school days were not reported in the MEPS in 1997 to 1998, and therefore our comparison for this productivity measure was from 2004 to 2006 with 1996 alone. Furthermore, our attempt to quantify the costs for missed work and school days was unable to account for decreased productivity while at work or school.

In summary, total direct expenditures in individuals with asthma appear to be increasing in the United States when comparing 2004 to 2006 and 1996 with 1998 data, with an increase in medication and outpatient visit expenditures and a decrease in missed school/work days. The most likely explanation for these findings is the diffusion of asthma guidelines that emphasize regular use of asthma controller medications. Data from Figure 2 displaying changes in asthma medication prescriptions support this explanation. We come to this conclusion with caution, however, as our cross-sectional study design does not allow for cause-and-effect assignment. Several other explanations for the asthma expenditure data we report exist, including changes in outpatient care models, pharmaceutical marketing, and changes in health insurance coverage policies. We anticipate that a more detailed study of asthma medication expenditures coupled with key clinical outcomes (ie, asthma-specific quality of life and asthma exacerbations) will identify risk-targeting opportunities that will increase the value of asthma medications.Author Affiliations: From Division of Allergic Diseases (MAR, JTL), Division of Health Care Policy and Research (JTL, JYZ, MEB, NDS), Division of Pulmonary and Critical Care Medicine (KGL), Mayo Clinic, Rochester, MN; Department of Research (BPY), Olmsted Medical Center, Rochester, MN.

Funding Source: Mayo Clinic Foundation.

Author Disclosures: Dr Yawn reports payment from GlaxoSmithKline for advisory board. Dr Li reports owning stock in Abbott Laboratories and Novartis. The other authors (MAR, JTL, JYZ, MEB, KGL, NDS) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (MAR, JTL, KGL, NDS); acquisition of data (MAR, NDS); analysis and interpretation of data (MAR, MEB, KGL, BPY, JTL, NDS); drafting of the manuscript (MAR, KGL, JTL); critical revision of the manuscript for important intellectual content (MAR, MEB, KGL, BPY, JTL, NDS); statistical analysis (MAR, JTL, MEB); provision of study materials or patients (MAR, JTL, NDS); obtaining funding (MAR, NDS); administrative, technical, or logistic support (JTL, MEB, KGL, NDS); supervision (MAR, NDS); and mentoring (JTL, BPY).

Address correspondence to: Matthew A. Rank, MD, 200 First St SW, Rochester, MN 55905. E-mail: rank.matthew@mayo.edu.1. Braman SS. The global burden of asthma. CHEST. 2006;130(1 suppl):4S-12S.

2. Barnett SB, Nurmagambetov TA. Costs of asthma in the United States: 2002-2007. J Allergy Clin Immunol. 2011;127(1):145-152.

3. Bahadori K, Doyle-Waters MM, Marra C, et al. Economic burden of asthma: a systematic review. BMC Pulm Med. 2009;9:24.

4. Weiss KB, Sullivan SD, Lyttle CS. Trends in the cost of illness for asthma in the United States, 1985-1994. J Allergy Clin Immunol. 2000;106(3):493-449.

5. Smith DH, Malone DC, Lawson KA, et al. A national estimate of the economic costs of asthma. Am J Respir Crit Care Med. 1997;156(3, pt 1):787-793.

6. Lozano P, Fishman P, VonKorff M, Hecht J. Health care utilization and cost among children with asthma who were enrolled in a health maintenance organization. Pediatrics. 1997;99(6):757-764.

7. Weiss KB, Gergen PJ, Hodgson TA. An economic evaluation of asthma in the United States. N Engl J Med. 1992;326(13):862-866.

8. Kamble S, Bharmal M. Incremental direct expenditure of treating asthma in the United States. J Asthma. 2009;46(1):73-80.

9. Druss BG, Marcus SC, Olfson M, Tanielian T, Elinson L, Pincus HA. Comparing the national burden of five chronic conditions. Health Aff (Millwood). 2001;20(6):233-241.

10. Sullivan PW, Ghushchyan VH, Slejko JF, et al. The burden of adult asthma in the United States: evidence from the Medical Expenditure Panel Survey. J Allergy Clin Immunol. 2011;127(2):363-369.e1-3.

11. Sarpong, E.M, Miller, GE. Changes in Children’s Use and Expenditures of Asthma Medications, United States, 1997—1998 and 2007–2008. Statistical Brief #341. Agency for Healthcare Research and Quality. http://www.meps.ahrq.gov/mepsweb/data_files/publications/st341/stat341.pdf. Published September 2011. Accessed December 5, 2011.

12. Center for Disease Control and Prevention. National surveillance for asthma-United States 1980-2004. MMWR. 2007;56(5508);1-14,18-54.

13. Eder W, Ege MJ, von Mutius E. Current concepts: the asthma epidemic. N Engl Med J. 2006;355:2226-2235.

14. Agency for Healthcare Research and Quality. Medical expenditure panel survey. http://www.meps.ahrq.gov/mepsweb/. Accessed May 19, 2011.

15. Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461-494.

16. Graubard BI, Korn EL. Predictive margins with survey data. Biometrics. 1999;55(2):652-659.

17. Rank MA, Liesinger JT, Ziegenfuss JY, et al. The impact of asthma medication guidelines on asthma controller use and on asthma exacerbation rates comparing 1997-1998 and 2004-2005. Ann Allergy Asthma Immunol. 2012;108(1):9-13.

18. Akibundu E, Ju J, Blatt L, Mullins CD. Cost-of-illness studies: a review of current methods. Pharmacoeconomics. 2006;24(9):869-890.

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